diff --git a/.gitattributes b/.gitattributes index f312dfe23..e2ce33cdd 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1 +1 @@ -src/rtctools_heat_network/_version.py export-subst +src/mesido/_version.py export-subst diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 4ed7caf8f..b90f3aa1f 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -1,14 +1,23 @@ name: PyPi release run-name: CI pipeline on: - push: + pull_request: branches: - '*' + types: + - opened + - reopened + - synchronize + - ready_for_review + push: + branches: + - main jobs: style: name: Check style runs-on: ubuntu-latest + if: ${{ !github.event.pull_request.draft }} env: TOXENV: flake8,black steps: @@ -27,6 +36,7 @@ jobs: build: name: Check build runs-on: ubuntu-latest + if: ${{ !github.event.pull_request.draft }} steps: - uses: actions/checkout@v3 @@ -39,10 +49,12 @@ jobs: - name: Check build run: python setup.py sdist bdist_wheel - - test: - name: Check test + + # Main testing + test_main: + name: Test main runs-on: ubuntu-latest + if: ${{ !github.event.pull_request.draft }} env: TOXENV: py38 steps: @@ -54,13 +66,81 @@ jobs: - name: deps run: python -m pip install -U tox + + - name: Check test + run: tox -vv -etest_env_main + + # Pre-processing testing + test_pre_processing: + name: Test pre-processing + runs-on: ubuntu-latest + if: ${{ !github.event.pull_request.draft }} + env: + TOXENV: py38 + steps: + - uses: actions/checkout@v3 + + - uses: actions/setup-python@v4 + with: + python-version: "3.8" + - name: deps + run: python -m pip install -U tox + - name: Check test - run: tox -vv + run: tox -vv -etest_env_pre + - name: Upload results + uses: actions/upload-artifact@v4 + with: + name: updated_esdl_file + path: examples/PoCTutorial/model/PoC Tutorial_GrowOptimized.esdl + retention-days: 5 + + - name: Upload results + uses: actions/upload-artifact@v4 + with: + name: updated_esdl_string_file + path: examples/PoCTutorial/model/PoC Tutorial_GrowOptimized_esdl_string.esdl + retention-days: 5 + + + # Post processing testing dependant on pre-processing + test_post_processing: + name: Test post-processing + needs: test_pre_processing + runs-on: ubuntu-latest + if: ${{ !github.event.pull_request.draft }} + env: + TOXENV: py38 + steps: + - uses: actions/checkout@v3 + + - uses: actions/setup-python@v4 + with: + python-version: "3.8" + + - name: deps + run: python -m pip install -U tox + + - name: Archive test artifacts + uses: actions/download-artifact@v4 + with: + name: updated_esdl_file + path: examples/PoCTutorial/model/ + - name: Archive test artifacts + uses: actions/download-artifact@v4 + with: + name: updated_esdl_string_file + path: examples/PoCTutorial/model/ + + - name: Check test + run: tox -vv -etest_env_post + documentation: name: Generate documentation runs-on: ubuntu-latest + if: ${{ !github.event.pull_request.draft }} steps: - uses: actions/checkout@v3 diff --git a/.gitignore b/.gitignore index 404870adc..5e9fbb449 100644 --- a/.gitignore +++ b/.gitignore @@ -25,9 +25,18 @@ src/*.egg-info .ipynb_checkpoints .vscode -# Kobus van Rooyen -run_pipe_compare.py -.venv/ +# Abbreviation to be added to files/folders name +# Meaning of abbreviation: exclude from version control +*_efvc_* + # Ignore ESDL files created by workflows *_GrowOptimized.esdl +*_GrowOptimized_esdl_string.esdl *_Simulation.esdl + +# Virtual environment files +.venv/* + +# Docs build folder +docs/_build/* +docs/_build_kvr_ \ No newline at end of file diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml index 94e649eb6..ef2fdbe9f 100644 --- a/.gitlab-ci.yml +++ b/.gitlab-ci.yml @@ -33,7 +33,12 @@ build: py37:linux: stage: test script: - - tox -vv + - echo "Demo" > Demo.txt + artifacts: + paths: + - ./Demo.txt + # - ./PoC Tutorial_GrowOptimized.esdl + expire_in: 1 week image: python:3.7 variables: TOXENV: py37 diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 000000000..d620fa035 --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,186 @@ +# [Unreleased-main] - 2025-06-25 + +## Added +- xx + +## Changed +- Previously variable operational cost of air-to-water heat pump was based on the thermal power usage. Now it is based on the electrical power usage + +## Fixed +- xxx + + +# [0.1.13] - 2025-06-25 + +## Added +- xx + +## Changed +- README update mesido install command for dev + +## Fixed +- Bug: Producer profiles specified in Watts and asset state=ENABLED + + +# [0.1.12] - 2025-06-12 + +## Added +- Maximum profile contraint (specified in Watts) to some heat producers + +## Changed +- xx + +## Fixed +- xx + + +# [0.1.11] - 2025-05-21 + +## Added +- xx + +## Changed +- Updated pyESDL to v25.5.1 + +## Fixed +- xx + + +# [0.1.10] - 2025-05-20 + +## Added +- Default database for gas pipe dimensions based on the ASA pipe schedule with thicknesses from the standard class +- Gas and electricity workflow has been added. Still a work in progress +- Internal energy content function added for natural gas and hydrogen +- OPEX added for gas and electricity source +- Commodity annotation for assets, to allow for easier postprocessing +- Added function to make pickle usable (exceptions) in the OMOTES back end +- More of the existing classes added to __init_ for local runs using the grow_workflow +- Generic functions for postprocessing are added. +- Generic function to adapt timeseries from hourly timesteps to user-defined timesteps by averaging. +- Error check for NaN values in profile data (csv & influxDB) +- Specify package (deepdiff used in pandapipes validation test) version number in test environment +- Reset POTENTIAL_ERRORS class instance (Singleton) in grow_workflow due to it being persistent +- Estimate grow worlfow progress status and update OMOTES progress status + +## Changed +- Updated the Financial section of the documentation to explain the annualized discounted costs calculation. +- Write output to json also saves the solver statistics. +- Updates in asset conversion from ESDL to pycml; gas and heat pipe split, generic conversion better specified. +- Adapt profiles for heating and cooling peak day separately & add test case +- For gas: Use energy content (heating value) instead of internal energy +- Option was added to allow a bypass of the heat exchanger, possible on both sides of the heat exchanger +- Option for electricity cables to be unidirectional +- Upgraded rtctools to v 2.6.1 +- Updated Casadi to 3.6.7 with gil fixes (see https://github.com/casadi/casadi/releases/tag/nightly-gil_release) +- Definition of power attribute of water-to-water heat pump is changed from electrical power to secondary heat power +- Enforce water-to-water heat pump upper bound heat capacity to conform to elect_power*cop + +## Fixed +- Bugfix: gas boiler mass flow constraint units +- Bugfix: same mip gap settings for all solvers in grow_workflow. +- Bugfix: head loss test case when minimum_velocity = 0.0 +- Bugs: state update of heat pump, heat buffer volume & ates charge rates update in ESDL, heat storage asset data output to influxDB +- Bugfix: get_density + get_internal_energy updated to ensure it checks commodity type for heat instead of the carrier name +- Bug: pipe class bounds when pipe DN none results from stage 1 in the grow_workflow + + +# [0.1.8.5] - 2025-02-12 + +## Added +- xx + +## Changed +- Updated Casadi to 3.6.7 with gil fixes (see https://github.com/casadi/casadi/releases/tag/nightly-gil_release) +- Upgraded rtctools to version 2.6.1 + +## Fixed +- Bug: pipe class bounds when pipe DN none results from stage 1 in the grow_workflow + + +# [0.1.8.4] - 2024-12-11 + +## Added +- More of the existing classes added to __init_ for local runs using the grow_workflow + +## Changed +- xxx + +## Fixed +- Bugs: state update of heat pump, heat buffer volume & ates charge rates update in ESDL, heat storage asset data output to influxDB + + +# [0.1.8.3] - 2024-12-02 + +## Added +- Added function to make pickle usable (exceptions) in the OMOTES back end + +## Changed +- xx + +## Fixed +- Bugfix: same mip gap settings for all solvers in grow_workflow. +- Bugfix: head loss test case when minimum_velocity = 0.0 + + +# [0.1.8.2] - 2024-11-15 + +## Added +- xx + +## Changed +- xx + +## Fixed +- Bugfix: same mip gap settings for all solvers in grow_workflow. +- Bugfix: head loss test case when minimum_velocity = 0.0 + + +# [0.1.8 & 0.1.8.1] - 2024-11-07 + +## Added +- Added MESIDO error exception class to raise applicable potential errors in a workflow & include required info for feedback in the mapeditor +- Limit the available pipe classes connetced to heat/gas demand/producers +- Add demands and sources to the topology object to have easy access to the connected pipes/cables later on +- Heating and cooling example case added (2 heating demands, 1 cold demand, hot and cold producer, WKO as seasonal storage) +- Gas physics documentation +- Gas & electricity 1st version of physics documentation +- Test case: Head loss validation with pandapipes. +- Example on ESDL file creation using pyESDL for the PoC Tutorial. +- Electrolyzer specific power curve valley location specified optionally specified in ESDL. +- Grow_workflow: Solver class created to allow the use of CPLEX as a solver for EndScenarioSizing classes. + +## Changed +- Cooling demand added to adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day (peak cooling day not used yet) +- Impact on the way EndScenarioSizing problems in MESIDO are run: The calling of the different optimization problem classes has been split from the solver classes. In EndScenarioSizing classes, the HIGHS solver is the default and the calling functions also cather for other solvers by adding the keyword "solver_class" with the respective solver class. +- Bugfix: No longer required to provide a power at the heating demands when a profile has been added. +- Bugfix: Scaling fix on ATES temperature variable when temperature modelling not used. +- Bugfix: Fix on nominals in electricity cables and gas pipes. Fix on nominals for nodes with logical links. +- Pipeline is only run when pull request is ready for review and synchronized or when opened, as well as when a pull request is merged to main. +- Speedup: Changed the way daily average profiles are created from hourly profiles to speed up the conversion. + +## Fixed +- Bug fix: Logical links: e_boiler & gas boiler update to use energy values +- Bug fix: Q max and nominal calculation update when reference energy value +- Bug fix: e-boiler expected order of inports while setting nominal values +- Bug fix: setting nominals while using logical links when all values are 1.0 +- Bug fix: machine error/rounding with updating lower bound values in the grow_workflow after stage 1 +- documentation: heat physics tank storage +- bug fix in grow_workflow (heat networks), changed minimum velocity from 0 to default value +- addition to tests checking the minimum velocity setting in a workflow + + +# [0.1.7] - 2024-08-23 + +## Added +- User feedback regarding demand type to be used in heat networks +- Functionality to connect assets with logical links + +## Changed +- Increased time limit for stage 1, priority 1 +- Replaced Retry loop to connect all assets and apply the correct modifiers of the linked assets + +## Fixed +- Error exit when stage 1, priority 1 was not successful + + diff --git a/COPYING.LESSER b/LICENSE similarity index 100% rename from COPYING.LESSER rename to LICENSE diff --git a/MANIFEST.in b/MANIFEST.in index 2cbe862c4..e19c5fb42 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1,4 +1,6 @@ -recursive-include src/rtctools_heat_network/modelica/WarmingUp * +recursive-include src/mesido/modelica/WarmingUp * include versioneer.py -include src/rtctools_heat_network/_version.py -include src/rtctools_heat_network/esdl/_edr_pipes.json +include src/mesido/_version.py +include src/mesido/esdl/_edr_pipes.json +include src/mesido/esdl/_gas_pipe_database.json +include additional_info_for_license.txt diff --git a/README.md b/README.md index 5346d5d34..50cae8ad4 100644 --- a/README.md +++ b/README.md @@ -1,35 +1,31 @@ -# rtc-tools-heat-network +# MESIDO -Rtc-tools-heat-network is an optimization application for optimal planning, design and -operation of Energy Systems with the current main focus on District Heating Systems (DHS). The current application focuses on a Mixed Integer Linear Problem (MILP) approach, with multiple linearization strategies to conservatively approximate the steady-state physics and financial models. -All physics are combined in the HeatMixin class. When inherited this class can be combined with objective functions (that typically incorporate the financial aspects) and interface methods to create an +MESIDO is an optimization application for optimal planning, design and +operation of Energy Systems with the current main focus on District Heating Systems (DHS). The current application focuses on a Mixed Integer Linear Problem (MILP) approach, with multiple linearization strategies to conservatively approximate the steady-state physics and financial models. See for example the head loss validation test, using pandapipes, in the test folder. All physics, placement, sizing and financial models are combined in the TechnoEconomicMixin class. When inherited this class can be combined with objective functions (that typically incorporate the financial aspects) and interface methods to create an optimization workflow (see also running an example). -The main supported method for defining your Energy system is ESDL (Energy System Description Language), which is a modelling language for energy systems. See also:https://github.com/EnergyTransition/ESDL. +The main supported method for defining your Energy system is ESDL (Energy System Description Language), which is a modelling language for energy systems. See also: https://github.com/EnergyTransition/ESDL. With ESDL you can define assets like demands, sources, pipes, etc. and fill in their attributes. The ESDLMixin class will parse the ESDL file and utilize the attributes to build up the model representation. -This optimization package was originally developed for operational optimization and hosts two -optimization approaches 1) A MILP approach -and 2) Nonlinear Problem (NLP) approach. These two approaches were developed to run sequentially for -operational optimization. the MILP would fix the integer decision for the NLP problem, such that only the continuous variables need to be solved. The NLP -problem would then find the optimized solution with the steady-state non-linear physics included. The existing outdated (still to be updated / update in progress) documentation can be found on: http://warmingup.pages.ci.tno.nl/rtc-tools-heat-network/ +The documentation on the mathematical modelling and workflow application can be found on: +readthedocs: https://mesido.readthedocs.io/en/latest/. Installation ============ -Installation of the RTC-Tools Heat Network library is as simple as:: +Installation of the MESIDO library is as simple as:: # 1a. Use pip to install directly - pip install rtc-tools-heat-network + pip install mesido If you are going to develop and change the source code, you probably want to do something like:: # 1b. Use git clone and pip to make an editable/developer installation - git clone https://ci.tno.nl/gitlab/warmingup/rtc-tools-heat-network - pip install -e rtc-tools-heat-network + git clone https://github.com/Multi-Energy-Systems-Optimization/mesido + python -m pip install -e . -RTC-Tools Heat Network depends on `RTC-Tools `_, which is automatically installed as one of its dependencies. +MESIDO depends on `RTC-Tools `_, which is automatically installed as one of its dependencies. Running an example ================== @@ -38,26 +34,26 @@ To make sure that everything is set-up correctly, you can run one of the example These do not come with the installation, and need to be downloaded separately:: # 1. Clone the repository - git clone https://github.com/Nieuwe-Warmte-Nu/rtc-tools-heat-network.git + git clone https://github.com/Multi-Energy-Systems-Optimization/mesido.git # 2. Change directory to the example folder - cd rtc-tools-heat-network/examples/pipe_diameter_sizing/src + cd mesido/examples/pipe_diameter_sizing/src # 3. Run the example python example.py -You will see the progress of RTC-Tools in your shell. +You will see the progress in your shell. If all is well, you should see something like the following output: ![img.png](img.png) In this example.py file you can see a small workflow being set-up. The PipeDiameterSizingProblem class -inherits from (Note only the *classes are defined in rtc-tools-heat-network the others come from rtc-tools package): +inherits from (Note only the *classes are defined in MESIDO the others come from rtc-tools package): - CollocatedIntegratedOptimizationProblem: This class does all the discretization of the state variables in your problem. - *ESDLMixin: This class does the parsing and setting up of a model based on an ESDL file. - GoalProgrammingMixin: This class allows you to add Goals (objective functions) with different priorities. - LinearizedOrderGoalProgrammingMixin: This class allows you to add higher order goals (e.g. order=2) for MILP problems. -- *HeatMixin: This class adds all the heat network physics for MILP problems. +- *TechnoEconomicMixin: This class combines all the Mixin classes required for a full techno-economic optimization. Within the PipeDiameterSizingProblem class you can see that the path_goals() function is overwritten and that a path_goal with priority one is added to meet the heat demands. The definition path_goal is used @@ -74,12 +70,12 @@ Contribute You can contribute to this code through Pull Request on GitHub. Please, make sure that your code is coming with unit tests to ensure full coverage and continuous integration in the API. -GitHub: https://github.com/Nieuwe-Warmte-Nu/rtc-tools-heat-network +GitHub: https://github.com/Multi-Energy-Systems-Optimization/mesido ## Release -This package is released on pypi [here](https://pypi.org/project/rtc-tools-heat-network/) whenever a new tag is pushed. +This package is released on pypi [here](https://pypi.org/project/mesido/) whenever a new tag is pushed. In order to release this package: 1. Make sure that all relevant merge requests and commits have been merged to the master and/or poc-release branch. @@ -87,6 +83,15 @@ In order to release this package: 3. Run `git pull origin master` or `git pull origin poc-release` to pull all latest changes. 4. Run `git tag ` where `` is the new version number. 5. Run `git push origin ` to push the tag to Github. -6. Check [Github](https://github.com/Nieuwe-Warmte-Nu/rtc-tools-heat-network/actions) to confirm the release is +6. Check [Github](https://github.com/Multi-Energy-Systems-Optimization/mesido/actions) to confirm the release is processed without errors. -7. Once the release has finished, confirm the new version is available on [pypi](https://pypi.org/project/rtc-tools-heat-network/). +7. Once the release has finished, confirm the new version is available on [pypi](https://pypi.org/project/mesido/). + + +License +======= + +This code base is licensed as LGPLv3 as specified in `LICENSE`. However, the LGPLv3 license +references the GPLv3 license. As such, we have added a copy of GPLv3 as a reference in the file +`additional_info_for_license.txt`. This does NOT entail that this code base is licensed as `GPLv3`. +The copy of the `GPLv3` license is only added as a reference. diff --git a/COPYING b/additional_info_for_license.txt similarity index 99% rename from COPYING rename to additional_info_for_license.txt index f288702d2..75d176cb5 100644 --- a/COPYING +++ b/additional_info_for_license.txt @@ -1,3 +1,10 @@ +In accordance with LGPLv3, a combined work should also contain a copy of the GPLv3 license. +A copy may be found below. This is added as a reference and this does NOT license this library +as GPLv3. + + +A copy of GPLv3 as reference (copied from https://www.gnu.org/licenses/gpl-3.0.txt): + GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007 diff --git a/docs/conf.py b/docs/conf.py index 546075d92..8f76bc2a8 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -13,7 +13,7 @@ import os import sys -from rtctools_heat_network._version import get_versions +from mesido._version import get_versions import sphinx_rtd_theme @@ -21,9 +21,10 @@ # -- Project information ----------------------------------------------------- -project = 'Nieuwe Warmte Nu - Design Toolkit' -author = 'Kelbij Star, Teresa Piovesan, et al.' -review = 'Jesus Andres Rodriguez Sarasty, Ivo Pothof, Mike van Meerkerk' +project = 'Multi-Energy-Systems Integrated Design and Operations' +html_title = 'MESIDO' +author = 'Jim Rojer, Kobus van Rooyen and Femke Janssen' +review = 'Kobus van Rooyen and Femke Janssen' # -- General configuration --------------------------------------------------- @@ -32,6 +33,7 @@ # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = ['sphinx.ext.autodoc', + 'sphinx.ext.autosummary', 'sphinx.ext.intersphinx', 'sphinx.ext.todo', 'sphinx.ext.coverage', @@ -46,6 +48,13 @@ bibtex_bibfiles = ['references.bib'] +autodoc_default_options = { + 'members': True, + 'member-order': 'bysource', + 'special-members': '__init__', + 'show-inheritance': True, +} + # -- GraphViz configuration ---------------------------------- graphviz_output_format = 'svg' @@ -79,8 +88,31 @@ # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # + + html_theme = 'sphinx_rtd_theme' -html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] +# html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] +html_theme_options = { + 'analytics_id': 'G-XXXXXXXXXX', # Provided by Google in your dashboard + 'analytics_anonymize_ip': False, + 'logo_only': False, + 'display_version': True, + 'prev_next_buttons_location': 'bottom', + 'style_external_links': False, + 'vcs_pageview_mode': '', + # 'style_nav_header_background': 'ba', + # Toc options + 'collapse_navigation': False, + 'sticky_navigation': False, + 'navigation_depth': 4, + 'includehidden': False, + 'titles_only': False +} + +# html_theme_options = { +# 'navigation_depth': -1, +# +# } # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, @@ -90,6 +122,3 @@ html_css_files = [ 'css/custom.css', ] - -# Intersphinx: refer to the RTC-Tools standard library. -# intersphinx_mapping = {'rtctools': ('https://rtc-tools.readthedocs.io/en/latest/', None)} diff --git a/docs/dev_docs/component_library_milp.rst b/docs/dev_docs/component_library_milp.rst new file mode 100644 index 000000000..52e81c0f5 --- /dev/null +++ b/docs/dev_docs/component_library_milp.rst @@ -0,0 +1,22 @@ + +Component Library +================= + +internal: + + + +.. .. automodule:: mesido.pycml.component_library.milp._internal.electricity_component + :private-members: +.. automodule:: mesido.pycml.component_library.milp.__init__ + :private-members: add_variable + :exclude-members: __init__ + +.. automodule:: mesido.pycml.component_library.milp.heat._non_storage_component +.. automodule:: mesido.pycml.component_library.milp._internal.electricity_component +.. automodule:: mesido.pycml.component_library.milp._internal.gas_component + :exclude-members: __init__ +.. automodule:: mesido.pycml.component_library.milp._internal.heat_component + :exclude-members: __init__ + + diff --git a/docs/dev_docs/esdl_conversion.rst b/docs/dev_docs/esdl_conversion.rst new file mode 100644 index 000000000..dc3810d52 --- /dev/null +++ b/docs/dev_docs/esdl_conversion.rst @@ -0,0 +1,13 @@ +ESDL to MESDIO conversion +========================= + +This section shows all the convert functions available to translate an ESDL asset to an asset in MESIDO. These convert +functions take the attributes from the ESDL asset, optionally do some calculations with them, after which they are +provided as modifiers to the MESIDO asset in the component library. + +.. automodule:: mesido.esdl.esdl_model_base + :members: + :private-members: + +.. automodule:: mesido.esdl.esdl_heat_model + :members: \ No newline at end of file diff --git a/docs/dev_docs/index.rst b/docs/dev_docs/index.rst new file mode 100644 index 000000000..9822616a5 --- /dev/null +++ b/docs/dev_docs/index.rst @@ -0,0 +1,12 @@ +Developers documentation +======================== + +.. toctree:: + :maxdepth: 4 + :numbered: + :caption: Contents: + + component_library_milp + esdl_conversion + physics_mixins + workflows \ No newline at end of file diff --git a/docs/dev_docs/physics_mixins.rst b/docs/dev_docs/physics_mixins.rst new file mode 100644 index 000000000..3e21e3f55 --- /dev/null +++ b/docs/dev_docs/physics_mixins.rst @@ -0,0 +1,16 @@ +Physcis Modelling +================= + +.. autoclass:: mesido.physics_mixin.PhysicsMixin + + +.. autoclass:: mesido.heat_physics_mixin.HeatPhysicsMixin + :private-members: + +.. autoclass:: mesido.electricity_physics_mixin.ElectricityPhysicsMixin + :private-members: + +.. autoclass:: mesido.gas_physics_mixin.GasPhysicsMixin + :private-members: + + diff --git a/docs/dev_docs/workflows.rst b/docs/dev_docs/workflows.rst new file mode 100644 index 000000000..692092534 --- /dev/null +++ b/docs/dev_docs/workflows.rst @@ -0,0 +1,17 @@ + +Workflows +========= + +GROW workflow +------------- + +.. automodule:: mesido.workflows.grow_workflow + +Utils +----- + +.. automodule:: mesido.workflows.utils.adapt_profiles +.. automodule:: mesido.workflows.utils.error_types +.. automodule:: mesido.workflows.utils.helpers + + diff --git a/docs/images/Discount_factor.png b/docs/images/Discount_factor.png new file mode 100644 index 000000000..a0ffccac9 Binary files /dev/null and b/docs/images/Discount_factor.png differ diff --git a/docs/images/dH_MESIDO_10_vs_pandapipes.png b/docs/images/dH_MESIDO_10_vs_pandapipes.png new file mode 100644 index 000000000..807010355 Binary files /dev/null and b/docs/images/dH_MESIDO_10_vs_pandapipes.png differ diff --git a/docs/images/linearlines.png b/docs/images/linearlines.png new file mode 100644 index 000000000..786ddfb63 Binary files /dev/null and b/docs/images/linearlines.png differ diff --git a/docs/index.rst b/docs/index.rst index 06fd6b782..e48d971ff 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -1,15 +1,16 @@ -Design Toolkit's optimizer documentation -======================================== +Multi-Energy-Systems Integrated Design and Operations Documentation +=================================================================== -This is the documentation for optimizer routine, to optimize the conceptional design of heating networks. +This is the documentation for MESIDO. .. toctree:: - :maxdepth: 2 - :caption: Optimizer routine + :maxdepth: 4 + :caption: MESIDO theory/index + dev_docs/index support bibliography diff --git a/docs/references.bib b/docs/references.bib index 969ef3c9b..f8e928417 100644 --- a/docs/references.bib +++ b/docs/references.bib @@ -6,6 +6,39 @@ @Book{Pothof2011 isbn = {978-90-89577-018-5}, } +@article{vielma2015mixed, + title={Mixed integer linear programming formulation techniques}, + author={Vielma, Juan Pablo}, + journal={Siam Review}, + volume={57}, + number={1}, + pages={3--57}, + year={2015}, + publisher={SIAM} +} + +@article{bohm, +author = {Bøhm, Benny and Kristjansson, Halldor}, +title = {Single, twin and triple buried heating pipes: on potential savings in heat losses and costs}, +journal = {International Journal of Energy Research}, +volume = {29}, +number = {14}, +pages = {1301-1312}, +keywords = {buried heating pipes, twin pipes, triple pipes, heat losses, insulation, costs}, +doi = {https://doi.org/10.1002/er.1118}, +comment = {https://onlinelibrary.wiley.com/doi/abs/10.1002/er.1118}, +eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/er.1118}, +abstract = {Abstract In order to make district heating systems competitive in areas with single family houses or in other areas with low heat demands it is necessary to reduce the heat losses from the pipes. In recent years the twin pipe has become popular in the Nordic countries. In the article we describe how the heat loss and the heat loss coefficients can be calculated. We introduce the triple pipe with three media pipes (two supply pipes and one return pipe). The temperature dependency and the ageing of polyurethane insulation are briefly discussed. A comparison is made for different 80 mm distribution pipes and for different service pipes with respect to heat losses and to resources, i.e. materials needed for the casing and polyurethane insulation and the gravel in the excavations. For the distribution pipe we found that an egg-shaped twin pipe can reduce the heat loss by 37\% and the investments by 12\% compared with a pair of single pipes. For the service pipes we found that the triple pipe reduces the heat loss by 45\% compared with a common pair of single pipes and by 24\% compared with circular twin pipes. The reduction in investment index is 21\%. The article also addresses the question of the heat exchange between the two media pipes in a twin pipe. Copyright © 2005 John Wiley \& Sons, Ltd.}, +year = {2005} +} + +@inproceedings{drijver2019state, + title={State of the art of HT-ATES in The Netherlands}, + author={Drijver, Benno and Bakema, Guido and Oerlemans, Peter}, + booktitle={European Geothermal Congress: Proceedings, Den Haag, Netherlands}, + year={2019} +} + @Article{Boehm2000, author = {Boehm, B.}, title = {On transient heat losses from buried district heating pipes}, diff --git a/docs/support.rst b/docs/support.rst index 545791be0..e0e041e57 100644 --- a/docs/support.rst +++ b/docs/support.rst @@ -2,4 +2,5 @@ Support ####### -Raise any issue on `Github `_ such that we can address your problem. +Raise any issue on `Github `_ such that we can address your problem. + diff --git a/docs/theory/Workflows.rst b/docs/theory/Workflows.rst new file mode 100644 index 000000000..63deabdc6 --- /dev/null +++ b/docs/theory/Workflows.rst @@ -0,0 +1,109 @@ +.. _chp_workflows: + +Design Toolkit Workflows +======================== + +This page eleborates on the available Design Toolkit workflows within MESIDO. +The Design Toolkit is a subsidy funded project (NieuweWarmteNu) to help different organizatons in the district heating value chain with draft and/or conceptual designing of District Heating Systems (DHS). +For more information see : https://nwn.nu/projecten/innovaties/design-toolkit-warmtenetten/. +MESIDO is by no means limited to only these workflows, but it is left to the user itself to define the most logical workflow if the ones below are unsuitable. + +Currently two main workflows are provided: + +* EndScenarioSizing +* GrowSimulator + +These two workflows only cover the district heat network commodity for now. + +EndScenarioSizing +----------------- + +The EndScenarioSizing workflow is designed to optimize a district heating network by taking into account both asset (pipes, sources, storages, etc.) sizing and operational strategy for the lowest Total Cost of Ownership. +This workflow comes in a few variants that give the user the possibility to trade-off computational time with model assumptions. + +* EndScenarioSizing +* EndScenarioSizingNoHeatLosses +* EndScenarioSizingDiscounted +* EndScenarioSizingHeadLoss +* EndScenarioSizingHeadLossDiscounted + +EndScenarioSizing +~~~~~~~~~~~~~~~~~ + +The EndScenarioSizing workflow in short: + +* The user needs to provide a district heating network in an ESDL file format which will contain: + * The existing as well as the potential assets of the system. + * User specified cost coefficients for all the assets (e.g. EUR/MW for sizing of source). + * User specified maximum sizes of the assets (e.g XX MW for sources, DN 400 for a pipe). + * User specified demand profiles, in hourly resolution for a full year, at all the demands in the system. +* The optimization routine will start by matching all the heat demands. +* After matching the demands the system cost is minimized, where both CAPEX and OPEX over the lifetime are minimized. This allows the optimizer to make trade-offs between investments and potential operational benefits (and vice-versa). +* A representative year is employed and the results are extrapolated to approximate cost over the lifetime. +* A smaller mathematical representation of the optimization problem is created by utilizing a time horizon with a default 5 day timestep size, except for the peak day which has an hourly resolution. + * The hourly resolution in the peak day is used to ensure that the system is sized to satisfy the demands under a maximum load condition. + * The 5 day timesteps are used for the remainder of the year to approximate the OPEX of the system by utilizing the averaged thermal powers. + * This also means that all time-series results will be in this adapted time-line. + +A two stage optimization approach is used for faster optimization. +In the first stage the system is optimized without heat losses in the network. +This allows for a much easier mathematical representation of the problem an hence a much faster optimization. +In the second stage the heat losses in the network are taken into account, however now the problem is bounded with the information of the first stage. +Pipes will only be allowed to be at least as large as the result of the first stage or one DN size larger. +Furthermore, the flow directions will be utilized if the flow meets a minimum threshold value. +Lastly, sources placed in the first stage will also be placed in the second stage. + +In its default configuration the workflow has the following main assumptions: + +* The whole network is realized instantaneously, as a single year is optimized and extrapolated for the lifetime. + * In reality the realization of DHS is done in phases over a period of years. Hence this assumption is not valid, but allows the user to judge the long term feasibilty of the DHS system. For closing business case computation the effects of phased realization should be taken into account. +* Pressure drops are not taken into account. However, a maximum flow velocity of 3 m/s is used for each pipe. + * This assumptions is sufficient when the user is still in a phase where the exact location of (booster-)pumps is to be determined and hence limiting the sizing of pipes with pressure drop calculations would not be representative. + * Note that EndScenarioSizingHeadLoss can be used when the user wants the pressure drop functionality. +* Investment costs are not discounted and all assets depreciate to zero over the system lifetime. + * This assumption comes out of an initial development phase, but now EndScenarioDiscounted can be used to consider discount rates and depreciation periods of assets. +* It is assumed that the user provides sufficient possibilities to the optimizer to match the heat demands. + * The optimization will become significantly slower in scenarios where the demands cannot be satisfied. If the user cannot garuantee to have sufficient assets to fullfill the demand, it is advised to use slack (peak) sources. +* It is assumed that the tank storage in the network can only be used for intra day buffering and hence can only be used by the optimizer for the peak day. + * If this assumption is not valid an extension of the workflow is required. +* It is assumed that the seasonal storage is cyclic over a calendar year. This implies that the stored thermal energy at the beginning and at the end of the year is the same. + * This assumption is required to ensure that the results of a single year can be extrapolated over the lifetime. + +For the assumptions on the physics and cost modelling the reader is referred to the respective modelling pages. + +EndScenarioSizingNoHeatLosses +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +The EndScenarioSizingNoHeatLosses workflow provides all the same functionality as the standard EndScenarioSizing, except that heat losses in the network are excluded. +This means that the required thermal energy of the system is underestimated and hence mainly the OPEX will be underestimated. +This workflow has the advantage that it is much faster (typically > factor 10) than the default EndScenarioSizing. +Therefore, it is recommended to use this workflow in the initial phases of analysis with larger networks. +This workflow will allow the user to make quicker iterations on the input ESDL file and debug possible errors in a shorter time-frame. + +EndScenarioSizingNoHeatLosses workflow should not be used as a replacement of the EndScenarioSizing workflow as heat losses can be up to 30% of the demand and should not be neglected for design. + + +EndScenarioSizingDiscounted +~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +The time value of money and the depreciation periods of assets are critical aspects of long-term financial planning. To account for these elements, this workflow specifies the Equivalent Annual Cost (EAC) in the objective function. +The EndScenarioSizingDiscounted workflow includes everything provided by the EndScenarioSizing workflow, with the addition of: + +* The ability to account for different depreciation periods of assets in the system. +* The ability to apply a CAPEX discount rate to assets to calculate their EAC. + +Additional details on the annualized cost calculations are discussed in the :ref:`discounted-cost-section` section. + +EndScenarioSizingHeadLoss +~~~~~~~~~~~~~~~~~~~~~~~~~ + +The EndScenarioSizingHeadLoss provides everything the EndScenarioSizing workflow provides, with the addition of: + +* Taking into account the pressure drops in the network. +* Computing the hydraulic power and thereby the pumping power. It is assumed that every source will have a pump. The pumping cost will be computed with the electricity price profile if an electricity carrier is specified in the ESDL file. + +EndScenarioSizingHeadLossDiscounted +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +The EndScenarioSizingHeadLossDiscounted workflow combines the added functionality of EndScenarioSizingDiscounted and EndScenarioSizingHeadLoss into one workflow. + diff --git a/docs/theory/asset_sizing.rst b/docs/theory/asset_sizing.rst new file mode 100644 index 000000000..c0b345a61 --- /dev/null +++ b/docs/theory/asset_sizing.rst @@ -0,0 +1,154 @@ +.. _chp_asset_sizing: + +Asset Sizing +============ + +MESIDO supports both the placing and sizing decisions. +Where placement is the integer decision if an optional location is selected or not. +The integer for whether or not an asset is placed is governed based on whether or not power is exchanged between the asset and other assets over the time horizon, see: + +.. math:: + :label: eq:max_placed_power + + \dot{Q}^{a}_{max}-q^{a}_{max}\delta^{a}_{placed} \leq 0 \;\; + +.. math:: + :label: eq:min_placed_power + + -\dot{Q}^{a}_{max}-q^{a}_{min}\delta^{a}_{placed} \leq 0 \;\; + +.. math:: + :label: eq:placement_variable + + \delta^{a}_{placed} \in \{0,1\} \;\; + +Where :math:`(q^{a}_{min}, q^{a}_{max})` are the lower and upper bounds of the power. + +For the sizing MESIDO supports three general methods, which can be applied to different assets depending on the physics. + +Continious Sizing +----------------- + +If an asset is continuously sized then the max size variable, :math:`x^{a}_{max}`, must be larger than the state, :math:`x^{a}`, (e.g. power) for every time step. + +.. math:: + :label: eq:limit_power_ates + + -x^{a}_{max}\leq x^{a} \leq x^{a}_{max} + +Sizing With Aggregation +----------------------- + +If an asset is sized based on its aggregation count, then the max size variable, :math:`x^{a}_{max}`, +will be bounded based on the amount of aggregations that exist for that asset. +Examples include the sizing of geothermal sources by their amount of wells, with the power per well. + +.. math:: + :label: eq:aggregationcount + + x^{a} \leq \delta^{a}_{aggr\_count} X^{a}_{single,max} + +Sizing With Integer Modelling +----------------------------- + +The integer method can be used if the size of the asset is determined by a number of predefined sizes, :math:`\delta_{j,a}`. +Of all the availabe options a single option should be selected. + +.. math:: + :label: eq:pipe_size_selection + + \sum_{j\in S^{a}} \delta_{j,a} = 1 \;\; + +where: + +.. math:: + :label: eq:pipe_size_variable + + \delta_{j,a} \in \{0,1\} \;\; \forall j \in S^{a} + +The sizing integer can then be used to limit the max size variable, e.g. max flow for a pipe. + +.. math:: + :label: eq:flow_restric_pipe + + x^{a}_{max} - \sum_{j\in S^{a}} \bar{e_j}\delta_{j,a} \leq 0 \;\; + +where :math:`\bar{e_j}` denotes the max value for the state at that sizing option. + +Asset sizing methods employed +----------------------------- + +.. list-table:: Asset Sizing Model + :widths: 25 25 25 25 50 + :header-rows: 1 + + * - Asset + - Sizing Constraints type + - Max Size variable + - Unit + - Notes + * - Heat source + - Continuous + - Max thermal power produced + - Watt + - ~ + * - Heat demand + - Continuous + - Max thermal power consumed + - Watt + - ~ + * - Heat storage: Tank + - Continuous + - tank size + - m3 + - ~ + * - Heat Storage: HT-ATES + - Aggregation Count + - Max thermal power produced + - [-] + - ~ + * - Geothermal (extension source) + - Aggregation Count + - Max thermal power produced + - [-] + - ~ + * - Heat Exchanger + - Continuous + - Max thermal Secondary Power + - Watt + - ~ + * - Heat Pump + - Continuous + - Max thermal Secondary Power + - Watt + - ~ + * - Heat Exchanger + - Continuous + - Max thermal Secondary Power + - Watt + - ~ + * - Heat/Gas Pipe + - Integer + - Diameter + - [-] + - Constraints on max flow and insulation materials. + * - Electricity source + - Continuous + - Max electrical power produced + - Watt + - ~ + * - Electricity demand + - Continuous + - Max electrical power consumed + - Watt + - ~ + * - Gas source + - Continuous + - Max max flow produced + - Watt + - ~ + * - Gas demand + - Continuous + - Max mass flow consumed + - Watt + - ~ diff --git a/docs/theory/code_structure.rst b/docs/theory/code_structure.rst new file mode 100644 index 000000000..4ae102cdd --- /dev/null +++ b/docs/theory/code_structure.rst @@ -0,0 +1,34 @@ +.. _chp_code_structure: + +Code Structure +============== + +Rtc-tools is used as the framework to define optimization problems, https://gitlab.com/deltares/rtc-tools. +Rtc-tools is a tool-box in which time-horizon optimization problems can be defined. It utilizes the Casadi package to parse the problems in formats that allow solvers such as Highs and Gurobi to solve the problem. +Internally rtc-tools makes heavy use of the python mixin (inheritance) structure, which results that MESIDO also adheres to the mixin structure that rtc-tools uses. + +Although the full structure is even more elaborate, the basic methods in the mixin are: + +* read: In this method all parsing of data files containing relevant information for the problem should be done, e.g. price profiles. +* times: In this function the time horizon is defined/adapted, note varying timestep size is supported. +* pre: In this method all variables and other operations needed before constraints and goals can be defined should be done. +* (path) constraints: In this method the constraints should be added to the problem, the path constraints are those applied to states which exist in every timestep. +* (path) goals: In this method the goals should be added to the problem, the path goals are those applied to states which exist in every timestep. +* optimize: Here the problem is transcribed and parsed to the solver (this method is never modified in MESIDO). +* post: In this method optional post processing including checks on the outcome of the optimization can be preformed. + +MESIDO offers a toolbox for optimization of multi energy systems with the following mixins: + +* PyCMLMixin: This mixin allows users to define component models with easy functions for adding variables and parameters. +* ESDLMixin: This mixin reads ESDL files and constructs a network model using the asset models defined in PyCML +* PhysicsMixin: This mixin adds constraints for the modelling of physics in asset components or interaction between assets. The PhysicsMixin inherits the individual commodity mixins and adds physics where interaction between the commodities exists. + * HeatPhysicsMixin: Adds physics for the modelling of district heating systems. + * ElectricityPhysicsMixin: Adds physics for the modelling of electricity grids. + * GasPhysicsMixin: Adds physics for the modelling of networks with gaseous mediums, e.g. natural gas or hydrogen. +* AssetSizingMixin: Adds variables and constraints allowing for the sizing and placement of assets in the energy system. +* FinancialMixin: Adds variables and constraints for financial computations, like OPEX, CAPEX and revenues. + +There are also workflows (which technically are also mixins) next to these toolbox mixins that MESIDO offers. The default workflows available are: + +* EndScenarioSizing: This workflow will optimize the energy system for total tost of ownership. +* GROWSimulator: This workflow allows one to do operational analysis with a source merit order usage strategy, where the use of sources is minimized in the reverse merit order to mimick simulator like behaviour. diff --git a/docs/theory/electricity_physics.rst b/docs/theory/electricity_physics.rst new file mode 100644 index 000000000..68cf23783 --- /dev/null +++ b/docs/theory/electricity_physics.rst @@ -0,0 +1,115 @@ +.. _chp_electricity_physics: + +Electricity Physics +=================== + +MESIDO models the electric power (:math:`\dot{P}`), the voltage (:math:`V`) and the current +(:math:`I`). +These variables are modelled over all timesteps :math:`K` and for each asset in the system +:math:`A`. +An asset :math:`a \in A` in the system is modelled using a set of in-ports, denoted by +:math:`I^a_{in} \neq \emptyset`, and a set of out-ports, denoted by +:math:`I^a_{out} \neq \emptyset`, with :math:`I^a` denoting the union of these two sets. +For an asset :math:`a` the variables :math:`\dot{P}_i, V_i` and +:math:`I_i` denote the electrical power, voltage and current for port :math:`i \in I^a`. +For readability, the variables and equations of the model, given below, are defined without +indexing the variables and sets for each timestep. +The equations below are assumed to hold for every timestep, unless otherwise specified. + +By modelling these variables the electrical power system can be approximated. + +General Physics +--------------- + +For all assets energy conservation should be guaranteed. + +.. math:: + :label: eq:Q_balance + + \sum_{i \in I} \dot{P}_i + \dot{P}^a_{consumed} = 0 \;\; \forall a \in A + +Where :math:`\dot{P}^a_{consumed}` is the electrical power consumed by asset :math:`a`. + +Network Physics +--------------- + +Electricity Cable +~~~~~~~~~~~~~~~~~ + +The main function of an electricity cable is to transport electrical power over the network. +Whilst doing so the cable dissepates part of this energy due to the resistance of the cable. +Within MESIDO the user can select whether or not to model this power loss (energy_system_options -> include_electric_cable_power_loss). When power loss is included it is represented with a DC (direct current) approximation as follows. + +.. math:: + :label: eq:V_drop + + V^a_{out} = V^a_{in} - r^a I \;\; \forall a \in A_{cables} + +.. math:: + :label: eq:P_drop + + P^a_{out} = P^a_{in} - r^a I^a_{max} I^a \;\; \forall a \in A_{cables} + +Where :math:`r^a` denotes the resistance of the cable and :math:`I_{max}` denotes the max current +of the cable. The linearization of the power loss is done using the max current to ensure a +conservative approximation of the power throughout the network. + +Bus +~~~ + +A bus is a point in the network where multiple electricity cables come together to ensure an +electrically feasible solution. The voltages of all these ports should be equal (similar with head at a node). + +.. math:: + :label: eq:bus_V + + V_i = V^a \;\; \forall i \in I^a \;\; a \in A_{busses} + + +Asset Physics +------------- + +Electricity Source +~~~~~~~~~~~~~~~~~~ + +The function of an electricity source is to add electrical power to the network. +The power balance is given by :eq:`eq:Q_balance` where :math:`\dot{P}_{consumed}` is equal to the +(negative) produced power of the source. + +Electricity Demand +~~~~~~~~~~~~~~~~~~ + +The function of an electricity demand is to subtract electrical power from the network. +The power balance is given by :eq:`eq:Q_balance` where :math:`\dot{P}_{consumed}` is equal to the +consumed power of the demand. + +Furthermore, demands typically consume their power at a prescribed voltage. + +.. math:: + :label: eq:V_min + + V^a_i = V_min \;\; \forall i \in I^a \;\; a \in A_{electricity demands} + +Electricity storage +~~~~~~~~~~~~~~~~~~~ + +Storage assets add time flexibility with the production and consumption of electrical power. +Batteries are typically used for the storage of electrical energy. + +:math:`\dot{P}^{a}_{consumed}` can be defined by the electical power substracted from or added to the +network, where the internal losses of the storage are subtracted: + +.. math:: + :label: eq:change_stored_gas + + \dot{P}^{a}_{consumed} = \sum_{i \in I^a_{in}} \dot{P}^{a}_{i} - \sum_{i \in I^a_{out}} \dot{P}^{a}_{i} - \dot{P}^{a}_{loss} \;\; \forall a \in A_{storage}. + +The consumed power of the storage assets is equated to the change in stored energy, :math:`\dot{P}^{a}_{stored}`: + +.. math:: + :label: eq:stored_gas + + \dot{P}^{a}_{consumed} = \dot{P}^{a}_{stored} \;\; \forall a \in A_{storage} + +Upcoming: ADD THE ENERGY LOSS MODEL + diff --git a/docs/theory/financial.rst b/docs/theory/financial.rst new file mode 100644 index 000000000..43383759a --- /dev/null +++ b/docs/theory/financial.rst @@ -0,0 +1,132 @@ +.. _chp_financial: + +Financial +========= + +MESIDO offers the posibility to model the cost and revenues based on the design and operation of the energy system. +The asset cost modelling includes both the CAPEX and OPEX over the time-horizon of the optimization. + +Asset Cost Components +--------------------- + +The asset cost modelling breaks down in four categories in which both the CAPEX and OPEX aspects are captured: + +- installation cost +- investment cost +- variable operational costs +- fixed operational cost + +These four categories help the optimizer in making both continuous and integer sizing decisions. + +Installation Cost +~~~~~~~~~~~~~~~~~ + +Installation cost is part of the CAPEX and is the fixed amount of cost required to place :math:`\delta^{a}_{aggr\_count}` units (aggregation count) of the asset :math:`a`. +This cost component helps the optimizer make asset placement decisions when several equivalent asset options are available. + +.. math:: + :label: eq:installation + + Cost^{a}_{installation} = C^{a}_{install} \delta^{a}_{aggr\_count} + +Investment Cost +~~~~~~~~~~~~~~~ + +The investment cost is the CAPEX required that scales with the asset size. +The investment cost is the cost component that helps to find the minimum asset sizes. + +.. math:: + :label: eq:invest + + Cost^{a}_{investment} = C^{a}_{invest} x^{a}_{max} + + +Variable Operational Cost +~~~~~~~~~~~~~~~~~~~~~~~~~ + +The variable operational cost is the cost component that depends on the usage of the asset over the time horizon. +Typically this is a power consumption or production, which is represented by :math:`x^{a}_{use}`. + +.. math:: + :label: eq:varopex + + Cost^{a}_{variable} = \sum_{K} C^{a}_{variable} x^{a}_{use} \Delta T_K + + +Fixed Operational Cost +~~~~~~~~~~~~~~~~~~~~~~ + +The fixed operational cost is the cost component that returns every X time (typically every calendar year) based on the size of the asset. + +.. math:: + :label: eq:fixedopex + + Cost^{a}_{fixed} = C^{a}_{fixed} x^{a}_{max} + +Total Cost Calculation +---------------------- + +The total cost is defined as the sum of CAPEX and OPEX over the set of assets in the optimization problem, as follows: + +.. math:: + :label: eq:totalcost + + Cost_{total} = \sum_{a} (Cost^{a}_{CAPEX} + Cost^{a}_{OPEX}) + +where the CAPEX is the sum of the installation and investment costs, i.e., + +.. math:: + :label: eq:capex_no_discount + + Cost^{a}_{CAPEX} = \sum_{a} (Cost^{a}_{investment} + Cost^{a}_{installation}), + +and the OPEX is the sum of the variable and fixed operational costs, i.e., + +.. math:: + :label: eq:opex + + Cost^{a}_{OPEX} = \sum_{a} (Cost^{a}_{fixed} + Cost^{a}_{variable}) + +.. _discounted-cost-section: + +Annualized Discounted Costs Calculation +--------------------------------------- + +Discounted cost calculations account for the time value of money, which reflects the principle that money available today is worth more than the same amount in the future due to its potential earning capacity. Discounted costs are commonly used for evaluating investment decisions. + +Since assets may have different depreciation periods, an Equivalent Annual Cost (EAC) provides a standardized comparison by converting the total cost of ownership to an annualized figure that accounts for both the time value of money and the different lifetimes of assets. + +Given that the OPEX :math:numref:`eq:opex` is already calculated on an annual basis, only the CAPEX needs to be converted to an annualized equivalent value using an EAC factor :math:`F_{a}`. This factor is computed as based on a discount rate (as an annual percentage) and the technical life (in years) of the asset, as follows: + +.. math:: + F_{a} = + \begin{cases} + \frac{1}{n} & \text{if } r = 0 \\ + \frac{r}{1 - (1 + r)^{-n}} & \text{if } r > 0 + \end{cases} + + +See this `link `_ for more details. + +This EAC factor, :math:`F_{a}`, is then applied to the asset's CAPEX to calculate the EAC of the initial investment or installation cost, as follows: + +.. math:: + :label: eq:capex_eac + + Cost^{a}_{CAPEX_{EAC}} = (Cost^{a}_{investment} + Cost^{a}_{installation}) * F_{a} + +Therefore, the discounted total cost becomes: + +.. math:: + :label: eq:total_eac + + Cost_{total_{EAC}} = \sum_{a} (Cost^{a}_{CAPEX_{EAC}} + Cost^{a}_{OPEX}) + +Note that the annual discount rate is a real number between 0 and 1. For instance, a discount rate of 5% should be specified as 0.05. +The technical life is a real number greater than 0. Both the discount rate and the technical life of assets can significantly affect the EAC of an asset, as shown below, where the inverse :math:`F_{a}` factor is plotted. + +.. figure:: ../images/Discount_factor.png + :figwidth: 6.94792in + :align: center + + Inverse Equivalent Annual Cost factor ( :math:`F_a^{-1}` ) versus discount rate ( `r` ) for different technical life values. diff --git a/docs/theory/gas_physics.rst b/docs/theory/gas_physics.rst new file mode 100644 index 000000000..333641946 --- /dev/null +++ b/docs/theory/gas_physics.rst @@ -0,0 +1,215 @@ +.. _chp_gas_physics: + +Gas Physics +=========== + +MESIDO models the volumetric flow (:math:`\dot{V}`), the mass flow (:math:`\dot{m}`), the head +(:math:`H`) and the hydraulic power (:math:`HP`). +These variables are modelled over all timesteps :math:`K` and for each asset in the system +:math:`A`. +An asset :math:`a \in A` in the system is modelled using a set of in-ports, denoted by +:math:`I^a_{in} \neq \emptyset`, and a set of out-ports, denoted by +:math:`I^a_{out} \neq \emptyset`, with :math:`I^a` denoting the union of these two sets. +For an asset :math:`a` the variables :math:`\dot{V}_i, \dot{m}_i`, +:math:`H_i` and :math:`HP_i` denote the volumetric flow, mass flow, head and hydraulic power for port :math:`i \in I^a`. +For readability, the variables and equations of the model, given below, are defined without +indexing the variables and sets for each timestep. +The equations below are assumed to hold for every timestep, unless otherwise specified. + +By modelling these variables the gaseous system can be closely approximated. The method will show that for the modelling assumptions a feasible conservative solution will be guaranteed. + +Incompressible Flow +------------------- + +Under incompressible flow assumption the volumetric- and mass flow for every asset should equate to zero. + +.. math:: + :label: eq:Q_balance + + \sum_{i \in I} \dot{V}_i + \dot{V}^a_{consumed} = 0 \;\; \forall a \in A. + +.. math:: + :label: eq:m_balance + + \sum_{i \in I} \dot{m}_i + \dot{m}^a_{consumed} = 0 \;\; \forall a \in A. + +:math:`\dot{V}^a_{consumed}` and :math:`\dot{m}^a_{consumed}` are the volumetric- and mass flow consumed by asset :math:`a`. + +Network Physics +--------------- + +Pipe +~~~~ +The main function of a pipe is to transport gas mass. +In reality it loses part of this mass as the pipe is pressurized and has small leaks. +Within MESIDO it is assumed that these leaks are small and are neglected in the optimization. + +Equality constraints are used to relate the volumetric flow to the mass flow. + +.. math:: + :label: eq:vol_to_mass + + \dot{m}^a = \rho \dot{V}^a \;\; \forall a \in A_{pipes}. + +Where :math:`\rho` is the density of the medium which is assumed constant in one hydrualic +coupled system and is set based on the design nominal pressure in the system. + +The head loss, :math:`dH` must be compensated by pumps which are assumed to be located at sources +and storage assets. + +.. math:: + :label: eq:gas_pipe_head + + H^a_{in} - dH = H^a_{out} \;\; \forall a \in A_{pipes}. + +Steady-state head losses can be closely modelled with a quadratic relation w.r.t. :math:`\dot{V}`. +A set of linear inequalities is used, see :numref:`inequalitydH`, to approximate the quadratic curve. +The general form of the inequalities is given below in :eq:`eq:pipe_head_loss1`-:eq:`eq:pipe_head_loss2`. +Note that the big M method is used with the flow direction and disconnected integers to allow for +modelling of bi-directional flow and the ability to disconnect pipes. + +.. math:: + :label: eq:gas_pipe_head_loss1 + + dH - (\alpha_j \dot{V} + \beta_j) + (\delta^a_{discon} + \delta^a_{dir})M\geq 0 \\ \forall (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:gas_pipe_head_loss2 + + dH + (\alpha_j\dot{V} + \beta_j) - (\delta^a_{discon} + (1-\delta^a_{dir}))M\leq 0 \\ \forall (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}. + +Where :math:`(\alpha_j, \beta_j)` are the coefficients and constants of the linear equations used to approximate the quadratic equation. + +These inequalities force the head loss to be greater or equal to the approximated quadratic curve. +Although the constraints by themselves will not guarantee a physically feasible answer, the optimization will in drag the solution to an equality constraint as the objective function will minimize cost which reduces with lower pressure drop. + +.. _inequalitydH: + +.. figure:: ../images/linearlines.png + :figwidth: 6.94792in + :align: center + + Schematic visualization of how the linear constraints are fitted to the gas pipe head loss curve. + +Similar as with head loss the hydraulic power, :math:`HP^a`, required to overcome the head losses is modelled with a set of linear inequalities: + +.. math:: + :label: eq:gas_pipe_hp1 + + HP^a - (c_j\dot{V} + d_j) + (\delta^a_{discon} + 1-\delta^a_{dir})M \geq 0 \\ + \forall (c_j, d_j) \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:gas_pipe_hp2 + + HP^a - (c_j\dot{V} + d_j) - (\delta_{discon}(k) - 1-\delta_{dir})M\geq 0 \\ + \forall (c_j, d_j) \;\; \forall a \in A_{pipes}. + +Here :math:`(c_j, d_j)` are the coefficients and constants of the linear equations used to approximate the quadratic equation. + +The method with linear inequalities, as represented above, is only valid when each possible unique flow path route in the network has a control valve to compensate non-physical head loss induced by the optimizer. Alternatively a (piece-wise) linear equality constraint between min and max flow rate can be configured for cases where this assumption is invalid, with the general form represented by :eq:`eq:pipe_head_loss3`-:eq:`eq:pipe_head_loss6`. + +.. math:: + :label: eq:gas_pipe_head_loss3 + + dH - (\alpha_j \dot{V} + \beta_j) + (\delta^a_{discon} + \delta^a_{dir} + (1 - \delta^a_{line\_seg_{k}}))M\geq 0 \\ \delta^a_{line\_seg_{k}} \in \{ 0, 1 \}, (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:gas_pipe_head_loss4 + + dH - (\alpha_j\dot{V} + \beta_j) - (\delta^a_{discon} + \delta^a_{dir} + (1 - \delta^a_{line\_seg_{k}}))M\leq 0 \\ \delta^a_{line\_seg_{k}} \in \{ 0, 1 \}, (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:gas_pipe_head_loss5 + + dH + (\alpha_j \dot{V} + \beta_j) - (\delta^a_{discon} + (1 - \delta^a_{dir}) + (1 - \delta^a_{line\_seg_{k}}))M\leq 0 \\ \delta^a_{line\_seg_{k}} \in \{ 0, 1 \}, (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:gas_pipe_head_loss6 + + dH + (\alpha_j\dot{V} + \beta_j) + (\delta^a_{discon} + (1-\delta^a_{dir}) + (1 - \delta^a_{line\_seg_{k}}))M\geq 0 \\ \delta^a_{line\_seg_{k}} \in \{ 0, 1 \}, (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}. + +Where :math:`(\alpha_j, \beta_j)` are the coefficients and constants of the linear equations used to approximate the quadratic equation. Variable :math:`\delta^a_{line\_seg_{k}}` reperesents an integer, for pipe :math:`a`, value indicating if a linear line segment :math:`k` is active (value = 1) or not (value = 0). This would imply that if a quadratic curve is represented by 3 linear lines for instance, then only 1 of the linear lines are appplicable at a specific timestep. + + +Node +~~~~ + +The node conserves the flow with :eq:`eq:Q_balance` and the energy with :eq:`eq:m_balance`. + +The head of all pipes connected to the node must be equal to ensure a hydraulically feasible solution: + +.. math:: + :label: eq:gas_node_head + + H_i = H^a \;\; \forall i \in I^a \;\; a \in A_{nodes}, + +where :math:`A_{nodes}` is the set of all nodes and :math:`H^a` is the headloss for node :math:`a`. + + +Asset Physics +------------- + +Source +~~~~~~ + +The source adds gas mass to the network. +The volumetric- and mass flow balance is given by :eq:`eq:Q_balance` and :eq:`eq:m_balance` where +:math:`\dot{V}^a_{consumed}` and :math:`\dot{m}^a_{consumed}` is equal to the (negative) value of the supplied gas to the network. + +A source is modelled with a pump to reach its desired flow rate and head: + +.. math:: + :label: eq:gas_source_pump_dh + + H^a_{pump} = H^a_{out} \;\; \forall a \in A_{prod}. + +Demand +~~~~~~ + +A demand extracts gas from the network, defined by :eq:`eq:Q_balance` and :eq:`eq:m_balance` where +:math:`\dot{V}^a_{consumed}` and :math:`\dot{m}^a_{consumed}` are the consumed gas from the network. + +Every demand is modelled with a control valve to regulate its flow. In reality a minimum head loss is often maintained: + +.. math:: + :label: eq:gas_demand_head + + H_{connected} - dH_{valve} = H^a_{out} \;\; \forall a \in A_{demand}. + +Where :math:`H_{connected}` is the head at the port of the connected asset (normally a pipe). + +Storage +~~~~~~~ + +Storage assets add time flexibility with the production and consumption of gas. For shorter +intra-day periods this capability is provided by tanks, alternatively storage over seasons is done +with underground storage like salt caverns. + +:math:`\dot{m}^{a}_{consumed}` can be defined by the gas mass substracted from or added to the +network, where the internal losses of the storage are subtracted: + +.. math:: + :label: eq:change_stored_gas + + \dot{m}^{a}_{consumed} = \sum_{i \in I^a_{in}} \dot{m}^{a}_{i} - \sum_{i \in I^a_{out}} \dot{m}^{a}_{i} - \dot{m}^{a}_{loss} \;\; \forall a \in A_{storage}. + +The consumed mass of the storage assets is equated to the change in stored gas mass, :math:`\dot{m}^{a}_{stored}`: + +.. math:: + :label: eq:stored_gas + + \dot{m}^{a}_{consumed} = \dot{m}^{a}_{stored} \;\; \forall a \in A_{storage} + +Compressor and Sub-station/control-valve +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +The compressor and sub-station are used to change the nominal pressure level in the system. +This means that these assets will have a different pressure level and thus density on their in port +w.r.t. their out port. +It is assumed that mass is maintained over the pressure step. + +.. math:: + :label: eq:mass_balance_pressure_level + + \sum_{i \in I^a_{in}} \dot{m}^{a} = \sum_{i \in I^a_{in}} \dot{m}^{a}\;\; \forall a \in A_{Compressor, sub-station} + diff --git a/docs/theory/heat_physics.rst b/docs/theory/heat_physics.rst new file mode 100644 index 000000000..c911d293e --- /dev/null +++ b/docs/theory/heat_physics.rst @@ -0,0 +1,395 @@ +.. _chp_heat_physics: + +Heat Physics +============ + +MESIDO models thermal power (:math:`\dot{Q}`), volumetric flow (:math:`\dot{V}`), and head (:math:`H`) for DHS systems. +These variables are modelled over all timesteps :math:`K` and for each asset in the system :math:`A`. +An asset :math:`a \in A` in the system is modelled using a set of in-ports, denoted by :math:`I^a_{in} \neq \emptyset`, and a set of out-ports, denoted by :math:`I^a_{out} \neq \emptyset`, with :math:`I^a` denoting the union of these two sets. +For an asset :math:`a` the three variables :math:`\dot{Q}_i, \dot{V}_i`, and :math:`H_i` denote the thermal power, volumetric flow and head for port :math:`i \in I^a`. For readability, the variables and equations of the model, given below, are defined without indexing the variables and sets for each timestep. +The equations below are assumed to hold for every timestep, unless otherwise specified. + +Modelling specifically these three variables allows to ensure a hydraulically feasible solution whilst linearizing the physics. +Energy changes are modelled with the assumption of a constant temperature throughout the network. +Although this assumption is not realistic, the linearizations made will show that the effects of these assumptions are relatively small and conservative to the objective function outcome. + +General Physics +--------------- + +The DHS is modelled as a closed loop system and thus at every timestep and for every asset, mass balance should hold. +The system is modelled with constant temperature and thus constant density and specific heat. +The mass balance is provided as a volumetric flow balance in :eq:`eq:flow_balance`. + +.. math:: + :label: eq:flow_balance + + \sum_{i \in I^a} \dot{V}_{i} = 0 \;\; \forall a \in A + + +The energy balance is guaranteed by :eq:`eq:general_energy_balance`. + +.. math:: + :label: eq:general_energy_balance + + \sum_{i \in I} \dot{Q}_i + \dot{Q}^a_{consumed} = 0 \;\; \forall a \in A + +:math:`\dot{Q}^a_{consumed}` is the thermal power consumed by asset :math:`a`. +The power losses for the asset are included in this variable. + +Network Physics +--------------- + +Pipe +~~~~ +The main function of a pipe is to transport thermal power. +It loses part of this thermal power to the surroundings as the ambient temperature is lower, thus :math:`\dot{Q}^a_{consumed}` equals the (negative) losses incurred in the pipe in :eq:`eq:general_energy_balance`. + +The thermal power losses are approximated with :eq:`eq:heat_loss`, utilizing the Bohm model, :cite:`bohm`. + +.. math:: + :label: eq:heat_loss + + \dot{Q}^a_{consumed} = L^a( (U_2 - U_1)T_{amb} + U_1 T_{sup} - U_2 T_{ret})\delta^a_{discon} \forall a \in A_{pipes} + +where + +.. math:: + :label: eq:pipe_heat_loss_U1 + + U_1 = \frac{R_{subsoil} + R_{ins}}{(R_{subsoil} + R_{ins})^2 - R_{neighbour}^2} + +.. math:: + :label: eq:pipe_heat_loss_U2 + + U_2 = \frac{R_{neighbour}}{(R_{subsoil} + R_{ins})^2 - R_{neighbour}^2} + +.. math:: + :label: eq:pipe_heat_loss_Rins + + R_{ins} = \sum_i \frac{ln(\frac{d^a_{outer}}{d^a_{inner}})}{2\pi k} + +.. math:: + :label: eq:pipe_heat_loss_Rneigh + + R_{neighbour} = \frac{ln(1 + (2H/2d^a_{outer})^2)}{4 \pi k_{subsoil}}, + +.. math:: + + R_{subsoil} = \frac{ln(\frac{4H}{d^a_{outer}})}{2 \pi k_{subsoil} }. + +.. math:: + + \delta^a_{discon} \in \{0, 1\} \;\; \forall a \in A_{pipes} + +:math:`T_{sup}, T_{ret}`, and :math:`T_{amb}` represent the supply, return and ambient temperatures. +:math:`A_{pipes}` define the set of pipes with :math:`L^a` being the length of pipe :math:`a`. +:math:`\delta^a_{discon}` is a boolean variable to model if pipe :math:`a` is in use for a specific timestep. +:math:`d^a_{inner}` and :math:`d^a_{outer}` are the inner and outer diameters of pipe :math:`a` and :math:`k_{subsoil}` is a constant used to model the resistance of the subsoil. +:math:`\delta^a_{discon}` is modelled by: + +.. math:: + + \dot{Q}_{i} + \delta_{discon}M \geq 0 \;\; \forall i \in I^{a} \;\; \forall a \in A_{pipes}, + +.. math:: + + \dot{Q}_{i} - \delta_{discon}M \leq 0 \;\; \forall i \in I^a \;\; \forall a \in A_{pipes}. + +Here :math:`M` is a sufficiently large constant used in a method called the big-M method :cite:`vielma2015mixed` to enable or disable a constraint. + +The thermal power loss is assumed to be constant as the pipe temperature is assumed to be constant. +The outgoing temperatures at the assets (e.g. supply at the source and return at the demand) are used to ensure an overestimation of the thermal loss. In reality the temperature w.r.t. the ambient decreases as the temperature drops over the pipe with the energy loss. + +Typical temperature drops in the primary network are up to 3 degrees, this implies that for medium temperature networks, operating at 75°C and with an ambient of 15°C, the error for the heat loss estimation is less than :math:`\frac{3}{75-15} \approx 5\%`. + +Inequality constraints are used to relate the volumetric flow :math:`\dot{V}` and the heat flow :math:`\dot{Q}` through pipes as a compensation of heat losses is required. +Please note that the :math:`\dot{V}` and the heat flow :math:`\dot{Q}` will be related by equality constraints for the outgoing flow at the assets, ensuring that the thermal power propagates correctly through the network. + +.. math:: + :label: eq:pipe_heat2discharge1 + + \dot{Q}_{i} - c_p \rho T^a \dot{V} - (1 - \delta^a_{dir})M \leq 0 \;\; \forall i \in I^a \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:pipe_heat2discharge2 + + \dot{Q}_{i} - c_p \rho T^{a} \dot{V} + \delta^a_{dir}M \geq 0 \;\; \forall i \in I^a + \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:pipe_flow_dir + + \delta^a_{dir} \in \{ 0, 1 \} \;\; \forall a \in A_{pipes}. + +Here :math:`T^a` is the temperature inside pipe :math:`a`, :math:`c_p` and :math:`\rho` are the specific heat capacity and density of water and :math:`M` is a sufficiently large constant number. +:math:`\delta^a_{dir}` is the variable for flow direction in the pipe, where a value of :math:`1` indicates a positive flow (from in-port to out-port). This is modelled using: + +.. math:: + :label: eq:flowdir1 + + \dot{Q}^a_{i} - \delta^a_{dir}M \leq 0 \;\; \forall i \in I^a \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:flowdir2 + + \dot{Q}_{i} + (1 - \delta_{dir})M \geq 0 \;\; \forall i \in I^{a} \;\; \forall a \in A_{pipes}. + +The head loss, :math:`dH` must be compensated by pumps which are assumed to be located at sources and storage assets: + +.. math:: + :label: eq:pipe_head + + H^a_{in} - dH = H^a_{out} \;\; \forall a \in A_{pipes}. + +Steady-state head losses can be closely modelled with a quadratic relation w.r.t. :math:`\dot{V}`. +A set of linear inequalities is used, see :numref:`inequalitydH`, to approximate the quadratic curve. +The general form of the inequalities is given below in :eq:`eq:pipe_head_loss1`-:eq:`eq:pipe_head_loss2`. Note that the big M method is used with the flow direction and disconnected integers to allow for modelling of bi-directional flow and the ability to disconnect pipes. + +.. math:: + :label: eq:pipe_head_loss1 + + dH - (\alpha_j \dot{V} + \beta_j) + (\delta^a_{discon} + \delta^a_{dir})M\geq 0 \\ \forall (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:pipe_head_loss2 + + dH + (\alpha_j\dot{V} + \beta_j) - (\delta^a_{discon} + (1-\delta^a_{dir}))M\leq 0 \\ \forall (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}. + +Where :math:`(\alpha_j, \beta_j)` are the coefficients and constants of the linear equations used to approximate the quadratic equation. + +These inequalities force the head loss to be greater or equal to the approximated quadratic curve. +Although the constraints by themselves will not guarantee a physically feasible answer, the optimization will in drag the solution to an equality constraint as the objective function will minimize cost which reduces with lower pressure drop. + +.. _inequalitydH: + +.. figure:: ../images/linearlines.png + :figwidth: 6.94792in + :align: center + + Schematic visualization of how the linear constraints are fitted to the head loss curve. + +Furthermore, this head loss approximation has been validated against pandapipes as shown in :numref:`validation1dH`. This validation work has also been incorprated into a test case, for more information see the test folder. + +.. _validation1dH: + +.. figure:: ../images/dH_MESIDO_10_vs_pandapipes.png + :figwidth: 6.94792in + :align: center + + Head loss approximation with 10 linear lines against pandapipes. + +Similar as with head loss the hydraulic power, :math:`HP^a`, required to overcome the head losses is modelled with a set of linear inequalities: + +.. math:: + :label: eq:pipe_hp1 + + HP^a - (c_j\dot{V} + d_j) + (\delta^a_{discon} + 1-\delta^a_{dir})M \geq 0 \\ + \forall (c_j, d_j) \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:pipe_hp2 + + HP^a - (c_j\dot{V} + d_j) - (\delta_{discon}(k) - 1-\delta_{dir})M\geq 0 \\ + \forall (c_j, d_j) \;\; \forall a \in A_{pipes}. + +Here :math:`(c_j, d_j)` are the coefficients and constants of the linear equations used to approximate the quadratic equation. + +The method with linear inequalities, as represented above, is only valid when each possible unique flow path route in the network has a control valve to compensate non-physical head loss induced by the optimizer. Alternatively a (piece-wise) linear equality constraint between min and max flow rate can be configured for cases where this assumption is invalid, with the general form represented by :eq:`eq:pipe_head_loss3`-:eq:`eq:pipe_head_loss6`. + +.. math:: + :label: eq:pipe_head_loss3 + + dH - (\alpha_j \dot{V} + \beta_j) + (\delta^a_{discon} + \delta^a_{dir} + (1 - \delta^a_{line\_seg_{k}}))M\geq 0 \\ \delta^a_{line\_seg_{k}} \in \{ 0, 1 \}, (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:pipe_head_loss4 + + dH - (\alpha_j\dot{V} + \beta_j) - (\delta^a_{discon} + \delta^a_{dir} + (1 - \delta^a_{line\_seg_{k}}))M\leq 0 \\ \delta^a_{line\_seg_{k}} \in \{ 0, 1 \}, (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:pipe_head_loss5 + + dH + (\alpha_j \dot{V} + \beta_j) - (\delta^a_{discon} + (1 - \delta^a_{dir}) + (1 - \delta^a_{line\_seg_{k}}))M\leq 0 \\ \delta^a_{line\_seg_{k}} \in \{ 0, 1 \}, (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}, + +.. math:: + :label: eq:pipe_head_loss6 + + dH + (\alpha_j\dot{V} + \beta_j) + (\delta^a_{discon} + (1-\delta^a_{dir}) + (1 - \delta^a_{line\_seg_{k}}))M\geq 0 \\ \delta^a_{line\_seg_{k}} \in \{ 0, 1 \}, (\alpha_j, \beta_j) \;\; \forall a \in A_{pipes}. + +Where :math:`(\alpha_j, \beta_j)` are the coefficients and constants of the linear equations used to approximate the quadratic equation. Variable :math:`\delta^a_{line\_seg_{k}}` reperesents an integer, for pipe :math:`a`, value indicating if a linear line segment :math:`k` is active (value = 1) or not (value = 0). This would imply that if a quadratic curve is represented by 3 linear lines for instance, then only 1 of the linear lines are appplicable at a specific timestep. + + +Node +~~~~ + +The node conserves the flow with :eq:`eq:flow_balance` and the energy with :eq:`eq:general_energy_balance`. + +The head of all pipes connected to the node must be equal to ensure a hydraulically feasible solution: + +.. math:: + :label: eq:node_head + + H_i = H^a \;\; \forall i \in I^a \;\; a \in A_{nodes}, + +where :math:`A_{nodes}` is the set of all nodes and :math:`H^a` is the headloss for node :math:`a`. + +Asset Physics +------------- + +Source +~~~~~~ + +The source adds thermal power to the network. +The energy balance is given by :eq:`eq:general_energy_balance` where :math:`\dot{Q}^a_{consumed}` is equal to the (negative) value of the produced heat. + +The addition of energy is executed by increasing the temperature of the incoming water (the return network) to the outgoing supply temperature. +Therefore, the volumetric flow rate is linked to the outgoing thermal power with the outgoing supply temperature with equality constraints: + + +.. math:: + :label: eq:source_heat2discharge + + \sum_{i \in I^a_{out}} \dot{Q}^a_i = c_p \rho \dot{V}^a T_{sup} \;\; \forall a \in A_{prod}, + +where :math:`A_{prod}` is the set of all producers. + +The equality constraints ensure that the thermal power equals what can be physically transported by the flow. +No constraints are set on the returning flow at the in port, as this is already implied by the constraints on pipes. + +The modelling errors from not modelling temperature are present in various parts of the costs. +The heat losses will be overestimated giving an overestimate w.r.t. the cost of the thermal energy produced. +The overestimation of the thermal power required will induce an overestimation of the flow and thereby of the transportation and pipe sizing. + +The source is assumed to act within one hydraulically coupled network, :eq:`eq:flow_balance`. + +A source is modelled with a pump to reach its desired flow rate and head: + +.. math:: + :label: eq:source_pump_dh + + H^a_{in} + dH_{pump} = H^a_{out} \;\; \forall a \in A_{prod}. + +Demand +~~~~~~ + +A demand extracts thermal power from the network, defined by :eq:`eq:general_energy_balance` where :math:`\dot{Q}^a_{consumed}` is the consumed thermal power. + +Similar to the source, no constraints are required at the in-going supply side of the demand, and +an equality constraint relates outgoing thermal power with volumetric flow: + +.. math:: + :label: eq:consumer_heat2discharge + + \sum_{i \in I^a_{out}} \dot{Q}^a_i = c_p \rho \dot{V}^a T_{ret} \;\; \forall a \in A_{demand}, + +where :math:`A_{demand}` is the set of demand assets. + +The combination of constraints at the producers and demands, results in a smaller achieved temperature difference at the demand than the difference between the given temperatures for the supply and return side, and a larger achieved temperature difference at the producer due to pipe heat losses. + +Similar as for the source, the demand acts within one hydraulically coupled system under the same assumptions, see :eq:`eq:flow_balance`. + +Every demand is modelled with a control valve to regulate its flow. In reality a minimum head loss is often maintained: + +.. math:: + :label: eq:demand_head + + H^a_{in} - dH_{valve} = H^a_{out} \;\; \forall a \in A_{demand}. + +Storage +~~~~~~~ + +Storage assets add time flexibility with the production and consumption of thermal power. For shorter intra-day periods this capability is provided by tanks, alternatively storage over seasons is done with underground thermal energy storage like HT-ATES, :cite:`drijver2019state`. + +:math:`\dot{Q}^{a}_{consumed}` can be defined by the thermal power substracted from or added to the network, where the internal losses of the storage are subtracted: + +.. math:: + :label: eq:change_stored_heat + + \dot{Q}^{a}_{consumed} = \sum_{i \in I^a_{in}} \dot{Q}^{a}_{i} - \sum_{i \in I^a_{out}} \dot{Q}^{a}_{i} - \dot{Q}^{a}_{loss} \;\; \forall a \in A_{storage}. + +The consumed heat of the storage assets is equated to the change in stored heat, :math:`\dot{Q}^{a}_{stored}`: + +.. math:: + :label: eq:stored_heat + + \dot{Q}^{a}_{consumed} = \dot{Q}^{a}_{stored} \;\; \forall a \in A_{storage} + +Like the source and demand assets, the storage needs equality constraints relating the outgoing flow to the thermal power. +Unlike the demand and source the outgoing flow can be either on the in or out port depending whether the storage is charging or discharging. +The default convention is that charging indicates positive flow, therefore :math:`\delta_{dir}` can be used as an integer for charging/discharging. +Equations :eq:`eq:storage_heat2discharge1` and :eq:`eq:storage_heat2discharge2` are active during charging, and during discharging, +:eq:`eq:storage_heat2discharge3` and :eq:`eq:storage_heat2discharge4` are activated by the big M method. + +.. math:: + :label: eq:storage_heat2discharge1 + + \sum_{i \in I^a_{in}} \dot{Q}^{a}_{i} - c_p \rho \dot{V}^{a} T_{sup} \leq 0 \;\; \forall a \in A_{storage} + +.. math:: + :label: eq:storage_heat2discharge2 + + \sum_{i \in I^a_{in}} \dot{Q}^{a}_{i} - c_p \rho \dot{V}^{a} T_{sup} + \delta^{a}_{dir} M \geq 0 \;\; \forall a \in A_{storage} + +.. math:: + :label: eq:storage_heat2discharge3 + + \sum_{i \in I^a_{out}} \dot{Q}^{a}_{i} - c_p \rho \dot{V}^{a} T_{ret} \geq 0 \;\; \forall a \in A_{storage} + +.. math:: + :label: eq:storage_heat2discharge4 + + \sum_{i \in I^a_{out}} \dot{Q}^{a}_{i} - c_p \rho \dot{V}^{a} T_{ret} - (1-\delta^{a}_{dir}) M \leq 0 \;\; \forall a \in A_{storage} + +Tank +^^^^ + +Heat loss in a tank is modelled as linear with the stored heat: + +.. math:: + :label: eq:storage_loss + + \dot{Q}^{a}_{loss} = \beta^{a} Q^{a}_{stored} \;\; \forall a \in A_{storage}, + +where :math:`Q^{a}_{stored}` is the heat stored in the storage asset and :math:`\beta` is the efficiency factor. + +The efficiency factor is approximated assuming that tanks are cylindrical and lose heat over their surface area. For cylindrical tanks their surface area approximately increases linearly with the stored heat. A radiation coefficient, :math:`c_r`, of 1 :math:`W/m^2` is used as an approximation. + +HT-ATES +^^^^^^^ + +Two HT-ATES modelling methods are available. The first approximation for heat loss is based on an efficiency that is reached in a period of time. In this research a value of 70\% over 100 days is used. + +.. math:: + + \beta_{HTATES} = \eta^{\frac{1}{time}} + +The second method: COMING SOON... + + +Similarly as for the other assets, the storage assets are assumed to act within the hydraulically coupled system; +nonetheless, the volumetric flow balance requires additional equations. +The storage is modelled as an asset with a hot and cold volume. +The total volume will be conserved by the in- and outflow at the storage. + +.. math:: + :label: eq:storage_volume_constant + + \dot{V}^{a}_{warm}-\dot{V}^{a}_{cold}=0 \;\; \forall a \in A_{storage}, + +where :math:`\dot{V}^{a}_{warm}` and :math:`\dot{V}^{a}_{cold}`, respectively denote the change in the hot and cold volume. +The warm volume will increase and decrease with the volumetric flow passing the storage: + +.. math:: + :label: eq:storage_volume_change + + \dot{V}^{a}-\dot{V}^{a}_{warm}=0 \;\; \forall a \in A_{storage}. + +The storage assets are assumed to have both a pump and a valve, as they fulfill both the source and demand role: + +.. math:: + :label: eq:source_pump + + H^{a}_{in} + dH^{a}_{pump} - dH^{a}_{valve} = H^{a}_{out} \;\; \forall a \in A_{storage}, + + + diff --git a/docs/theory/index.rst b/docs/theory/index.rst index 31e3df6b4..7153e8e9f 100644 --- a/docs/theory/index.rst +++ b/docs/theory/index.rst @@ -1,7 +1,15 @@ .. toctree:: :maxdepth: 3 + :numbered: introduction - approach - Validation_pipe_diameter_sizing - pipe_classes + code_structure + philosophy + Workflows + financial + asset_sizing + physics + heat_physics + electricity_physics + gas_physics + diff --git a/docs/theory/introduction.rst b/docs/theory/introduction.rst index 54a410c4d..78e5477f0 100644 --- a/docs/theory/introduction.rst +++ b/docs/theory/introduction.rst @@ -1,23 +1,40 @@ +.. _chp_introduction: + Introduction ============ -The purpose of the optimizer routine is to provide a framework for design and operational optimization of heat networks. -It provides automatic construction of your heat network model based on a ESDL file. +MESIDO is the abbreviation for Multi Energy System Integrated Design and Operation. This documentation is meant to give the user of the MESIDO package insight in how to use the different functionalities available. + +Why MESIDO? +----------- + +MESIDO aims to fill the gap between available tools used in early feasibility studies and the more detailed tools (typically simulators). +Tools for feasibilty studies like EnergyPlan, https://www.energyplan.eu, provide a good framework for initial feasibility of high level system concepts. +These tools often have little to no physics included in their models, typically energy balancing with efficiencies and capacity limits. +On the other hand there are more detailed tools, examples include detailed simulators like pandapower and pandapipes. +These simulators include more detailed modelling of physics allowing one to analyze networks and/or assets close to real life operational conditions. + +The high level system concept that comes out of the initial feasibility is typically still subjected to many uncertainties. Therefore, many design choices are still to be made like placement and exact sizing of assets, optimal routing of the network, etc. +Although, the more detailed simulators can analyze various energy system designs by running different design options, it typically becomes infeasible in practice as the amount of open design choices after initial feasibility is too high. +The increased complexity of the new and future energy systems plays a significant part. New energy systems consists out of networks which have multiple producers and consumers, often extended with storages (possibly seasonal). Most notably the interconnections between these different energy commodities resulting in a larger possible solution space than ever. + +MESIDO aims to play the connecting role between the initial feasibility and the detailed analyses. This is achieved by offering a techno-economic optimization framework that allows one to make design choices, resulting in an (limited set of) energy system design(s) that can be refined (more detail) with simulators. + +What is MESIDO? +--------------- + +MESIDO is a python package that allows users to define techno-economic optimization workflows (or use the available ones). Users can define which KPIs they wish to optimize for, e.g. cost or business case optimization. +Furthermore, the users can select which physics fidelity level they need for their analyses. Where the physics are typically approximations of steady-state conditions, the modelling is done such that the solutions are close and conservative. +The inclusion of the physics approximations allows the user to make more design choices compared to the tools used in initial feasibility analyses. +However, this comes at the cost of the user needing to provide more information of the energy system in order to use MESIDO in an effective way, hence MESIDO is proposed as a sequential tool for analysis. + +Under the hood, MESIDO is a Mixed Integer Linear Problem (MILP) formulation. This means that the physics and financial models are limited to linear constraints. +The computational power advantages of MILP optimizations allows MESIDO to optimize Multi Energy/Multi Commodity networks in an integral manner. +Nevertheless, the modelling limitations of MILP will in the vast majority of cases, require optimized networks to be refined with simulation tools before closing business cases and going to implementation. + + -For the optimization one needs to define a model of your network and objective that you want to attain. -A common way to formulate these objectives is to use hierarchical "goals", see the `RTC-Tools documentation `_ for more information on this. -See also the RTC-Tools Heat Network examples for some ideas on goals related to heat network optimization. -This documentation will elaborate on the ins and outs of the optimizer routine. -The routine depends on `RTC-Tools `_, which is automatically installed as one of its dependencies. -Constructing a network with ESDL --------------------------------- -You can use an ESDL file description of a network. -Most importantly these files contain which components are in the network and how they are connected. -Some properties of the components can also be read from the file. -ESDL (Energy System Description Language) allows to describe your energy network in the conceptual phases. -You can draw networks in the `MapEditor `_ and save the ESDL file. -This allows for an user friendly way of drawing networks and setting component properties. diff --git a/docs/theory/philosophy.rst b/docs/theory/philosophy.rst new file mode 100644 index 000000000..f3515390f --- /dev/null +++ b/docs/theory/philosophy.rst @@ -0,0 +1,18 @@ +.. _chp_philosophy: + + +Modelling Philosophy +==================== + +The conceptual design including operational strategy for energy systems starts simultaneously with the initial feasibility studies. +This early phase is challenging as it comes with many uncertainties, such as the expected demand profiles and many possible design choices. Examples of the latter being network routing, asset sizing, and multiple optional locations for the placement of assets such as sources and storage options. + +Nevertheless, in practice it is seen that the decisions made in these early phases are crucial for the eventual system performance, as they set the boundaries for interactions between assets and sub-parts of the overall energy system. +Later design phases can therefore be limited by decisions made during the initial feasibility phases. +Good trade-offs take into account the interaction between assets, but also trade-offs between design and operational strategy are key in reducing the overall system cost. + +MESIDO applies a Mixed Integer Linear Problem (MILP) formulation to address these challenges. The main reasons are: + +* In the early phases of designing an energy system, decision makers are typically not looking for high accuracy physical insight, but rather for directions in investment choices. Hence MILP approximation methods that are conservative and feasible, whilst staying within accuracy bounds of the available input data, will suffice. This allows the decision makers to make plans in this early phase with lower financial risk, as these plans will become more detailed over time. +* Part of the decisions for designing an energy system have an integer nature, e.g. placing a source or options for a pipe size. These design choices cannot be modelled with continuous formulation in a representative manner. +* Due to the large number of uncertainties it is key to have the ability to iterate quickly over input data variations. The computational speed of the optimization is therefore of vital importance. diff --git a/docs/theory/physics.rst b/docs/theory/physics.rst new file mode 100644 index 000000000..c0ccc67f2 --- /dev/null +++ b/docs/theory/physics.rst @@ -0,0 +1,45 @@ +.. _chp_physics: + +Physics +======= + +Within MESIDO the physics are approximated utilizing the mixed integer linear constraints. +The goal within MESIDO is to approximate the physics in such a way such that the approximation errors result in conservative estimates of the financial aspects of the system, e.g. overestimating cost and underestimating revenue. +To cater for different design phases different approximation fidelities can be configuration in MESIDO. +Examples include the approximation of head loss which can be ignored or approximated with multiple linear constraints. +MESIDO allows for the integral optimization of energy systems having: + +* A heat commodity (closed loop district heating networks where water is used as the medium) +* A gaseous commodity where pipes transport the gas. +* Electricity commodity where cables transport the energy + +There are documentation pages for the three respective commodities and the physics that are modelled for each. +This page will focus on the assets, physics and other functionality that involves multiple commodities. + +Multi-Commodity Asset Physics +----------------------------- + +Electrolyzer +~~~~~~~~~~~~ + + +Water-water Heat Pump Electrical +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + + + +Air-water Heat Pump Electrical +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + + +Electrical Boiler +~~~~~~~~~~~~~~~~~ + + +Gas Boiler +~~~~~~~~~~ + + +Setpoint Constraints +~~~~~~~~~~~~~~~~~~~~ + diff --git a/examples/PoCTutorial/model/PoC Tutorial.esdl b/examples/PoCTutorial/model/PoC Tutorial.esdl index 8ea28e64c..0b6215465 100644 --- a/examples/PoCTutorial/model/PoC Tutorial.esdl +++ b/examples/PoCTutorial/model/PoC Tutorial.esdl @@ -11,7 +11,7 @@ - + @@ -33,7 +33,7 @@ - + @@ -120,7 +120,7 @@ - + @@ -180,7 +180,7 @@ - + @@ -206,7 +206,7 @@ - + @@ -222,7 +222,7 @@ - + @@ -287,7 +287,7 @@ - + @@ -318,7 +318,7 @@ - + @@ -347,7 +347,7 @@ - + diff --git a/examples/PoCTutorial/src/esdl_generator.py b/examples/PoCTutorial/src/esdl_generator.py new file mode 100644 index 000000000..afad41434 --- /dev/null +++ b/examples/PoCTutorial/src/esdl_generator.py @@ -0,0 +1,478 @@ +import os +from uuid import uuid4 + +import esdl +from esdl.esdl_handler import EnergySystemHandler + +from pyecore.ecore import EDate + + +def create_in_out_ports(asset, in_carrier, out_carrier, demand_profile=None): + # Adds in an out ports to an assets and assigns them the corresponding carriers. + in_port = esdl.InPort(id=str(uuid4()), name="In_port", carrier=in_carrier) + out_port = esdl.OutPort(id=str(uuid4()), name="Out_port", carrier=out_carrier) + if demand_profile is not None: + in_port.profile.append(demand_profile) + asset.port.append(in_port) + asset.port.append(out_port) + + +def get_in_out_ports(asset): + # Gets the ports of an asset and sorts them as in and out. + for port in asset.port: + if isinstance(port, esdl.InPort): + in_port = port + else: + out_port = port + return in_port, out_port + + +def add_geometry_point(asset, lat_lon_list): + # Adds an esdl point to an asset. + point = esdl.Point(lat=lat_lon_list[0], lon=lat_lon_list[1]) + asset.geometry = point + + +def define_area(area, points): + # Creates a polygon given a series of points and assigns it to the given area. + area.geometry = esdl.Polygon() + area_shape = esdl.SubPolygon() + for point in points: + point_add = esdl.Point(lat=point[0], lon=point[1]) + area_shape.point.append(point_add) + area.geometry.exterior = area_shape + + +def create_cost_value_profile(cost_value, unit, per_unit=None, per_multiplier=None): + # Creates a cost profile with a single constant value that can be used to be assigned + # to any asset. + qua_per = esdl.QuantityAndUnitType(id=str(uuid4())) + qua_per.unit = esdl.UnitEnum.from_string(unit) + if per_unit is not None: + qua_per.perUnit = esdl.UnitEnum.from_string(per_unit) + if per_multiplier is not None: + qua_per.perMultiplier = esdl.MultiplierEnum.from_string(per_multiplier) + qua_per.physicalQuantity = esdl.PhysicalQuantityEnum.from_string("COST") + esdl_cost_profile = esdl.SingleValue( + id=str(uuid4()), value=cost_value, profileQuantityAndUnit=qua_per + ) + + return esdl_cost_profile + + +def import_demand_profile(demand_profile_parameters, profile_quantity): + # Imports the demand profile from InfluxDB and creates the demand object. + # demand_profile_parameters is a dictionary (see below) and the profile quantity + # must be an esdl.QuantityAndUnitType object. + + demand_profile = esdl.InfluxDBProfile( + id=str(uuid4()), + multiplier=demand_profile_parameters["multiplier"], + database=demand_profile_parameters["database"], + measurement=demand_profile_parameters["measurement"], + host=demand_profile_parameters["host"], + field=demand_profile_parameters["field"], + port=demand_profile_parameters["port"], + startDate=demand_profile_parameters["startDate"], + endDate=demand_profile_parameters["endDate"], + ) + + demand_profile.profileQuantityAndUnit = esdl.QuantityAndUnitReference( + reference=profile_quantity + ) + + return demand_profile + + +def create_joint(joint_name, carrier, location, area): + # Creates a joint, assigns it its carrier and ports and appends it to + # the selected area + + joint = esdl.Joint(id=str(uuid4()), name=joint_name) + create_in_out_ports(joint, carrier, carrier) + add_geometry_point(joint, location) + area.asset.append(joint) + + return joint + + +def create_pipe( + name_pipe, from_asset, to_asset, carrier, area, elbow_point=None, state_pipe="ENABLED" +): + # Creates a pipe, connects it to its corresponding assets, assigns it its + # carrier, geometry and state ("ENABLED" or "OPTIONAL") and appends it to + # its corresponding area. + + pipe = esdl.Pipe(id=str(uuid4()), diameter=pipe_d, name=name_pipe, state=state_pipe) + create_in_out_ports(pipe, carrier, carrier) + + _, connect_from = get_in_out_ports(from_asset) + connect_to, _ = get_in_out_ports(to_asset) + pipe_ports = get_in_out_ports(pipe) + # Connect the corresponding ports to each other + for port in pipe_ports: + if isinstance(port, esdl.InPort): + port.connectedTo.append(connect_from) + pipe_start = esdl.Point(lat=from_asset.geometry.lat, lon=from_asset.geometry.lon) + else: + port.connectedTo.append(connect_to) + pipe_end = esdl.Point(lat=to_asset.geometry.lat, lon=to_asset.geometry.lon) + # Configure pipe geometry + pipe.geometry = esdl.Line() + pipe.geometry.point.append(pipe_start) + if elbow_point: + pipe_elbow = esdl.Point(lat=elbow_point[0], lon=elbow_point[1]) + pipe.geometry.point.append(pipe_elbow) + pipe.geometry.point.append(pipe_end) + + area.asset.append(pipe) + + return pipe + + +if __name__ == "__main__": + + # -------------------------------------------------- # + # INPUT # + # -------------------------------------------------- # + + esdl_file_name = "tutorial_generated.esdl" # Name of the output esdl file. + save_folder = "examples/PoCTutorial/model" # Folder to output the esdl to. + + # System parameters + temp_supply = 80.0 # degC + temp_ret = 30.0 # degC + + # Heat demand 1 parameters + demand_1_power = 15e6 # W + demand_1_inv_cost = 1e6 # eur/MW + demand_1_inst_cost = 1e6 # eur + area_1_coord = [ + [52.003232185574326, 4.376142024993897], + [52.002228236493224, 4.372107982635499], + [52.0031132980428, 4.3712711334228525], + [52.00197724570447, 4.366979598999024], + [51.99826505971136, 4.369254112243653], + [51.99945404958839, 4.373760223388673], + [51.995635958872874, 4.3776869773864755], + [51.9963626102222, 4.380712509155274], + ] + demand_1_coord = [52.00107, 4.37353] + demand_1_profile_params = { + "multiplier": 0.75, + "database": "energy_profiles", + "measurement": "WarmingUp default profiles", + "host": "profiles.warmingup.info", + "field": "demand4_MW", + "port": 443, + "startDate": EDate.from_string("2018-12-31T23:00:00.000000+0000"), + "endDate": EDate.from_string("2019-12-31T22:00:00.000000+0000"), + } + + # Demand 2 parameters + demand_2_power = 15e6 # W + demand_2_inv_cost = 1e6 # eur/MW + demand_2_inst_cost = 1e6 # eur + area_2_coord = [ + [51.99817258139733, 4.3692970275878915], + [51.99932194116153, 4.373695850372315], + [51.99534529503086, 4.376678466796876], + [51.99624370444482, 4.38081979751587], + [51.99490929572965, 4.381613731384278], + [51.99272923553559, 4.372708797454835], + ] + demand_2_coord = [51.99653, 4.3731] + demand_2_profile_params = { + "multiplier": 0.5, + "database": "energy_profiles", + "measurement": "WarmingUp default profiles", + "host": "profiles.warmingup.info", + "field": "demand4_MW", + "port": 443, + "startDate": EDate.from_string("2018-12-31T23:00:00.000000+0000"), + "endDate": EDate.from_string("2019-12-31T22:00:00.000000+0000"), + } + + # Demand 3 parameters + demand_3_power = 15e6 # W + demand_3_inv_cost = 1e6 # eur/MW + demand_3_inst_cost = 1e6 # eur + area_3_coord = [ + [51.992279997820766, 4.372987747192384], + [51.994235470276436, 4.382214546203614], + [51.989333415199866, 4.38581943511963], + [51.98688879367896, 4.37633514404297], + ] + demand_3_coord = [51.99074, 4.3791] + demand_3_profile_params = { + "multiplier": 0.3, + "database": "energy_profiles", + "measurement": "WarmingUp default profiles", + "host": "profiles.warmingup.info", + "field": "demand4_MW", + "port": 443, + "startDate": EDate.from_string("2018-12-31T23:00:00.000000+0000"), + "endDate": EDate.from_string("2019-12-31T22:00:00.000000+0000"), + } + + # Source 1 parameters + source_1_power = 50e6 # W + source_1_inv_cost = 1.5e6 # eur/MW + source_1_inst_cost = 10e6 # eur + source_1_varop_cost = 100.0 # eur/MWh + source_1_fixop_cost = 6e5 # eur/MW + prod_1_coord = [52.00483, 4.37272] + + # Source 2 parameters + source_2_power = 50e6 # W + source_2_inv_cost = 2e6 # eur/MW + source_2_inst_cost = 20e6 # eur + source_2_varop_cost = 200.0 # eur/MWh + source_2_fixop_cost = 9e5 # eur/MW + prod_2_coord = [51.99543, 4.36457] + + # Joints + joint_1_coord = [52.00098, 4.36702] + joint_2_coord = [51.99596, 4.36951] + joint_1ret_coord = [52.00033, 4.36646] + joint_2ret_coord = [51.99537, 4.36895] + + # Pipes + pipe_diam = "DN400" # Assumes all pipes have the same diameter. + pipe_1_elbow_coord = [52.00353, 4.36593] + pipe_3_elbow_coord = [51.9898, 4.37191] + pipe_1ret_elbow_coord = [52.00363, 4.36492] + pipe_3ret_elbow_coord = [51.98922, 4.3717] + + # -------------------------------------------------- # + # PROCESSING # + # -------------------------------------------------- # + + esh = EnergySystemHandler() + energy_system = esh.create_empty_energy_system(name="Generated PoC tutorial") + main_area = energy_system.instance[0].area # Logical high level area. + + # Create heat carriers + heat_commodity_primary = esdl.HeatCommodity( + id=str(uuid4()), name="HeatCommodityPrimary", supplyTemperature=temp_supply + ) + heat_commodity_ret = esdl.HeatCommodity( + id=str(uuid4()), name="HeatCommodityRet", returnTemperature=temp_ret + ) + heat_carrs = esdl.Carriers(id=str(uuid4())) + heat_carrs.carrier.append(heat_commodity_primary) + heat_carrs.carrier.append(heat_commodity_ret) + id_primary_carr = heat_commodity_primary.id + id_ret_carr = heat_commodity_ret.id + esi = esh.energy_system.energySystemInformation + if not esi: + esi = esdl.EnergySystemInformation(id=str(uuid4())) + esh.energy_system.energySystemInformation = esi + esh.add_object(esi) + + quantities = esdl.QuantityAndUnits(id=str(uuid4())) + power_quantity = esdl.QuantityAndUnitType( + id=str(uuid4()), + description="Power in MW", + physicalQuantity="POWER", + multiplier="MEGA", + unit="WATT", + ) + quantities.quantityAndUnit.append(power_quantity) + + esi.quantityAndUnits = quantities + esi.carriers = heat_carrs + + # Area 1 (demand 1) + area_1 = esdl.Area(id=str(uuid4()), name="Area_demand_1") + define_area(area_1, area_1_coord) + main_area.area.append(area_1) + + heat_demand_1 = esdl.HeatingDemand(id=str(uuid4()), name="Heat_demand1") + area_1.asset.append(heat_demand_1) + add_geometry_point(heat_demand_1, demand_1_coord) + heat_demand_1.power = demand_1_power + + heat_demand_1.costInformation = esdl.CostInformation(id=str(uuid4())) + cost_info = heat_demand_1.costInformation + cost_info.investmentCosts = create_cost_value_profile( + demand_1_inv_cost, "EURO", per_unit="WATT", per_multiplier="MEGA" + ) + cost_info.installationCosts = create_cost_value_profile(demand_1_inst_cost, "EURO") + + in_carrier = heat_commodity_primary + out_carrier = heat_commodity_ret + + heat_demand_profile = import_demand_profile(demand_1_profile_params, power_quantity) + create_in_out_ports(heat_demand_1, in_carrier, out_carrier, demand_profile=heat_demand_profile) + + # Area 2 (demand 2) + area_2 = esdl.Area(id=str(uuid4()), name="Area_demand_2") + define_area(area_2, area_2_coord) + main_area.area.append(area_2) + + heat_demand_2 = esdl.HeatingDemand(id=str(uuid4()), name="Heat_demand2") + area_2.asset.append(heat_demand_2) + add_geometry_point(heat_demand_2, demand_2_coord) + heat_demand_2.power = demand_2_power + + heat_demand_2.costInformation = esdl.CostInformation(id=str(uuid4())) + cost_info = heat_demand_2.costInformation + cost_info.investmentCosts = create_cost_value_profile( + demand_2_inv_cost, "EURO", per_unit="WATT", per_multiplier="MEGA" + ) + cost_info.installationCosts = create_cost_value_profile(demand_2_inst_cost, "EURO") + + in_carrier = heat_commodity_primary + out_carrier = heat_commodity_ret + + heat_demand_profile = import_demand_profile(demand_2_profile_params, power_quantity) + create_in_out_ports(heat_demand_2, in_carrier, out_carrier, demand_profile=heat_demand_profile) + + # Area 3 (demand 3) + area_3 = esdl.Area(id=str(uuid4()), name="Area_demand_3") + define_area(area_3, area_3_coord) + main_area.area.append(area_3) + + heat_demand_3 = esdl.HeatingDemand(id=str(uuid4()), name="Heat_demand3") + area_3.asset.append(heat_demand_3) + add_geometry_point(heat_demand_3, demand_3_coord) + heat_demand_3.power = demand_3_power + + heat_demand_3.costInformation = esdl.CostInformation(id=str(uuid4())) + cost_info = heat_demand_3.costInformation + cost_info.investmentCosts = create_cost_value_profile( + demand_3_inv_cost, "EURO", per_unit="WATT", per_multiplier="MEGA" + ) + cost_info.installationCosts = create_cost_value_profile(demand_3_inst_cost, "EURO") + + in_carrier = heat_commodity_primary + out_carrier = heat_commodity_ret + + heat_demand_profile = import_demand_profile(demand_3_profile_params, power_quantity) + create_in_out_ports(heat_demand_3, in_carrier, out_carrier, demand_profile=heat_demand_profile) + + # Main area (sources) + heat_source_1 = esdl.ResidualHeatSource(id=str(uuid4()), name="Heat_source1", state="OPTIONAL") + heat_source_2 = esdl.ResidualHeatSource(id=str(uuid4()), name="Heat_source2", state="OPTIONAL") + main_area.asset.append(heat_source_1) + main_area.asset.append(heat_source_2) + add_geometry_point(heat_source_1, prod_1_coord) + add_geometry_point(heat_source_2, prod_2_coord) + + heat_source_1.power = source_1_power + heat_source_2.power = source_2_power + + heat_source_1.costInformation = esdl.CostInformation(id=str(uuid4())) + cost_info = heat_source_1.costInformation + cost_info.investmentCosts = create_cost_value_profile( + source_1_inv_cost, "EURO", per_unit="WATT", per_multiplier="MEGA" + ) + cost_info.installationCosts = create_cost_value_profile(source_1_inst_cost, "EURO") + cost_info.variableOperationalCosts = create_cost_value_profile( + source_1_varop_cost, "EURO", per_unit="WATTHOUR", per_multiplier="MEGA" + ) + cost_info.fixedOperationalCosts = create_cost_value_profile( + source_1_fixop_cost, "EURO", per_unit="WATT", per_multiplier="MEGA" + ) + + heat_source_2.costInformation = esdl.CostInformation(id=str(uuid4())) + cost_info = heat_source_2.costInformation + cost_info.investmentCosts = create_cost_value_profile( + source_2_inv_cost, "EURO", per_unit="WATT", per_multiplier="MEGA" + ) + cost_info.installationCosts = create_cost_value_profile(source_2_inst_cost, "EURO") + cost_info.variableOperationalCosts = create_cost_value_profile( + source_2_varop_cost, "EURO", per_unit="WATTHOUR", per_multiplier="MEGA" + ) + cost_info.fixedOperationalCosts = create_cost_value_profile( + source_2_fixop_cost, "EURO", per_unit="WATT", per_multiplier="MEGA" + ) + + in_carrier = heat_commodity_ret + out_carrier = heat_commodity_primary + create_in_out_ports(heat_source_1, in_carrier, out_carrier) + in_carrier = heat_commodity_ret + out_carrier = heat_commodity_primary + create_in_out_ports(heat_source_2, in_carrier, out_carrier) + + # Main netowrk joints joints + primary_carr = heat_commodity_primary + + joint_1 = create_joint("Joint_1", primary_carr, joint_1_coord, main_area) + joint_2 = create_joint("Joint_2", primary_carr, joint_2_coord, main_area) + + # Primary network pipes + pipe_d = esdl.PipeDiameterEnum.from_string(pipe_diam) # Pipe diameters + + pipe_1 = create_pipe( + "Pipe_1", + heat_source_1, + joint_1, + primary_carr, + main_area, + elbow_point=pipe_1_elbow_coord, + state_pipe="OPTIONAL", + ) + + pipe_2 = create_pipe( + "Pipe_2", + joint_1, + joint_2, + primary_carr, + main_area, + ) + + pipe_3 = create_pipe( + "Pipe_3", joint_2, heat_demand_3, primary_carr, main_area, elbow_point=pipe_3_elbow_coord + ) + + pipe_4 = create_pipe("Pipe_4", joint_1, heat_demand_1, primary_carr, main_area) + + pipe_5 = create_pipe("Pipe_5", joint_2, heat_demand_2, primary_carr, main_area) + + pipe_6 = create_pipe( + "Pipe_6", heat_source_2, joint_2, primary_carr, main_area, state_pipe="OPTIONAL" + ) + + # Return network joints + ret_carr = heat_commodity_ret + + joint_1ret = create_joint("Joint_1ret", ret_carr, joint_1ret_coord, main_area) + joint_2ret = create_joint("Joint_2ret", ret_carr, joint_2ret_coord, main_area) + + # Return network pipes. + + pipe_1ret = create_pipe( + "Pipe_1ret", + joint_1ret, + heat_source_1, + ret_carr, + main_area, + elbow_point=pipe_1ret_elbow_coord, + state_pipe="OPTIONAL", + ) + + pipe_2ret = create_pipe("Pipe_2ret", joint_2ret, joint_1ret, ret_carr, main_area) + + pipe_3ret = create_pipe( + "Pipe_3ret", + heat_demand_3, + joint_2ret, + ret_carr, + main_area, + elbow_point=pipe_3ret_elbow_coord, + ) + + pipe_4ret = create_pipe("Pipe_4ret", heat_demand_1, joint_1ret, ret_carr, main_area) + + pipe_5ret = create_pipe("Pipe_5ret", heat_demand_2, joint_2ret, ret_carr, main_area) + + pipe_6ret = create_pipe( + "Pipe_6ret", joint_2ret, heat_source_2, ret_carr, main_area, state_pipe="OPTIONAL" + ) + + # File export and saving + save_dir = save_folder + os.chdir(save_dir) + esh.save(filename=esdl_file_name) diff --git a/examples/PoCTutorial/src/run_grow_tutorial.py b/examples/PoCTutorial/src/run_grow_tutorial.py new file mode 100644 index 000000000..d28d91a05 --- /dev/null +++ b/examples/PoCTutorial/src/run_grow_tutorial.py @@ -0,0 +1,34 @@ +from pathlib import Path + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.workflows import EndScenarioSizingStaged, run_end_scenario_sizing + + +class EndScenarioSizingStagedHighs(EndScenarioSizingStaged): + pass + + +if __name__ == "__main__": + import time + + kwargs = { + "write_result_db_profiles": True, + "influxdb_host": "localhost", + "influxdb_port": 8086, + "influxdb_username": None, + "influxdb_password": None, + "influxdb_ssl": False, + "influxdb_verify_ssl": False, + } + + start_time = time.time() + base_folder = Path(__file__).resolve().parent.parent + solution = run_end_scenario_sizing( + EndScenarioSizingStagedHighs, + base_folder=base_folder, + esdl_file_name="PoC Tutorial.esdl", + esdl_parser=ESDLFileParser, + **kwargs, + ) + + print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) diff --git a/examples/gas_electricity_network/input/Example_gas_demand_nom_m3_s.csv b/examples/gas_electricity_network/input/Example_gas_demand_nom_m3_s.csv new file mode 100644 index 000000000..af726e0fd --- /dev/null +++ b/examples/gas_electricity_network/input/Example_gas_demand_nom_m3_s.csv @@ -0,0 +1,5 @@ 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+ diff --git a/examples/gas_electricity_network/model/Example_gas_elec.esdl b/examples/gas_electricity_network/model/Example_gas_elec.esdl new file mode 100644 index 000000000..2392c184a --- /dev/null +++ b/examples/gas_electricity_network/model/Example_gas_elec.esdl @@ -0,0 +1,3061 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples/gas_electricity_network/src/run_example.py b/examples/gas_electricity_network/src/run_example.py new file mode 100644 index 000000000..d86905892 --- /dev/null +++ b/examples/gas_electricity_network/src/run_example.py @@ -0,0 +1,140 @@ +# Note: The commented out items are requried for the manual checks/print outs below in this file +# import os +# import sys +# from pathlib import Path + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.workflows.gas_elect_workflow import GasElectProblem +from mesido.workflows.utils.helpers import run_optimization_problem_solver + +# root_folder = os.path.join(str(Path(__file__).resolve().parent.parent.parent.parent), "tests") +# sys.path.insert(1, root_folder) + +# from utils_tests import ( +# demand_matching_test, +# electric_power_conservation_test, +# energy_conservation_test, +# heat_to_discharge_test, +# ) + +if __name__ == "__main__": + import time + + start_time = time.time() + + solution = run_optimization_problem_solver( + GasElectProblem, + esdl_parser=ESDLFileParser, + esdl_file_name="Example_gas_elec.esdl", + profile_reader=ProfileReaderFromFile, + input_timeseries_file="Example_gas_demand_nom_m3_s.csv", + ) + + results = solution.extract_results() + + # ---------------------------------------------------------------------------------------------- + # Do not delete the code below: manual checking and testing of values + usefull prints to + # terminal + + # demand_matching_test(solution, results) + # energy_conservation_test(solution, results) + # heat_to_discharge_test(solution, results) + + # for asset_name in [*solution.energy_system_components.get("air_water_heat_pump_elec", [])]: + # power_cons = results[f"{asset_name}.Power_consumed"] + # print(f"{asset_name} power consumed: {power_cons}") + + # for asset_name in [*solution.energy_system_components.get("gas_boiler", [])]: + # power_cons = results[f"{asset_name}.Gas_demand_mass_flow"] + # print(f"{asset_name} gas consumed: {power_cons}") + + # # Check gas consumption vs production balance + # total_gas_demand_g = [0] * len(np.diff(solution.times())) + # total_gas_source_g = [0] * len(np.diff(solution.times())) + # for asset_name in [*solution.energy_system_components.get("gas_boiler", [])]: + # for ii in range(1, len(results[f"{asset_name}.Gas_demand_mass_flow"])): + # total_gas_demand_g[ii - 1] += ( + # results[f"{asset_name}.Gas_demand_mass_flow"][ii] + # * np.diff(solution.times())[ii - 1] + # ) + + # for asset_name in [*solution.energy_system_components.get("gas_source", [])]: + # for ii in range(1, len(results[f"{asset_name}.Gas_source_mass_flow"])): + # total_gas_source_g[ii - 1] += ( + # results[f"{asset_name}.Gas_source_mass_flow"][ii] + # * np.diff(solution.times())[ii - 1] + # ) + # np.testing.assert_allclose(total_gas_source_g, total_gas_demand_g) + + # # Check elect power demand vs production balance + # electric_power_conservation_test(solution, results) + + # Check OPEX costs + # np.testing.assert_allclose( + # sum( + # results["STATION_5.Gas_source_mass_flow"][1:] * 0.0037926 * np.diff(solution.times()) + # ), + # results["STATION_5__variable_operational_cost"][0], + # ) + # np.testing.assert_allclose( + # sum( + # results["Elec_prod_5.Electricity_source"][1:] + # * (np.diff(solution.times())) + # / 3600.0 + # * 0.00027 + # ), + # results["Elec_prod_5__variable_operational_cost"][0], + # atol=1e-10, + # ) + # np.testing.assert_allclose( + # sum( + # results["STATION_10.Gas_source_mass_flow"][1:] * 0.0037926 * np.diff(solution.times()) + # ), + # results["STATION_10__variable_operational_cost"][0], + # ) + # np.testing.assert_allclose( + # sum( + # results["Elec_prod_10.Electricity_source"][1:] + # * (np.diff(solution.times())) + # / 3600.0 + # * 0.00027 + # ), + # results["Elec_prod_10__variable_operational_cost"][0], + # atol=1e-10, + # ) + + # # Check that heat energy balance + # for asset_name in [*solution.energy_system_components.get("heat_demand", [])]: + # dmnd_num = asset_name.strip("Demand_") + # dmnd_val = results[f"Demand_{dmnd_num}.Heat_flow"] + # prod_perc_hp = results[f"Heatpump_{dmnd_num}.Heat_flow"] / dmnd_val + # prod_perc_gb = results[f"Gasboiler_{dmnd_num}.Heat_flow"] / dmnd_val + # # Do not delete: use for manual checks + # print( + # f"dmnd_num: {dmnd_num} demand {dmnd_val/1.0e3}kW, source % split " + # f"HP: {[round(elem*100.0, 1) for elem in prod_perc_hp]} & " + # f"GasBoiler{[round(elem*100.0, 1) for elem in prod_perc_gb]}" + # ) + # np.testing.assert_allclose(prod_perc_hp + prod_perc_gb, 1.0) + + # # Costs + # opex_gas = ( + # results["STATION_5__variable_operational_cost"][0] + # + results["STATION_10__variable_operational_cost"][0] + # ) + # opex_elect = ( + # results["Elec_prod_10__variable_operational_cost"][0] + # + results["Elec_prod_5__variable_operational_cost"][0] + # ) + # opex_tot = opex_gas + opex_elect + # print(f"OPEX for gas:{opex_gas} + elect:{opex_elect} = total OPEX {opex_tot}") + + # # Check that the gas energy content + # np.testing.assert_allclose( + # # g/s /1000 * energy_content J/kg + # results["Gasboiler_4391.Gas_demand_mass_flow"] / 1000 * 41373333.404736854, + # results["Gasboiler_4391.Heat_flow"], + # ) + # ---------------------------------------------------------------------------------------------- + print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) diff --git a/examples/heating_and_cooling/input/timeseries_4.csv b/examples/heating_and_cooling/input/timeseries_4.csv new file mode 100644 index 000000000..5452b3923 --- /dev/null +++ b/examples/heating_and_cooling/input/timeseries_4.csv @@ -0,0 +1,8761 @@ +DateTime,CoolingDemand_1,HeatingDemand_1,HeatingDemand_2 +31-12-2018 23:00,7153333.333,0.050329049,0.050329049 +01-01-2019 0:00,7153333.762,0.019461529,0.019461529 +01-01-2019 1:00,7153335.048,0.005371142,0.005371142 +01-01-2019 2:00,7153337.192,0.002531358,0.002531358 +01-01-2019 3:00,7153340.193,0.006376971,0.006376971 +01-01-2019 4:00,7153344.051,0.039930779,0.039930779 +01-01-2019 5:00,7153348.767,0.189693727,0.189693727 +01-01-2019 6:00,7153354.34,0.398271631,0.398271631 +01-01-2019 7:00,7153360.771,0.545202955,0.545202955 +01-01-2019 8:00,7153368.059,0.664203859,0.664203859 +01-01-2019 9:00,7153376.205,0.552707393,0.552707393 +01-01-2019 10:00,7153385.208,0.51662341,0.51662341 +01-01-2019 11:00,7153395.068,0.639689954,0.639689954 +01-01-2019 12:00,7153405.786,0.54726439,0.54726439 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network with return network.esdl new file mode 100644 index 000000000..06fdedb28 --- /dev/null +++ b/examples/heating_and_cooling/model/Heating and cooling network with return network.esdl @@ -0,0 +1,271 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples/heating_and_cooling/src/run_case.py b/examples/heating_and_cooling/src/run_case.py new file mode 100644 index 000000000..b6881a689 --- /dev/null +++ b/examples/heating_and_cooling/src/run_case.py @@ -0,0 +1,150 @@ +import logging +from pathlib import Path +from unittest import TestCase + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization +from mesido.workflows.utils.adapt_profiles import ( + adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day, +) + +logger = logging.getLogger("WarmingUP-MPC") +logger.setLevel(logging.INFO) + + +class HeatColdDemand(TestCase): + + def heating_cooling_case(self): + """ + In this case we have a network with an air-water hp, a WKO (warm and cold well) and both + hot and cold demand. The heat and cold demand was balanced such that the seasonal storage + gets utilized as intended. + """ + import os + import sys + + root_folder = os.path.join(Path(__file__).resolve().parent.parent.parent.parent, "tests") + sys.path.insert(1, root_folder) + + from models.wko.src.example import HeatProblem + from utils_tests import demand_matching_test, energy_conservation_test + + base_folder = Path(__file__).resolve().parent.parent + + # ------------------------------------------------------------------------------------------ + class HeatingCoolingProblem(HeatProblem): + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self._number_of_years = 30.0 + + self.__indx_max_peak = None + self.__day_steps = 5 + + def energy_system_options(self): + options = super().energy_system_options() + options["neglect_pipe_heat_losses"] = False + return options + + def parameters(self, ensemble_member): + parameters = super().parameters(ensemble_member) + parameters["peak_day_index"] = self.__indx_max_peak + parameters["time_step_days"] = self.__day_steps + parameters["number_of_years"] = self._number_of_years + return parameters + + def read(self): + super().read() + + # Set the peak of the heating demand since the specified profile is normalized to 1 + + for d in self.energy_system_components["heat_demand"]: + target = self.get_timeseries(f"{d}.target_heat_demand") + for ii in range(len(target.values)): + target.values[ii] = target.values[ii] * 7.0e6 + + self.io.set_timeseries( + f"{d}.target_heat_demand", + self.io._DataStore__timeseries_datetimes, + target.values, + 0, + ) + # Cold demand specified profile is not normalized + # Cold demand value is reduced to get the correct balance between the heat and cold + # demand such that the seasonal storage is utilized + for d in self.energy_system_components["cold_demand"]: + target = self.get_timeseries(f"{d}.target_cold_demand") + for ii in range(len(target.values)): + target.values[ii] = target.values[ii] * 0.25 + + self.io.set_timeseries( + f"{d}.target_cold_demand", + self.io._DataStore__timeseries_datetimes, + target.values, + 0, + ) + + ( + self.__indx_max_peak, + self.__heat_demand_nominal, + self.__cold_demand_nominal, + ) = adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day( + self, + self.__day_steps, + ) + + def constraints(self, ensemble_member): + constraints = super().constraints(ensemble_member) + + # TODO: confirm if volume or heat balance is required over year. This will + # determine if cyclic contraint below is for stored_heat or stored_volume + # Add stored_heat cyclic constraint, this will also ensure that the total heat + # change in the wko is 0 over the timeline + # Note: + # - WKO in cooling mode: Hot well is being charged with heat and the cold well is + # being discharged + # - WKO in heating mode: Cold well is being charged and the hot well is being + # discharged. + # for a in self.energy_system_components.get("low_temperature_ates", []): + # stored_heat = self.state_vector(f"{a}.Stored_heat") + # constraints.append(((stored_heat[-1] - stored_heat[0]), 0.0, 0.0)) + # This code below might be needed + # Add stored_heat cyclic constraint, this will also ensure that the volume + # into the lower temp & out of the higher temp is the same as the volume + # out of the lower temp & into the higher temp over the timeline. + # Note: + # - Volume increase: Hot well is being charged and the cold well is being + # discharged. -> WKO in cooling mode + # - Volume decrease: Cold well is being charged and the hot well is being + # discharged. -> WKO in heating mode + + for ates_id in self.energy_system_components.get("low_temperature_ates", []): + stored_volume = self.state_vector(f"{ates_id}.Stored_volume") + volume_usage = 0.0 + volume_usage = stored_volume[0] - stored_volume[-1] + constraints.append((volume_usage, 0.0, 0.0)) + + return constraints + + heat_problem = run_esdl_mesido_optimization( + HeatingCoolingProblem, + base_folder=base_folder, + esdl_file_name="Heating and cooling network with return network.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_4.csv", + ) + results = heat_problem.extract_results() + + # checks to make sure the run was valid + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + # TODO: check below can be added, once the heat_to_discharge_test have been updated such + # that a pipe can absorb heat + # heat_to_discharge_test(heat_problem, results) + + +if __name__ == "__main__": + test_cold_demand = HeatColdDemand() + test_cold_demand.heating_cooling_case() diff --git a/examples/municipality/model/demand_profiles.csv b/examples/municipality/model/demand_profiles.csv new file mode 100644 index 000000000..07c660222 --- /dev/null +++ b/examples/municipality/model/demand_profiles.csv @@ -0,0 +1,8761 @@ 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a/examples/municipality/src/run_municipality.py +++ b/examples/municipality/src/run_municipality.py @@ -1,7 +1,7 @@ from pathlib import Path -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.workflows import EndScenarioSizingStagedHIGHS, run_end_scenario_sizing +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.workflows import EndScenarioSizingStaged, run_end_scenario_sizing if __name__ == "__main__": @@ -11,7 +11,7 @@ base_folder = Path(__file__).resolve().parent.parent solution = run_end_scenario_sizing( - EndScenarioSizingStagedHIGHS, + EndScenarioSizingStaged, base_folder=base_folder, esdl_file_name="GROW_withATES_Prod_install.esdl", esdl_parser=ESDLFileParser, diff --git a/examples/pandapipes/input/timeseries_constant.csv b/examples/pandapipes/input/timeseries_constant.csv new file mode 100644 index 000000000..de3d5a6a0 --- /dev/null +++ b/examples/pandapipes/input/timeseries_constant.csv @@ -0,0 +1,11 @@ +DateTime,demand_1 +2013-05-19 22:00:00,50000000.0 +2013-05-19 23:00:00,44444444.0 +2013-05-20 00:00:00,38888889.0 +2013-05-20 01:00:00,33333333.0 +2013-05-20 02:00:00,27777778.0 +2013-05-20 03:00:00,22222222.0 +2013-05-20 04:00:00,16666667.0 +2013-05-20 05:00:00,11111111.0 +2013-05-20 06:00:00,5555556.0 +2013-05-20 07:00:00,10.0 \ No newline at end of file diff --git a/examples/pandapipes/model/Test_Tree_S1C1.esdl b/examples/pandapipes/model/Test_Tree_S1C1.esdl new file mode 100644 index 000000000..ba3c6a9b6 --- /dev/null +++ b/examples/pandapipes/model/Test_Tree_S1C1.esdl @@ -0,0 +1,57 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples/pandapipes/src/pandapipeesdlparser.py b/examples/pandapipes/src/pandapipeesdlparser.py new file mode 100644 index 000000000..0cb8de959 --- /dev/null +++ b/examples/pandapipes/src/pandapipeesdlparser.py @@ -0,0 +1,346 @@ +# THIS CODE DOES NOT MEET THE CODE FORMATTING STANDARD +# Reason: this is only used to parse the esdl for the pandapipes validation test case + +""" +PandapipeEsdlParser +==================================== +The module for reading ESDL file to pandapipe format +""" + +from esdl.esdl_handler import EnergySystemHandler +import esdl +import pandapipes as pp +import math +import uuid + + +class PandapipeEsdlParserClass(object): + """ Class of Pandapipe ESDL Parser """ + def __init__(self): + """ + Function initialize class attribute + + Attributes + ------------ + esdlFileName + A string describes the name of esdl file + esh + An object EnergySystemHandler + esdl_asset + A mapping to the ESDL asset + """ + + self.esdlFileName = None + self.esh = EnergySystemHandler() + self.esdl_asset = {'heat':{}} + self.initAsset() + + def initAsset(self): + """ + Function clean esdl_asset attribute + """ + + self.esdl_asset['heat'] = {'consumer': [], 'producer': [], 'buffer': [], 'ates': [], 'heatpump': [], 'pump': [], + 'heatexchanger': [], 'pipe': [], 'joint': []} + + def get_assets_by_commodity_type(self, commodity_type: str): + """ + Function read asset from ESDL based on commodity + + Parameters + ----------- + commodity_type + HeatCommodity, GasCommodity or ElectricityCommodity + + """ + + assets = [] + for item in self.esh.energy_system.eAllContents(): + if isinstance(item, esdl.EnergyAsset): + for port in item.port: + if port.carrier.__class__.__name__ == commodity_type: + assets.append({"type": item.__class__.__name__, "name": item.name, "id": item.id}) + break + return assets + + def loadESDLFile(self, esdlFile): + """ + Function read esdl file and mapping the asset + + Parameters + ----------- + esdlFile + file name of ESDL file + """ + self.esdlFileName = esdlFile + self.esh.load_file(self.esdlFileName) + + assets = self.get_assets_by_commodity_type('HeatCommodity') + for asset in assets: + asset_obj = self.esh.get_by_id(asset["id"]) + self.add_asset_heat(asset_obj) + + def add_asset_heat(self, asset): + """ Function mapping ESDL asset to esdl_asset attribute""" + if isinstance(asset, esdl.Consumer): + self.esdl_asset['heat']['consumer'].append(asset) + + if isinstance(asset, esdl.Producer) or isinstance(asset, esdl.GasHeater): + self.esdl_asset['heat']['producer'].append(asset) + + if isinstance(asset, esdl.HeatStorage): + self.esdl_asset['heat']['buffer'].append(asset) + + if isinstance(asset, esdl.Pipe): + self.esdl_asset['heat']['pipe'].append(asset) + + if isinstance(asset, esdl.HeatExchange): + self.esdl_asset['heat']['heatexchanger'].append(asset) + + if isinstance(asset, esdl.Joint): + self.esdl_asset['heat']['joint'].append(asset) + + def add_additional_joint(self): + """ Function add extra joint when pipe is connected directly to producer/consumer""" + + for asset in self.esdl_asset['heat']['consumer'] + self.esdl_asset['heat']['producer']: + for port in asset.port: + if isinstance(port,esdl.InPort): + if not isinstance(port.connectedTo[0].eContainer(), esdl.Joint): + #add extra joint + coord=esdl.Point(lon=asset.geometry.lon+1e-4,lat=asset.geometry.lat+1e-4) + newjoint = esdl.Joint(id=str(uuid.uuid4()),name='inport joint ' + asset.name,geometry=coord) + newjoint_inport = esdl.InPort(id=str(uuid.uuid4()), name='inport') + newjoint_inport.carrier = port.carrier + newjoint_outport = esdl.OutPort(id=str(uuid.uuid4()), name='outport') + newjoint_outport.carrier = port.carrier + newjoint.port.append(newjoint_inport) + newjoint.port.append(newjoint_outport) + self.esdl_asset['heat']['joint'].append(newjoint) + + #change connection to newjoint + in_asset = port.connectedTo[0].eContainer() + in_asset.port[1].connectedTo[0] = newjoint_inport + port.connectedTo.append(newjoint_outport) + + if isinstance(port, esdl.OutPort): + if not isinstance(port.connectedTo[0].eContainer(), esdl.Joint): + # add extra joint + coord = esdl.Point(lon=asset.geometry.lon -1e-4, lat=asset.geometry.lat -1e-4) + newjoint = esdl.Joint(id=str(uuid.uuid4()), name='outport joint ' + asset.name,geometry=coord) + newjoint_inport = esdl.InPort(id=str(uuid.uuid4()), name='inport') + newjoint_inport.carrier = port.carrier + newjoint_outport = esdl.OutPort(id=str(uuid.uuid4()), name='outport') + newjoint_outport.carrier = port.carrier + newjoint.port.append(newjoint_inport) + newjoint.port.append(newjoint_outport) + self.esdl_asset['heat']['joint'].append(newjoint) + + # change connection to newjoint + out_asset = port.connectedTo[0].eContainer() + out_asset.port[0].connectedTo[0] = newjoint_outport + port.connectedTo.append(newjoint_inport) + + + + def createpandapipenet(self): + """ + Function create pandapipe network from esdl_asset + + return argument + + Parameters + ----------- + net + pandapipe network + net_asset + system component + Tsup + Supply temperature + Tret + Return temperature + """ + + # specify water properties + print("\nNote that the water properties have been hardcoded\n") + + import pandapipes.properties.fluids as fl + water_const = fl.Fluid("water_const", "liquid") + + density_mesido = 988 + density_const = fl.FluidPropertyConstant(density_mesido) + kinematic_viscosity_mesido = 3.6437149167588743e-07 # @ T=80 degrees + viscosity_const = fl.FluidPropertyConstant(kinematic_viscosity_mesido * density_mesido) + heat_capacity_const = fl.FluidPropertyConstant(4200) + + water_const.add_property(property_name="density", prop=density_const) + water_const.add_property(property_name="viscosity", prop=viscosity_const) + water_const.add_property(property_name="heat_capacity", prop=heat_capacity_const) + + net = pp.create_empty_network(fluid="water") + + fl._add_fluid_to_net(net, water_const) # checl fluid used -->> net.fluid + + + net_asset = {'DemandCluster': [], 'ProductionCluster': [], 'Buffer': [], 'ATES': [], 'Heatpump': [], 'Pump': [], + 'HeatExchanger': [], 'Pipe': []} + + + nodeids = [] + for asset in self.esdl_asset['heat']['joint']: + for port in asset.port: + if port.carrier.__class__.__name__ == 'HeatCommodity': + if not port.carrier.supplyTemperature == 0: + Tfluid = port.carrier.supplyTemperature + if not port.carrier.returnTemperature == 0: + Tfluid = port.carrier.returnTemperature + + coord = (asset.geometry.lon, asset.geometry.lat) + + pp.create_junction(net, + pn_bar=100, + tfluid_k=273.15 + Tfluid, + name=asset.name, + geodata=coord) + + nodeids.append(asset.id) + + + dx = 1000 #m + for asset in self.esdl_asset['heat']['pipe']: + for port in asset.port: + if isinstance(port, esdl.InPort): + node_input_id = port.connectedTo[0].eContainer().id + if isinstance(port, esdl.OutPort): + node_output_id = port.connectedTo[0].eContainer().id + + coord = [] + for point in asset.geometry.point: + coord.append((point.lon, point.lat)) + + # temp_inner_diam_m = ( + # asset.innerDiameter if asset.diameter.name=='DN200' + # else float(asset.diameter.name[2:])*1e-3 + # ) + pp.create_pipe_from_parameters(net, + from_junction=nodeids.index(node_input_id), + to_junction=nodeids.index(node_output_id), + length_km=asset.length * 1e-3, + sections=math.ceil(asset.length / dx), + alpha_w_per_m2k=0.5, + k_mm=0.2, + text_k=273.15 + 10.0, + diameter_m=asset.innerDiameter, + name=asset.name, + geodata=coord) + + producer = 0 + for asset in self.esdl_asset['heat']['producer']: + producer = producer + 1 + for port in asset.port: + if isinstance(port, esdl.InPort): + node_input_id = port.connectedTo[0].eContainer().id + if isinstance(port, esdl.OutPort): + node_output_id = port.connectedTo[0].eContainer().id + + for port in asset.port: + if port.carrier.__class__.__name__ == 'HeatCommodity': + if not port.carrier.supplyTemperature == 0: + Tsup = port.carrier.supplyTemperature + if not port.carrier.returnTemperature == 0: + Tret = port.carrier.returnTemperature + + coord = (asset.geometry.lon, asset.geometry.lat) + + node_valve = pp.create_junction(net, + pn_bar=100, + tfluid_k=273.15 + Tsup, + name='valve joint ' + asset.name, + geodata=coord) + + pp.create_flow_control(net, + from_junction=node_valve, + to_junction=nodeids.index(node_output_id), + controlled_mdot_kg_per_s=0, + diameter_m=0.5, + control_active=True, + name='valve ' + asset.name) + + pp.create_circ_pump_const_mass_flow(net, + return_junction=nodeids.index(node_input_id), + flow_junction=node_valve, + p_flow_bar=100, + mdot_flow_kg_per_s=0.0, + t_flow_k=273.15 + Tsup, + name=asset.name, + type='auto') + + + for asset in self.esdl_asset['heat']['consumer']: + for port in asset.port: + if isinstance(port, esdl.InPort): + node_input_id = port.connectedTo[0].eContainer().id + if isinstance(port, esdl.OutPort): + node_output_id = port.connectedTo[0].eContainer().id + + for port in asset.port: + if port.carrier.__class__.__name__ == 'HeatCommodity': + if not port.carrier.supplyTemperature == 0: + Tsup = port.carrier.supplyTemperature + if not port.carrier.returnTemperature == 0: + Tret = port.carrier.returnTemperature + + coord = (asset.geometry.lon, asset.geometry.lat) + + node_valve = pp.create_junction(net, + pn_bar=100, + tfluid_k=273.15 + Tsup, + name='valve joint ' + asset.name, + geodata=coord) + + + pp.create_flow_control(net, + from_junction=nodeids.index(node_input_id), + to_junction=node_valve, + controlled_mdot_kg_per_s=0, + diameter_m=0.5, + control_active=True, + name='valve ' + asset.name) + + pp.create_heat_exchanger(net, + from_junction=node_valve, + to_junction=nodeids.index(node_output_id), + diameter_m=0.5, + qext_w=0.0, + name=asset.name) + + + return net, net_asset, Tsup, Tret + + + def correcting_pressure_return(self, net): + + + # find minimum pressure at inlet consumer + min_inlet_pressure = net.res_flow_control.p_from_bar.min() + idxmin = net.res_flow_control.p_from_bar.idxmin() + + dP_cons = net.res_flow_control.p_from_bar.values - net.res_flow_control.p_to_bar.values + + dP_offset = 0.5 - dP_cons[idxmin] + + # shift junction pressure (return side only) + idx_node_return = net.junction.index[net.junction.tfluid_k==net.junction.tfluid_k.min()] + net.res_junction.p_bar[idx_node_return] = net.res_junction.p_bar[idx_node_return] - dP_offset + + + # update pressure at pipe + net.res_pipe.p_from_bar = net.res_junction.p_bar[net.pipe.from_junction].values + net.res_pipe.p_to_bar = net.res_junction.p_bar[net.pipe.to_junction].values + + # update pressure at producer + net.res_circ_pump_mass.deltap_bar = net.res_junction.p_bar[net.circ_pump_mass.flow_junction].values - net.res_junction.p_bar[net.circ_pump_mass.return_junction].values + + + + return net \ No newline at end of file diff --git a/examples/pandapipes/src/run_example.py b/examples/pandapipes/src/run_example.py new file mode 100644 index 000000000..0e6ddb863 --- /dev/null +++ b/examples/pandapipes/src/run_example.py @@ -0,0 +1,125 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.io.write_output import ScenarioOutput + + +from rtctools.optimization.collocated_integrated_optimization_problem import ( + CollocatedIntegratedOptimizationProblem, +) +from rtctools.optimization.goal_programming_mixin import Goal +from rtctools.optimization.linearized_order_goal_programming_mixin import ( + LinearizedOrderGoalProgrammingMixin, +) +from rtctools.optimization.single_pass_goal_programming_mixin import SinglePassGoalProgrammingMixin +from rtctools.util import run_optimization_problem + + +class TargetDemandGoal(Goal): + priority = 1 + + order = 2 + + def __init__(self, optimization_problem): + self.target_min = optimization_problem.get_timeseries("demand_1.target_heat_demand") + self.target_max = optimization_problem.get_timeseries("demand_1.target_heat_demand") + self.function_range = (0.0, 60e6) + self.function_nominal = 1e6 + + def function(self, optimization_problem, ensemble_member): + return optimization_problem.state("demand_1.Heat_demand") + + +class MinimizeProduction(Goal): + priority = 2 + + order = 1 + + def __init__(self): + self.function_nominal = 1e6 + + def function(self, optimization_problem, ensemble_member): + sum = 0 + for source in optimization_problem.energy_system_components.get("heat_source", []): + sum = optimization_problem.state(f"{source}.Heat_source") + return sum + + +class SourcePipeSink( + ScenarioOutput, + TechnoEconomicMixin, + LinearizedOrderGoalProgrammingMixin, + SinglePassGoalProgrammingMixin, + ESDLMixin, + CollocatedIntegratedOptimizationProblem, +): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + def path_goals(self): + g = super().path_goals().copy() + g.append(TargetDemandGoal(self)) + g.append(MinimizeProduction()) + return g + + def post(self): + super().post() + + +class HeatProblemHydraulic(SourcePipeSink): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.heat_network_settings["head_loss_option"] = ( + HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY + ) + self.heat_network_settings["n_linearization_lines"] = 3 + self.heat_network_settings["minimize_head_losses"] = True + + def energy_system_options(self): + options = super().energy_system_options() + + return options + + def solver_options(self): + options = super().solver_options() + # options["solver"] = "gurobi" + + return options + + +if __name__ == "__main__": + solution = run_optimization_problem( + HeatProblemHydraulic, + esdl_file_name="Test_Tree_S1C1.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_constant.csv", + ) + results = solution.extract_results() + + # mdata_points = 10 + # print("dP, bar") + # print(-results[f"Pipe1.dH"] * 988.0 * 9.81 / 100e3) # pressure in bar + # print(-results[f"Pipe1_ret.dH"] * 988.0 * 9.81 / 100e3) # pressure in bar + + # print("dP, kPa") + # print(-results[f"Pipe1.dH"] * 988.0 * 9.81 / 1e3) # kPa + # print(-results[f"Pipe1_ret.dH"] * 988.0 * 9.81 / 1e3) # kPa + + # print("dH, m") + # print(-results[f"Pipe1.dH"]) # m + # print(-results[f"Pipe1_ret.dH"]) # m + + # print("mass flow, kg/s") + # print(results[f"Pipe1.Q"][0:mdata_points] * 988.0) + + # print("v, m/s") + # print(results[f"Pipe1.Q"][0:mdata_points] / solution.parameters(0)[f"Pipe1.area"]) + # print(results[f"Pipe1_ret.Q"][0:mdata_points] / solution.parameters(0)[f"Pipe1_ret.area"]) + + # print("dHP, W") + # print(results["Pipe1_ret.Hydraulic_power"][0:mdata_points]) + + # a = 1 diff --git a/examples/pipe_diameter_sizing/input/timeseries_import.xml b/examples/pipe_diameter_sizing/input/timeseries_import.xml index 513e247b9..329f810f5 100644 --- a/examples/pipe_diameter_sizing/input/timeseries_import.xml +++ b/examples/pipe_diameter_sizing/input/timeseries_import.xml @@ -13,8 +13,8 @@ -999.0 W - - + +
@@ -28,8 +28,8 @@ -999.0 W
- - + +
@@ -43,7 +43,7 @@ -999.0 W
- - + + diff --git a/examples/pipe_diameter_sizing/model/2a.esdl b/examples/pipe_diameter_sizing/model/2a.esdl index 5413b8e74..06f9a58c7 100644 --- a/examples/pipe_diameter_sizing/model/2a.esdl +++ b/examples/pipe_diameter_sizing/model/2a.esdl @@ -49,7 +49,7 @@ - + @@ -182,7 +182,7 @@ - + @@ -191,7 +191,7 @@ - + @@ -200,7 +200,7 @@ - + @@ -345,7 +345,7 @@ - + diff --git a/examples/pipe_diameter_sizing/src/example.py b/examples/pipe_diameter_sizing/src/example.py index 7e7ca070d..95a0ebf81 100644 --- a/examples/pipe_diameter_sizing/src/example.py +++ b/examples/pipe_diameter_sizing/src/example.py @@ -1,3 +1,9 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.pipe_class import PipeClass +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -15,12 +21,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.pipe_class import PipeClass -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 @@ -53,7 +53,7 @@ def function(self, optimization_problem, ensemble_member): length = parameters[f"{p}.length"] var_name = optimization_problem.pipe_diameter_symbol_name(p) - nominal += length * optimization_problem.variable_nominal(var_name) + nominal += length * optimization_problem.variable_nominal(var_name) * 2.0 obj += optimization_problem.extra_variable(var_name, ensemble_member) * length @@ -76,9 +76,12 @@ def energy_system_options(self): return options def pipe_classes(self, pipe): + # Do not delete pipeclass DN40, locally it runs with DN40, but in pipeline it seems + # that scaling is a bit too much off resulting in infeasibility probably because of + # machine accuracy. If scaling can be improved DN40 can be included again. return [ PipeClass("None", 0.0, 0.0, (0.0, 0.0), 0.0), - PipeClass("DN40", 0.0431, 1.5, (0.179091, 0.005049), 1.0), + # PipeClass("DN40", 0.0431, 1.5, (0.179091, 0.005049), 1.0), PipeClass("DN50", 0.0545, 1.7, (0.201377, 0.006086), 2.0), PipeClass("DN65", 0.0703, 1.9, (0.227114, 0.007300), 3.0), PipeClass("DN80", 0.0825, 2.2, (0.238244, 0.007611), 4.0), diff --git a/manual_run/testing_bugs/model/Demo_areas with return network.esdl b/manual_run/testing_bugs/model/Demo_areas with return network.esdl new file mode 100644 index 000000000..7bf80977f --- /dev/null +++ b/manual_run/testing_bugs/model/Demo_areas with return network.esdl @@ -0,0 +1,598 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/manual_run/testing_bugs/model/test2.esdl b/manual_run/testing_bugs/model/test2.esdl new file mode 100644 index 000000000..01a586d8f --- /dev/null +++ b/manual_run/testing_bugs/model/test2.esdl @@ -0,0 +1,68 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/manual_run/testing_bugs/src/run_grow.py b/manual_run/testing_bugs/src/run_grow.py new file mode 100644 index 000000000..f7ec98bd0 --- /dev/null +++ b/manual_run/testing_bugs/src/run_grow.py @@ -0,0 +1,19 @@ +from pathlib import Path + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.workflows import EndScenarioSizingStaged, run_end_scenario_sizing + +if __name__ == "__main__": + import time + + start_time = time.time() + base_folder = Path(__file__).resolve().parent.parent + + solution = run_end_scenario_sizing( + EndScenarioSizingStaged, + base_folder=base_folder, + esdl_file_name="Base Netwerk Delft.esdl", + esdl_parser=ESDLFileParser, + ) + + print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) diff --git a/setup.cfg b/setup.cfg index d3fb191dd..cbfe35f91 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,5 +1,5 @@ [metadata] -license_file = COPYING.LESSER +license_file = LICENSE # See the docstring in versioneer.py for instructions. Note that you must # re-run 'versioneer.py setup' after changing this section, and commit the @@ -8,10 +8,10 @@ license_file = COPYING.LESSER [versioneer] VCS = git style = pep440 -versionfile_source = src/rtctools_heat_network/_version.py -versionfile_build = rtctools_heat_network/_version.py +versionfile_source = src/mesido/_version.py +versionfile_build = mesido/_version.py tag_prefix = -parentdir_prefix = rtctools_heat_network- +parentdir_prefix = mesido- [flake8] diff --git a/setup.py b/setup.py index 3c6aa32d2..1ba616261 100644 --- a/setup.py +++ b/setup.py @@ -1,6 +1,6 @@ -"""Heat network models for RTC-Tools 2. +"""Multi Energy System Optimization -Includes Modelica models and their accompanying Mixins for milp networks. +MILP optimization for design and operational optimization """ import sys @@ -37,40 +37,37 @@ sys.exit(f"Sorry, Python 3.8 to 3.10 is required. You are using {sys.version_info}") setup( - name="rtc-tools-milp-network", + name="mesido", version=versioneer.get_version(), description=DOCLINES[0], long_description=long_description, long_description_content_type="text/markdown", classifiers=[_f for _f in CLASSIFIERS.split("\n") if _f], - url="https://github.com/Nieuwe-Warmte-Nu/rtc-tools-heat-network", + url="https://github.com/Multi-Energy-Systems-Optimization/mesido/", author="Jim Rojer", author_email="jim.rojer@tno.nl", maintainer="Jim Rojer, Kobus van Rooyen, Kelbij Star, " "Femke Janssen, Jesús Andrés Rodríguez Sarasty, " "Thijs van der Klauw", license="LGPLv3", - keywords="milp network optimization rtc tools", + keywords="Multi-Energy-Systems, optimization", platforms=["Windows", "Linux", "Mac OS-X", "Unix"], packages=find_packages("src"), package_dir={"": "src"}, install_requires=[ "influxdb >= 5.3.1", - "pyecore", + "pyecore >= 0.13.2", "pymoca >= 0.9.0", - "rtc-tools == 2.6.0a3", - "pyesdl >= 23.12, < 24.0", + "rtc-tools-gil-comp == 2.6.1", + "pyesdl == 25.5.1", "pandas >= 1.3.1, < 2.0", - "casadi == 3.6.3", + "casadi-gil-comp == 3.6.7", "StrEnum == 0.4.15", "CoolProp==6.6.0", - "iapws==1.5.3", ], tests_require=["pytest", "pytest-runner", "numpy"], include_package_data=True, python_requires=">=3.8,<3.11", cmdclass=versioneer.get_cmdclass(), - entry_points={ - "rtctools.libraries.modelica": ["library_folder = rtctools_heat_network:modelica"] - }, + entry_points={"rtctools.libraries.modelica": ["library_folder = mesido:modelica"]}, ) diff --git a/src/rtctools_heat_network/__init__.py b/src/mesido/__init__.py similarity index 100% rename from src/rtctools_heat_network/__init__.py rename to src/mesido/__init__.py diff --git a/src/rtctools_heat_network/_darcy_weisbach.py b/src/mesido/_darcy_weisbach.py similarity index 88% rename from src/rtctools_heat_network/_darcy_weisbach.py rename to src/mesido/_darcy_weisbach.py index 395c764e3..32aea1d7e 100644 --- a/src/rtctools_heat_network/_darcy_weisbach.py +++ b/src/mesido/_darcy_weisbach.py @@ -2,13 +2,11 @@ import CoolProp as cP -from iapws import IAPWS95 +from mesido.constants import GRAVITATIONAL_CONSTANT +from mesido.network_common import NetworkSettings import numpy as np -from .constants import GRAVITATIONAL_CONSTANT -from .network_common import NetworkSettings - def _kinematic_viscosity(temperature, network_type=NetworkSettings.NETWORK_TYPE_HEAT, pressure=0.0): """ @@ -20,11 +18,17 @@ def _kinematic_viscosity(temperature, network_type=NetworkSettings.NETWORK_TYPE_ which the pressure [Pa] and temperature [K] are provided as inputs. The gas composition is based on Groninger gas. """ + + # Kinematic viscosity [m2/s] = Dynamic viscosity [Pa-s] / density [kg/m3] if network_type == NetworkSettings.NETWORK_TYPE_HEAT: - return IAPWS95(T=273.15 + temperature, P=0.5).nu + return cP.CoolProp.PropsSI( + "V", "T", 273.15 + temperature, "P", 0.5 * 10**6, "WATER" + ) / cP.CoolProp.PropsSI("D", "T", 273.15 + temperature, "P", 0.5 * 10**6, "WATER") elif network_type == NetworkSettings.NETWORK_TYPE_HYDROGEN: pressure = pressure if pressure else 101325 - return cP.CoolProp.PropsSI("V", "T", 273.15 + temperature, "P", pressure, "HYDROGEN") + return cP.CoolProp.PropsSI( + "V", "T", 273.15 + temperature, "P", pressure, "HYDROGEN" + ) / cP.CoolProp.PropsSI("D", "T", 273.15 + temperature, "P", pressure, "HYDROGEN") elif network_type == NetworkSettings.NETWORK_TYPE_GAS: pressure = pressure if pressure else 101325 return cP.CoolProp.PropsSI( @@ -34,6 +38,13 @@ def _kinematic_viscosity(temperature, network_type=NetworkSettings.NETWORK_TYPE_ "P", pressure, NetworkSettings.NETWORK_COMPOSITION_GAS, + ) / cP.CoolProp.PropsSI( + "D", + "T", + 273.15 + temperature, + "P", + pressure, + NetworkSettings.NETWORK_COMPOSITION_GAS, ) else: raise Exception("Unknown network type for computing dynamic viscosity") diff --git a/src/rtctools_heat_network/_heat_loss_u_values_pipe.py b/src/mesido/_heat_loss_u_values_pipe.py similarity index 99% rename from src/rtctools_heat_network/_heat_loss_u_values_pipe.py rename to src/mesido/_heat_loss_u_values_pipe.py index d3fb7889b..7ae0355e1 100644 --- a/src/rtctools_heat_network/_heat_loss_u_values_pipe.py +++ b/src/mesido/_heat_loss_u_values_pipe.py @@ -165,7 +165,7 @@ def pipe_heat_loss( + (length * u_2 * dtemp) ) - if heat_loss < 0: + if heat_loss < 0 and temperature > temperature_ground: raise Exception(f"Heat loss of pipe {p} should be nonnegative.") return heat_loss diff --git a/src/rtctools_heat_network/_version.py b/src/mesido/_version.py similarity index 99% rename from src/rtctools_heat_network/_version.py rename to src/mesido/_version.py index 57704679a..9c52cbbbc 100644 --- a/src/rtctools_heat_network/_version.py +++ b/src/mesido/_version.py @@ -43,8 +43,8 @@ def get_config(): cfg.VCS = "git" cfg.style = "pep440" cfg.tag_prefix = "" - cfg.parentdir_prefix = "rtctools_heat_network-" - cfg.versionfile_source = "src/rtctools_heat_network/_version.py" + cfg.parentdir_prefix = "mesido-" + cfg.versionfile_source = "src/mesido/_version.py" cfg.verbose = False return cfg diff --git a/src/rtctools_heat_network/asset_sizing_mixin.py b/src/mesido/asset_sizing_mixin.py similarity index 77% rename from src/rtctools_heat_network/asset_sizing_mixin.py rename to src/mesido/asset_sizing_mixin.py index 5c716dcc4..b70eae3b4 100644 --- a/src/rtctools_heat_network/asset_sizing_mixin.py +++ b/src/mesido/asset_sizing_mixin.py @@ -1,8 +1,18 @@ import logging +import sys from typing import List, Set import casadi as ca +import esdl + +from mesido._heat_loss_u_values_pipe import pipe_heat_loss +from mesido.base_component_type_mixin import BaseComponentTypeMixin +from mesido.demand_insulation_class import DemandInsulationClass +from mesido.head_loss_class import HeadLossOption +from mesido.network_common import NetworkSettings +from mesido.pipe_class import CableClass, GasPipeClass, PipeClass + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -10,15 +20,7 @@ ) from rtctools.optimization.timeseries import Timeseries -from rtctools_heat_network._heat_loss_u_values_pipe import pipe_heat_loss - - -from .base_component_type_mixin import BaseComponentTypeMixin -from .demand_insulation_class import DemandInsulationClass -from .head_loss_class import HeadLossOption -from .pipe_class import CableClass, GasPipeClass, PipeClass - -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") class AssetSizingMixin(BaseComponentTypeMixin, CollocatedIntegratedOptimizationProblem): @@ -40,52 +42,52 @@ def __init__(self, *args, **kwargs): self._asset_aggregation_count_var_map = {} # Variable for the maximum discharge under pipe class optimization - self.__pipe_topo_max_discharge_var = {} - self._pipe_topo_max_discharge_map = {} - self.__pipe_topo_max_discharge_nominals = {} - self.__pipe_topo_max_discharge_var_bounds = {} + self.__heat_pipe_topo_max_discharge_var = {} + self._heat_pipe_topo_max_discharge_map = {} + self.__heat_pipe_topo_max_discharge_nominals = {} + self.__heat_pipe_topo_max_discharge_var_bounds = {} # Variable for the diameter of a pipe during pipe-class optimization - self.__pipe_topo_diameter_var = {} - self.__pipe_topo_diameter_var_bounds = {} - self._pipe_topo_diameter_map = {} - self.__pipe_topo_diameter_nominals = {} + self.__heat_pipe_topo_diameter_var = {} + self.__heat_pipe_topo_diameter_var_bounds = {} + self._heat_pipe_topo_diameter_map = {} + self.__heat_pipe_topo_diameter_nominals = {} # Variable for the investmentcost in eur/m during pipe-class optimization - self.__pipe_topo_cost_var = {} - self.__pipe_topo_cost_var_bounds = {} - self._pipe_topo_cost_map = {} - self.__pipe_topo_cost_nominals = {} + self.__heat_pipe_topo_cost_var = {} + self.__heat_pipe_topo_cost_var_bounds = {} + self._heat_pipe_topo_cost_map = {} + self.__heat_pipe_topo_cost_nominals = {} # Boolean variables for the various pipe class options per pipe - # The self._pipe_topo_pipe_class_map is already initiated in the HeatPhysicsMixin - self.__pipe_topo_pipe_class_var = {} - self.__pipe_topo_pipe_class_var_bounds = {} - self.__pipe_topo_pipe_class_result = {} + # The self._heat_pipe_topo_pipe_class_map is already initiated in the HeatPhysicsMixin + self.__heat_pipe_topo_pipe_class_var = {} + self.__heat_pipe_topo_pipe_class_var_bounds = {} + self.__heat_pipe_topo_pipe_class_result = {} - self.__pipe_topo_pipe_class_discharge_ordering_var = {} - self.__pipe_topo_pipe_class_discharge_ordering_var_bounds = {} - self.__pipe_topo_pipe_class_discharge_ordering_map = {} + self.__heat_pipe_topo_pipe_class_discharge_ordering_var = {} + self.__heat_pipe_topo_pipe_class_discharge_ordering_var_bounds = {} + self.__heat_pipe_topo_pipe_class_discharge_ordering_map = {} - self.__pipe_topo_pipe_class_cost_ordering_map = {} - self.__pipe_topo_pipe_class_cost_ordering_var = {} - self.__pipe_topo_pipe_class_cost_ordering_var_bounds = {} + self.__heat_pipe_topo_pipe_class_cost_ordering_map = {} + self.__heat_pipe_topo_pipe_class_cost_ordering_var = {} + self.__heat_pipe_topo_pipe_class_cost_ordering_var_bounds = {} - self.__pipe_topo_pipe_class_heat_loss_ordering_map = {} - self.__pipe_topo_pipe_class_heat_loss_ordering_var = {} - self.__pipe_topo_pipe_class_heat_loss_ordering_var_bounds = {} + self.__heat_pipe_topo_pipe_class_heat_loss_ordering_map = {} + self.__heat_pipe_topo_pipe_class_heat_loss_ordering_var = {} + self.__heat_pipe_topo_pipe_class_heat_loss_ordering_var_bounds = {} - self.__pipe_topo_global_pipe_class_count_var = {} - self.__pipe_topo_global_pipe_class_count_map = {} - self.__pipe_topo_global_pipe_class_count_var_bounds = {} + self.__heat_pipe_topo_global_pipe_class_count_var = {} + self.__heat_pipe_topo_global_pipe_class_count_map = {} + self.__heat_pipe_topo_global_pipe_class_count_var_bounds = {} # Dict to specifically update the discharge bounds under pipe-class optimization - self.__pipe_topo_heat_discharge_bounds = {} + self.__heat_pipe_topo_heat_discharge_bounds = {} # list with entry per ensemble member containing dicts of pipe parameter values for # diameter, area and heatloss. - self.__pipe_topo_diameter_area_parameters = [] - self.__pipe_topo_heat_loss_parameters = [] + self.__heat_pipe_topo_diameter_area_parameters = [] + self.__heat_pipe_topo_heat_loss_parameters = [] # Gas # Variable for the maximum discharge under pipe class optimization @@ -107,7 +109,7 @@ def __init__(self, *args, **kwargs): self.__gas_pipe_topo_cost_nominals = {} # Boolean variables for the various pipe class options per pipe - # The self._pipe_topo_pipe_class_map is already initiated in the HeatPhysicsMixin + # The self._gas_pipe_topo_pipe_class_map is already initiated in the GasPhysicsMixin self.__gas_pipe_topo_pipe_class_var = {} self.__gas_pipe_topo_pipe_class_var_bounds = {} self.__gas_pipe_topo_pipe_class_result = {} @@ -144,7 +146,8 @@ def __init__(self, *args, **kwargs): self.__electricity_cable_topo_cost_nominals = {} # Boolean variables for the various pipe class options per pipe - # The self._pipe_topo_pipe_class_map is already initiated in the HeatPhysicsMixin + # The self._electricity_cable_topo_cable_class_map is already initiated in the + # ElectricityPhysicsMixin self.__electricity_cable_topo_cable_class_var = {} self.__electricity_cable_topo_cable_class_var_bounds = {} self.__electricity_cable_topo_cable_class_result = {} @@ -192,17 +195,17 @@ def pre(self): # than a single pipe class for a certain pipe, we set the diameter # and area to NaN to prevent erroneous constraints. for _ in range(self.ensemble_size): - self.__pipe_topo_diameter_area_parameters.append({}) - self.__pipe_topo_heat_loss_parameters.append({}) + self.__heat_pipe_topo_diameter_area_parameters.append({}) + self.__heat_pipe_topo_heat_loss_parameters.append({}) unique_pipe_classes = self.get_unique_pipe_classes() for pc in unique_pipe_classes: pipe_class_count = f"{pc.name}__global_pipe_class_count" - self.__pipe_topo_global_pipe_class_count_var[pipe_class_count] = ca.MX.sym( + self.__heat_pipe_topo_global_pipe_class_count_var[pipe_class_count] = ca.MX.sym( pipe_class_count ) - self.__pipe_topo_global_pipe_class_count_map[f"{pc.name}"] = pipe_class_count - self.__pipe_topo_global_pipe_class_count_var_bounds[pipe_class_count] = ( + self.__heat_pipe_topo_global_pipe_class_count_map[f"{pc.name}"] = pipe_class_count + self.__heat_pipe_topo_global_pipe_class_count_var_bounds[pipe_class_count] = ( 0.0, len(self.energy_system_components.get("heat_pipe", [])), ) @@ -252,16 +255,18 @@ def pre(self): self._electricity_cable_topo_max_current_map[cable] = max_current_var_name if len(cable_classes) > 0: - self.__electricity_cable_topo_max_current_nominals[cable] = np.median(max_currents) - self.__electricity_cable_topo_max_current_var_bounds[cable] = ( + self.__electricity_cable_topo_max_current_nominals[max_current_var_name] = ( + np.median(max_currents) + ) + self.__electricity_cable_topo_max_current_var_bounds[max_current_var_name] = ( -max(max_currents), max(max_currents), ) else: - self.__electricity_cable_topo_max_current_nominals[cable] = parameters[ - f"{cable}.max_current" - ] - self.__electricity_cable_topo_max_current_var_bounds[cable] = ( + self.__electricity_cable_topo_max_current_nominals[max_current_var_name] = ( + parameters[f"{cable}.max_current"] + ) + self.__electricity_cable_topo_max_current_var_bounds[max_current_var_name] = ( -parameters[f"{cable}.max_current"], parameters[f"{cable}.max_current"], ) @@ -386,17 +391,19 @@ def pre(self): self._gas_pipe_topo_max_discharge_map[pipe] = max_discharge_var_name if len(pipe_classes) > 0: - self.__gas_pipe_topo_max_discharge_nominals[pipe] = np.median(max_discharges) - self.__gas_pipe_topo_max_discharge_var_bounds[pipe] = ( + self.__gas_pipe_topo_max_discharge_nominals[max_discharge_var_name] = np.median( + max_discharges + ) + self.__gas_pipe_topo_max_discharge_var_bounds[max_discharge_var_name] = ( -max(max_discharges), max(max_discharges), ) else: max_velocity = self.gas_network_settings["maximum_velocity"] - self.__gas_pipe_topo_max_discharge_nominals[pipe] = ( + self.__gas_pipe_topo_max_discharge_nominals[max_discharge_var_name] = ( parameters[f"{pipe}.area"] * max_velocity ) - self.__gas_pipe_topo_max_discharge_var_bounds[pipe] = ( + self.__gas_pipe_topo_max_discharge_var_bounds[max_discharge_var_name] = ( -parameters[f"{pipe}.area"] * max_velocity, parameters[f"{pipe}.area"] * max_velocity, ) @@ -488,6 +495,7 @@ def pre(self): pipe_class_cost_ordering_name ] = (0.0, 1.0) + set_self_hot_pipes = set(self.hot_pipes) for pipe in self.energy_system_components.get("heat_pipe", []): pipe_classes = self.pipe_classes(pipe) # cold_pipe = self.hot_to_cold_pipe(pipe) @@ -503,32 +511,34 @@ def pre(self): # to the user. Contrary to that, the pipe class booleans are very # much an internal affair. diam_var_name = f"{pipe}__hn_diameter" - self.__pipe_topo_diameter_var[diam_var_name] = ca.MX.sym(diam_var_name) - self._pipe_topo_diameter_map[pipe] = diam_var_name + self.__heat_pipe_topo_diameter_var[diam_var_name] = ca.MX.sym(diam_var_name) + self._heat_pipe_topo_diameter_map[pipe] = diam_var_name cost_var_name = f"{pipe}__hn_cost" - self.__pipe_topo_cost_var[cost_var_name] = ca.MX.sym(cost_var_name) - self._pipe_topo_cost_map[pipe] = cost_var_name + self.__heat_pipe_topo_cost_var[cost_var_name] = ca.MX.sym(cost_var_name) + self._heat_pipe_topo_cost_map[pipe] = cost_var_name max_discharge_var_name = f"{pipe}__hn_max_discharge" max_discharges = [c.maximum_discharge for c in pipe_classes] - self.__pipe_topo_max_discharge_var[max_discharge_var_name] = ca.MX.sym( + self.__heat_pipe_topo_max_discharge_var[max_discharge_var_name] = ca.MX.sym( max_discharge_var_name ) - self._pipe_topo_max_discharge_map[pipe] = max_discharge_var_name + self._heat_pipe_topo_max_discharge_map[pipe] = max_discharge_var_name if len(pipe_classes) > 0: - self.__pipe_topo_max_discharge_nominals[pipe] = np.median(max_discharges) - self.__pipe_topo_max_discharge_var_bounds[pipe] = ( + self.__heat_pipe_topo_max_discharge_nominals[max_discharge_var_name] = np.median( + max_discharges + ) + self.__heat_pipe_topo_max_discharge_var_bounds[max_discharge_var_name] = ( -max(max_discharges), max(max_discharges), ) else: max_velocity = self.heat_network_settings["maximum_velocity"] - self.__pipe_topo_max_discharge_nominals[pipe] = ( + self.__heat_pipe_topo_max_discharge_nominals[max_discharge_var_name] = ( parameters[f"{pipe}.area"] * max_velocity ) - self.__pipe_topo_max_discharge_var_bounds[pipe] = ( + self.__heat_pipe_topo_max_discharge_var_bounds[max_discharge_var_name] = ( -parameters[f"{pipe}.area"] * max_velocity, parameters[f"{pipe}.area"] * max_velocity, ) @@ -537,47 +547,53 @@ def pre(self): # No pipe class decision to make for this pipe w.r.t. diameter diameter = parameters[f"{pipe}.diameter"] investment_cost = parameters[f"{pipe}.investment_cost_coefficient"] - self.__pipe_topo_diameter_var_bounds[diam_var_name] = (diameter, diameter) - self.__pipe_topo_cost_var_bounds[cost_var_name] = (investment_cost, investment_cost) + self.__heat_pipe_topo_diameter_var_bounds[diam_var_name] = (diameter, diameter) + self.__heat_pipe_topo_cost_var_bounds[cost_var_name] = ( + investment_cost, + investment_cost, + ) if diameter > 0.0: - self.__pipe_topo_diameter_nominals[diam_var_name] = diameter - self.__pipe_topo_cost_nominals[cost_var_name] = max(investment_cost, 1.0) + self.__heat_pipe_topo_diameter_nominals[diam_var_name] = diameter + self.__heat_pipe_topo_cost_nominals[cost_var_name] = max(investment_cost, 1.0) elif len(pipe_classes) == 1: # No pipe class decision to make for this pipe w.r.t. diameter diameter = pipe_classes[0].inner_diameter investment_cost = pipe_classes[0].investment_costs - self.__pipe_topo_diameter_var_bounds[diam_var_name] = (diameter, diameter) - self.__pipe_topo_cost_var_bounds[cost_var_name] = (investment_cost, investment_cost) + self.__heat_pipe_topo_diameter_var_bounds[diam_var_name] = (diameter, diameter) + self.__heat_pipe_topo_cost_var_bounds[cost_var_name] = ( + investment_cost, + investment_cost, + ) if diameter > 0.0: - self.__pipe_topo_diameter_nominals[diam_var_name] = diameter - self.__pipe_topo_cost_nominals[cost_var_name] = max(investment_cost, 1.0) + self.__heat_pipe_topo_diameter_nominals[diam_var_name] = diameter + self.__heat_pipe_topo_cost_nominals[cost_var_name] = max(investment_cost, 1.0) if investment_cost == 0.0: RuntimeWarning(f"{pipe} has an investment cost of 0. €/m") for ensemble_member in range(self.ensemble_size): - d = self.__pipe_topo_diameter_area_parameters[ensemble_member] + d = self.__heat_pipe_topo_diameter_area_parameters[ensemble_member] d[f"{pipe}.diameter"] = diameter d[f"{pipe}.area"] = pipe_classes[0].area else: diameters = [c.inner_diameter for c in pipe_classes] - self.__pipe_topo_diameter_var_bounds[diam_var_name] = ( + self.__heat_pipe_topo_diameter_var_bounds[diam_var_name] = ( min(diameters), max(diameters), ) costs = [c.investment_costs for c in pipe_classes] - self.__pipe_topo_cost_var_bounds[cost_var_name] = ( + self.__heat_pipe_topo_cost_var_bounds[cost_var_name] = ( min(costs), max(costs), ) - self.__pipe_topo_cost_nominals[cost_var_name] = np.median(costs) + self.__heat_pipe_topo_cost_nominals[cost_var_name] = np.median(costs) - self.__pipe_topo_diameter_nominals[diam_var_name] = min( + self.__heat_pipe_topo_diameter_nominals[diam_var_name] = min( x for x in diameters if x > 0.0 ) for ensemble_member in range(self.ensemble_size): - d = self.__pipe_topo_diameter_area_parameters[ensemble_member] + d = self.__heat_pipe_topo_diameter_area_parameters[ensemble_member] d[f"{pipe}.diameter"] = np.nan d[f"{pipe}.area"] = np.nan @@ -591,20 +607,28 @@ def pre(self): if not pipe_classes or options["neglect_pipe_heat_losses"]: # No pipe class decision to make for this pipe w.r.t. milp loss heat_loss = pipe_heat_loss(self, options, parameters, pipe) + if parameters[f"{pipe}.temperature"] > parameters[f"{pipe}.T_ground"]: + lb = 0.0 + else: + lb = 2.0 * heat_loss self._pipe_heat_loss_var_bounds[heat_loss_var_name] = ( - 0.0, - 2.0 * heat_loss, + lb, + 2.0 * abs(heat_loss), ) if heat_loss > 0: - self._pipe_heat_loss_nominals[heat_loss_var_name] = heat_loss + self._pipe_heat_loss_nominals[heat_loss_var_name] = abs(heat_loss) else: self._pipe_heat_loss_nominals[heat_loss_var_name] = max( - pipe_heat_loss(self, {"neglect_pipe_heat_losses": False}, parameters, pipe), + abs( + pipe_heat_loss( + self, {"neglect_pipe_heat_losses": False}, parameters, pipe + ) + ), 1.0, ) for ensemble_member in range(self.ensemble_size): - h = self.__pipe_topo_heat_loss_parameters[ensemble_member] + h = self.__heat_pipe_topo_heat_loss_parameters[ensemble_member] h[f"{pipe}.Heat_loss"] = pipe_heat_loss(self, options, parameters, pipe) elif len(pipe_classes) == 1: @@ -625,7 +649,7 @@ def pre(self): ) for ensemble_member in range(self.ensemble_size): - h = self.__pipe_topo_heat_loss_parameters[ensemble_member] + h = self.__heat_pipe_topo_heat_loss_parameters[ensemble_member] h[f"{pipe}.Heat_loss"] = heat_loss else: heat_losses = [ @@ -643,7 +667,7 @@ def pre(self): ) for ensemble_member in range(self.ensemble_size): - h = self.__pipe_topo_heat_loss_parameters[ensemble_member] + h = self.__heat_pipe_topo_heat_loss_parameters[ensemble_member] h[f"{pipe}.Heat_loss"] = max( pipe_heat_loss(self, options, parameters, pipe), 1.0 ) @@ -653,14 +677,14 @@ def pre(self): # No pipe class decision to make for this pipe pass else: - self._pipe_topo_pipe_class_map[pipe] = {} - self.__pipe_topo_pipe_class_discharge_ordering_map[pipe] = {} - self.__pipe_topo_pipe_class_cost_ordering_map[pipe] = {} - self.__pipe_topo_pipe_class_heat_loss_ordering_map[pipe] = {} + self._heat_pipe_topo_pipe_class_map[pipe] = {} + self.__heat_pipe_topo_pipe_class_discharge_ordering_map[pipe] = {} + self.__heat_pipe_topo_pipe_class_cost_ordering_map[pipe] = {} + self.__heat_pipe_topo_pipe_class_heat_loss_ordering_map[pipe] = {} for c in pipe_classes: neighbour = self.has_related_pipe(pipe) - if neighbour and pipe not in self.hot_pipes: + if neighbour and pipe not in set_self_hot_pipes: cold_pipe = self.cold_to_hot_pipe(pipe) pipe_class_var_name = f"{cold_pipe}__hn_pipe_class_{c.name}" pipe_class_ordering_name = ( @@ -684,39 +708,39 @@ def pre(self): f"{pipe}__hn_pipe_class_{c.name}_heat_loss_ordering" ) - self._pipe_topo_pipe_class_map[pipe][c] = pipe_class_var_name - self.__pipe_topo_pipe_class_var[pipe_class_var_name] = ca.MX.sym( + self._heat_pipe_topo_pipe_class_map[pipe][c] = pipe_class_var_name + self.__heat_pipe_topo_pipe_class_var[pipe_class_var_name] = ca.MX.sym( pipe_class_var_name ) - self.__pipe_topo_pipe_class_var_bounds[pipe_class_var_name] = (0.0, 1.0) + self.__heat_pipe_topo_pipe_class_var_bounds[pipe_class_var_name] = (0.0, 1.0) - self.__pipe_topo_pipe_class_discharge_ordering_map[pipe][ + self.__heat_pipe_topo_pipe_class_discharge_ordering_map[pipe][ c ] = pipe_class_ordering_name - self.__pipe_topo_pipe_class_discharge_ordering_var[pipe_class_ordering_name] = ( - ca.MX.sym(pipe_class_ordering_name) - ) - self.__pipe_topo_pipe_class_discharge_ordering_var_bounds[ + self.__heat_pipe_topo_pipe_class_discharge_ordering_var[ + pipe_class_ordering_name + ] = ca.MX.sym(pipe_class_ordering_name) + self.__heat_pipe_topo_pipe_class_discharge_ordering_var_bounds[ pipe_class_ordering_name ] = (0.0, 1.0) - self.__pipe_topo_pipe_class_cost_ordering_map[pipe][ + self.__heat_pipe_topo_pipe_class_cost_ordering_map[pipe][ c ] = pipe_class_cost_ordering_name - self.__pipe_topo_pipe_class_cost_ordering_var[pipe_class_cost_ordering_name] = ( - ca.MX.sym(pipe_class_cost_ordering_name) - ) - self.__pipe_topo_pipe_class_cost_ordering_var_bounds[ + self.__heat_pipe_topo_pipe_class_cost_ordering_var[ + pipe_class_cost_ordering_name + ] = ca.MX.sym(pipe_class_cost_ordering_name) + self.__heat_pipe_topo_pipe_class_cost_ordering_var_bounds[ pipe_class_cost_ordering_name ] = (0.0, 1.0) - self.__pipe_topo_pipe_class_heat_loss_ordering_map[pipe][ + self.__heat_pipe_topo_pipe_class_heat_loss_ordering_map[pipe][ c ] = pipe_class_heat_loss_ordering_name - self.__pipe_topo_pipe_class_heat_loss_ordering_var[ + self.__heat_pipe_topo_pipe_class_heat_loss_ordering_var[ pipe_class_heat_loss_ordering_name ] = ca.MX.sym(pipe_class_heat_loss_ordering_name) - self.__pipe_topo_pipe_class_heat_loss_ordering_var_bounds[ + self.__heat_pipe_topo_pipe_class_heat_loss_ordering_var_bounds[ pipe_class_heat_loss_ordering_name ] = (0.0, 1.0) @@ -724,11 +748,14 @@ def pre(self): # optimized. Note that the flow direction may have already been fixed # based on the original bounds, if that was desired. We can therefore # naively override the bounds without taking this into account. - for pipe in self._pipe_topo_pipe_class_map: - pipe_classes = self._pipe_topo_pipe_class_map[pipe] + for pipe in self._heat_pipe_topo_pipe_class_map: + pipe_classes = self._heat_pipe_topo_pipe_class_map[pipe] max_discharge = max([c.maximum_discharge for c in pipe_classes]) - self.__pipe_topo_heat_discharge_bounds[f"{pipe}.Q"] = (-max_discharge, max_discharge) + self.__heat_pipe_topo_heat_discharge_bounds[f"{pipe}.Q"] = ( + -max_discharge, + max_discharge, + ) # Heat on cold side is zero, so no change needed cp = parameters[f"{pipe}.cp"] @@ -738,11 +765,17 @@ def pre(self): # TODO: if temperature is variable these bounds should be set differently max_heat = 2.0 * cp * rho * temperature * max_discharge - self.__pipe_topo_heat_discharge_bounds[f"{pipe}.HeatIn.Heat"] = (-max_heat, max_heat) - self.__pipe_topo_heat_discharge_bounds[f"{pipe}.HeatOut.Heat"] = (-max_heat, max_heat) + self.__heat_pipe_topo_heat_discharge_bounds[f"{pipe}.HeatIn.Heat"] = ( + -max_heat, + max_heat, + ) + self.__heat_pipe_topo_heat_discharge_bounds[f"{pipe}.HeatOut.Heat"] = ( + -max_heat, + max_heat, + ) # When optimizing for pipe size, we do not yet support all options - if self._pipe_topo_pipe_class_map: + if self._heat_pipe_topo_pipe_class_map: if np.isfinite(options["maximum_temperature_der"]) and np.isfinite( options["maximum_flow_der"] ): @@ -764,6 +797,22 @@ def _make_max_size_var(name, lb, ub, nominal): for asset_name in self.energy_system_components.get("heat_source", []): ub = bounds[f"{asset_name}.Heat_source"][1] + + # Update bound to account for profile constraint being used instead of 1 value + esdl_asset_attributes = self.esdl_assets[ + self.esdl_asset_name_to_id_map[asset_name] + ].attributes["constraint"] + if ( + len(esdl_asset_attributes) > 0 + and hasattr(esdl_asset_attributes.items[0], "maximum") + and esdl_asset_attributes.items[0].maximum.profileQuantityAndUnit.reference.unit + == esdl.UnitEnum.WATT + and parameters[f"{asset_name}.state"] == 2 # Optional asset + ): + max_profile = max(self.get_timeseries(f"{asset_name}.maximum_heat_source").values) + if ub > max_profile: + ub = max_profile + lb = 0.0 if parameters[f"{asset_name}.state"] != 1 else ub _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) @@ -778,8 +827,32 @@ def _make_max_size_var(name, lb, ub, nominal): lb = 0.0 if np.isinf(bounds[f"{asset_name}.Heat_demand"][1]) else ub _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) - for asset_name in self.energy_system_components.get("ates", []): - ub = bounds[f"{asset_name}.Heat_ates"][1] + for asset_name in self.energy_system_components.get("airco", []): + ub = bounds[f"{asset_name}.Heat_airco"][1] + # Note that we only enforce the upper bound in state enabled if it was explicitly + # specified for the demand + lb = 0.0 if np.isinf(bounds[f"{asset_name}.Heat_airco"][1]) else ub + _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) + + for asset_name in self.energy_system_components.get("cold_demand", []): + ub = ( + bounds[f"{asset_name}.Cold_demand"][1] + if not np.isinf(bounds[f"{asset_name}.Cold_demand"][1]) + else bounds[f"{asset_name}.HeatIn.Heat"][1] + ) + # Note that we only enforce the upper bound in state enabled if it was explicitly + # specified for the demand + lb = 0.0 if np.isinf(bounds[f"{asset_name}.Cold_demand"][1]) else ub + _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) + + for asset_name in [ + *self.energy_system_components.get("ates", []), + *self.energy_system_components.get("low_temperature_ates", []), + ]: + if asset_name in self.energy_system_components.get("ates", []): + ub = bounds[f"{asset_name}.Heat_ates"][1] + else: + ub = bounds[f"{asset_name}.Heat_low_temperature_ates"][1] lb = 0.0 if parameters[f"{asset_name}.state"] != 1 else ub _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) @@ -826,22 +899,38 @@ def _make_max_size_var(name, lb, ub, nominal): for asset_name in self.energy_system_components.get("gas_tank_storage", []): ub = bounds[f"{asset_name}.Stored_gas_mass"][1] + ub = ub if isinstance(ub, float) else max(ub.values) lb = 0.0 if parameters[f"{asset_name}.state"] == 2 else ub _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) for asset_name in self.energy_system_components.get("gas_substation", []): ub = bounds[f"{asset_name}.GasIn.Q"][1] + ub = ub if isinstance(ub, float) else max(ub.values) + lb = 0.0 if parameters[f"{asset_name}.state"] == 2 else ub + _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) + + for asset_name in self.energy_system_components.get("compressor", []): + ub = bounds[f"{asset_name}.GasIn.Q"][1] + ub = ub if isinstance(ub, float) else max(ub.values) lb = 0.0 if parameters[f"{asset_name}.state"] == 2 else ub _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) for asset_name in self.energy_system_components.get("electrolyzer", []): ub = bounds[f"{asset_name}.ElectricityIn.Power"][1] + ub = ub if isinstance(ub, float) else max(ub.values) lb = 0.0 if parameters[f"{asset_name}.state"] == 2 else ub _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) for asset_name in self.energy_system_components.get("electricity_demand", []): v = bounds[f"{asset_name}.Electricity_demand"][1] ub = v if not np.isinf(v) else bounds[f"{asset_name}.ElectricityIn.Power"][1] + ub = ub if isinstance(ub, float) else max(ub.values) + lb = 0.0 if parameters[f"{asset_name}.state"] == 2 else ub + _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) + + for asset_name in self.energy_system_components.get("transformer", []): + ub = bounds[f"{asset_name}.ElectricityIn.Power"][1] + ub = ub if isinstance(ub, float) else max(ub.values) lb = 0.0 if parameters[f"{asset_name}.state"] == 2 else ub _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) @@ -854,6 +943,15 @@ def _make_max_size_var(name, lb, ub, nominal): lb = 0.0 if parameters[f"{asset_name}.state"] == 2 else ub _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) + for asset_name in self.energy_system_components.get("electricity_storage", []): + ub = ( + bounds[f"{asset_name}.Stored_electricity"][1] + if not isinstance(bounds[f"{asset_name}.Stored_electricity"][1], Timeseries) + else np.max(bounds[f"{asset_name}.Stored_electricity"][1].values) + ) + lb = 0.0 if parameters[f"{asset_name}.state"] == 2 else ub + _make_max_size_var(name=asset_name, lb=lb, ub=ub, nominal=ub / 2.0) + # Making the __aggregation_count variable for each asset for asset_list in self.energy_system_components.values(): for asset in asset_list: @@ -873,7 +971,7 @@ def energy_system_options(self): Returns a dictionary of milp network specific options. """ - options = {} + options = super().energy_system_options() return options @@ -951,7 +1049,7 @@ def get_optimized_pipe_class(self, pipe: str) -> PipeClass: Return the optimized pipe class for a specific pipe. If no optimized pipe class is available (yet), a `KeyError` is returned. """ - return self.__pipe_topo_pipe_class_result[pipe] + return self.__heat_pipe_topo_pipe_class_result[pipe] def get_optimized_deman_insulation_class(self, demand_insulation: str) -> DemandInsulationClass: """ @@ -964,13 +1062,13 @@ def pipe_diameter_symbol_name(self, pipe: str) -> str: """ Return the symbol name for the pipe diameter """ - return self._pipe_topo_diameter_map[pipe] + return self._heat_pipe_topo_diameter_map[pipe] def pipe_cost_symbol_name(self, pipe: str) -> str: """ Return the symbol name for the pipe investment cost per meter """ - return self._pipe_topo_cost_map[pipe] + return self._heat_pipe_topo_cost_map[pipe] @property def extra_variables(self): @@ -979,21 +1077,21 @@ def extra_variables(self): problem. Note that these are only the normal variables not path variables. """ variables = super().extra_variables.copy() - variables.extend(self.__pipe_topo_diameter_var.values()) - variables.extend(self.__pipe_topo_cost_var.values()) - variables.extend(self.__pipe_topo_pipe_class_var.values()) + variables.extend(self.__heat_pipe_topo_diameter_var.values()) + variables.extend(self.__heat_pipe_topo_cost_var.values()) + variables.extend(self.__heat_pipe_topo_pipe_class_var.values()) variables.extend(self.__gas_pipe_topo_diameter_var.values()) variables.extend(self.__gas_pipe_topo_cost_var.values()) variables.extend(self.__gas_pipe_topo_pipe_class_var.values()) variables.extend(self.__asset_max_size_var.values()) variables.extend(self.__asset_aggregation_count_var.values()) variables.extend(self.__gas_pipe_topo_max_discharge_var.values()) - variables.extend(self.__pipe_topo_max_discharge_var.values()) - variables.extend(self.__pipe_topo_global_pipe_class_count_var.values()) + variables.extend(self.__heat_pipe_topo_max_discharge_var.values()) + variables.extend(self.__heat_pipe_topo_global_pipe_class_count_var.values()) variables.extend(self.__gas_pipe_topo_global_pipe_class_count_var.values()) - variables.extend(self.__pipe_topo_pipe_class_discharge_ordering_var.values()) - variables.extend(self.__pipe_topo_pipe_class_cost_ordering_var.values()) - variables.extend(self.__pipe_topo_pipe_class_heat_loss_ordering_var.values()) + variables.extend(self.__heat_pipe_topo_pipe_class_discharge_ordering_var.values()) + variables.extend(self.__heat_pipe_topo_pipe_class_cost_ordering_var.values()) + variables.extend(self.__heat_pipe_topo_pipe_class_heat_loss_ordering_var.values()) variables.extend(self.__gas_pipe_topo_pipe_class_discharge_ordering_var.values()) variables.extend(self.__gas_pipe_topo_pipe_class_cost_ordering_var.values()) variables.extend(self.__electricity_cable_topo_max_current_var.values()) @@ -1021,11 +1119,11 @@ def variable_is_discrete(self, variable): All variables that only can take integer values should be added to this function. """ if ( - variable in self.__pipe_topo_pipe_class_var + variable in self.__heat_pipe_topo_pipe_class_var or variable in self.__asset_aggregation_count_var - or variable in self.__pipe_topo_pipe_class_discharge_ordering_var - or variable in self.__pipe_topo_pipe_class_cost_ordering_var - or variable in self.__pipe_topo_pipe_class_heat_loss_ordering_var + or variable in self.__heat_pipe_topo_pipe_class_discharge_ordering_var + or variable in self.__heat_pipe_topo_pipe_class_cost_ordering_var + or variable in self.__heat_pipe_topo_pipe_class_heat_loss_ordering_var or variable in self.__gas_pipe_topo_pipe_class_discharge_ordering_var or variable in self.__gas_pipe_topo_pipe_class_cost_ordering_var or variable in self.__gas_pipe_topo_pipe_class_var @@ -1041,16 +1139,16 @@ def variable_nominal(self, variable): """ In this function we add all the nominals for the variables defined/added in the HeatMixin. """ - if variable in self.__pipe_topo_diameter_nominals: - return self.__pipe_topo_diameter_nominals[variable] + if variable in self.__heat_pipe_topo_diameter_nominals: + return self.__heat_pipe_topo_diameter_nominals[variable] elif variable in self._pipe_heat_loss_nominals: return self._pipe_heat_loss_nominals[variable] - elif variable in self.__pipe_topo_cost_nominals: - return self.__pipe_topo_cost_nominals[variable] + elif variable in self.__heat_pipe_topo_cost_nominals: + return self.__heat_pipe_topo_cost_nominals[variable] elif variable in self.__asset_max_size_nominals: return self.__asset_max_size_nominals[variable] - elif variable in self.__pipe_topo_max_discharge_nominals: - return self.__pipe_topo_max_discharge_nominals[variable] + elif variable in self.__heat_pipe_topo_max_discharge_nominals: + return self.__heat_pipe_topo_max_discharge_nominals[variable] elif variable in self.__gas_pipe_topo_diameter_nominals: return self.__gas_pipe_topo_diameter_nominals[variable] elif variable in self.__gas_pipe_topo_cost_nominals: @@ -1072,23 +1170,23 @@ def bounds(self): the HeatMixin. """ bounds = super().bounds() - bounds.update(self.__pipe_topo_pipe_class_var_bounds) - bounds.update(self.__pipe_topo_diameter_var_bounds) - bounds.update(self.__pipe_topo_cost_var_bounds) + bounds.update(self.__heat_pipe_topo_pipe_class_var_bounds) + bounds.update(self.__heat_pipe_topo_diameter_var_bounds) + bounds.update(self.__heat_pipe_topo_cost_var_bounds) bounds.update(self._pipe_heat_loss_var_bounds) - bounds.update(self.__pipe_topo_heat_discharge_bounds) + bounds.update(self.__heat_pipe_topo_heat_discharge_bounds) bounds.update(self.__gas_pipe_topo_pipe_class_var_bounds) bounds.update(self.__gas_pipe_topo_diameter_var_bounds) bounds.update(self.__gas_pipe_topo_cost_var_bounds) bounds.update(self.__asset_max_size_bounds) bounds.update(self.__asset_aggregation_count_var_bounds) - bounds.update(self.__pipe_topo_max_discharge_var_bounds) + bounds.update(self.__heat_pipe_topo_max_discharge_var_bounds) bounds.update(self.__gas_pipe_topo_max_discharge_var_bounds) - bounds.update(self.__pipe_topo_global_pipe_class_count_var_bounds) + bounds.update(self.__heat_pipe_topo_global_pipe_class_count_var_bounds) bounds.update(self.__gas_pipe_topo_global_pipe_class_count_var_bounds) - bounds.update(self.__pipe_topo_pipe_class_discharge_ordering_var_bounds) - bounds.update(self.__pipe_topo_pipe_class_cost_ordering_var_bounds) - bounds.update(self.__pipe_topo_pipe_class_heat_loss_ordering_var_bounds) + bounds.update(self.__heat_pipe_topo_pipe_class_discharge_ordering_var_bounds) + bounds.update(self.__heat_pipe_topo_pipe_class_cost_ordering_var_bounds) + bounds.update(self.__heat_pipe_topo_pipe_class_heat_loss_ordering_var_bounds) bounds.update(self.__gas_pipe_topo_pipe_class_discharge_ordering_var_bounds) bounds.update(self.__gas_pipe_topo_pipe_class_cost_ordering_var_bounds) bounds.update(self.__electricity_cable_topo_max_current_var_bounds) @@ -1111,10 +1209,10 @@ def parameters(self, ensemble_member): # parameters in e.g. constraints when those are variable, we set them # to NaN in that case. In post(), they are set to their resulting # values once again. - if self.__pipe_topo_diameter_area_parameters: - parameters.update(self.__pipe_topo_diameter_area_parameters[ensemble_member]) - if self.__pipe_topo_heat_loss_parameters: - parameters.update(self.__pipe_topo_heat_loss_parameters[ensemble_member]) + if self.__heat_pipe_topo_diameter_area_parameters: + parameters.update(self.__heat_pipe_topo_diameter_area_parameters[ensemble_member]) + if self.__heat_pipe_topo_heat_loss_parameters: + parameters.update(self.__heat_pipe_topo_heat_loss_parameters[ensemble_member]) return parameters @@ -1146,7 +1244,7 @@ def __get_maximum_total_head_loss(self): # TODO: asset sizing is currently hard coded to use only the milp network settings for pipe in components.get("heat_pipe", []): try: - pipe_classes = self._pipe_topo_pipe_class_map[pipe].keys() + pipe_classes = self._heat_pipe_topo_pipe_class_map[pipe].keys() head_loss += max( self._hn_head_loss_class._hn_pipe_head_loss( pipe, @@ -1211,15 +1309,16 @@ def __pipe_topology_constraints(self, ensemble_member): unique_pipe_classes = self.get_unique_pipe_classes() pipe_class_count_sum = {pc.name: 0 for pc in unique_pipe_classes} + set_self_hot_pipes = set(self.hot_pipes) for p in self.energy_system_components.get("heat_pipe", []): try: - pipe_classes = self._pipe_topo_pipe_class_map[p] + pipe_classes = self._heat_pipe_topo_pipe_class_map[p] except KeyError: pass else: for pc in pipe_classes: neighbour = self.has_related_pipe(p) - if neighbour and p not in self.hot_pipes: + if neighbour and p not in set_self_hot_pipes: var_name = f"{self.cold_to_hot_pipe(p)}__hn_pipe_class_{pc.name}" else: var_name = f"{p}__hn_pipe_class_{pc.name}" @@ -1227,15 +1326,15 @@ def __pipe_topology_constraints(self, ensemble_member): for pc in unique_pipe_classes: var = self.extra_variable( - self.__pipe_topo_global_pipe_class_count_map[pc.name], ensemble_member + self.__heat_pipe_topo_global_pipe_class_count_map[pc.name], ensemble_member ) constraints.append(((pipe_class_count_sum[pc.name] - var), 0.0, 0.0)) # These are the constraints to order the discharge capabilities of the pipe classes - for p, pipe_classes in self.__pipe_topo_pipe_class_discharge_ordering_map.items(): - max_discharge = self.extra_variable(self._pipe_topo_max_discharge_map[p]) + for p, pipe_classes in self.__heat_pipe_topo_pipe_class_discharge_ordering_map.items(): + max_discharge = self.extra_variable(self._heat_pipe_topo_max_discharge_map[p]) max_discharges = { - pc.name: pc.maximum_discharge for pc in self._pipe_topo_pipe_class_map[p] + pc.name: pc.maximum_discharge for pc in self._heat_pipe_topo_pipe_class_map[p] } median_discharge = np.median(list(max_discharges.values())) @@ -1269,10 +1368,10 @@ def __pipe_topology_constraints(self, ensemble_member): ) # These are the constraints to order the costs of the pipe classes - for p, pipe_classes in self.__pipe_topo_pipe_class_cost_ordering_map.items(): - cost_sym_name = self._pipe_topo_cost_map[p] + for p, pipe_classes in self.__heat_pipe_topo_pipe_class_cost_ordering_map.items(): + cost_sym_name = self._heat_pipe_topo_cost_map[p] cost_sym = self.extra_variable(cost_sym_name, ensemble_member) - costs = {pc.name: pc.investment_costs for pc in self._pipe_topo_pipe_class_map[p]} + costs = {pc.name: pc.investment_costs for pc in self._heat_pipe_topo_pipe_class_map[p]} big_m = 2.0 * max(costs.values()) for pc, var_name in pipe_classes.items(): @@ -1298,8 +1397,11 @@ def __pipe_topology_constraints(self, ensemble_member): # These are the constraints to order the milp loss of the pipe classes. if not self.energy_system_options()["neglect_pipe_heat_losses"]: - for pipe, pipe_classes in self.__pipe_topo_pipe_class_heat_loss_ordering_map.items(): - if pipe in self.hot_pipes and self.has_related_pipe(pipe): + for ( + pipe, + pipe_classes, + ) in self.__heat_pipe_topo_pipe_class_heat_loss_ordering_map.items(): + if pipe in set_self_hot_pipes and self.has_related_pipe(pipe): heat_loss_sym_name = self._pipe_heat_loss_map[pipe] heat_loss_sym = self.extra_variable(heat_loss_sym_name, ensemble_member) cold_name = self._pipe_heat_loss_map[self.hot_to_cold_pipe(pipe)] @@ -1311,7 +1413,7 @@ def __pipe_topology_constraints(self, ensemble_member): self._pipe_heat_losses[self.hot_to_cold_pipe(pipe)], ) ] - elif pipe in self.hot_pipes and not self.has_related_pipe(pipe): + elif pipe in set_self_hot_pipes and not self.has_related_pipe(pipe): heat_loss_sym_name = self._pipe_heat_loss_map[pipe] heat_loss_sym = self.extra_variable(heat_loss_sym_name, ensemble_member) @@ -1345,7 +1447,7 @@ def __pipe_topology_constraints(self, ensemble_member): ) ) - for p, pipe_classes in self._pipe_topo_pipe_class_map.items(): + for p, pipe_classes in self._heat_pipe_topo_pipe_class_map.items(): variables = { pc.name: self.extra_variable(var_name, ensemble_member) for pc, var_name in pipe_classes.items() @@ -1355,7 +1457,7 @@ def __pipe_topology_constraints(self, ensemble_member): constraints.append((sum(variables.values()), 1.0, 1.0)) # set the max discharge - max_discharge = self.extra_variable(self._pipe_topo_max_discharge_map[p]) + max_discharge = self.extra_variable(self._heat_pipe_topo_max_discharge_map[p]) max_discharges = {pc.name: pc.maximum_discharge for pc in pipe_classes} max_discharge_expr = sum( variables[pc_name] * max_discharges[pc_name] for pc_name in variables @@ -1364,14 +1466,14 @@ def __pipe_topology_constraints(self, ensemble_member): constraints.append( ( (max_discharge - max_discharge_expr) - / self.variable_nominal(self._pipe_topo_max_discharge_map[p]), + / self.variable_nominal(self._heat_pipe_topo_max_discharge_map[p]), 0.0, 0.0, ) ) # Match the indicators to the diameter symbol - diam_sym_name = self._pipe_topo_diameter_map[p] + diam_sym_name = self._heat_pipe_topo_diameter_map[p] diam_sym = self.extra_variable(diam_sym_name, ensemble_member) diameters = {pc.name: pc.inner_diameter for pc in pipe_classes} @@ -1382,7 +1484,7 @@ def __pipe_topology_constraints(self, ensemble_member): constraints.append(((diam_sym - diam_expr) / constraint_nominal, 0.0, 0.0)) # match the indicators to the cost symbol - cost_sym_name = self._pipe_topo_cost_map[p] + cost_sym_name = self._heat_pipe_topo_cost_map[p] cost_sym = self.extra_variable(cost_sym_name, ensemble_member) investment_costs = {pc.name: pc.investment_costs for pc in pipe_classes} @@ -1691,7 +1793,9 @@ def __pipe_topology_path_constraints(self, ensemble_member): discharge_sym = self.state(f"{p}.Q") nominal = self.variable_nominal(f"{p}.Q") - max_discharge = self.__pipe_topo_max_discharge_var[self._pipe_topo_max_discharge_map[p]] + max_discharge = self.__heat_pipe_topo_max_discharge_var[ + self._heat_pipe_topo_max_discharge_map[p] + ] constraints.append(((max_discharge - discharge_sym) / nominal, 0.0, np.inf)) constraints.append(((-max_discharge - discharge_sym) / nominal, -np.inf, 0.0)) @@ -1735,12 +1839,12 @@ def __electricity_cable_topology_path_constraints(self, ensemble_member): current_sym = self.state(f"{cable}.I") nominal = self.variable_nominal(f"{cable}.I") - max_discharge = self.__electricity_cable_topo_max_current_var[ + max_current_var = self.__electricity_cable_topo_max_current_var[ self._electricity_cable_topo_max_current_map[cable] ] - constraints.append(((max_discharge - current_sym) / nominal, 0.0, np.inf)) - constraints.append(((-max_discharge - current_sym) / nominal, -np.inf, 0.0)) + constraints.append(((max_current_var - current_sym) / nominal, 0.0, np.inf)) + constraints.append(((-max_current_var - current_sym) / nominal, -np.inf, 0.0)) return constraints @@ -1756,8 +1860,13 @@ def __max_size_constraints(self, ensemble_member): """ constraints = [] bounds = self.bounds() + np_ones = np.ones(len(self.times())) + + energy_system_component_types = list(self.energy_system_components.keys()) + max_var_types = set() for b in self.energy_system_components.get("heat_buffer", []): + max_var_types.add("heat_buffer") max_var = self._asset_max_size_map[b] max_heat = self.extra_variable(max_var, ensemble_member) stored_heat = self.__state_vector_scaled(f"{b}.Stored_heat", ensemble_member) @@ -1765,34 +1874,107 @@ def __max_size_constraints(self, ensemble_member): constraints.append( ( - (np.ones(len(self.times())) * max_heat - stored_heat) / constraint_nominal, + (np_ones * max_heat - stored_heat) / constraint_nominal, 0.0, np.inf, ) ) - # Same as for the buffer but now for the source for s in self.energy_system_components.get("heat_source", []): + max_var_types.add("heat_source") max_var = self._asset_max_size_map[s] max_heat = self.extra_variable(max_var, ensemble_member) heat_source = self.__state_vector_scaled(f"{s}.Heat_source", ensemble_member) constraint_nominal = self.variable_nominal(f"{s}.Heat_source") - try: - profile = self.get_timeseries(f"{s}.maximum_heat_source").values - profile_scaled = profile / max(profile) - for i in range(0, len(self.times())): - constraints.append( - ( - (profile_scaled[i] * max_heat - heat_source[i]) / constraint_nominal, - 0.0, - np.inf, + if f"{s}.maximum_heat_source" in self.io.get_timeseries_names(): + profile_non_scaled = self.get_timeseries(f"{s}.maximum_heat_source").values + max_profile_non_scaled = max(profile_non_scaled) + profile_scaled = profile_non_scaled / max_profile_non_scaled + + # Cap the heat produced via a profile. Two profile options below. + # Option 1: Profile specified in absolute values [W] via a ProfileConstraint + esdl_asset_attributes = self.esdl_assets[ + self.esdl_asset_name_to_id_map[s] + ].attributes["constraint"] + if ( + len(esdl_asset_attributes) > 0 + and hasattr(esdl_asset_attributes.items[0], "maximum") + and esdl_asset_attributes.items[0].maximum.profileQuantityAndUnit.reference.unit + == esdl.UnitEnum.WATT + ): + parameters = self.parameters(ensemble_member) + + if parameters[f"{s}.state"] == 1: # Enabled asset + constraints.append( + ( + (max_heat - max_profile_non_scaled) / constraint_nominal, + 0.0, + np.inf, + ) ) - ) - except KeyError: + max_heat_var = max_profile_non_scaled + + elif parameters[f"{s}.state"] == 2: # Optional asset + max_heat_var = max_heat + + else: + state_val = parameters[f"{s}.state"] + logger.error(f"Unexpected state: {state_val}") + sys.exit(1) + + for i in range(0, len(self.times())): + constraints.append( + ( + (profile_scaled[i] * max_heat_var - heat_source[i]) + / constraint_nominal, + 0.0, + np.inf, + ) + ) + # Option 2: Normalised profile (0.0-1.0) shape that scales with maximum size of the + # producer + # Note: If the asset is not optional then the profile will be scaled to the + # installed capacity + elif ( + # profile is specified without units (xlm/csv) + len(esdl_asset_attributes) == 0 + or ( + esdl_asset_attributes.items[ + 0 + ].maximum.profileQuantityAndUnit.reference.physicalQuantity + == esdl.PhysicalQuantityEnum.COEFFICIENT + and ( + esdl_asset_attributes.items[ + 0 + ].maximum.profileQuantityAndUnit.reference.unit + == esdl.UnitEnum.PERCENT + or esdl_asset_attributes.items[ + 0 + ].maximum.profileQuantityAndUnit.reference.unit + == esdl.UnitEnum.NONE + ) + ) # profile from esdl + ): + # TODO: currently this can only be used with a csv file since units must be set + # for ProfileContraint. Future addition can be to use a different unit/quantity + # etc. so that the profile is used in a normalised way and scale to max_size + + for i in range(0, len(self.times())): + constraints.append( + ( + (profile_scaled[i] * max_heat - heat_source[i]) + / constraint_nominal, + 0.0, + np.inf, + ) + ) + else: + RuntimeError(f"{s}: Unforeseen error in adding a profile contraint") + else: constraints.append( ( - (np.ones(len(self.times())) * max_heat - heat_source) / constraint_nominal, + (np_ones * max_heat - heat_source) / constraint_nominal, 0.0, np.inf, ) @@ -1802,6 +1984,7 @@ def __max_size_constraints(self, ensemble_member): *self.energy_system_components.get("heat_exchanger", []), *self.energy_system_components.get("heat_pump", []), ]: + max_var_types.update(["heat_pump", "heat_exchanger"]) max_var = self._asset_max_size_map[hx] max_heat = self.extra_variable(max_var, ensemble_member) heat_secondary = self.__state_vector_scaled(f"{hx}.Secondary_heat", ensemble_member) @@ -1809,13 +1992,14 @@ def __max_size_constraints(self, ensemble_member): constraints.append( ( - (np.ones(len(self.times())) * max_heat - heat_secondary) / constraint_nominal, + (np_ones * max_heat - heat_secondary) / constraint_nominal, 0.0, np.inf, ) ) for d in self.energy_system_components.get("heat_demand", []): + max_var_types.add("heat_demand") max_var = self._asset_max_size_map[d] max_heat = self.extra_variable(max_var, ensemble_member) heat_demand = self.__state_vector_scaled(f"{d}.Heat_demand", ensemble_member) @@ -1824,34 +2008,45 @@ def __max_size_constraints(self, ensemble_member): ) constraints.append( ( - (np.ones(len(self.times())) * max_heat - heat_demand) / constraint_nominal, + (np_ones * max_heat - heat_demand) / constraint_nominal, 0.0, np.inf, ) ) - for a in self.energy_system_components.get("ates", []): + for a in [ + *self.energy_system_components.get("ates", []), + *self.energy_system_components.get("low_temperature_ates", []), + ]: + max_var_types.update(["ates", "low_temperature_ates"]) max_var = self._asset_max_size_map[a] max_heat = self.extra_variable(max_var, ensemble_member) - heat_ates = self.__state_vector_scaled(f"{a}.Heat_ates", ensemble_member) - constraint_nominal = bounds[f"{a}.Heat_ates"][1] + if a in self.energy_system_components.get("ates", []): + heat_ates = self.__state_vector_scaled(f"{a}.Heat_ates", ensemble_member) + constraint_nominal = bounds[f"{a}.Heat_ates"][1] + else: + heat_ates = self.__state_vector_scaled( + f"{a}.Heat_low_temperature_ates", ensemble_member + ) + constraint_nominal = bounds[f"{a}.Heat_low_temperature_ates"][1] constraints.append( ( - (np.ones(len(self.times())) * max_heat - heat_ates) / constraint_nominal, + (np_ones * max_heat - heat_ates) / constraint_nominal, 0.0, np.inf, ) ) constraints.append( ( - (np.ones(len(self.times())) * max_heat + heat_ates) / constraint_nominal, + (np_ones * max_heat + heat_ates) / constraint_nominal, 0.0, np.inf, ) ) for d in self.energy_system_components.get("electricity_demand", []): + max_var_types.add("electricity_demand") max_var = self._asset_max_size_map[d] max_power = self.extra_variable(max_var, ensemble_member) electricity_demand = self.__state_vector_scaled( @@ -1861,14 +2056,14 @@ def __max_size_constraints(self, ensemble_member): constraints.append( ( - (np.ones(len(self.times())) * max_power - electricity_demand) - / constraint_nominal, + (np_ones * max_power - electricity_demand) / constraint_nominal, 0.0, np.inf, ) ) for d in self.energy_system_components.get("electricity_source", []): + max_var_types.add("electricity_source") max_var = self._asset_max_size_map[d] max_power = self.extra_variable(max_var, ensemble_member) electricity_source = self.__state_vector_scaled( @@ -1878,14 +2073,31 @@ def __max_size_constraints(self, ensemble_member): constraints.append( ( - (np.ones(len(self.times())) * max_power - electricity_source) - / constraint_nominal, + (np_ones * max_power - electricity_source) / constraint_nominal, + 0.0, + np.inf, + ) + ) + + for d in self.energy_system_components.get("electricity_storage", []): + max_var_types.add("electricity_storage") + max_var = self._asset_max_size_map[d] + max_stored_energy = self.extra_variable(max_var, ensemble_member) + electricity_stored = self.__state_vector_scaled( + f"{d}.Stored_electricity", ensemble_member + ) + constraint_nominal = self.variable_nominal(f"{d}.Stored_electricity") + + constraints.append( + ( + (np_ones * max_stored_energy - electricity_stored) / constraint_nominal, 0.0, np.inf, ) ) for d in self.energy_system_components.get("electrolyzer", []): + max_var_types.add("electrolyzer") max_var = self._asset_max_size_map[d] max_power = self.extra_variable(max_var, ensemble_member) electricity_electrolyzer = self.__state_vector_scaled( @@ -1895,14 +2107,14 @@ def __max_size_constraints(self, ensemble_member): constraints.append( ( - (np.ones(len(self.times())) * max_power - electricity_electrolyzer) - / constraint_nominal, + (np_ones * max_power - electricity_electrolyzer) / constraint_nominal, 0.0, np.inf, ) ) for d in self.energy_system_components.get("gas_tank_storage", []): + max_var_types.add("gas_tank_storage") max_var = self._asset_max_size_map[d] max_size = self.extra_variable(max_var, ensemble_member) gas_mass = self.__state_vector_scaled(f"{d}.Stored_gas_mass", ensemble_member) @@ -1910,12 +2122,21 @@ def __max_size_constraints(self, ensemble_member): constraints.append( ( - (np.ones(len(self.times())) * max_size - gas_mass) / constraint_nominal, + (np_ones * max_size - gas_mass) / constraint_nominal, 0.0, np.inf, ) ) + max_var_assets_not_included = [ + a for a in energy_system_component_types if a not in max_var_types + ] + if len(max_var_assets_not_included) >= 0: + logger.warning( + f"The following asset types are not included in the maximum sizing " + f"constraints {max_var_assets_not_included}" + ) + return constraints def __add_optional_asset_path_constraints( @@ -1995,11 +2216,20 @@ def __optional_asset_path_constraints(self, ensemble_member): # TODO: can we generalize to all possible components to avoid having to skip # joints and other components in the future? continue - else: + elif ( + self.energy_system_components_commodity.get(asset_name) + == NetworkSettings.NETWORK_TYPE_HEAT + ): state_var = self.state(f"{asset_name}.Heat_flow") single_power = bounds[f"{asset_name}.Heat_flow"][1] nominal_value = single_power nominal_var = self.variable_nominal(f"{asset_name}.Heat_flow") + else: + logger.warning( + f"{asset_name} is not yet included in the optional asset path " + f"constraints" + ) + continue constraints = self.__add_optional_asset_path_constraints( constraints, asset_name, nominal_value, nominal_var, single_power, state_var @@ -2091,12 +2321,12 @@ def __pipe_class_to_results(self): else: pipe_class = next( c - for c, s in self._pipe_topo_pipe_class_map[pipe].items() + for c, s in self._heat_pipe_topo_pipe_class_map[pipe].items() if round(results[s][0]) == 1.0 ) for p in [pipe, self.hot_to_cold_pipe(pipe)]: - self.__pipe_topo_pipe_class_result[p] = pipe_class + self.__heat_pipe_topo_pipe_class_result[p] = pipe_class def _pipe_heat_loss_to_parameters(self): """ @@ -2107,7 +2337,7 @@ def _pipe_heat_loss_to_parameters(self): for ensemble_member in range(self.ensemble_size): parameters = self.parameters(ensemble_member) - h = self.__pipe_topo_heat_loss_parameters[ensemble_member] + h = self.__heat_pipe_topo_heat_loss_parameters[ensemble_member] for pipe in self._pipe_heat_losses: pipe_class = self.get_optimized_pipe_class(pipe) @@ -2121,8 +2351,8 @@ def __pipe_diameter_to_parameters(self): optimization """ for ensemble_member in range(self.ensemble_size): - d = self.__pipe_topo_diameter_area_parameters[ensemble_member] - for pipe in self._pipe_topo_pipe_class_map: + d = self.__heat_pipe_topo_diameter_area_parameters[ensemble_member] + for pipe in self._heat_pipe_topo_pipe_class_map: pipe_class = self.get_optimized_pipe_class(pipe) for p in [pipe, self.hot_to_cold_pipe(pipe)]: diff --git a/src/rtctools_heat_network/base_component_type_mixin.py b/src/mesido/base_component_type_mixin.py similarity index 92% rename from src/rtctools_heat_network/base_component_type_mixin.py rename to src/mesido/base_component_type_mixin.py index c9a04ff59..42938274e 100644 --- a/src/rtctools_heat_network/base_component_type_mixin.py +++ b/src/mesido/base_component_type_mixin.py @@ -20,10 +20,18 @@ def energy_system_components(self) -> Dict[str, str]: """ raise NotImplementedError + @property + @abstractmethod + def energy_system_components_commodity(self) -> Dict[str, List[str]]: + """ + This method return a dict with the components ad their network types. + """ + raise NotImplementedError + def energy_system_components_get(self, list_types: list) -> list: components = [] for component_type in list_types: - components.extend(self.energy_system_components.get(component_type)) + components.extend(self.energy_system_components.get(component_type, [])) components = list(set(components)) return components diff --git a/src/mesido/component_type_mixin.py b/src/mesido/component_type_mixin.py new file mode 100644 index 000000000..e48936491 --- /dev/null +++ b/src/mesido/component_type_mixin.py @@ -0,0 +1,507 @@ +import logging +from typing import Dict, Set + +from mesido.base_component_type_mixin import BaseComponentTypeMixin +from mesido.heat_network_common import NodeConnectionDirection +from mesido.network_common import NetworkSettings +from mesido.topology import Topology + +import numpy as np + +from pymoca.backends.casadi.alias_relation import AliasRelation + +logger = logging.getLogger("mesido") + + +class ModelicaComponentTypeMixin(BaseComponentTypeMixin): + """ + This class is used to make the milp network component information easily accesible in the + heat_mixin. This is achieved by creating a heat_network_components dict where the assets are + sorted by asset_type. Furthermore, the topology object is created in which for specific assets + the connections with directions are saved for later use in the constraints. + """ + + def __init__(self, *args, **kwargs): + super().__init__(**kwargs) + self.__hn_component_types = None + self.__commodity_types = None + + def pre(self): + """ + In this function the topology object of the milp network is constructed. Meaning that for + nodes, busses and storage assets their relevant information on the positive flow direction + and connections on the ports is gathered and stored in the topology object. + """ + components = self.energy_system_components + nodes = components.get("node", []) + busses = components.get("electricity_node", []) + gas_nodes = components.get("gas_node", []) + buffers = components.get("heat_buffer", []) + atess = [*components.get("ates", []), *components.get("low_temperature_ates", [])] + demands = [ + *components.get("heat_demand", []), + *components.get("electricity_demand", []), + *components.get("gas_demand", []), + ] + sources = [ + *components.get("heat_source", []), + *components.get("electricity_source", []), + *components.get("gas_source", []), + ] + pipes = components.get("heat_pipe", []) + + # An energy system should have at least one asset. + assert len(components) > 1 + + # Figure out which pipes are connected to which nodes, which pipes + # are connected in series, and which pipes are connected to which buffers. + + pipes_set = set(pipes) + parameters = [self.parameters(e) for e in range(self.ensemble_size)] + node_connections = {} + bus_connections = {} + gas_node_connections = {} + + heat_network_model_type = NetworkSettings.NETWORK_TYPE_HEAT + + # Note that a pipe series can include both hot and cold pipes for + # QTH models. It is only about figuring out which pipes are + # related direction-wise. + # For Heat models, only hot pipes are allowed to be part of pipe + # series, as the cold part is zero milp by construction. + if heat_network_model_type == "QTH": + alias_relation = self.alias_relation + elif heat_network_model_type == NetworkSettings.NETWORK_TYPE_HEAT: + # There is no proper AliasRelation yet (because there is milp loss in pipes). + # So we build one, as that is the easiest way to figure out which pipes are + # connected to each other in series. We do this by making a temporary/shadow + # discharge (".Q") variable per pipe, as that way we can share the processing + # logic for determining pipe series with that of QTH models. + alias_relation = AliasRelation() + + # Look for aliases only in the hot pipes. All cold pipes are zero by convention anyway. + hot_pipes = self.hot_pipes.copy() + + pipes_map = {f"{pipe}.HeatIn.Heat": pipe for pipe in hot_pipes} + pipes_map.update({f"{pipe}.HeatOut.Heat": pipe for pipe in hot_pipes}) + + for p in hot_pipes: + for port in ["In", "Out"]: + heat_port = f"{p}.Heat{port}.Heat" + connected = self.alias_relation.aliases(heat_port).intersection( + pipes_map.keys() + ) + connected.remove(heat_port) + + if connected: + other_pipe_port = next(iter(connected)) + if other_pipe_port.endswith(f".Heat{port}.Heat"): + sign_prefix = "-" + else: + sign_prefix = "" + other_pipe = pipes_map[other_pipe_port] + if f"{other_pipe}.Q" not in alias_relation.canonical_variables: + alias_relation.add(f"{p}.Q", f"{sign_prefix}{other_pipe}.Q") + + node_to_node_logical_link_map = {} + + for n in [*nodes, *busses, *gas_nodes]: + n_connections = [ens_params[f"{n}.n"] for ens_params in parameters] + + if len(set(n_connections)) > 1: + raise Exception( + "Nodes and busses cannot have differing number of connections per " + "ensemble member" + ) + + n_connections = n_connections[0] + + # Note that we do this based on temperature, because discharge may + # be an alias of yet some other further away connected pipe. + if n in nodes: + node_connections[n] = connected_pipes = {} + elif n in busses: + bus_connections[n] = connected_pipes = {} + elif n in gas_nodes: + gas_node_connections[n] = connected_pipes = {} + + for i in range(n_connections): + if n in nodes: + cur_port = f"{n}.{heat_network_model_type}Conn[{i + 1}]" + prop = ( + "T" + if heat_network_model_type == "QTH" + else NetworkSettings.NETWORK_TYPE_HEAT + ) + prop_h = "H" + in_suffix = ".QTHIn.T" if heat_network_model_type == "QTH" else ".HeatIn.Heat" + out_suffix = ( + ".QTHOut.T" if heat_network_model_type == "QTH" else ".HeatOut.Heat" + ) + in_suffix_h = ".HeatIn.H" + out_suffix_h = ".HeatOut.H" + node_suffix = ".HeatConn[1].Heat" + elif n in busses: + cur_port = f"{n}.ElectricityConn[{i + 1}]" + prop = "Power" + prop_h = "V" + in_suffix = ".ElectricityIn.Power" + out_suffix = ".ElectricityOut.Power" + in_suffix_h = ".ElectricityIn.V" + out_suffix_h = ".ElectricityOut.V" + node_suffix = ".ElectricityConn[1].Power" + elif n in gas_nodes: + # TODO: Ideally a temporary variable would be created to make the connections + # map that is not passed to the problem + cur_port = f"{n}.GasConn[{i + 1}]" + prop = "Q" + prop_h = "H" + in_suffix = ".GasIn.Q" + out_suffix = ".GasOut.Q" + in_suffix_h = ".GasIn.H" + out_suffix_h = ".GasOut.H" + node_suffix = ".GasConn[1].Q" + aliases = [ + x + for x in self.alias_relation.aliases(f"{cur_port}.{prop}") + if not x.startswith(n) and x.endswith(f".{prop}") + ] + + if len(aliases) == 0: + raise Exception(f"Found no connection to {cur_port}") + + # Here we make a count of the amount of in and out port aliases. + in_suffix_count = np.sum([1 if x.endswith(in_suffix) else 0 for x in aliases]) + out_suffix_count = np.sum([1 if x.endswith(out_suffix) else 0 for x in aliases]) + + # Here we gather the aliases for a property that is equal for all node ports. + aliases_h = [ + x + for x in self.alias_relation.aliases(f"{cur_port}.{prop_h}") + if not x.startswith(n) and x.endswith(f".{prop_h}") + ] + pipe_out_port = False + # We can have multiple aliases, specifically when a pipe is connected to a port the + # direction of that pipe matters. To determine if the connected alias is a pipe and + # which direction it has we look for the overlap between the prop and prop_h in the + # aliases. This means that if a pipe is both in the aliases and in the aliases_h, + # then that must be the pipe connected to the port of the node. + for k in range(len(aliases)): + pipe_name = aliases[k].split(".")[0] + if pipe_name + out_suffix_h in aliases_h: + pipe_out_port = True + node_connection_direction = NodeConnectionDirection.IN + elif pipe_name + in_suffix_h in aliases_h: + pipe_out_port = True + node_connection_direction = NodeConnectionDirection.OUT + + if pipe_out_port: + # This is only for when a pipe is connected to a gas node to determine direction + asset_w_orientation = ( + pipe_name, + node_connection_direction, + ) + elif out_suffix_count > in_suffix_count: + # This is for the case of Non pipe asset is logically linked to a node + asset_w_orientation = ( + aliases[0][: -len(out_suffix)], + NodeConnectionDirection.IN, + ) + elif out_suffix_count < in_suffix_count: + # This is for the case of Non pipe asset is logically linked to a node + asset_w_orientation = ( + aliases[0][: -len(in_suffix)], + NodeConnectionDirection.OUT, + ) + elif out_suffix_count == in_suffix_count: + # This is for the case of logical links between node to node + # Note that we cannot determine the direction of node to node logical links, we + # therefore, always take the first node with an in port and the second node with + # and out port. + if n not in list(node_to_node_logical_link_map.values()): + node_to_node_logical_link_map[n] = aliases[0][: -len(node_suffix)] + asset_w_orientation = ( + aliases[0][: -len(node_suffix)], + NodeConnectionDirection.IN, + ) + else: + asset_w_orientation = ( + aliases[0][: -len(node_suffix)], + NodeConnectionDirection.OUT, + ) + else: + logger.error("connections are not properly matched") + + connected_pipes[i] = asset_w_orientation + + canonical_pipe_qs = {p: alias_relation.canonical_signed(f"{p}.Q") for p in pipes} + # Move sign from canonical to alias + canonical_pipe_qs = {(p, d): c for p, (c, d) in canonical_pipe_qs.items()} + # Reverse the dictionary from `Dict[alias, canonical]` to `Dict[canonical, Set[alias]]` + pipe_sets = {} + for a, c in canonical_pipe_qs.items(): + pipe_sets.setdefault(c, []).append(a) + + pipe_series_with_orientation = list(pipe_sets.values()) + + # Check that all pipes in the series have the same orientation + pipe_series = [] + for ps in pipe_series_with_orientation: + if not len({orientation for _, orientation in ps}) == 1: + raise Exception(f"Pipes in series {ps} do not all have the same orientation") + pipe_series.append([name for name, _ in ps]) + + buffer_connections = {} + + for b in buffers: + buffer_connections[b] = [] + + for k in ["In", "Out"]: + b_conn = f"{b}.{heat_network_model_type}{k}" + prop = ( + "T" if heat_network_model_type == "QTH" else NetworkSettings.NETWORK_TYPE_HEAT + ) + aliases = [ + x + for x in self.alias_relation.aliases(f"{b_conn}.{prop}") + if not x.startswith(b) and x.endswith(f".{prop}") + ] + + if len(aliases) > 1: + raise Exception(f"More than one connection to {b_conn}") + elif len(aliases) == 0: + raise Exception(f"Found no connection to {b_conn}") + + in_suffix = ".QTHIn.T" if heat_network_model_type == "QTH" else ".HeatIn.Heat" + out_suffix = ".QTHOut.T" if heat_network_model_type == "QTH" else ".HeatOut.Heat" + alias = aliases[0] + if alias.endswith(out_suffix): + asset_w_orientation = ( + alias[: -len(out_suffix)], + NodeConnectionDirection.IN, + ) + else: + assert alias.endswith(in_suffix) + asset_w_orientation = ( + alias[: -len(in_suffix)], + NodeConnectionDirection.OUT, + ) + + assert asset_w_orientation[0] in pipes_set + + if k == "In": + assert self.is_hot_pipe(asset_w_orientation[0]) + else: + assert self.is_cold_pipe(asset_w_orientation[0]) + + buffer_connections[b].append(asset_w_orientation) + + buffer_connections[b] = tuple(buffer_connections[b]) + + ates_connections = {} + + for a in atess: + ates_connections[a] = [] + + for k in ["In", "Out"]: + a_conn = f"{a}.{heat_network_model_type}{k}" + prop = ( + "T" if heat_network_model_type == "QTH" else NetworkSettings.NETWORK_TYPE_HEAT + ) + aliases = [ + x + for x in self.alias_relation.aliases(f"{a_conn}.{prop}") + if not x.startswith(a) and x.endswith(f".{prop}") + ] + + if len(aliases) > 1: + raise Exception(f"More than one connection to {a_conn}") + elif len(aliases) == 0: + raise Exception(f"Found no connection to {a_conn}") + + in_suffix = ".QTHIn.T" if heat_network_model_type == "QTH" else ".HeatIn.Heat" + out_suffix = ".QTHOut.T" if heat_network_model_type == "QTH" else ".HeatOut.Heat" + + if aliases[0].endswith(out_suffix): + asset_w_orientation = ( + aliases[0][: -len(out_suffix)], + NodeConnectionDirection.IN, + ) + else: + assert aliases[0].endswith(in_suffix) + asset_w_orientation = ( + aliases[0][: -len(in_suffix)], + NodeConnectionDirection.OUT, + ) + + assert asset_w_orientation[0] in pipes_set + + if k == "Out": + assert self.is_cold_pipe(asset_w_orientation[0]) + else: + assert self.is_hot_pipe(asset_w_orientation[0]) + + ates_connections[a].append(asset_w_orientation) + + ates_connections[a] = tuple(ates_connections[a]) + + demand_connections = {} + + for a in demands: + if a in components.get("heat_demand", []): + network_type = NetworkSettings.NETWORK_TYPE_HEAT + prop = NetworkSettings.NETWORK_TYPE_HEAT + elif a in components.get("electricity_demand", []): + network_type = "Electricity" + prop = "Power" + elif a in components.get("gas_demand", []): + network_type = NetworkSettings.NETWORK_TYPE_GAS + prop = "H" + else: + logger.error(f"{a} cannot be modelled with heat, gas or electricity") + a_conn = f"{a}.{network_type}In" + aliases = [ + x + for x in self.alias_relation.aliases(f"{a_conn}.{prop}") + if not x.startswith(a) and x.endswith(f".{prop}") + ] + + if len(aliases) > 1: + raise Exception(f"More than one connection to {a_conn}") + elif len(aliases) == 0: + # the connection was a logical link to a node + continue + + in_suffix = f".{network_type}In.{prop}" + out_suffix = f".{network_type}Out.{prop}" + + if aliases[0].endswith(out_suffix): + asset_w_orientation = ( + aliases[0][: -len(out_suffix)], + NodeConnectionDirection.IN, + ) + else: + asset_w_orientation = ( + aliases[0][: -len(in_suffix)], + NodeConnectionDirection.OUT, + ) + + if asset_w_orientation[0] in [ + *components.get("heat_pipe", []), + *components.get("gas_pipe", []), + *components.get("electricity_cable", []), + ]: + demand_connections[a] = asset_w_orientation + + source_connections = {} + + for a in sources: + if a in components.get("heat_source", []): + network_type = NetworkSettings.NETWORK_TYPE_HEAT + prop = NetworkSettings.NETWORK_TYPE_HEAT + elif a in components.get("electricity_source", []): + network_type = "Electricity" + prop = "Power" + elif a in components.get("gas_source", []): + network_type = NetworkSettings.NETWORK_TYPE_GAS + prop = "H" + else: + logger.error(f"{a} cannot be modelled with heat, gas or electricity") + a_conn = f"{a}.{network_type}Out" + aliases = [ + x + for x in self.alias_relation.aliases(f"{a_conn}.{prop}") + if not x.startswith(a) and x.endswith(f".{prop}") + ] + + if len(aliases) > 1: + raise Exception(f"More than one connection to {a_conn}") + elif len(aliases) == 0: + # the connection was a logical link to a node + continue + + in_suffix = f".{network_type}In.{prop}" + out_suffix = f".{network_type}Out.{prop}" + + if aliases[0].endswith(out_suffix): + asset_w_orientation = ( + aliases[0][: -len(out_suffix)], + NodeConnectionDirection.IN, + ) + else: + asset_w_orientation = ( + aliases[0][: -len(in_suffix)], + NodeConnectionDirection.OUT, + ) + + if asset_w_orientation[0] in [ + *components.get("heat_pipe", []), + *components.get("gas_pipe", []), + *components.get("electricity_cable", []), + ]: + source_connections[a] = asset_w_orientation + + self.__topology = Topology( + node_connections, + gas_node_connections, + pipe_series, + buffer_connections, + ates_connections, + bus_connections, + demand_connections, + source_connections, + ) + + super().pre() + + @property + def energy_system_components(self) -> Dict[str, Set[str]]: + """ + This method return a dict with the milp network assets ordered per asset type. + """ + if self.__hn_component_types is None: + # Create the dictionary once after that it will be available + string_parameters = self.string_parameters(0) + + # Find the components in model, detection by string + # (name.component_type: type) + component_types = sorted( + {v for k, v in string_parameters.items() if "network_type" not in k} + ) + + components = {} + for c in component_types: + components[c] = sorted( + {k.split(".")[0] for k, v in string_parameters.items() if v == c} + ) + + self.__hn_component_types = components + + return self.__hn_component_types + + @property + def energy_system_components_commodity(self) -> Dict[str, Set[str]]: + """ + This method returns a dict with the milp network assets and their commodity type. + """ + if self.__commodity_types is None: + # Create the dictionary once after that it will be available + string_parameters = self.string_parameters(0) + + # Find the components in model, detection by string + # (name.component_type: type) + commodity_types = { + k.split(".")[0]: v for k, v in string_parameters.items() if "network_type" in k + } + + self.__commodity_types = commodity_types + + return self.__commodity_types + + @property + def energy_system_topology(self) -> Topology: + """ + This method returns the topology object of the milp network. Which contains specific assets + with directions on the ports that are needed in the constraints. + """ + return self.__topology diff --git a/src/rtctools_heat_network/constants.py b/src/mesido/constants.py similarity index 100% rename from src/rtctools_heat_network/constants.py rename to src/mesido/constants.py diff --git a/src/rtctools_heat_network/control_variables.py b/src/mesido/control_variables.py similarity index 100% rename from src/rtctools_heat_network/control_variables.py rename to src/mesido/control_variables.py diff --git a/src/rtctools_heat_network/demand_insulation_class.py b/src/mesido/demand_insulation_class.py similarity index 100% rename from src/rtctools_heat_network/demand_insulation_class.py rename to src/mesido/demand_insulation_class.py diff --git a/src/mesido/electricity_physics_mixin.py b/src/mesido/electricity_physics_mixin.py new file mode 100644 index 000000000..bb15d04ca --- /dev/null +++ b/src/mesido/electricity_physics_mixin.py @@ -0,0 +1,965 @@ +import copy +import logging +from enum import IntEnum +from math import isclose +from typing import List, Tuple + +import casadi as ca + +from mesido.base_component_type_mixin import BaseComponentTypeMixin + +import numpy as np + +from rtctools.optimization.collocated_integrated_optimization_problem import ( + CollocatedIntegratedOptimizationProblem, +) +from rtctools.optimization.timeseries import Timeseries + + +logger = logging.getLogger("mesido") + + +class ElectrolyzerOption(IntEnum): + """ + Enumeration for the possible options to model the electrolyzer. + For detailed calculations related to these options, see the equations themselves. + + CONSTANT_EFFICIENCY + A constant efficiency is used to determine the H2 produced per energy electricity entering + + LINEARIZED_THREE_LINES_WEAK_INEQUALITY + The efficiency curve is linearized in 3 lines, which are all inequalities and with proper + goals will move towards these lines + + LINEARIZED_THREE_LINES_EQUALITY + The efficiency curve is linearized in 3 lines, which are all equalities using binary + variables and the big-M method to select the relevant lines. + """ + + CONSTANT_EFFICIENCY = 1 + LINEARIZED_THREE_LINES_WEAK_INEQUALITY = 2 + LINEARIZED_THREE_LINES_EQUALITY = 3 + + +class ElectricityPhysicsMixin(BaseComponentTypeMixin, CollocatedIntegratedOptimizationProblem): + """ + This class is used to model the physics of an electricity network with its assets. We model + the different components with variety of linearization strategies. + """ + + def __init__(self, *args, **kwargs): + """ + In this __init__ we prepare the dicts for the variables added by the HeatMixin class + """ + + super().__init__(*args, **kwargs) + + # Variable for when in time an asset switched on due to meeting a requirement + self.__asset_is_switched_on_map = {} + self.__asset_is_switched_on_var = {} + self.__asset_is_switched_on_bounds = {} + + self.__electricity_producer_upper_bounds = {} + + self._electricity_cable_topo_cable_class_map = {} + + # Boolean path-variable for the charging of storage assets + self.__storage_charging_var = {} + self.__storage_charging_bounds = {} + self.__storage_charging_map = {} + + self.__set_point_var = {} + self.__set_point_bounds = {} + self.__set_point_map = {} + + # Boolean path-variable for the equality constraint of the electrolyzer + self.__electrolyzer_is_active_linear_segment_map = {} + self.__electrolyzer_is_active_linear_segment_var = {} + self.__electrolyzer_is_active_linear_segment_bounds = {} + self.__electricity_storage_discharge_var = {} + self.__electricity_storage_discharge_bounds = {} + self.__electricity_storage_discharge_nominals = {} + self.__electricity_storage_discharge_map = {} + + # Map for setting node nominals in case of logical links. + self.__bus_variable_nominal = {} + + def energy_system_options(self): + r""" + Returns a dictionary of milp network specific options. + """ + + options = {} + + options["include_asset_is_switched_on"] = False + options["include_electric_cable_power_loss"] = False + options["electrolyzer_efficiency"] = ( + ElectrolyzerOption.LINEARIZED_THREE_LINES_WEAK_INEQUALITY + ) + options["electricity_storage_discharge_variables"] = False + + return options + + def electricity_carriers(self): + """ + This function should be overwritten by the problem and should give a dict with the + carriers as keys and a list of voltage values. + """ + return {} + + def pre(self): + """ + In this pre method we fill the dicts initiated in the __init__. This means that we create + the Casadi variables and determine the bounds, nominals and create maps for easier + retrieving of the variables. + """ + super().pre() + + options = self.energy_system_options() + + self.__update_electricity_producer_upper_bounds() + + if options["include_asset_is_switched_on"]: + for asset in [ + *self.energy_system_components.get("electrolyzer", []), + ]: + var_name = f"{asset}__asset_is_switched_on" + self.__asset_is_switched_on_map[asset] = var_name + self.__asset_is_switched_on_var[var_name] = ca.MX.sym(var_name) + self.__asset_is_switched_on_bounds[var_name] = (0.0, 1.0) + + if options["electrolyzer_efficiency"] == ElectrolyzerOption.LINEARIZED_THREE_LINES_EQUALITY: + for asset in [ + *self.energy_system_components.get("electrolyzer", []), + ]: + self.__electrolyzer_is_active_linear_segment_map[asset] = {} + n_lines = 3 + for n_line in range(n_lines): + var_name = f"{asset}__line_{n_line}_active" + + self.__electrolyzer_is_active_linear_segment_map[asset][ + f"line_{n_line}" + ] = var_name + self.__electrolyzer_is_active_linear_segment_var[var_name] = ca.MX.sym(var_name) + self.__electrolyzer_is_active_linear_segment_bounds[var_name] = (0.0, 1.0) + + for asset in [*self.energy_system_components.get("electricity_storage", [])]: + var_name = f"{asset}__is_charging" + self.__storage_charging_map[asset] = var_name + self.__storage_charging_var[var_name] = ca.MX.sym(var_name) + self.__storage_charging_bounds[var_name] = (0.0, 1.0) + + if options["electricity_storage_discharge_variables"]: + bound_storage = -self.bounds()[f"{asset}.Effective_power_charging"][0] + if isinstance(bound_storage, Timeseries): + bound_storage = copy.deepcopy(bound_storage) + bound_storage.values[bound_storage.values < 0] = 0.0 + var_name = f"{asset}__effective_power_discharging" + self.__electricity_storage_discharge_map[asset] = var_name + self.__electricity_storage_discharge_var[var_name] = ca.MX.sym(var_name) + self.__electricity_storage_discharge_bounds[var_name] = (0, bound_storage) + self.__electricity_storage_discharge_nominals[var_name] = self.variable_nominal( + f"{asset}.Effective_power_charging" + ) + + for asset in [*self.energy_system_components.get("electricity_source", [])]: + if isinstance(self.bounds()[f"{asset}.Electricity_source"][1], Timeseries): + var_name = f"{asset}__set_point" + self.__set_point_map[asset] = var_name + self.__set_point_var[var_name] = ca.MX.sym(var_name) + self.__set_point_bounds[var_name] = (0.0, 1.0) + + # Setting the bus nominals using the connected assets. + for node, connected_assets in self.energy_system_topology.busses.items(): + nominals = {} + for var in ["Power", "I", "V"]: + nominals[var] = [] + for _, (asset, _orientation) in connected_assets.items(): + var_nom = self.variable_nominal(f"{asset}.ElectricityOut.{var}") + if var_nom != 1: + nominals[var].append(var_nom) + elif self.variable_nominal(f"{asset}.ElectricityIn.{var}") != 1: + nominals[var].append(self.variable_nominal(f"{asset}.ElectricityIn.{var}")) + else: + nominals[var].append(1) + + for i in range(len(connected_assets)): + if self.variable_nominal(f"{node}.ElectricityConn[{i + 1}].{var}") == 1: + if nominals[var][i] != 1: + # Here we set a nominal based directly on the connected asset. + self.__bus_variable_nominal[ + f"{node}.ElectricityConn[{i + 1}].{var}" + ] = nominals[var][i] + else: + # Here we set a nominal based on median of all the connected assets to + # the node. This is specifically done when we have a logical link for + # node to node. In this case we cannot set the nominal based on the + # connected node, hence we assume a node has at least one not node + # asset connected to it. + self.__bus_variable_nominal[ + f"{node}.ElectricityConn[{i + 1}].{var}" + ] = ( + np.median([x for x in nominals[var] if x != 1]) + if np.sum(nominals[var]) != len(nominals[var]) + else 1.0 + ) + + @property + def extra_variables(self): + """ + In this function we add all the variables defined in the HeatMixin to the optimization + problem. Note that these are only the normal variables not path variables. + """ + variables = super().extra_variables.copy() + + return variables + + @property + def path_variables(self): + """ + In this function we add all the path variables defined in the HeatMixin to the + optimization problem. Note that path_variables are variables that are created for each + time-step. + """ + variables = super().path_variables.copy() + + variables.extend(self.__asset_is_switched_on_var.values()) + variables.extend(self.__storage_charging_var.values()) + variables.extend(self.__set_point_var.values()) + variables.extend(self.__electrolyzer_is_active_linear_segment_var.values()) + variables.extend(self.__electricity_storage_discharge_var.values()) + + return variables + + def variable_is_discrete(self, variable): + """ + All variables that only can take integer values should be added to this function. + """ + + if variable in self.__electrolyzer_is_active_linear_segment_var: + return True + if variable in self.__asset_is_switched_on_var: + return True + if variable in self.__storage_charging_var: + return True + else: + return super().variable_is_discrete(variable) + + def variable_nominal(self, variable): + """ + In this function we add all the nominals for the variables defined/added in the HeatMixin. + """ + if variable in self.__electricity_storage_discharge_nominals: + return self.__electricity_storage_discharge_nominals[variable] + elif variable in self.__bus_variable_nominal: + return self.__bus_variable_nominal[variable] + else: + return super().variable_nominal(variable) + + def bounds(self): + """ + In this function we add the bounds to the problem for all the variables defined/added in + the HeatMixin. + """ + bounds = super().bounds() + + bounds.update(self.__electrolyzer_is_active_linear_segment_bounds) + bounds.update(self.__asset_is_switched_on_bounds) + bounds.update(self.__storage_charging_bounds) + bounds.update(self.__electricity_producer_upper_bounds) + bounds.update(self.__set_point_bounds) + bounds.update(self.__electricity_storage_discharge_bounds) + + return bounds + + @staticmethod + def __get_abs_max_bounds(*bounds): + """ + This function returns the absolute maximum of the bounds given. Note that bounds can also be + a timeseries. + """ + max_ = 0.0 + + for b in bounds: + if isinstance(b, np.ndarray): + max_ = max(max_, max(abs(b))) + elif isinstance(b, Timeseries): + max_ = max(max_, max(abs(b.values))) + else: + max_ = max(max_, abs(b)) + + return max_ + + def __state_vector_scaled(self, variable, ensemble_member): + """ + This functions returns the casadi symbols scaled with their nominal for the entire time + horizon. + """ + canonical, sign = self.alias_relation.canonical_signed(variable) + return ( + self.state_vector(canonical, ensemble_member) * self.variable_nominal(canonical) * sign + ) + + def __update_electricity_producer_upper_bounds(self): + # TODO: When a profile is assigned via esdl, this code below needs to be aligned with + # profile constraints implemented for heat to ensure compatibility + t = self.times() + + timeseries_io_names = self.io.get_timeseries_names() + for asset in self.energy_system_components.get("electricity_source", []): + if f"{asset}.maximum_electricity_source" in timeseries_io_names: + lb = Timeseries(t, np.zeros(len(t))) + ub = self.get_timeseries(f"{asset}.maximum_electricity_source") + start_indx = np.where(ub.times == t[0])[0][0] + end_indx = np.where(ub.times == t[-1])[0][0] + 1 + ub = Timeseries(t, (np.asarray(ub.values)[start_indx:end_indx]).tolist()) + self.__electricity_producer_upper_bounds[f"{asset}.Electricity_source"] = (lb, ub) + + def __electricity_producer_set_point_constraints(self, ensemble_member): + """ + This function adds constraints for wind parks which generates electrical power. The + produced electrical power is capped with a user specified percentage value of the maximum + value. + """ + constraints = [] + + # TODO: When a profile is assigned via esdl, this code below needs to be aligned with + # profile constraints implemented for heat to ensure compatibility + + for asset in [*self.energy_system_components.get("electricity_source", [])]: + if asset in self.__set_point_map.keys(): + var_name = self.__set_point_map[asset] + set_point = self.__state_vector_scaled(var_name, ensemble_member) + electricity_source = self.__state_vector_scaled( + f"{asset}.Electricity_source", ensemble_member + ) + # TODO: [: len(self.times())] should be removed once the emerge test is properly + # time-sampled. + max_ = self.bounds()[f"{asset}.Electricity_source"][1].values[: len(self.times())] + a = [x for x in max_ if abs(x) > 0.0] + nominal = ( + self.variable_nominal(f"{asset}.Electricity_source") * min(a) * np.median(a) + ) ** (1.0 / 3.0) + + constraints.append(((set_point * max_ - electricity_source) / nominal, 0.0, 0.0)) + + return constraints + + def __electricity_node_mixing_path_constraints(self, ensemble_member): + """ + This function adds constraints for power/energy and current conservation at nodes/busses. + """ + constraints = [] + + for bus, connected_cables in self.energy_system_topology.busses.items(): + power_sum = 0.0 + i_sum = 0.0 + power_nominal = [] + i_nominal = [] + + for i_conn, (_cable, orientation) in connected_cables.items(): + power_con = f"{bus}.ElectricityConn[{i_conn + 1}].Power" + i_port = f"{bus}.ElectricityConn[{i_conn + 1}].I" + power_sum += orientation * self.state(power_con) + i_sum += orientation * self.state(i_port) + power_nominal.append(self.variable_nominal(power_con)) + i_nominal.append(self.variable_nominal(i_port)) + + power_nominal = np.median(power_nominal) + constraints.append((power_sum / power_nominal, 0.0, 0.0)) + + i_nominal = np.median(i_nominal) + constraints.append((i_sum / i_nominal, 0.0, 0.0)) + + return constraints + + def __electricity_cable_mixing_path_constraints(self, ensemble_member): + """ + This function adds constraints relating the electrical power to the current flowing through + the cable. The power through the cable is limited by the maximum voltage and the actual + current variable with an inequality constraint. This is done to allow power losses through + the network. As the current and power are related with an equality constraint at the + demands exactly matching the P = U*I equation, we allow the inequalities for the lines. By + overestimating the power losses and voltage drops, together we ensure that U*I>P. + + + Furthermore, the power loss is estimated by linearizing with the maximum current, meaning + that we are always overestimating the power loss in the cable. + """ + constraints = [] + parameters = self.parameters(ensemble_member) + + for cable in self.energy_system_components.get("electricity_cable", []): + current = self.state(f"{cable}.ElectricityIn.I") + power_in = self.state(f"{cable}.ElectricityIn.Power") + power_out = self.state(f"{cable}.ElectricityOut.Power") + power_loss = self.state(f"{cable}.Power_loss") + # v_loss = self.state(f"{cable}.V_loss") + r = parameters[f"{cable}.r"] + i_max = parameters[f"{cable}.max_current"] + v_nom = parameters[f"{cable}.nominal_voltage"] + v_max = parameters[f"{cable}.max_voltage"] + # v_loss_nom = parameters[f"{cable}.nominal_voltage_loss"] + length = parameters[f"{cable}.length"] + + # Ensure that the current is sufficient to transport the power + constraints.append(((power_in - current * v_max) / (i_max * v_max), -np.inf, 0.0)) + constraints.append(((power_out - current * v_max) / (i_max * v_max), -np.inf, 0.0)) + # Power loss constraint + options = self.energy_system_options() + if options["include_electric_cable_power_loss"]: + if cable in self._electricity_cable_topo_cable_class_map.keys(): + cable_classes = self._electricity_cable_topo_cable_class_map[cable] + max_res = max([cc.resistance for cc in cable_classes]) + max_i_max = max([cc.maximum_current for cc in cable_classes]) + big_m = max_i_max**2 * max_res * length + constraint_nominal = max_i_max * v_nom * max_res * length + for cc_data, cc_name in cable_classes.items(): + if cc_name != "None": + i_max = cc_data.maximum_current + res = cc_data.resistance + exp = current * res * length * i_max + is_selected = self.variable(cc_name) + constraints.append( + ( + (power_loss - exp + big_m * (1 - is_selected)) + / constraint_nominal, + 0.0, + np.inf, + ) + ) + constraints.append( + ( + (power_loss - exp - big_m * (1 - is_selected)) + / (constraint_nominal), + -np.inf, + 0.0, + ) + ) + else: + constraints.append( + ((power_loss - current * r * i_max) / (i_max * v_nom * r), 0.0, 0.0) + ) + else: + constraints.append(((power_loss) / (i_max * v_nom * r), 0.0, 0.0)) + + return constraints + + def __voltage_loss_path_constraints(self, ensemble_member): + """ + Furthermore, the voltage_loss symbol is set, as it depends on the chosen pipe + class, e.g. the related resistance and the current through the cable. + + Parameters + ---------- + ensemble_member : The ensemble of the optimization + + Returns + ------- + list of the added constraints + """ + constraints = [] + parameters = self.parameters(ensemble_member) + + for cable in self.energy_system_components.get("electricity_cable", []): + cable_classes = [] + + current = self.state(f"{cable}.ElectricityIn.I") + v_loss = self.state(f"{cable}.V_loss") + r = parameters[f"{cable}.r"] + # v_loss_nom = parameters[f"{cable}.nominal_voltage_loss"] + v_nom = parameters[f"{cable}.nominal_voltage"] + c_length = parameters[f"{cable}.length"] + + constraint_nominal = self.variable_nominal(v_loss) + + # TODO: still have to check for proper scaling + if cable in self._electricity_cable_topo_cable_class_map.keys(): + cable_classes = self._electricity_cable_topo_cable_class_map[cable] + variables = { + cc.name: self.variable(var_name) for cc, var_name in cable_classes.items() + } + resistances = {cc.name: cc.resistance for cc in cable_classes} + + # to be updated for a better value, but it should also cover the gap between two + # nodes when no cable is placed, so should be able to reach v_max + big_m = v_nom + + for var_size, variable in variables.items(): + if var_size != "None": + expr = resistances[var_size] * c_length * current + constraints.append( + ( + (v_loss - expr + big_m * (1 - variable)) / constraint_nominal, + 0.0, + np.inf, + ) + ) + constraints.append( + ( + (v_loss - expr - big_m * (1 - variable)) / constraint_nominal, + -np.inf, + 0.0, + ) + ) + + else: + constraints.append(((v_loss - r * current) / constraint_nominal, 0.0, 0.0)) + + return constraints + + def __electricity_demand_path_constraints(self, ensemble_member): + """ + This function adds the constraints for the electricity commodity at the demand assets. We + enforce that a minimum voltage is exactly met together with the power that is carried by + the current. By fixing the voltage at the demand we ensure that at the demands + P = U * I is met exactly at this point in the network and the power is conservatively + in the cables at all locations in the network. + """ + constraints = [] + parameters = self.parameters(ensemble_member) + + for elec_demand in [ + *self.energy_system_components.get("electricity_demand", []), + *self.energy_system_components.get("heat_pump_elec", []), + *self.energy_system_components.get("electrolyzer", []), + *self.energy_system_components.get("transformer", []), + ]: + min_voltage = parameters[f"{elec_demand}.min_voltage"] + voltage = self.state(f"{elec_demand}.ElectricityIn.V") + # to ensure that voltage entering is equal or larger than the minimum voltage + constraints.append(((voltage - min_voltage) / min_voltage, 0.0, np.inf)) + + power_nom = self.variable_nominal(f"{elec_demand}.ElectricityIn.Power") + curr_nom = self.variable_nominal(f"{elec_demand}.ElectricityIn.I") + power_in = self.state(f"{elec_demand}.ElectricityIn.Power") + current_in = self.state(f"{elec_demand}.ElectricityIn.I") + + constraints.append( + ( + (power_in - min_voltage * current_in) + / (power_nom * curr_nom * min_voltage) ** 0.5, + 0, + 0, + ) + ) + + return constraints + + def __electricity_storage_path_constraints(self, ensemble_member): + """ + This function adds the constraints for the electricity commodity at the storage assets. + When charging the electricity_storage acts as an electrcicity demand and during discharging + it acts as a electricity producer. The constraints are selected using the bigM method using + the boolean for charging and using a charging efficiency during charging. + """ + constraints = [] + parameters = self.parameters(ensemble_member) + + for asset in [ + *self.energy_system_components.get("electricity_storage", []), + ]: + min_voltage = parameters[f"{asset}.min_voltage"] + voltage = self.state(f"{asset}.ElectricityIn.V") + + # when charging act like a demand, when discharging act like a source + # to ensure that voltage is equal or larger than the minimum voltage + constraints.append(((voltage - min_voltage) / min_voltage, 0.0, np.inf)) + + power_nom = self.variable_nominal(f"{asset}.ElectricityIn.Power") + curr_nom = self.variable_nominal(f"{asset}.ElectricityIn.I") + power_in = self.state(f"{asset}.ElectricityIn.Power") + current_in = self.state(f"{asset}.ElectricityIn.I") + + # is_charging is 1 if charging and powerin>0 + big_m = 2 * max(np.abs(self.bounds()[f"{asset}.ElectricityIn.Power"])) + is_charging = self.state(f"{asset}__is_charging") + constraints.append(((power_in + (1 - is_charging) * big_m) / power_nom, 0.0, np.inf)) + constraints.append(((power_in - is_charging * big_m) / power_nom, -np.inf, 0.0)) + + constraints.append( + ( + (power_in - min_voltage * current_in + (1 - is_charging) * big_m) + / (power_nom * curr_nom * min_voltage) ** 0.5, + 0, + np.inf, + ) + ) + constraints.append( + ( + (power_in - min_voltage * current_in - (1 - is_charging) * big_m) + / (power_nom * curr_nom * min_voltage) ** 0.5, + -np.inf, + 0, + ) + ) + + # power charging using discharge/charge efficiency, needs boolean + eff_power = self.state(f"{asset}.Effective_power_charging") + discharge_eff = parameters[f"{asset}.discharge_efficiency"] + charge_eff = parameters[f"{asset}.charge_efficiency"] + # charging + constraints.append( + ( + (eff_power - charge_eff * power_in + (1 - is_charging) * big_m) / power_nom, + 0, + np.inf, + ) + ) + constraints.append( + ( + (eff_power - charge_eff * power_in - (1 - is_charging) * big_m) / power_nom, + -np.inf, + 0, + ) + ) + # discharging + constraints.append( + ( + (eff_power * discharge_eff - power_in + is_charging * big_m) / power_nom, + 0, + np.inf, + ) + ) + constraints.append( + ( + (eff_power * discharge_eff - power_in - is_charging * big_m) / power_nom, + -np.inf, + 0, + ) + ) + + return constraints + + def __electricity_storage_discharge_var_path_constraints( + self, ensemble_member: int + ) -> List[Tuple[ca.MX, float, float]]: + """ + The discharge variables are added such that two separate goals for charging and discharging + can be created. The discharging variable has a lower bound of 0 and should always be larger + or equal to the negative of the inflow variable. This allows for first a minimization of + the discharging and afterwards a maximisation of the charging without conflicting goals or + constraints. + + :param ensemble_member: + :return: list of the additional constraints that are created + """ + + constraints = [] + options = self.energy_system_options() + + if options["electricity_storage_discharge_variables"]: + for storage in self.energy_system_components.get("electricity_storage", []): + storage_eff_power_charge_var = self.state(f"{storage}.Effective_power_charging") + discharge_var_name = self.__electricity_storage_discharge_map[storage] + storage_discharge_var = self.__electricity_storage_discharge_var[discharge_var_name] + nominal = self.variable_nominal(discharge_var_name) + + # P_effective_charge represents both charging and discharing based on the sign. + # P_discharge >= -P_effective_charge + constraints.append( + ((storage_discharge_var + storage_eff_power_charge_var) / nominal, 0.0, np.inf) + ) + + return constraints + + def __get_electrolyzer_gas_mass_flow_out( + self, coef_a, coef_b, coef_c, electrical_power_input + ) -> float: + """ + This function returns the gas mass flow rate [g/s] out of an electrolyzer based on the + theoretical efficiency curve: + energy [Ws] / gas mass [kg] = + (coef_a / electrical_power_input) + (b * electrical_power_input) + coef_c + + Parameters + ---------- + coef_a: electrolyzer efficience curve coefficent + coef_b: electrolyzer efficience curve coefficent + coef_c: electrolyzer efficience curve coefficent + electrical_power_input: electrical power consumed [W] + + Returns + ------- + gas mass flow rate produced by the electrolyzer [g/s] + """ + + if not isclose(electrical_power_input, 0.0): + eff = (coef_a / electrical_power_input) + (coef_b * electrical_power_input) + coef_c + gas_mass_flow_out = (1.0 / eff) * electrical_power_input * (1 / (3600)) # g/s + + else: + gas_mass_flow_out = 0.0 + + return gas_mass_flow_out + + def _get_linear_coef_electrolyzer_mass_vs_epower_fit( + self, coef_a, coef_b, coef_c, n_lines, electrical_power_min, electrical_power_max + ) -> Tuple[np.array, np.array]: + """ + This function returns a set of coefficients to approximate a gas mass flow rate curve with + linear functions in the form of: gass mass flow rate [g/s] = b + (a * electrical_power) + + Parameters + ---------- + coef_a: electrolyzer efficience curve coefficent + coef_b: electrolyzer efficience curve coefficent + coef_c: electrolyzer efficience curve coefficent + n_lines: number of linear lines used to approximate the non-linear curve + electrical_power_min: minimum electrical power consumed [W] + electrical_power_max: maximum electrical power consumed [W] + + Returns + ------- + coefficients for linear curve fit(s) to the theoretical non-linear electrolyzer curve + """ + + electrical_power_points = np.linspace( + electrical_power_min, electrical_power_max, n_lines + 1 + ) + + gas_mass_flow_points = np.array( + [ + self.__get_electrolyzer_gas_mass_flow_out(coef_a, coef_b, coef_c, ep) + for ep in electrical_power_points + ] + ) + + a_vals = np.diff(gas_mass_flow_points) / np.diff(electrical_power_points) + b_vals = gas_mass_flow_points[1:] - a_vals * electrical_power_points[1:] + + return a_vals, b_vals + + def __electrolyzer_path_constaint(self, ensemble_member): + """ + This functions add the constraints for the gas mass flow production based as a functions of + electrical power input. This production is approximated by an electrolyzer efficience curve + (energy/gas mass vs electrical power input, [KWh/kg] vs [W]) which is then linearized. If + the load becomes lower than the minimum load both the gass_mass_flow and the electricity + power should be 0. + """ + constraints = [] + parameters = self.parameters(ensemble_member) + options = self.energy_system_options() + # TODO: CHECK UNITS MASSFLOW + for asset in self.energy_system_components.get("electrolyzer", []): + gas_mass_flow_out = self.state(f"{asset}.Gas_mass_flow_out") + power_consumed = self.state(f"{asset}.Power_consumed") + var_name = self.__asset_is_switched_on_map[asset] + asset_is_switched_on = self.state(var_name) + if options["electrolyzer_efficiency"] == ElectrolyzerOption.CONSTANT_EFFICIENCY: + nominal = ( + self.variable_nominal(f"{asset}.Gas_mass_flow_out") + * self.variable_nominal(f"{asset}.Power_consumed") + ) ** 0.5 * 3600 + big_m = ( + self.bounds()[f"{asset}.Power_consumed"][1] + / parameters[f"{asset}.efficiency"] + / 3600 + ) * 2 + constraints.extend( + [ + ( + ( + gas_mass_flow_out * parameters[f"{asset}.efficiency"] * 3600 + - power_consumed + ) + / nominal, + 0.0, + 0.0, + ), + ] + ) + + elif ( + options["electrolyzer_efficiency"] + == ElectrolyzerOption.LINEARIZED_THREE_LINES_WEAK_INEQUALITY + or options["electrolyzer_efficiency"] + == ElectrolyzerOption.LINEARIZED_THREE_LINES_EQUALITY + ): + if ( + options["electrolyzer_efficiency"] + == ElectrolyzerOption.LINEARIZED_THREE_LINES_WEAK_INEQUALITY + ): + curve_fit_number_of_lines = 3 + else: + curve_fit_number_of_lines = len( + self.__electrolyzer_is_active_linear_segment_map[asset] + ) + + linear_coef_a, linear_coef_b = ( + self._get_linear_coef_electrolyzer_mass_vs_epower_fit( + parameters[f"{asset}.a_eff_coefficient"], + parameters[f"{asset}.b_eff_coefficient"], + parameters[f"{asset}.c_eff_coefficient"], + n_lines=curve_fit_number_of_lines, + electrical_power_min=max( + parameters[f"{asset}.minimum_load"], + 0.01 * self.bounds()[f"{asset}.ElectricityIn.Power"][1], + ), + electrical_power_max=self.bounds()[f"{asset}.ElectricityIn.Power"][1], + ) + ) + power_consumed_vect = ca.repmat(power_consumed, len(linear_coef_a)) + gas_mass_flow_out_vect = ca.repmat(gas_mass_flow_out, len(linear_coef_a)) + gass_mass_out_linearized_vect = linear_coef_a * power_consumed_vect + linear_coef_b + + gass_mass_out_max = ( + linear_coef_a[-1] * self.bounds()[f"{asset}.Power_consumed"][1] + + linear_coef_b[-1] + ) + nominal = ( + self.variable_nominal(f"{asset}.Gas_mass_flow_out") + * min(linear_coef_a) + * self.variable_nominal(f"{asset}.Power_consumed") + ) ** 0.5 + big_m = gass_mass_out_max * 2 + constraints.extend( + [ + ( + ( + gas_mass_flow_out_vect + - gass_mass_out_linearized_vect + - (1 - asset_is_switched_on) * big_m + ) + / nominal, + -np.inf, + 0.0, + ), + ] + ) + if ( + options["electrolyzer_efficiency"] + == ElectrolyzerOption.LINEARIZED_THREE_LINES_EQUALITY + ): + is_line_segment_active_sum = 0.0 + for n_line in range(curve_fit_number_of_lines): + var_name = self.__electrolyzer_is_active_linear_segment_map[asset][ + f"line_{n_line}" + ] + is_line_segment_active = self.state(var_name) + # Equality constraint to map the input power to the output massflow + # of the electrolyzer + constraints.append( + ( + ( + gas_mass_flow_out_vect[n_line] + - gass_mass_out_linearized_vect[n_line] + - (1 - is_line_segment_active) * big_m + ) + / nominal, + -np.inf, + 0.0, + ), + ) + # + constraints.append( + ( + ( + gas_mass_flow_out_vect[n_line] + - gass_mass_out_linearized_vect[n_line] + + (1 - is_line_segment_active) * big_m + ) + / nominal, + 0.0, + np.inf, + ), + ) + is_line_segment_active_sum += is_line_segment_active + # Constraint to ensure that only one line is active, if the electrolyzer + # is switched on + constraints.append( + (is_line_segment_active_sum + (1 - asset_is_switched_on), 1.0, 1.0), + ) + + constraints.append( + ((gas_mass_flow_out + asset_is_switched_on * big_m) / big_m, 0.0, np.inf) + ) + constraints.append( + ((gas_mass_flow_out - asset_is_switched_on * big_m) / big_m, -np.inf, 0.0) + ) + + # Add constraints to ensure the electrolyzer is switched off when it reaches a power + # input below the minimum operating value + + big_m = self.bounds()[f"{asset}.ElectricityIn.Power"][1] * 1.5 * 10.0 + constraints.append( + ( + ( + power_consumed + - parameters[f"{asset}.minimum_load"] + + (1.0 - asset_is_switched_on) * big_m + ) + / self.variable_nominal(f"{asset}.Power_consumed"), + 0.0, + np.inf, + ) + ) + constraints.append( + ((power_consumed + asset_is_switched_on * big_m) / big_m, 0.0, np.inf) + ) + constraints.append( + ((power_consumed - asset_is_switched_on * big_m) / big_m, -np.inf, 0.0) + ) + + return constraints + + def path_constraints(self, ensemble_member): + """ + Here we add all the path constraints to the optimization problem. Please note that the + path constraints are the constraints that are applied to each time-step in the problem. + """ + + constraints = super().path_constraints(ensemble_member) + + constraints.extend(self.__electricity_demand_path_constraints(ensemble_member)) + constraints.extend(self.__electricity_node_mixing_path_constraints(ensemble_member)) + constraints.extend(self.__electricity_cable_mixing_path_constraints(ensemble_member)) + constraints.extend(self.__voltage_loss_path_constraints(ensemble_member)) + constraints.extend(self.__electrolyzer_path_constaint(ensemble_member)) + constraints.extend(self.__electricity_storage_path_constraints(ensemble_member)) + constraints.extend( + self.__electricity_storage_discharge_var_path_constraints(ensemble_member) + ) + + return constraints + + def constraints(self, ensemble_member): + """ + This function adds the normal constraints to the problem. Unlike the path constraints these + are not applied to every time-step in the problem. Meaning that these constraints either + consider global variables that are independent of time-step or that the relevant time-steps + are indexed within the constraint formulation. + """ + constraints = super().constraints(ensemble_member) + + constraints.extend(self.__electricity_producer_set_point_constraints(ensemble_member)) + + return constraints + + def goal_programming_options(self): + """ + Here we set the goal programming configuration. We use soft constraints for consecutive + goals. + """ + options = super().goal_programming_options() + options["keep_soft_constraints"] = True + return options + + def solver_options(self): + """ + Here we define the solver options. By default we use the open-source solver cbc and casadi + solver qpsol. + """ + options = super().solver_options() + options["casadi_solver"] = "qpsol" + options["solver"] = "highs" + return options + + def compiler_options(self): + """ + In this function we set the compiler configuration. + """ + options = super().compiler_options() + options["resolve_parameter_values"] = True + return options diff --git a/src/rtctools_heat_network/esdl/__init__.py b/src/mesido/esdl/__init__.py similarity index 100% rename from src/rtctools_heat_network/esdl/__init__.py rename to src/mesido/esdl/__init__.py diff --git a/src/rtctools_heat_network/esdl/_edr_pipes.json b/src/mesido/esdl/_edr_pipes.json similarity index 100% rename from src/rtctools_heat_network/esdl/_edr_pipes.json rename to src/mesido/esdl/_edr_pipes.json diff --git a/src/rtctools_heat_network/esdl/_exceptions.py b/src/mesido/esdl/_exceptions.py similarity index 100% rename from src/rtctools_heat_network/esdl/_exceptions.py rename to src/mesido/esdl/_exceptions.py diff --git a/src/mesido/esdl/_gas_pipe_database.json b/src/mesido/esdl/_gas_pipe_database.json new file mode 100644 index 000000000..d7fc0e303 --- /dev/null +++ b/src/mesido/esdl/_gas_pipe_database.json @@ -0,0 +1,205 @@ +{ + "DN6": { + "name": "DN6", + "inner_diameter": "0.00684", + "wall_thickness": "0.00173", + "outer_diameter": "0.0103", + "roughness": "1.50E-05" + }, + "DN8": { + "name": "DN8", + "inner_diameter": "0.00922", + "wall_thickness": "0.00224", + "outer_diameter": "0.0137", + "roughness": "1.50E-05" + }, + "DN10": { + "name": "DN10", + "inner_diameter": "0.01248", + "wall_thickness": "0.00231", + "outer_diameter": "0.0171", + "roughness": "1.50E-05" + }, + "DN15": { + "name": "DN15", + "inner_diameter": "0.01576", + "wall_thickness": "0.00277", + "outer_diameter": "0.0213", + "roughness": "1.50E-05" + }, + "DN20": { + "name": "DN20", + "inner_diameter": "0.02096", + "wall_thickness": "0.00287", + "outer_diameter": "0.0267", + "roughness": "1.50E-05" + }, + "DN25": { + "name": "DN25", + "inner_diameter": "0.02664", + "wall_thickness": "0.00338", + "outer_diameter": "0.0334", + "roughness": "1.50E-05" + }, + "DN32": { + "name": "DN32", + "inner_diameter": "0.03508", + "wall_thickness": "0.00356", + "outer_diameter": "0.0422", + "roughness": "1.50E-05" + }, + "DN40": { + "name": "DN40", + "inner_diameter": "0.04094", + "wall_thickness": "0.00368", + "outer_diameter": "0.0483", + "roughness": "1.50E-05" + }, + "DN50": { + "name": "DN50", + "inner_diameter": "0.05248", + "wall_thickness": "0.00391", + "outer_diameter": "0.0603", + "roughness": "1.50E-05" + }, + "DN65": { + "name": "DN65", + "inner_diameter": "0.06268", + "wall_thickness": "0.00516", + "outer_diameter": "0.073", + "roughness": "1.50E-05" + }, + "DN80": { + "name": "DN80", + "inner_diameter": "0.07792", + "wall_thickness": "0.00549", + "outer_diameter": "0.0889", + "roughness": "1.50E-05" + }, + "DN90": { + "name": "DN90", + "inner_diameter": "0.09012", + "wall_thickness": "0.00574", + "outer_diameter": "0.1016", + "roughness": "1.50E-05" + }, + "DN100": { + "name": "DN100", + "inner_diameter": "0.10226", + "wall_thickness": "0.00602", + "outer_diameter": "0.1143", + "roughness": "1.50E-05" + }, + "DN125": { + "name": "DN125", + "inner_diameter": "0.1282", + "wall_thickness": "0.00655", + "outer_diameter": "0.1413", + "roughness": "1.50E-05" + }, + "DN150": { + "name": "DN150", + "inner_diameter": "0.15408", + "wall_thickness": "0.00711", + "outer_diameter": "0.1683", + "roughness": "1.50E-05" + }, + "DN200": { + "name": "DN200", + "inner_diameter": "0.20274", + "wall_thickness": "0.00818", + "outer_diameter": "0.2191", + "roughness": "1.50E-05" + }, + "DN250": { + "name": "DN250", + "inner_diameter": "0.25456", + "wall_thickness": "0.00927", + "outer_diameter": "0.2731", + "roughness": "1.50E-05" + }, + "DN300": { + "name": "DN300", + "inner_diameter": "0.30484", + "wall_thickness": "0.00953", + "outer_diameter": "0.3239", + "roughness": "1.50E-05" + }, + "DN350": { + "name": "DN350", + "inner_diameter": "0.33654", + "wall_thickness": "0.00953", + "outer_diameter": "0.3556", + "roughness": "1.50E-05" + }, + "DN400": { + "name": "DN400", + "inner_diameter": "0.38734", + "wall_thickness": "0.00953", + "outer_diameter": "0.4064", + "roughness": "1.50E-05" + }, + "DN450": { + "name": "DN450", + "inner_diameter": "0.43814", + "wall_thickness": "0.00953", + "outer_diameter": "0.4572", + "roughness": "1.50E-05" + }, + "DN500": { + "name": "DN500", + "inner_diameter": "0.48894", + "wall_thickness": "0.00953", + "outer_diameter": "0.508", + "roughness": "1.50E-05" + }, + "DN600": { + "name": "DN600", + "inner_diameter": "0.59094", + "wall_thickness": "0.00953", + "outer_diameter": "0.61", + "roughness": "1.50E-05" + }, + "DN700": { + "name": "DN700", + "inner_diameter": "0.69194", + "wall_thickness": "0.00953", + "outer_diameter": "0.711", + "roughness": "1.50E-05" + }, + "DN800": { + "name": "DN800", + "inner_diameter": "0.79394", + "wall_thickness": "0.00953", + "outer_diameter": "0.813", + "roughness": "1.50E-05" + }, + "DN900": { + "name": "DN900", + "inner_diameter": "0.89494", + "wall_thickness": "0.00953", + "outer_diameter": "0.914", + "roughness": "1.50E-05" + }, + "DN1000": { + "name": "DN1000", + "inner_diameter": "0.99694", + "wall_thickness": "0.00953", + "outer_diameter": "1.016", + "roughness": "1.50E-05" + }, + "DN1100": { + "name": "DN1100", + "inner_diameter": "1.09894", + "wall_thickness": "0.00953", + "outer_diameter": "1.118", + "roughness": "1.50E-05" + }, + "DN1200": { + "name": "DN1200", + "inner_diameter": "1.1936", + "wall_thickness": "0.0127", + "outer_diameter": "1.219", + "roughness": "1.50E-05" + } +} \ No newline at end of file diff --git a/src/rtctools_heat_network/esdl/_update_edr_pipes_json.py b/src/mesido/esdl/_update_edr_pipes_json.py similarity index 97% rename from src/rtctools_heat_network/esdl/_update_edr_pipes_json.py rename to src/mesido/esdl/_update_edr_pipes_json.py index eecdf382c..9fe7479c6 100644 --- a/src/rtctools_heat_network/esdl/_update_edr_pipes_json.py +++ b/src/mesido/esdl/_update_edr_pipes_json.py @@ -2,9 +2,9 @@ import xml.etree.ElementTree as ET # noqa: N817 from typing import Tuple -import requests +from mesido._heat_loss_u_values_pipe import heat_loss_u_values_pipe -from rtctools_heat_network._heat_loss_u_values_pipe import heat_loss_u_values_pipe +import requests def main(): diff --git a/src/rtctools_heat_network/esdl/asset_to_component_base.py b/src/mesido/esdl/asset_to_component_base.py similarity index 56% rename from src/rtctools_heat_network/esdl/asset_to_component_base.py rename to src/mesido/esdl/asset_to_component_base.py index 9b0377177..5c15fd93f 100644 --- a/src/rtctools_heat_network/esdl/asset_to_component_base.py +++ b/src/mesido/esdl/asset_to_component_base.py @@ -5,15 +5,19 @@ from pathlib import Path from typing import Any, Dict, Tuple, Type, Union +import CoolProp as cP + import esdl from esdl import TimeUnitEnum, UnitEnum -from rtctools_heat_network.pycml import Model as _Model +from mesido.esdl._exceptions import _RetryLaterException +from mesido.esdl.common import Asset +from mesido.network_common import NetworkSettings +from mesido.potential_errors import MesidoAssetIssueType, get_potential_errors +from mesido.pycml import Model as _Model -from ._exceptions import _RetryLaterException -from .common import Asset -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") MODIFIERS = Dict[str, Union[str, int, float]] @@ -42,6 +46,118 @@ } +def get_internal_energy(asset_name, carrier): + # The default of 20°C is also used in the head_loss_class. Thus, when updating ensure it + # is also updated in the head_loss_class. + temperature = 20.0 + + if isinstance(carrier, esdl.HeatCommodity): + internal_energy = cP.CoolProp.PropsSI( + "U", + "T", + 273.15 + temperature, + "P", + 1.0 * 1.0e5, # TODO: defualt 1 bar pressure should be set for the carrier + "WATER", + ) + elif NetworkSettings.NETWORK_TYPE_GAS in carrier.name: + internal_energy = cP.CoolProp.PropsSI( + "U", + "T", + 273.15 + temperature, + "P", + carrier.pressure * 1.0e5, + NetworkSettings.NETWORK_COMPOSITION_GAS, + ) + elif NetworkSettings.NETWORK_TYPE_HYDROGEN in carrier.name: + internal_energy = cP.CoolProp.PropsSI( + "U", + "T", + 273.15 + temperature, + "P", + carrier.pressure * 1.0e5, + str(NetworkSettings.NETWORK_TYPE_HYDROGEN).upper(), + ) + else: + logger.warning( + f"Neither gas/hydrogen/heat was used in the carrier " f"name of pipe {asset_name}." + ) + # TODO: resolve heating value (default value below) vs internal energy values (above) + internal_energy = 46.0e6 # natural gas at about 1 bar [J/kg] heating value + return internal_energy # [J/kg] + + +def get_energy_content(asset_name, carrier) -> float: + # Return the heating value + energy_content_j_kg = 0.0 # [J/kg] + density_kg_m3 = ( + get_density(asset_name, carrier, temperature_degrees_celsius=20.0, pressure_pa=1.0e5) + / 1000.0 + ) + if str(NetworkSettings.NETWORK_TYPE_GAS).upper() in str(carrier.name).upper(): + # Groningen gas: 31,68 MJ/m3 LCV + energy_content_j_kg = 31.68 * 10.0**6 / density_kg_m3 # LCV / lower heating value + elif str(NetworkSettings.NETWORK_TYPE_HYDROGEN).upper() in str(carrier.name).upper(): + # This value can be lower / higher heating value depending on the case + # Currently the lower heating value is used below (120.0 MJ/kg) + energy_content_j_kg = 120.0 * 10.0**6 / density_kg_m3 + else: + raise logger.error( + f"Neither gas/hydrogen was used in the carrier " f"name of pipe {asset_name}." + ) + return energy_content_j_kg + + +def get_density(asset_name, carrier, temperature_degrees_celsius=20.0, pressure_pa=None): + # TODO: gas carrier temperature still needs to be resolved. + # The default for temperature_degrees_celsius=20.0, this should be the same as the value (20°C) + # used in the head_loss_class for the calculation of the friction factor + # (linked to _kinematic_viscosity). Thus, when updating the default value of + # temperature_degrees_celsius ensure it is also updated in the head_loss_class. + if pressure_pa is None: + if isinstance(carrier, esdl.HeatCommodity): + pressure_pa = 16.0e5 # 16bar is expected to be the upper limit in networks + else: + pressure_pa = carrier.pressure * 1.0e5 # convert bar to Pa + elif pressure_pa < 0.0: + raise logger.error("The pressure should be > 0.0 to calculate density") + + if isinstance(carrier, esdl.HeatCommodity): + density = cP.CoolProp.PropsSI( + "D", + "T", + 273.15 + temperature_degrees_celsius, + "P", + pressure_pa, + "INCOMP::Water", + ) + return density # kg/m3 + elif NetworkSettings.NETWORK_TYPE_GAS in carrier.name: + density = cP.CoolProp.PropsSI( + "D", + "T", + 273.15 + temperature_degrees_celsius, + "P", + pressure_pa, + NetworkSettings.NETWORK_COMPOSITION_GAS, + ) + elif NetworkSettings.NETWORK_TYPE_HYDROGEN in carrier.name: + density = cP.CoolProp.PropsSI( + "D", + "T", + 273.15 + temperature_degrees_celsius, + "P", + pressure_pa, + str(NetworkSettings.NETWORK_TYPE_HYDROGEN).upper(), + ) + else: + logger.warning( + f"Neither gas/hydrogen/heat was used in the carrier " f"name of pipe {asset_name}" + ) + density = 6.2 # natural gas at about 8 bar + return density * 1.0e3 # to convert from kg/m3 to g/m3 + + class _AssetToComponentBase: # A map of pipe class name to edr asset in _edr_pipes.json STEEL_S1_PIPE_EDR_ASSETS = { @@ -72,39 +188,53 @@ class _AssetToComponentBase: } # A map of the esdl assets to the asset types in pycml component_map = { + "Airco": "airco", "ATES": "ates", + "Battery": "electricity_storage", + "Bus": "electricity_node", + "ElectricBoiler": "elec_boiler", "ElectricityCable": "electricity_cable", "ElectricityDemand": "electricity_demand", "ElectricityProducer": "electricity_source", "Electrolyzer": "electrolyzer", - "Bus": "electricity_node", + "Export": "export", + "Compressor": "compressor", "GenericConsumer": "heat_demand", + "CoolingDemand": "cold_demand", "HeatExchange": "heat_exchanger", "HeatingDemand": "heat_demand", "HeatPump": "heat_pump", - "GasHeater": "heat_source", + "GasHeater": "gas_boiler", "GasProducer": "gas_source", "GasDemand": "gas_demand", "GasConversion": "gas_substation", "GasStorage": "gas_tank_storage", "GenericProducer": "heat_source", "GeothermalSource": "heat_source", + "Losses": "heat_demand", "HeatProducer": "heat_source", + "Import": "import", "ResidualHeatSource": "heat_source", - "GenericConversion": "heat_exchanger", + "GenericConversion": "generic_conversion", "Joint": "node", - "Pipe": "heat_pipe", + "Pipe": "pipe", "Pump": "pump", + "PressureReducingValve": "gas_substation", + "PVInstallation": "electricity_source", "HeatStorage": "heat_buffer", "Sensor": "skip", "Valve": "control_valve", "WindPark": "electricity_source", + "WindTurbine": "electricity_source", + "Transformer": "transformer", "CheckValve": "check_valve", } primary_port_name_convention = "primary" secondary_port_name_convention = "secondary" + __power_keys = ["power", "maxDischargeRate", "maxChargeRate", "capacity"] + def __init__(self, **kwargs): """ In this init we initialize some dicts and we load the edr pipes. @@ -117,6 +247,10 @@ def __init__(self, **kwargs): self._edr_pipes = json.load( open(os.path.join(Path(__file__).parent, "_edr_pipes.json"), "r") ) + # The default gas pipe database is based on the ASA pipe catalogue schedule standard (std). + self._gas_pipes = json.load( + open(os.path.join(Path(__file__).parent, "_gas_pipe_database.json"), "r") + ) def convert(self, asset: Asset) -> Tuple[Type[_Model], MODIFIERS]: """ @@ -125,6 +259,25 @@ def convert(self, asset: Asset) -> Tuple[Type[_Model], MODIFIERS]: With more descriptive variable names the return type would be: Tuple[pycml_heat_component_type, Dict[component_attribute, new_attribute_value]] """ + + dispatch_method_name = f"convert_{self.component_map[asset.asset_type]}" + return getattr(self, dispatch_method_name)(asset) + + def port_asset_type_connections(self, asset): + """ + Here we populate a map between ports and asset types that we need before we can convert + the individual assets. This is because for the parsing of some assets we need to know if + they are connected to a certain type of asset, like a is disconnectable depending on which + asset type it is connected. + + Parameters + ---------- + asset : Asset pipe object with it's properties from ESDL + + Returns + ------- + None + """ ports = [] if asset.in_ports is not None: ports.extend(asset.in_ports) @@ -135,9 +288,6 @@ def convert(self, asset: Asset) -> Tuple[Type[_Model], MODIFIERS]: for port in ports: self._port_to_esdl_component_type[port] = asset.asset_type - dispatch_method_name = f"convert_{self.component_map[asset.asset_type]}" - return getattr(self, dispatch_method_name)(asset) - def _pipe_get_diameter_and_insulation(self, asset: Asset) -> Tuple[float, list, list]: """ There are multiple ways to specify pipe properties like inner-diameter and @@ -218,6 +368,89 @@ def _pipe_get_diameter_and_insulation(self, asset: Asset) -> Tuple[float, list, return inner_diameter, insulation_thicknesses, conductivies_insulation + def _gas_pipe_get_diameter_and_roughness(self, asset: Asset) -> Tuple[float, float]: + """ + There are multiple ways to specify pipe properties like inner-diameter and + pipe material and thickness. The user specified nominal diameter (DN size) + takes precedence over potential user specified innerDiameter (while logging + warnings when either of these are specified in combination with the pipe DN). + Similarly, for the wall roughness, the order of preference is; based on the + DN size from the default database in this repo, the wall_roughness attribute + from the ESDL asset or the default value. + Parameters + ---------- + asset : Asset pipe object with itss properties from ESDL + + Returns + ------- + pipe inner diameter [m], wall roughness [m] + """ + + full_name = f"{asset.asset_type} '{asset.name}'" + if asset.attributes["innerDiameter"] and asset.attributes["diameter"].value > 0: + logger.warning( + f"{full_name}' has both 'innerDiameter' and 'diameter' specified. " + f"Diameter of {asset.attributes['diameter'].name} will be used." + ) + + edr_dn_size = None + if asset.attributes["diameter"].value > 0: + edr_dn_size = str(asset.attributes["diameter"].name) + elif not asset.attributes["innerDiameter"]: + logger.error( + f"{full_name}' has no DN size or innerDiameter specified, default is set to DN200. " + ) + edr_dn_size = "DN200" + # TODO: ideally no default diameter size is set, test cases have to be updated for this + # to be removed. + + # NaN means the default values will be used + wall_roughness = math.nan + + if edr_dn_size: + # Get insulation and diameter properties from EDR asset with this size. + edr_asset = self._gas_pipes[edr_dn_size] + inner_diameter = float(edr_asset["inner_diameter"]) + wall_roughness = float(edr_asset["roughness"]) + else: + assert asset.attributes["innerDiameter"] + inner_diameter = asset.attributes["innerDiameter"] + if asset.attributes["roughness"] > 0.0: + wall_roughness = float(asset.attributes["roughness"]) + else: + wall_roughness = 1.0e-4 + + return inner_diameter, wall_roughness + + def _cable_get_resistance(self, asset: Asset) -> Tuple: + """ + Determines the resistance in ohm/m defined by the inverse of the electrical conductivity + in the cable's material properties. If no material is defined a default resistance of + 1e-6 ohm/m is used. + + Parameters + ---------- + asset : Asset cable object with it's properties from ESDL + + Returns + ------- + resistance [ohm/m] + """ + + default_res = 1e-6 + material = asset.attributes["material"] + el_conductivity = None + if material: + el_conductivity = material.electricalConductivity + if not el_conductivity: + logger.warning( + f"Cable {asset.name} does not have a material with conductivity assigned," + f" using default resistance of {default_res} ohm/m" + ) + res_ohm_per_m = 1 / el_conductivity if el_conductivity else default_res + + return res_ohm_per_m + def _is_disconnectable_pipe(self, asset: Asset) -> bool: """ This function checks if the pipe is connected to specific assets (e.g. source) and if so @@ -234,6 +467,12 @@ def _is_disconnectable_pipe(self, asset: Asset) -> bool: A bool that specifies whether we should have a disconnectable variable for this pipe. """ + # TODO: this functionality combined with heat_loss_disconnected_pipe is not functioning as + # intended anymore. When heat_loss_disconnected_pipe = True, then a pipe should be able to + # be disconnected but still include head losses for a pipe (with v=0m/s in the pipe). + # Currently if heat_loss_disconnected_pipe = True then a pipe cannot be disconnected + # anymore. This was checked with PoC tutorial example while trying to use this + # functionality on a pipe connected to a heating demand. assert asset.asset_type == "Pipe" if len(asset.in_ports) == 1 and len(asset.out_ports) == 1: connected_type_in = self._port_to_esdl_component_type.get( @@ -256,6 +495,7 @@ def _is_disconnectable_pipe(self, asset: Asset) -> bool: "ates", "heat_exchanger", "heat_pump", + "cold_demand", } } @@ -343,52 +583,204 @@ def _set_electricity_current_nominal_and_max( pass def _get_connected_q_max(self, asset: Asset) -> float: - if asset.in_ports is None or asset.asset_type == "Electrolyzer": - connected_port = asset.out_ports[0].connectedTo[0] - q_max = self._port_to_q_max.get(connected_port, None) - if q_max is not None: - self._set_q_nominal(asset, q_max) - return q_max - else: - raise _RetryLaterException( - f"Could not determine max discharge for {asset.asset_type} '{asset.name}'" + if asset.in_ports is not None and asset.asset_type != "Electrolyzer": + for port in asset.in_ports: + convert_density_units = 1.0 + energy_reference_j_kg = 1.0 + if not isinstance(port.carrier, esdl.HeatCommodity): + convert_density_units = 1.0e3 # convert g/m3 to kg/m3 if needed + energy_reference_j_kg = get_energy_content(asset.name, port.carrier) + else: + # heat_value / rho * minimum_dT => [J/m3K] / [kg/m3] * 1.0 [K] => [J/kg] + energy_reference_j_kg = HEAT_STORAGE_M3_WATER_PER_DEGREE_CELCIUS / 988.0 + + connected_port = port.connectedTo[0] + q_max = ( + self._port_to_q_max.get(connected_port, None) + if self._port_to_q_max.get(connected_port, False) + else max([asset.attributes.get(key, -1) for key in self.__power_keys]) + / ( + # note rho -> gas/hydrogen g/m3, heat kg/m3 + get_density(asset.name, port.carrier) + * energy_reference_j_kg + / convert_density_units + ) ) - elif asset.out_ports is None: - connected_port = asset.in_ports[0].connectedTo[0] - q_max = self._port_to_q_max.get(connected_port, None) - if q_max is not None: - self._set_q_max(asset, q_max) - return q_max - else: - raise _RetryLaterException( - f"Could not determine max discharge for {asset.asset_type} '{asset.name}'" + if q_max is not None: + self._set_q_max(asset, q_max) + return q_max + else: + logger.error( + f"Tried to get the maximum flow for {asset.name}, however this was never " + f"set" + ) + elif asset.out_ports is not None: + for port in asset.out_ports: + convert_density_units = 1.0 + energy_reference_j_kg = 1.0 + if not isinstance(port.carrier, esdl.HeatCommodity): + convert_density_units = 1.0e3 # convert g/m3 to kg/m3 if needed + energy_reference_j_kg = get_energy_content(asset.name, port.carrier) + else: + # heat_value / rho * minimum_dT => [J/m3K] / [kg/m3] * 1.0 [K] => [J/kg] + energy_reference_j_kg = HEAT_STORAGE_M3_WATER_PER_DEGREE_CELCIUS / 988.0 + + connected_port = port.connectedTo[0] + q_max = ( + self._port_to_q_max.get(connected_port, None) + if self._port_to_q_max.get(connected_port, False) + else max([asset.attributes.get(key, -1) for key in self.__power_keys]) + / ( + # note rho -> gas/hydrogen g/m3, heat kg/m3 + get_density(asset.name, port.carrier) + * energy_reference_j_kg + / convert_density_units + ) ) + if q_max is not None: + self._set_q_max(asset, q_max) + return q_max + else: + logger.error( + f"Tried to get the maximum flow for {asset.name}, however this was never " + f"set" + ) + else: + logger.error( + f"Tried to get the maximum flow for {asset.name}, however this was never set" + ) def _get_connected_i_nominal_and_max(self, asset: Asset) -> Tuple[float, float]: - if asset.in_ports is None: + + if ( + asset.in_ports is not None + and asset.out_ports is not None + and len(asset.in_ports) == 1 + and len(asset.out_ports) == 1 + and isinstance(asset.in_ports[0].carrier, esdl.ElectricityCommodity) + and isinstance(asset.out_ports[0].carrier, esdl.ElectricityCommodity) + ): # Transformer connected_port = asset.out_ports[0].connectedTo[0] - i_max = self._port_to_i_max.get(connected_port, None) - i_nom = self._port_to_i_nominal.get(connected_port, None) - if i_max is not None: - self._set_electricity_current_nominal_and_max(asset, i_max, i_nom) - return i_max, i_nom + i_max_out = ( + self._port_to_i_max.get(connected_port, None) + if self._port_to_i_max.get(connected_port, False) + else max( + [ + asset.attributes.get(key, -1) / connected_port.carrier.voltage + for key in self.__power_keys + ] + ) + ) + i_nom_out = ( + self._port_to_i_nominal.get(connected_port, None) + if self._port_to_i_nominal.get(connected_port, False) + else max( + [ + asset.attributes.get(key, -1) / connected_port.carrier.voltage / 2.0 + for key in self.__power_keys + ] + ) + ) + connected_port = asset.in_ports[0].connectedTo[0] + i_max_in = ( + self._port_to_i_max.get(connected_port, None) + if self._port_to_i_max.get(connected_port, False) + else max( + [ + asset.attributes.get(key, -1) / connected_port.carrier.voltage + for key in self.__power_keys + ] + ) + ) + i_nom_in = ( + self._port_to_i_nominal.get(connected_port, None) + if self._port_to_i_nominal.get(connected_port, False) + else max( + [ + asset.attributes.get(key, -1) / connected_port.carrier.voltage / 2.0 + for key in self.__power_keys + ] + ) + ) + if i_nom_in > 0.0 and i_nom_out > 0.0: + self._port_to_i_nominal[asset.in_ports[0]] = i_nom_in + self._port_to_i_max[asset.in_ports[0]] = i_max_in + self._port_to_i_nominal[asset.out_ports[0]] = i_nom_out + self._port_to_i_max[asset.out_ports[0]] = i_max_out + return i_max_in, i_nom_in, i_max_out, i_nom_out else: - raise _RetryLaterException( + raise logger.error( f"Could not determine max and nominal current for {asset.asset_type}" " '{asset.name}'" ) - elif asset.out_ports is None or asset.asset_type == "Electrolyzer": - connected_port = asset.in_ports[0].connectedTo[0] - i_max = self._port_to_i_max.get(connected_port, None) - i_nom = self._port_to_i_nominal.get(connected_port, None) - if i_max is not None: + + elif asset.in_ports is None: + connected_port = asset.out_ports[0].connectedTo[0] + i_max = ( + self._port_to_i_max.get(connected_port, None) + if self._port_to_i_max.get(connected_port, False) + else max( + [ + asset.attributes.get(key, -1) / connected_port.carrier.voltage + for key in self.__power_keys + ] + ) + ) + i_nom = ( + self._port_to_i_nominal.get(connected_port, None) + if self._port_to_i_nominal.get(connected_port, False) + else max( + [ + asset.attributes.get(key, -1) / connected_port.carrier.voltage / 2.0 + for key in self.__power_keys + ] + ) + ) + if i_max > 0.0: self._set_electricity_current_nominal_and_max(asset, i_max, i_nom) return i_max, i_nom else: - raise _RetryLaterException( + raise logger.error( f"Could not determine max and nominal current for {asset.asset_type}" - f" '{asset.name}'" + " '{asset.name}'" ) + elif ( + asset.out_ports is None + or asset.asset_type == "Electrolyzer" + or asset.asset_type == "ElectricBoiler" + or asset.asset_type == "HeatPump" + ): + for port in asset.in_ports: + if isinstance(port.carrier, esdl.ElectricityCommodity): + connected_port = port.connectedTo[0] + i_max = ( + self._port_to_i_max.get(connected_port, None) + if self._port_to_i_max.get(connected_port, False) + else max( + [ + asset.attributes.get(key, -1) / connected_port.carrier.voltage + for key in self.__power_keys + ] + ) + ) + i_nom = ( + self._port_to_i_nominal.get(connected_port, None) + if self._port_to_i_nominal.get(connected_port, False) + else max( + [ + asset.attributes.get(key, -1) / connected_port.carrier.voltage / 2.0 + for key in self.__power_keys + ] + ) + ) + if i_max > 0.0: + self._set_electricity_current_nominal_and_max(asset, i_max, i_nom) + return i_max, i_nom + else: + raise logger.error( + f"Could not determine max and nominal current for {asset.asset_type}" + f" '{asset.name}'" + ) def _get_connected_q_nominal(self, asset: Asset) -> Union[float, Dict]: """ @@ -406,70 +798,190 @@ def _get_connected_q_nominal(self, asset: Asset) -> Union[float, Dict]: Either the connected nominal flow [m3/s] if it is only connected to one hydraulic system, otherwise a dict with the flow nominals of both the primary and secondary side. """ - if asset.in_ports is None: - connected_port = asset.out_ports[0].connectedTo[0] - q_nominal = self._port_to_q_nominal.get(connected_port, None) - if q_nominal is not None: - self._set_q_nominal(asset, q_nominal) - return q_nominal - else: - raise _RetryLaterException( - f"Could not determine nominal discharge for {asset.asset_type} '{asset.name}'" - ) - elif asset.out_ports is None: - connected_port = asset.in_ports[0].connectedTo[0] - q_nominal = self._port_to_q_nominal.get(connected_port, None) - if q_nominal is not None: - self._set_q_nominal(asset, q_nominal) - return q_nominal - else: - raise _RetryLaterException( - f"Could not determine nominal discharge for {asset.asset_type} '{asset.name}'" - ) - elif ( - len(asset.in_ports) == 1 + + if ( + asset.in_ports is not None + and asset.out_ports is not None + and len(asset.in_ports) == 1 and len(asset.out_ports) == 1 and asset.in_ports[0].carrier.id != asset.out_ports[0].carrier.id and isinstance(asset.in_ports[0].carrier, esdl.GasCommodity) and isinstance(asset.out_ports[0].carrier, esdl.GasCommodity) ): # Cater for gas substation - try: - connected_port = asset.in_ports[0].connectedTo[0] - q_nominal_in = self._port_to_q_nominal[connected_port] - except KeyError: - connected_port = asset.out_ports[0].connectedTo[0] - q_nominal_out = self._port_to_q_nominal.get(connected_port, None) - - try: - connected_port = asset.out_ports[0].connectedTo[0] - q_nominal_out = self._port_to_q_nominal[connected_port] - except KeyError: - connected_port = asset.in_ports[0].connectedTo[0] - q_nominal_in = self._port_to_q_nominal.get(connected_port, None) + connected_port = asset.in_ports[0].connectedTo[0] + q_nominal_in = ( + self._port_to_q_nominal.get(connected_port, None) + if self._port_to_q_nominal.get(connected_port, False) + else 0.0 + ) + connected_port = asset.out_ports[0].connectedTo[0] + q_nominal_out = ( + self._port_to_q_nominal.get(connected_port, None) + if self._port_to_q_nominal.get(connected_port, False) + else 0.0 + ) - if q_nominal_in is not None and q_nominal_out is not None: + if q_nominal_in > 0.0 and q_nominal_out > 0.0: self._port_to_q_nominal[asset.in_ports[0]] = q_nominal_in self._port_to_q_nominal[asset.out_ports[0]] = q_nominal_out return q_nominal_in, q_nominal_out - else: - raise _RetryLaterException( - f"Could not determine nominal discharge for {asset.asset_type} '{asset.name}'" - ) - elif len(asset.in_ports) == 1 and len(asset.out_ports) == 1: + elif ( + asset.in_ports is not None + and asset.out_ports is not None + and len(asset.in_ports) == 1 + and len(asset.out_ports) == 1 + ): + for port in [*asset.in_ports, *asset.out_ports]: + if isinstance(port.carrier, esdl.GasCommodity) or isinstance( + port.carrier, esdl.HeatCommodity + ): + convert_density_units = 1.0 + energy_reference_j_kg = 1.0 + if not isinstance(port.carrier, esdl.HeatCommodity): + convert_density_units = 1.0e3 # convert g/m3 to kg/m3 if needed + energy_reference_j_kg = get_energy_content(asset.name, port.carrier) + else: + # heat_value / rho * minimum_dT => [J/m3K] / [kg/m3] * 1.0 [K] => [J/kg] + energy_reference_j_kg = HEAT_STORAGE_M3_WATER_PER_DEGREE_CELCIUS / 988.0 + + connected_port = port.connectedTo[0] + q_nominal = ( + self._port_to_q_nominal.get(connected_port, None) + if self._port_to_q_nominal.get(connected_port, False) + else max([asset.attributes.get(key, -1) for key in self.__power_keys]) + / ( + # note rho -> gas/hydrogen g/m3, heat kg/m3 + get_density(asset.name, port.carrier) + * energy_reference_j_kg + / convert_density_units + ) + ) + if q_nominal is not None: + self._set_q_nominal(asset, q_nominal) + return q_nominal + elif asset.in_ports is not None and asset.out_ports is None and len(asset.in_ports) == 1: + for port in asset.in_ports: + if isinstance(port.carrier, esdl.GasCommodity) or isinstance( + port.carrier, esdl.HeatCommodity + ): + convert_density_units = 1.0 + energy_reference_j_kg = 1.0 + if not isinstance(port.carrier, esdl.HeatCommodity): + convert_density_units = 1.0e3 # convert g/m3 to kg/m3 if needed + energy_reference_j_kg = get_energy_content(asset.name, port.carrier) + else: + # heat_value / rho * minimum_dT => [J/m3K] / [kg/m3] * 1.0 [K] => [J/kg] + energy_reference_j_kg = HEAT_STORAGE_M3_WATER_PER_DEGREE_CELCIUS / 988.0 + + connected_port = port.connectedTo[0] + q_nominal = ( + self._port_to_q_nominal.get(connected_port, None) + if self._port_to_q_nominal.get(connected_port, False) + else max([asset.attributes.get(key, -1) for key in self.__power_keys]) + / ( + # note rho -> gas/hydrogen g/m3, heat kg/m3 + get_density(asset.name, port.carrier) + * energy_reference_j_kg + / convert_density_units + ) + ) + if q_nominal is not None: + self._set_q_nominal(asset, q_nominal) + return q_nominal + elif asset.out_ports is not None and asset.in_ports is None and len(asset.out_ports) == 1: + for port in asset.out_ports: + if isinstance(port.carrier, esdl.GasCommodity) or isinstance( + port.carrier, esdl.HeatCommodity + ): + convert_density_units = 1.0 + energy_reference_j_kg = 1.0 + if not isinstance(port.carrier, esdl.HeatCommodity): + convert_density_units = 1.0e3 # convert g/m3 to kg/m3 if needed + energy_reference_j_kg = get_energy_content(asset.name, port.carrier) + else: + # heat_value / rho * minimum_dT => [J/m3K] / [kg/m3] * 1.0 [K] => [J/kg] + energy_reference_j_kg = HEAT_STORAGE_M3_WATER_PER_DEGREE_CELCIUS / 988.0 + + connected_port = port.connectedTo[0] + q_nominal = ( + self._port_to_q_nominal.get(connected_port, None) + if self._port_to_q_nominal.get(connected_port, False) + else max([asset.attributes.get(key, -1) for key in self.__power_keys]) + / ( + # note rho -> gas/hydrogen g/m3, heat kg/m3 + get_density(asset.name, port.carrier) + * energy_reference_j_kg + / convert_density_units + ) + ) + if q_nominal is not None: + self._set_q_nominal(asset, q_nominal) + return q_nominal + elif len(asset.in_ports) == 2 and len(asset.out_ports) == 1: # for gas_boiler or e_boiler + q_nominals = {} try: - connected_port = asset.in_ports[0].connectedTo[0] - q_nominal = self._port_to_q_nominal[connected_port] + for port in asset.in_ports: + connected_port = port.connectedTo[0] + if isinstance(port.carrier, esdl.GasCommodity) or isinstance( + port.carrier, esdl.HeatCommodity + ): + nominal_string = "Q_nominal" + convert_density_units = 1.0 + energy_reference_j_kg = 1.0 + if isinstance(port.carrier, esdl.GasCommodity): + nominal_string += "_gas" + convert_density_units = 1.0e3 # convert g/m3 to kg/m3 if needed + energy_reference_j_kg = get_energy_content(asset.name, port.carrier) + elif isinstance(port.carrier, esdl.HeatCommodity): + # heat_value / rho * minimum_dT => [J/m3K] / [kg/m3] * 1.0 [K] => [J/kg] + energy_reference_j_kg = HEAT_STORAGE_M3_WATER_PER_DEGREE_CELCIUS / 988.0 + + if isinstance(connected_port.energyasset, esdl.Joint): + q_nominal = ( + self._port_to_q_nominal.get(connected_port, None) + if self._port_to_q_nominal.get(connected_port, False) + else max( + [asset.attributes.get(key, -1) for key in self.__power_keys] + ) + / ( + # note rho -> gas/hydrogen g/m3, heat kg/m3 + get_density(asset.name, port.carrier) + * energy_reference_j_kg + / convert_density_units + ) + ) + if q_nominal is not None: + q_nominals[nominal_string] = q_nominal + self._port_to_q_nominal[port] = q_nominals[nominal_string] + else: + q_nominals[nominal_string] = self._port_to_q_nominal[connected_port] + self._port_to_q_nominal[port] = q_nominals[nominal_string] + if q_nominals is None: + logger.error( + f"{asset.name} should have at least gas or heat specified on " + f"one of the in ports" + ) + exit(1) except KeyError: - connected_port = asset.out_ports[0].connectedTo[0] - q_nominal = self._port_to_q_nominal.get(connected_port, None) + if isinstance(asset.out_ports[0].carrier, esdl.GasCommodity): + connected_port = asset.out_ports[0].connectedTo[0] + q_nominals["Q_nominal"] = ( + self._port_to_q_nominal.get(connected_port, None) + if self._port_to_q_max.get(connected_port, False) + else max([asset.attributes.get(key, -1) for key in self.__power_keys]) + / ( + # note rho -> gas/hydrogen g/m3, heat kg/m3 + get_density(asset.name, port.carrier) + * get_energy_content(asset.name, port.carrier) + / 1.0e3 + ) + ) + else: + logger.error(f"{asset.name} should have a heat carrier on out port") - if q_nominal is not None: - self._set_q_nominal(asset, q_nominal) - return q_nominal - else: - raise _RetryLaterException( - f"Could not determine nominal discharge for {asset.asset_type} '{asset.name}'" - ) + if q_nominals["Q_nominal"] is not None: + self._port_to_q_nominal[asset.out_ports[0]] = q_nominals["Q_nominal"] + return q_nominals elif len(asset.in_ports) >= 2 and len(asset.out_ports) == 2: q_nominals = {} for p in asset.in_ports: @@ -485,19 +997,24 @@ def _get_connected_q_nominal(self, asset: Asset) -> Union[float, Dict]: q_nominal = self._port_to_q_nominal[connected_port] except KeyError: connected_port = out_port.connectedTo[0] - q_nominal = self._port_to_q_nominal.get(connected_port, None) + q_nominal = ( + self._port_to_q_nominal.get(connected_port, None) + if self._port_to_q_max.get(connected_port, False) + else max([asset.attributes.get(key, -1) for key in self.__power_keys]) + / ( + # note rho -> gas/hydrogen g/m3, heat kg/m3 + get_density(asset.name, p.carrier) + * (HEAT_STORAGE_M3_WATER_PER_DEGREE_CELCIUS / 988.0) + ) + ) if q_nominal is not None: self._port_to_q_nominal[p] = q_nominal self._port_to_q_nominal[out_port] = q_nominal - if "_ret" in p.carrier.name: + if "sec" in p.name.lower(): q_nominals["Secondary"] = {"Q_nominal": q_nominal} else: q_nominals["Primary"] = {"Q_nominal": q_nominal} - else: - raise _RetryLaterException( - f"Could not determine nominal discharge for {asset.asset_type} " - f"{asset.name}" - ) + return q_nominals def _get_cost_figure_modifiers(self, asset: Asset) -> Dict: @@ -544,6 +1061,8 @@ def _get_cost_figure_modifiers(self, asset: Asset) -> Dict: modifiers["installation_cost"] = self.get_installation_costs(asset) elif asset.asset_type == "GasDemand": modifiers["variable_operational_cost_coefficient"] = self.get_variable_opex_costs(asset) + elif asset.asset_type == "GasProducer": + modifiers["variable_operational_cost_coefficient"] = self.get_variable_opex_costs(asset) elif asset.asset_type == "Electrolyzer": modifiers["variable_operational_cost_coefficient"] = self.get_variable_opex_costs(asset) modifiers["fixed_operational_cost_coefficient"] = self.get_fixed_opex_costs(asset) @@ -576,9 +1095,11 @@ def _get_supply_return_temperatures(asset: Asset) -> Tuple[float, float]: Tuple with the supply and return temperature. """ - assert len(asset.in_ports) == 1 and len(asset.out_ports) == 1 + assert len(asset.in_ports) <= 2 and len(asset.out_ports) == 1 - in_carrier = asset.global_properties["carriers"][asset.in_ports[0].carrier.id] + for port in asset.in_ports: + if isinstance(port.carrier, esdl.HeatCommodity): + in_carrier = asset.global_properties["carriers"][port.carrier.id] out_carrier = asset.global_properties["carriers"][asset.out_ports[0].carrier.id] if in_carrier["id"] == out_carrier["id"]: @@ -633,7 +1154,7 @@ def _supply_return_temperature_modifiers(self, asset: Asset) -> MODIFIERS: dict with all the temperatures. """ - if len(asset.in_ports) == 1 and len(asset.out_ports) == 1: + if len(asset.in_ports) <= 2 and len(asset.out_ports) == 1: modifiers = self._get_supply_return_temperatures(asset) return modifiers elif len(asset.in_ports) >= 2 and len(asset.out_ports) == 2: @@ -663,10 +1184,27 @@ def _supply_return_temperature_modifiers(self, asset: Asset) -> MODIFIERS: f"primary and secondary ports ('prim' and 'sec') for the hydraulically " f"decoupled networks" ) - assert sec_supply_temperature > sec_return_temperature + assert sec_supply_temperature >= sec_return_temperature assert sec_return_temperature > 0.0 - assert prim_supply_temperature > prim_return_temperature + assert prim_supply_temperature >= prim_return_temperature assert prim_return_temperature > 0.0 + + if ( + sec_supply_temperature == sec_return_temperature + or prim_return_temperature == prim_supply_temperature + ): + asset_id = asset.id + get_potential_errors().add_potential_issue( + MesidoAssetIssueType.HEAT_EXCHANGER_TEMPERATURES, + asset_id, + f"Asset named {asset.name}: The temperature on the primary side " + f"supply side is {prim_supply_temperature} and on the return side is " + f"{prim_return_temperature} and on the secondary side the supply temperature " + f"is {sec_supply_temperature} and return temperature is " + f"{sec_return_temperature}. This would result in a bypass of the " + f"heatexchanger.", + ) + temperatures = { "Primary": { "T_supply": prim_supply_temperature, @@ -752,6 +1290,7 @@ def get_variable_opex_costs(self, asset: Asset) -> float: continue if per_unit != UnitEnum.WATTHOUR and asset.asset_type not in [ "GasDemand", + "GasProducer", "GasStorage", "Electrolyzer", ]: @@ -762,7 +1301,7 @@ def get_variable_opex_costs(self, asset: Asset) -> float: ) continue if ( - asset.asset_type in ["GasDemand", "GasStorage", "Electrolyzer"] + asset.asset_type in ["GasDemand", "GasProducer", "GasStorage", "Electrolyzer"] and per_unit != UnitEnum.GRAM ): logger.warning( diff --git a/src/rtctools_heat_network/esdl/common.py b/src/mesido/esdl/common.py similarity index 100% rename from src/rtctools_heat_network/esdl/common.py rename to src/mesido/esdl/common.py diff --git a/src/rtctools_heat_network/esdl/edr_pipe_class.py b/src/mesido/esdl/edr_pipe_class.py similarity index 95% rename from src/rtctools_heat_network/esdl/edr_pipe_class.py rename to src/mesido/esdl/edr_pipe_class.py index 1893207d4..54aa7620f 100644 --- a/src/rtctools_heat_network/esdl/edr_pipe_class.py +++ b/src/mesido/esdl/edr_pipe_class.py @@ -1,7 +1,7 @@ from dataclasses import dataclass -from rtctools_heat_network.esdl.asset_to_component_base import _AssetToComponentBase -from rtctools_heat_network.pipe_class import GasPipeClass, PipeClass +from mesido.esdl.asset_to_component_base import _AssetToComponentBase +from mesido.pipe_class import GasPipeClass, PipeClass @dataclass(frozen=True) diff --git a/src/mesido/esdl/esdl_additional_vars_mixin.py b/src/mesido/esdl/esdl_additional_vars_mixin.py new file mode 100644 index 000000000..80993c253 --- /dev/null +++ b/src/mesido/esdl/esdl_additional_vars_mixin.py @@ -0,0 +1,277 @@ +import logging +from typing import List + +import esdl + +from mesido.network_common import NetworkSettings +from mesido.pipe_class import PipeClass + +import numpy as np + +from rtctools.optimization.collocated_integrated_optimization_problem import ( + CollocatedIntegratedOptimizationProblem, +) + +logger = logging.getLogger("mesido") + + +class ESDLAdditionalVarsMixin(CollocatedIntegratedOptimizationProblem): + __temperature_options = {} + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + def read(self): + super().read() + parameters = self.parameters(0) + bounds = self.bounds() + + # ------------------------------------------------------------------------------------------ + # Limit available pipe classes + # TODO: cater for varying temperature when limiting pipe classes below + # Here we do a check between the available pipe classes and the demand profiles. This is to + # ensure that we don't have unneeded large amount of available pipe classes for pipes + # connected to smaller demands. + # TODO: add the same for electricity ones we have proper support for that in the ESDLMixin + if len(self.temperature_carriers().items()) == 0: + for asset, ( + connected_asset, + _orientation, + ) in self.energy_system_topology.demands.items(): + # TODO: add test case for gas once optional gas pipes are used + if asset in self.energy_system_components.get("gas_demand", []): + try: + max_demand_g_s = min( + max(self.get_timeseries(f"{asset}.target_gas_demand").values), + bounds[f"{asset}.Gas_demand_mass_flow"][1], + ) + except KeyError: + max_demand_g_s = bounds[f"{asset}.Gas_demand_mass_flow"][1] + is_there_always_mass_flow = False + try: + if min(self.get_timeseries(f"{asset}.target_gas_demand").values) > 0.0: + is_there_always_mass_flow = True + except KeyError: + is_there_always_mass_flow = False + + new_pcs = [] + found_pc_large_enough = False + for pc in self.gas_pipe_classes(connected_asset): + if not found_pc_large_enough: + new_pcs.append(pc) + if ( + new_pcs[-1].maximum_discharge + * self.parameters(0)[f"{connected_asset}.rho"] + >= max_demand_g_s + ): # m3/s * g/m3 = g/s + found_pc_large_enough = True + + self.remove_dn0(new_pcs, is_there_always_mass_flow) + self._override_gas_pipe_classes[connected_asset] = new_pcs + + if asset in self.energy_system_components.get("heat_demand", []): + try: + max_demand = min( + max(self.get_timeseries(f"{asset}.target_heat_demand").values), + bounds[f"{asset}.Heat_demand"][1], + ) + except KeyError: + max_demand = bounds[f"{asset}.Heat_demand"][1] + is_there_always_mass_flow = False + try: + if min(self.get_timeseries(f"{asset}.target_heat_demand").values) > 0.0: + is_there_always_mass_flow = True + except KeyError: + is_there_always_mass_flow = False + + max_demand *= 1.3 # 30% added for expected worst case heat losses + + new_pcs = [] + found_pc_large_enough = False + for pc in self.pipe_classes(connected_asset): + if not found_pc_large_enough: + new_pcs.append(pc) + if ( + new_pcs[-1].maximum_discharge + * parameters[f"{asset}.cp"] + * parameters[f"{asset}.rho"] + * (parameters[f"{asset}.T_supply"] - parameters[f"{asset}.T_return"]) + ) >= max_demand: + found_pc_large_enough = True + + self.remove_dn0(new_pcs, is_there_always_mass_flow) + self._override_pipe_classes[connected_asset] = new_pcs + + if not self.is_hot_pipe(self.hot_to_cold_pipe(connected_asset)): + self._override_pipe_classes[self.hot_to_cold_pipe(connected_asset)] = ( + new_pcs + ) + + # Here we do the same for sources as for the sources. + for asset, ( + connected_asset, + _orientation, + ) in self.energy_system_topology.sources.items(): + if asset in self.energy_system_components.get("gas_source", []): + try: + max_prod_g_s = min( + max(self.get_timeseries(f"{asset}.maximum_gas_source").values), + bounds[f"{asset}.Gas_source_mass_flow"][1], + ) + except KeyError: + max_prod_g_s = bounds[f"{asset}.Gas_source_mass_flow"][1] + new_pcs = [] + found_pc_large_enough = False + for pc in self.gas_pipe_classes(connected_asset): + if not found_pc_large_enough: + new_pcs.append(pc) + if ( + new_pcs[-1].maximum_discharge + * self.parameters(0)[f"{connected_asset}.rho"] + >= max_prod_g_s + ): + found_pc_large_enough = True + self._override_gas_pipe_classes[connected_asset] = new_pcs + if asset in self.energy_system_components.get("heat_source", []): + try: + max_prod = min( + max(self.get_timeseries(f"{asset}.maximum_heat_source").values), + bounds[f"{asset}.Heat_source"][1], + ) + except KeyError: + max_prod = bounds[f"{asset}.Heat_source"][1] + new_pcs = [] + found_pc_large_enough = False + for pc in self.pipe_classes(connected_asset): + if not found_pc_large_enough: + new_pcs.append(pc) + if ( + new_pcs[-1].maximum_discharge + * parameters[f"{asset}.cp"] + * parameters[f"{asset}.rho"] + * (parameters[f"{asset}.T_supply"] - parameters[f"{asset}.T_return"]) + ) >= max_prod: + found_pc_large_enough = True + self._override_pipe_classes[connected_asset] = new_pcs + if not self.is_hot_pipe(self.hot_to_cold_pipe(connected_asset)): + self._override_pipe_classes[self.hot_to_cold_pipe(connected_asset)] = ( + new_pcs + ) + else: + logger.warning("Limiting pipe classes do not cater for varying temperature yet") + # ------------------------------------------------------------------------------------------ + + for asset in [ + *self.energy_system_components.get("heat_source", []), + *self.energy_system_components.get("ates", []), + *self.energy_system_components.get("heat_buffer", []), + *self.energy_system_components.get("heat_pump", []), + ]: + esdl_asset = self.esdl_assets[self.esdl_asset_name_to_id_map[asset]] + for constraint in esdl_asset.attributes.get("constraint", []): + if constraint.name == "setpointconstraint": + time_unit = constraint.range.profileQuantityAndUnit.perTimeUnit + if time_unit == esdl.TimeUnitEnum.HOUR: + time_hours = 1 + elif time_unit == esdl.TimeUnitEnum.DAY: + time_hours = 24 + elif time_unit == esdl.TimeUnitEnum.WEEK: + time_hours = 24 * 7 + elif time_unit == esdl.TimeUnitEnum.MOTH: + time_hours = 24 * 7 * 30 + elif time_unit == esdl.TimeUnitEnum.DAY: + time_hours = 365 * 24 + else: + logger.error( + f"{asset} has a setpoint constaint specified with unknown" + f"per time unit" + ) + + asset_setpoints = {asset: (time_hours, constraint.range.maxValue)} + + self._timed_setpoints.update(asset_setpoints) + + def remove_dn0(self, new_pcs: List[PipeClass], is_there_always_mass_flow: bool) -> None: + """Remove pipe DN0 from the available pipe list, if there is always flow required""" + # TODO: Bug to be resolved. Currently the solution is infeasible when only + # 1 pipe class is available, but it should be able to working. + # Then remove the need for having 2 pipes classes available in new_pcs. + if is_there_always_mass_flow and len(new_pcs) > 2 and new_pcs[0].maximum_discharge == 0.0: + new_pcs.remove(new_pcs[0]) + + def pipe_classes(self, p): + return self._override_pipe_classes.get(p, []) + + def gas_pipe_classes(self, p): + return self._override_gas_pipe_classes.get(p, []) + + def esdl_heat_model_options(self): + """Overwrites the fraction of the minimum tank volume""" + options = super().esdl_heat_model_options() + options["min_fraction_tank_volume"] = 0.0 + return options + + def temperature_carriers(self): + return self.esdl_carriers_typed(type=[str(NetworkSettings.NETWORK_TYPE_HEAT).lower()]) + + def electricity_carriers(self): + return self.esdl_carriers_typed( + type=[str(NetworkSettings.NETWORK_TYPE_ELECTRICITY).lower()] + ) + + def gas_carriers(self): + return self.esdl_carriers_typed( + type=[ + str(NetworkSettings.NETWORK_TYPE_GAS).lower(), + str(NetworkSettings.NETWORK_TYPE_HYDROGEN).lower(), + ] + ) + + def temperature_regimes(self, carrier): + temperature_options = [] + temperature_step = 2.5 + + try: + temperature_options = self.__temperature_options[carrier] + except KeyError: + for asset in [ + *self.energy_system_components.get("heat_source", []), + *self.energy_system_components.get("ates", []), + *self.energy_system_components.get("heat_buffer", []), + *self.energy_system_components.get("heat_pump", []), + *self.energy_system_components.get("heat_exchanger", []), + *self.energy_system_components.get("heat_demand", []), + ]: + esdl_asset = self.esdl_assets[self.esdl_asset_name_to_id_map[asset]] + parameters = self.parameters(0) + for i in range(len(esdl_asset.attributes["constraint"].items)): + constraint = esdl_asset.attributes["constraint"].items[i] + if ( + constraint.name == "supply_temperature" + and carrier == parameters[f"{asset}.T_supply_id"] + ) or ( + constraint.name == "return_temperature" + and carrier == parameters[f"{asset}.T_return_id"] + ): + try: + lb = self.__temperature_options[carrier][0] + ub = self.__temperature_options[carrier][-1] + lb = constraint.range.minValue if constraint.range.minValue > lb else lb + ub = constraint.range.maxValue if constraint.range.maxValue < ub else ub + except KeyError: + lb = constraint.range.minValue + ub = constraint.range.maxValue + n_options = round((ub - lb) / temperature_step) + temperature_options = np.linspace(lb, ub, n_options + 1) + if ( + constraint.range.profileQuantityAndUnit.unit + != esdl.UnitEnum.DEGREES_CELSIUS + ): + RuntimeError( + f"{asset} has a temperature constraint with wrong unit " + f"{constraint.range.profileQuantityAndUnit.unit}, should " + f"always be in degrees celcius." + ) + self.__temperature_options[carrier] = temperature_options + + return temperature_options diff --git a/src/mesido/esdl/esdl_heat_model.py b/src/mesido/esdl/esdl_heat_model.py new file mode 100644 index 000000000..4db2bbf5c --- /dev/null +++ b/src/mesido/esdl/esdl_heat_model.py @@ -0,0 +1,2687 @@ +import ast +import inspect +import logging +import math +from typing import Dict, Tuple, Type, Union + +import esdl + +from mesido.esdl.asset_to_component_base import ( + MODIFIERS, + _AssetToComponentBase, + get_density, + get_energy_content, +) +from mesido.esdl.common import Asset +from mesido.esdl.esdl_model_base import _ESDLModelBase +from mesido.potential_errors import MesidoAssetIssueType, get_potential_errors +from mesido.pycml.component_library.milp import ( + ATES, + AirWaterHeatPump, + AirWaterHeatPumpElec, + Airco, + CheckValve, + ColdDemand, + Compressor, + ControlValve, + ElecBoiler, + ElectricityCable, + ElectricityDemand, + ElectricityNode, + ElectricitySource, + ElectricityStorage, + Electrolyzer, + GasBoiler, + GasDemand, + GasNode, + GasPipe, + GasSource, + GasSubstation, + GasTankStorage, + GeothermalSource, + HeatBuffer, + HeatDemand, + HeatExchanger, + HeatPipe, + HeatPump, + HeatPumpElec, + HeatSource, + LowTemperatureATES, + Node, + Pump, + SolarPV, + Transformer, + WindPark, +) + +from scipy.optimize import fsolve + +logger = logging.getLogger("mesido") + + +class _ESDLInputException(Exception): + pass + + +def docs_esdl_modifiers(class__): + modifiers_dict = {} + input_dict = {} + + def extract_asset_info(bod): + if isinstance(bod.value, ast.Subscript): + if isinstance(bod.value.value, ast.Attribute): + if ( + bod.value.value.attr == "attributes" + and bod.value.value.value.id == "asset" + and isinstance(bod.targets[0], ast.Name) + ): + input_dict[node.name][ + bod.targets[0].id + ] = f"{bod.targets[0].id}: asset.attributes[{bod.value.slice.value}]" + + ast_of_init: ast.Module = ast.parse(inspect.getsource(class__)) + for node in ast.walk(ast_of_init): + if isinstance(node, ast.FunctionDef) and "convert_" in node.name: + modifiers_dict[node.name] = [] + input_dict[node.name] = {} + for bod in node.body: + if isinstance(bod, ast.Assign): + if isinstance(bod.targets[0], ast.Name) and bod.targets[0].id == "modifiers": + for key in bod.value.keywords: + if isinstance(key.arg, str): + modifiers_dict[node.name].append(key.arg) + elif ( + key.arg is None + and isinstance(key.value, ast.Call) + and isinstance(key.value.func, ast.Attribute) + ): + modifiers_dict[node.name].append(key.value.func.attr) + else: + extract_asset_info(bod) + + func = getattr(class__, node.name) + if len(modifiers_dict[node.name]) > 0: + line_with_hook = next( + ( + line + for line in func.__doc__.splitlines() + if "{" "automatically_add_modifiers_here}" in line + ), + None, + ) + if line_with_hook is None: + indent = "" + else: + format_modifiers_dict = [f"* {mod}" for mod in modifiers_dict[node.name]] + (indent, _) = line_with_hook.split("{automatically_add_modifiers_here}") + func.__doc__ = func.__doc__.replace( + "{automatically_add_modifiers_here}", + f"\n{indent}".join(format_modifiers_dict), + ) + + # TODO: the input dictionary is still needed in the documentation + return class__ + + +@docs_esdl_modifiers +class AssetToHeatComponent(_AssetToComponentBase): + """ + This class is used for the converting logic from the esdl assets with their properties to pycml + objects and set their respective properties. + + """ + + def __init__( + self, + *args, + v_nominal=1.0, + v_max=5.0, + rho=988.0, + cp=4200.0, + min_fraction_tank_volume=0.05, + v_max_gas=15.0, + **kwargs, + ): + super().__init__(*args, **kwargs) + + self.v_nominal = v_nominal + self.v_max = v_max + self.rho = rho + self.cp = cp + self.v_max_gas = v_max_gas + self.min_fraction_tank_volume = min_fraction_tank_volume + if "primary_port_name_convention" in kwargs.keys(): + self.primary_port_name_convention = kwargs["primary_port_name_convention"] + if "secondary_port_name_convention" in kwargs.keys(): + self.secondary_port_name_convention = kwargs["secondary_port_name_convention"] + + @property + def _rho_cp_modifiers(self) -> Dict: + """ + For giving the density, rho, in kg/m3 and specic milp, cp, in J/(K*kg) + + Returns: + rho and cp + """ + return dict(rho=self.rho, cp=self.cp) + + def get_asset_attribute_value( + self, + asset: Asset, + attribute_name: str, + default_value: float, + min_value: float, + max_value: float, + ) -> float: + """ + Get the value of the specified attribute for the given asset. + + Args: + asset: The asset to retrieve the attribute value for. + attribute_name: The name of the attribute to retrieve. + default_value: The default value to use if the attribute is not present. + min_value: The minimum value for the attribute. + max_value: The maximum value for the attribute. + Returns: + The value of the specified attribute for the given asset. + Raises: + ValueError: If the attribute value is not within the specified range. + """ + if attribute_name == "discountRate": + attribute_value = ( + asset.attributes["costInformation"].discountRate.value + if asset.attributes["costInformation"] + and asset.attributes["costInformation"].discountRate is not None + and asset.attributes["costInformation"].discountRate.value is not None + else default_value + ) + else: + attribute_value = ( + asset.attributes[attribute_name] + if asset.attributes[attribute_name] and asset.attributes[attribute_name] != 0 + else default_value + ) + self.validate_attribute_input( + # NOTE: this validation happens after assigning default values + # discountRate and technicalLife need to be included in input files of tests + # before this input validation can be relocated earlier in this function + asset.name, + attribute_name, + attribute_value, + min_value, + max_value, + ) + return attribute_value + + def validate_attribute_input( + self, + asset_name: str, + attribute_name: str, + input_value: float, + min_value: float, + max_value: float, + ) -> None: + """ + Validates if the input value is within the specified range. + Args: + asset_name (str): The name of the asset. + attribute_name (str): The name of the attribute. + input_value (float): The value to be validated. + min_value (float): The minimum value of the range. + max_value (float): The maximum value of the range. + Raises: + ValueError: If the input value is not within the specified range. + """ + if input_value < min_value or input_value > max_value: + warning_msg = ( + f"Input value {input_value} of attribute {attribute_name} " + f"is not within range ({min_value}, {max_value}) for asset {asset_name}." + ) + logger.warning(warning_msg) + + def convert_heat_buffer(self, asset: Asset) -> Tuple[Type[HeatBuffer], MODIFIERS]: + """ + This function converts the buffer object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + + - Setting the dimensions of the buffer needed for heat loss computation. Currently, + assume cylinder with height equal to radius. + - setting a minimum fill level and minimum asscociated milp + - Setting a maximum stored energy based on the size. + - Setting a cap on the thermal power. + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Required ESDL fields: + - volume/capacity + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - max(Dis)ChargeRate + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + + Parameters: + asset : The asset object with its properties. + + Returns: + Buffer class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type == "HeatStorage" + + temperature_modifiers = self._supply_return_temperature_modifiers(asset) + + supply_temperature = temperature_modifiers["T_supply"] + return_temperature = temperature_modifiers["T_return"] + + # Assume that: + # - the capacity is the relative milp that can be stored in the buffer; + # - the tanks are always at least `min_fraction_tank_volume` full; + # - same height as radius to compute dimensions. + if asset.attributes["capacity"] and asset.attributes["volume"]: + logger.warning( + f"{asset.asset_type} '{asset.name}' has both capacity and volume specified. " + f"Volume with value of {asset.attributes['volume']} m3 will be used." + ) + + capacity = 0.0 + if asset.attributes["volume"]: + capacity = ( + asset.attributes["volume"] + * self.rho + * self.cp + * (supply_temperature - return_temperature) + ) + elif asset.attributes["capacity"]: + capacity = asset.attributes["capacity"] + else: + logger.error( + f"{asset.asset_type} '{asset.name}' has both not capacity and volume specified. " + f"Please specify one of the two" + ) + + assert capacity > 0.0 + min_fraction_tank_volume = self.min_fraction_tank_volume + if self.get_state(asset) == 0 or self.get_state(asset) == 2: + min_fraction_tank_volume = 0.0 + # We assume that the height equals the radius of the buffer. + r = ( + capacity + * (1 + min_fraction_tank_volume) + / (self.rho * self.cp * (supply_temperature - return_temperature) * math.pi) + ) ** (1.0 / 3.0) + + min_heat = capacity * min_fraction_tank_volume + max_heat = capacity * (1 + min_fraction_tank_volume) + assert max_heat > 0.0 + # default is set to 10MW + + hfr_charge_max = ( + asset.attributes.get("maxChargeRate") + if asset.attributes.get("maxChargeRate") + else 10.0e6 + ) + hfr_discharge_max = ( + asset.attributes.get("maxDischargeRate") + if asset.attributes.get("maxDischargeRate") + else 10.0e6 + ) + + q_nominal = self._get_connected_q_nominal(asset) + + modifiers = dict( + Q_nominal=q_nominal, + height=r, + radius=r, + heat_transfer_coeff=1.0, + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + state=self.get_state(asset), + min_fraction_tank_volume=min_fraction_tank_volume, + Stored_heat=dict(min=min_heat, max=max_heat), + Heat_buffer=dict(min=-hfr_discharge_max, max=hfr_charge_max), + Heat_flow=dict(min=-hfr_discharge_max, max=hfr_charge_max, nominal=hfr_charge_max), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + init_Heat=min_heat, + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + **self._get_cost_figure_modifiers(asset), + ) + + return HeatBuffer, modifiers + + def convert_heat_demand(self, asset: Asset) -> Tuple[Type[HeatDemand], MODIFIERS]: + """ + This function converts the demand object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + + - Setting a cap on the thermal power. + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - power + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + Demand class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"GenericConsumer", "HeatingDemand", "Losses"} + + max_demand = asset.attributes["power"] if asset.attributes["power"] else math.inf + + q_nominal = self._get_connected_q_nominal(asset) + + modifiers = dict( + Q_nominal=q_nominal, + Heat_demand=dict(max=max_demand, nominal=max_demand / 2.0), + Heat_flow=dict(max=max_demand, nominal=max_demand / 2.0), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + state=self.get_state(asset), + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + **self._get_cost_figure_modifiers(asset), + ) + + return HeatDemand, modifiers + + def convert_airco(self, asset: Asset) -> Tuple[Type[Airco], MODIFIERS]: + """ + This function converts the airco object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + + - Setting a cap on the thermal power. + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Parameters: + asset : The asset object with its properties. + + Returns: + Demand class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"Airco"} + + max_ = asset.attributes["power"] if asset.attributes["power"] else math.inf + + q_nominal = self._get_connected_q_nominal(asset) + + modifiers = dict( + Q_nominal=q_nominal, + Heat_airco=dict(max=max_, nominal=max_ / 2.0), + Heat_flow=dict(max=max_, nominal=max_ / 2.0), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + state=self.get_state(asset), + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + **self._get_cost_figure_modifiers(asset), + ) + + return Airco, modifiers + + def convert_cold_demand(self, asset: Asset) -> Tuple[Type[ColdDemand], MODIFIERS]: + """ + This function converts the demand object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + - Setting a cap on the thermal power. + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Parameters: + asset : The asset object with its properties. + Returns: + Demand class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"CoolingDemand"} + + max_demand = asset.attributes["power"] if asset.attributes["power"] else math.inf + + q_nominal = self._get_connected_q_nominal(asset) + + modifiers = dict( + Q_nominal=q_nominal, + Cold_demand=dict(min=0.0, max=max_demand, nominal=max_demand / 2.0), + Heat_flow=dict(min=0.0, max=max_demand, nominal=max_demand / 2.0), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + state=self.get_state(asset), + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + **self._get_cost_figure_modifiers(asset), + ) + + return ColdDemand, modifiers + + def convert_node(self, asset: Asset) -> Tuple[Type[Node], MODIFIERS]: + """ + This function converts the node object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + + - Setting the amount of connections + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with (note only one inport and one outport): + - xsi:type + - id + - name + - connectedTo (allowed to have multiple connections) + - carrier with temperature specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + Node class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type == "Joint" + + sum_in = 0 + sum_out = 0 + + node_carrier = None + for x in asset.attributes["port"].items: + if node_carrier is None: + node_carrier = x.carrier.name + else: + if node_carrier != x.carrier.name: + raise _ESDLInputException( + f"{asset.name} has multiple carriers mixing which is not allowed. " + f"Only one carrier (carrier couple) allowed in hydraulicly " + f"coupled system" + ) + if isinstance(x, esdl.esdl.InPort): + sum_in += len(x.connectedTo) + if isinstance(x, esdl.esdl.OutPort): + sum_out += len(x.connectedTo) + + modifiers = dict( + n=sum_in + sum_out, + state=self.get_state(asset), + ) + + if isinstance(asset.in_ports[0].carrier, esdl.esdl.GasCommodity) or isinstance( + asset.out_ports[0].carrier, esdl.esdl.GasCommodity + ): + return GasNode, modifiers + + return Node, modifiers + + def convert_pipe(self, asset: Asset) -> Tuple[Union[Type[HeatPipe], Type[GasPipe]], MODIFIERS]: + """ + This function converts the pipe object in esdl to a set of modifiers that can be used in + a pycml object. Most important, it checks whether it should be converted to a gas or heat + pipe based on the connected commodity. + :param asset: The asset object with its properties. + :return: + """ + + assert asset.asset_type == "Pipe" + + if isinstance(asset.in_ports[0].carrier, esdl.esdl.GasCommodity): + return self.convert_gas_pipe(asset) + elif isinstance(asset.in_ports[0].carrier, esdl.esdl.HeatCommodity): + return self.convert_heat_pipe(asset) + else: + logger.error( + f"{asset.name} is of type {asset.asset_type} but is connected with a commodity of " + f"type {str(type(asset.in_ports[0].carrier))}, while only the commodities Heat and " + f"Gas are allowed" + ) + + def convert_gas_pipe( + self, asset: Asset + ) -> Tuple[Union[Type[HeatPipe], Type[GasPipe]], MODIFIERS]: + """ + This function converts the pipe object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + + - Setting the dimensions of the pipe needed for head loss computation. + - setting if a pipe is disconnecteable for the optimization. + - Setting the state (enabled, disabled, optional) + - Setting the relevant pressure. + - Setting the relevant cost figures. + + Required ESDL fields: + - Diameter/inner_diameter [m] + - length [m] + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with (note only one inport and one outport): + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + Pipe class with modifiers: + {automatically_add_modifiers_here} + """ + + length = asset.attributes["length"] + if length < 25.0: + length = 25.0 + logger.warning( + f"{asset.name} was shorter then the minimum length, thus is set to " + f"{length} meter" + ) + + id_mapping = asset.global_properties["carriers"][asset.in_ports[0].carrier.id][ + "id_number_mapping" + ] + (diameter, wall_roughness) = self._gas_pipe_get_diameter_and_roughness(asset) + q_nominal = math.pi * diameter**2 / 4.0 * self.v_max_gas / 2.0 + self._set_q_nominal(asset, q_nominal) + q_max = math.pi * diameter**2 / 4.0 * self.v_max_gas + self._set_q_max(asset, q_max) + pressure = asset.in_ports[0].carrier.pressure * 1.0e5 + density = get_density(asset.name, asset.in_ports[0].carrier) + bounds_nominals = dict( + Q=dict(min=-q_max, max=q_max, nominal=q_nominal), + mass_flow=dict(min=-q_max * density, max=q_max * density, nominal=q_nominal * density), + Hydraulic_power=dict(nominal=q_nominal * pressure), + ) + modifiers = dict( + id_mapping_carrier=id_mapping, + length=length, + density=density, + diameter=diameter, + pressure=pressure, + # disconnectable=self._is_disconnectable_pipe(asset), + # TODO: disconnectable option for gaspipes needs to be added. + GasIn=bounds_nominals, + GasOut=bounds_nominals, + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + + return GasPipe, modifiers + + def convert_heat_pipe( + self, asset: Asset + ) -> Tuple[Union[Type[HeatPipe], Type[GasPipe]], MODIFIERS]: + """ + This function converts the pipe object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + + - Setting the dimensions of the pipe needed for milp loss computation. Currently, + assume cylinder with height equal to radius. + - setting if a pipe is disconnecteable for the optimization. + - Setting the isolative properties of the pipe. + - Setting a cap on the thermal power. + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Required ESDL fields: + - Diameter/inner_diameter [m] + - length [m] + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with (note only one inport and one outport): + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - Material (for insulation) + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + Pipe class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type == "Pipe" + + length = asset.attributes["length"] + if length < 25.0: + length = 25.0 + logger.warning( + f"{asset.name} was shorter then the minimum length, thus is set to " + f"{length} meter" + ) + + ( + diameter, + insulation_thicknesses, + conductivies_insulation, + ) = self._pipe_get_diameter_and_insulation(asset) + + temperature_modifiers = self._supply_return_temperature_modifiers(asset) + + temperature = temperature_modifiers["temperature"] + + # Compute the maximum milp flow based on an assumed maximum velocity + area = math.pi * diameter**2 / 4.0 + q_max = area * self.v_max + q_nominal = area * self.v_nominal + + self._set_q_nominal(asset, q_nominal) + + # TODO: This might be an underestimation. We need to add the total + # milp losses in the system to get a proper upper bound. Maybe move + # calculation of Heat bounds to the HeatMixin? + hfr_max = 2.0 * ( + self.rho * self.cp * q_max * temperature + ) # TODO: are there any physical implications of using this bound + + assert hfr_max > 0.0 + + modifiers = dict( + Q_nominal=q_nominal, + length=length, + diameter=diameter, + disconnectable=self._is_disconnectable_pipe(asset), + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + HeatIn=dict( + Heat=dict(min=-hfr_max, max=hfr_max), + Q=dict(min=-q_max, max=q_max), + Hydraulic_power=dict(nominal=q_nominal * 16.0e5), + ), + HeatOut=dict( + Heat=dict(min=-hfr_max, max=hfr_max), + Q=dict(min=-q_max, max=q_max), + Hydraulic_power=dict(nominal=q_nominal * 16.0e5), + ), + Heat_flow=dict(min=-hfr_max, max=hfr_max, nominal=hfr_max), + insulation_thickness=insulation_thicknesses, + conductivity_insulation=conductivies_insulation, + state=self.get_state(asset), + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + **self._get_cost_figure_modifiers(asset), + ) + if "T_ground" in asset.attributes.keys(): + modifiers["T_ground"] = asset.attributes["T_ground"] + + return HeatPipe, modifiers + + def convert_pump(self, asset: Asset) -> Tuple[Type[Pump], MODIFIERS]: + """ + This function converts the pump object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with (note only one inport and one outport): + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + Pump class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type == "Pump" + + q_nominal = self._get_connected_q_nominal(asset) + + modifiers = dict( + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + Q_nominal=self._get_connected_q_nominal(asset), + state=self.get_state(asset), + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + ) + + return Pump, modifiers + + def convert_generic_conversion( + self, asset: Asset + ) -> Tuple[Union[Type[Transformer], Type[HeatExchanger]], MODIFIERS]: + """ + This function determines the type to which the generic conversion should be changed, based + on the connected commodities and calls the required conversion function. + + Parameters: + asset: The asset object with its properties. + + Returns: + Transformer class or HeatExchanger class + """ + + assert asset.asset_type in { + "GenericConversion", + } + + if isinstance(asset.in_ports[0].carrier, esdl.ElectricityCommodity) and isinstance( + asset.out_ports[0].carrier, esdl.ElectricityCommodity + ): + return self.convert_transformer(asset) + elif isinstance(asset.in_ports[0].carrier, esdl.HeatCommodity) and isinstance( + asset.out_ports[0].carrier, esdl.HeatCommodity + ): + return self.convert_heat_exchanger(asset) + else: + logger.error( + f"{asset.name} is of type {asset.asset_type} which is currently only " + f"supported as a heat exchanger or an electric transformer, thus either " + f"heat commodities or electricity commodities need to be connected to the " + f"ports. Currently the connected commodities are of type, " + f"{str(type(asset.in_ports[0].carrier))} and " + f"{str(type(asset.out_ports[0].carrier))}" + ) + + def convert_heat_exchanger(self, asset: Asset) -> Tuple[Type[HeatExchanger], MODIFIERS]: + """ + This function converts the Heat Exchanger object in esdl to a set of modifiers that can be + used in a pycml object. Most important: + + - Setting the thermal power transfer efficiency. + - Setting a caps on the thermal power on both the primary and secondary side. + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures (also checked for making sense physically). + - Setting the relevant cost figures. + + Required ESDL fields: + - heatTransferCoefficient/power + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - 2 InPorts and 2 OutPorts with: + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - efficiency + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + HeatExchanger class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in { + "GenericConversion", + "HeatExchange", + } + + params_t = self._supply_return_temperature_modifiers(asset) + params_q = self._get_connected_q_nominal(asset) + params = {} + + if params_t["Primary"]["T_supply"] < params_t["Secondary"]["T_supply"]: + get_potential_errors().add_potential_issue( + MesidoAssetIssueType.HEAT_EXCHANGER_TEMPERATURES, + asset.id, + f"Asset named {asset.name}: The supply temperature on the primary side " + f"of the heat exchanger ({params_t['Primary']['T_supply']}°C) should be larger " + f"than the supply temperature on the secondary side " + f"({params_t['Secondary']['T_supply']}°C), as the heat exchanger can only " + f"transfer heat from primary to secondary.", + ) + if params_t["Primary"]["T_return"] < params_t["Secondary"]["T_return"]: + get_potential_errors().add_potential_issue( + MesidoAssetIssueType.HEAT_EXCHANGER_TEMPERATURES, + asset.id, + f"Asset named {asset.name}: The return temperature on the primary side " + f"of the heat exchanger ({params_t['Primary']['T_return']}°C) should be larger " + f"than the return temperature on the secondary side " + f"({params_t['Secondary']['T_return']}°C), as the heat exchanger can only " + f"transfer heat from primary to secondary.", + ) + + if asset.asset_type == "GenericConversion": + max_power = asset.attributes["power"] if asset.attributes["power"] else math.inf + else: + # TODO: Current max_power estimation is not very accurate, a more physics based + # estimation should be implemented, maybe using other ESDL attributs. + max_power = ( + asset.attributes["heatTransferCoefficient"] + * (params_t["Primary"]["T_supply"] - params_t["Secondary"]["T_return"]) + / 2.0 + ) + if max_power == 0.0: + max_power = ( + asset.attributes["capacity"] if asset.attributes["capacity"] else math.inf + ) + # This default delta temperature is used when on the primary or secondary side the + # temperature difference is 0.0. It is set to 10.0 to ensure that maximum/nominal + # flowrates and heat transport are set at realistic values. + default_dt = 10.0 + dt_prim = params_t["Primary"]["T_supply"] - params_t["Primary"]["T_return"] + dt_prim = dt_prim if dt_prim > 0.0 else default_dt + params_t["Primary"]["dT"] = dt_prim + max_heat_transport = params_t["Primary"]["T_supply"] * max_power / (dt_prim) + + prim_heat = dict( + HeatIn=dict( + Heat=dict(min=-max_heat_transport, max=max_heat_transport, nominal=max_power / 2.0), + Hydraulic_power=dict(nominal=params_q["Primary"]["Q_nominal"] * 16.0e5), + ), + HeatOut=dict( + Heat=dict(min=-max_heat_transport, max=max_heat_transport, nominal=max_power / 2.0), + Hydraulic_power=dict(nominal=params_q["Primary"]["Q_nominal"] * 16.0e5), + ), + Q_nominal=max_power / (2 * self.rho * self.cp * (dt_prim)), + ) + + dt_sec = params_t["Secondary"]["T_supply"] - params_t["Secondary"]["T_return"] + dt_sec = dt_sec if dt_sec > 0.0 else default_dt + params_t["Secondary"]["dT"] = dt_sec + sec_heat = dict( + HeatIn=dict( + Heat=dict(min=-max_heat_transport, max=max_heat_transport, nominal=max_power / 2.0), + Hydraulic_power=dict(nominal=params_q["Secondary"]["Q_nominal"] * 16.0e5), + ), + HeatOut=dict( + Heat=dict(min=-max_heat_transport, max=max_heat_transport, nominal=max_power / 2.0), + Hydraulic_power=dict(nominal=params_q["Secondary"]["Q_nominal"] * 16.0e5), + ), + Q_nominal=max_power / (2 * self.cp * self.rho * (dt_sec)), + ) + params["Primary"] = {**params_t["Primary"], **params_q["Primary"], **prim_heat} + params["Secondary"] = { + **params_t["Secondary"], + **params_q["Secondary"], + **sec_heat, + } + + if not asset.attributes["efficiency"]: + efficiency = 1.0 + else: + efficiency = asset.attributes["efficiency"] + + modifiers = dict( + efficiency=efficiency, + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + nominal=max_power / 2.0, + Primary_heat=dict(min=0.0, max=max_power, nominal=max_power / 2.0), + Secondary_heat=dict(min=0.0, max=max_power, nominal=max_power / 2.0), + Heat_flow=dict(min=0.0, max=max_power, nominal=max_power / 2.0), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + **params, + ) + return HeatExchanger, modifiers + + def convert_heat_pump( + self, asset: Asset + ) -> Tuple[Union[Type[HeatPump], Type[HeatSource], Type[AirWaterHeatPumpElec]], MODIFIERS]: + """ + This function converts the HeatPump object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + + - Setting the COP of the heatpump + - Setting the cap on the electrical power. + - Setting a caps on the thermal power on both the primary and secondary side. + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Required ESDL fields: + - power + - COP + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - 2 InPorts and 2 OutPorts with: + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - efficiency + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + HeatPump class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in { + "HeatPump", + } + + # In this case we only have the secondary side ports, here we assume a air-water HP + if len(asset.in_ports) == 1 and len(asset.out_ports) == 1: + # TODO: the power filled in at the heatpmp should always be the electric power, thus, + # the max heat supply should be power*cop + _, modifiers = self.convert_heat_source(asset) + return AirWaterHeatPump, modifiers + # In this case we only have the secondary side ports, here we assume a air-water HP elec + if len(asset.in_ports) == 2 and len(asset.out_ports) == 1: + _, modifiers = self.convert_air_water_heat_pump_elec(asset) + return AirWaterHeatPumpElec, modifiers + + if not asset.attributes["COP"]: + raise _ESDLInputException( + f"{asset.name} has no COP specified, this is required for the model" + ) + else: + cop = asset.attributes["COP"] + + if not asset.attributes["power"]: + raise _ESDLInputException(f"{asset.name} has no power specified") + else: + power_secondary = asset.attributes["power"] + power_electrical = power_secondary / cop + + params_t = self._supply_return_temperature_modifiers(asset) + params_q = self._get_connected_q_nominal(asset) + prim_heat = dict( + HeatIn=dict(Hydraulic_power=dict(nominal=params_q["Primary"]["Q_nominal"] * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=params_q["Primary"]["Q_nominal"] * 16.0e5)), + ) + sec_heat = dict( + HeatIn=dict(Hydraulic_power=dict(nominal=params_q["Secondary"]["Q_nominal"] * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=params_q["Secondary"]["Q_nominal"] * 16.0e5)), + ) + params = {} + params["Primary"] = {**params_t["Primary"], **params_q["Primary"], **prim_heat} + params["Secondary"] = {**params_t["Secondary"], **params_q["Secondary"], **sec_heat} + + max_power_heat = power_secondary + + modifiers = dict( + COP=cop, + efficiency=asset.attributes["efficiency"] if asset.attributes["efficiency"] else 0.5, + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + Power_elec=dict(min=0.0, max=power_electrical, nominal=power_electrical / 2.0), + Primary_heat=dict(min=0.0, max=max_power_heat, nominal=max_power_heat / 2.0), + Secondary_heat=dict(min=0.0, max=max_power_heat, nominal=max_power_heat / 2.0), + Heat_flow=dict(min=0.0, max=max_power_heat, nominal=max_power_heat / 2.0), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + **params, + ) + if len(asset.in_ports) == 2: + return HeatPump, modifiers + elif len(asset.in_ports) == 3: + return HeatPumpElec, modifiers + + def convert_heat_source(self, asset: Asset) -> Tuple[Type[HeatSource], MODIFIERS]: + """ + This function converts the Source object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + + - Setting the CO2 emission coefficient in case this is specified as an KPI + - Setting a caps on the thermal power. + - In case of a GeothermalSource object we read the _aggregation count to model the + number of doublets, we then assume that the power specified was also for one doublet + and thus increase the thermal power caps. + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Required ESDL fields: + - power + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - aggregationCount + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + Source class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in { + "GasHeater", + "GenericProducer", + "HeatProducer", + "GeothermalSource", + "ResidualHeatSource", + "HeatPump", + } + + max_supply = asset.attributes["power"] + + if not max_supply: + logger.error(f"{asset.asset_type} '{asset.name}' has no max power specified. ") + assert max_supply > 0.0 + + # get price per unit of energy, + # assume cost of 1. if nothing is given (effectively milp loss minimization) + # TODO: Use an attribute or use and KPI for CO2 coefficient of a source + + q_nominal = self._get_connected_q_nominal(asset) + + modifiers = dict( + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + Q_nominal=q_nominal, + state=self.get_state(asset), + Heat_source=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + Heat_flow=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + **self._get_cost_figure_modifiers(asset), + ) + + if asset.asset_type == "GeothermalSource": + modifiers["nr_of_doublets"] = asset.attributes["aggregationCount"] + modifiers["Heat_source"] = dict( + min=0.0, + max=max_supply * asset.attributes["aggregationCount"], + nominal=max_supply / 2.0, + ) + modifiers["Heat_flow"] = dict( + min=0.0, + max=max_supply * asset.attributes["aggregationCount"], + nominal=max_supply / 2.0, + ) + try: + modifiers["single_doublet_power"] = asset.attributes["single_doublet_power"] + except KeyError: + modifiers["single_doublet_power"] = max_supply + # Note that the ESDL target flow rate is in kg/s, but we want m3/s + try: + modifiers["target_flow_rate"] = asset.attributes["flowRate"] / self.rho + except KeyError: + logger.warning( + f"{asset.asset_type} '{asset.name}' has no desired flow rate specified. " + f"'{asset.name}' will not be actuated in a constant manner" + ) + + return GeothermalSource, modifiers + elif asset.asset_type == "HeatPump": + modifiers["cop"] = asset.attributes["COP"] + return AirWaterHeatPump, modifiers + else: + return HeatSource, modifiers + + def convert_ates(self, asset: Asset) -> Tuple[Type[ATES], MODIFIERS]: + """ + This function converts the ATES object in esdl to a set of modifiers that can be used in + a pycml object. Most important: + + - Setting the milp loss coefficient based upon the efficiency. Here we assume that this + efficiency is realized in 100 days. + - Setting a caps on the thermal power. + - Similar as for the geothermal source we use the aggregation count to model the amount + of doublets. + - Setting caps on the maximum stored energy where we assume that at maximum you can + charge for 180 days at full power. + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - max(Dis)ChargeRate + - aquiferMidTemperature + - aggregationCount + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + ATES class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in { + "ATES", + } + + hfr_charge_max = asset.attributes.get("maxChargeRate", math.inf) + hfr_discharge_max = asset.attributes.get("maxDischargeRate", math.inf) + single_doublet_power = hfr_discharge_max + + # We assume the efficiency is realized over a period of 100 days + efficiency = asset.attributes["dischargeEfficiency"] + if not efficiency: + efficiency = 0.7 + + # TODO: temporary value for standard dT on which capacity is based, Q in m3/s + temperatures = self._supply_return_temperature_modifiers(asset) + dt = temperatures["T_supply"] - temperatures["T_return"] + rho = self.rho + cp = self.cp + q_max_ates = hfr_discharge_max / (cp * rho * dt) + + q_nominal = min( + self._get_connected_q_nominal(asset), q_max_ates * asset.attributes["aggregationCount"] + ) + + modifiers = dict( + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + Q_nominal=q_nominal, + Q=dict( + min=-q_max_ates * asset.attributes["aggregationCount"], + max=q_max_ates * asset.attributes["aggregationCount"], + nominal=q_nominal, + ), + single_doublet_power=single_doublet_power, + heat_loss_coeff=(1.0 - efficiency ** (1.0 / 100.0)) / (3600.0 * 24.0), + state=self.get_state(asset), + nr_of_doublets=asset.attributes["aggregationCount"], + Stored_heat=dict( + min=0.0, + max=hfr_charge_max * asset.attributes["aggregationCount"] * 180.0 * 24 * 3600.0, + nominal=hfr_charge_max * asset.attributes["aggregationCount"] * 30.0 * 24 * 3600.0, + ), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + **self._get_cost_figure_modifiers(asset), + ) + + # if no maxStorageTemperature is specified we assume a "regular" HT ATES model + if ( + asset.attributes["maxStorageTemperature"] + and asset.attributes["maxStorageTemperature"] <= 30.0 + ): + modifiers.update( + dict( + Heat_low_temperature_ates=dict( + min=-hfr_charge_max * asset.attributes["aggregationCount"], + max=hfr_discharge_max * asset.attributes["aggregationCount"], + nominal=hfr_discharge_max / 2.0, + ) + ) + ) + logger.warning( + "ATES in use: WKO (koude-warmteopslag, cold and heat storage) since the" + " maximum temperature has been specified to be <= 30 degrees Celcius" + ) + return LowTemperatureATES, modifiers + else: + modifiers.update( + dict( + Heat_ates=dict( + min=-hfr_charge_max * asset.attributes["aggregationCount"], + max=hfr_discharge_max * asset.attributes["aggregationCount"], + nominal=hfr_discharge_max / 2.0, + ), + T_amb=asset.attributes["aquiferMidTemperature"], + Temperature_ates=dict( + min=temperatures["T_return"], # or potentially 0 + max=temperatures["T_supply"], + nominal=temperatures["T_return"], + ), + ) + ) + logger.warning( + "ATES in use: High Temperature ATES since the maximum temperature has" + " been specified to be > 30 degrees Celcius or not specified at all" + ) + return ATES, modifiers + + def convert_control_valve(self, asset: Asset) -> Tuple[Type[ControlValve], MODIFIERS]: + """ + This function converts the ControlValve object in esdl to a set of modifiers that can be + used in a pycml object. Most important: + + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + ControlValve class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type == "Valve" + + q_nominal = self._get_connected_q_nominal(asset) + + modifiers = dict( + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + Q_nominal=q_nominal, + state=self.get_state(asset), + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + ) + + return ControlValve, modifiers + + def convert_check_valve(self, asset: Asset) -> Tuple[Type[CheckValve], MODIFIERS]: + """ + This function converts the CheckValve object in esdl to a set of modifiers that can be + used in a pycml object. Most important: + + - Setting the state (enabled, disabled, optional) + - Setting the relevant temperatures. + - Setting the relevant cost figures. + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with temperature specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + CheckValve class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type == "CheckValve" + + q_nominal = self._get_connected_q_nominal(asset) + + modifiers = dict( + Q_nominal=q_nominal, + state=self.get_state(asset), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + ) + + return CheckValve, modifiers + + def convert_electricity_demand(self, asset: Asset) -> Tuple[Type[ElectricityDemand], MODIFIERS]: + """ + This function converts the ElectricityDemand object in esdl to a set of modifiers that can + be used in a pycml object. Most important: + + - Setting the electrical power caps + + Required ESDL fields: + - power + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with voltage specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + ElectricityDemand class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"ElectricityDemand", "Export"} + + max_demand = asset.attributes.get("power", math.inf) + min_voltage = asset.in_ports[0].carrier.voltage + i_max, i_nom = self._get_connected_i_nominal_and_max(asset) + + id_mapping = asset.global_properties["carriers"][asset.in_ports[0].carrier.id][ + "id_number_mapping" + ] + + modifiers = dict( + min_voltage=min_voltage, + id_mapping_carrier=id_mapping, + elec_power_nominal=max_demand / 2.0, + Electricity_demand=dict(max=max_demand, nominal=max_demand / 2.0), + ElectricityIn=dict( + Power=dict(min=0.0, max=max_demand, nominal=max_demand / 2.0), + I=dict(min=0.0, max=i_max, nominal=i_nom), + V=dict(min=min_voltage, nominal=min_voltage), + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + + return ElectricityDemand, modifiers + + def convert_import(self, asset: Asset): + """ + The definition of an Import asset, is an asset that imports energy, thus adds energy to + the network, thereby it acts as a producer." + """ + assert asset.asset_type in {"Import"} + + if isinstance(asset.out_ports[0].carrier, esdl.esdl.GasCommodity): + return self.convert_gas_source(asset) + elif isinstance(asset.out_ports[0].carrier, esdl.esdl.ElectricityCommodity): + return self.convert_electricity_source(asset) + else: + raise RuntimeError( + f"Commodity of type {type(asset.out_ports[0].carrier)} for asset Import " + f"{asset.name} cannot be converted" + ) + + def convert_export(self, asset: Asset): + """ + The definition of an Export asset, is an asset that exports energy from the network, thus + extracts energy to the network, thereby it acts as a consumer." + """ + assert asset.asset_type in {"Export"} + + if isinstance(asset.in_ports[0].carrier, esdl.esdl.GasCommodity): + return self.convert_gas_demand(asset) + elif isinstance(asset.in_ports[0].carrier, esdl.esdl.ElectricityCommodity): + return self.convert_electricity_demand(asset) + else: + raise RuntimeError( + f"Commodity of type {type(asset.in_ports[0].carrier)} for asset Export " + f"{asset.name} cannot be converted" + ) + + def convert_electricity_source(self, asset: Asset) -> Tuple[Type[ElectricitySource], MODIFIERS]: + """ + This function converts the ElectricitySource object in esdl to a set of modifiers that can + be used in a pycml object. Most important: + + - Setting the electrical power caps + + Required ESDL fields: + - power + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with voltage specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + ElectricitySource class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in { + "ElectricityProducer", + "WindPark", + "WindTurbine", + "PVInstallation", + "Import", + } + + max_supply = asset.attributes.get( + "power", math.inf + ) # I think it would break with math.inf as input + i_max, i_nom = self._get_connected_i_nominal_and_max(asset) + v_min = asset.out_ports[0].carrier.voltage + + modifiers = dict( + power_nominal=max_supply / 2.0, + Electricity_source=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + ElectricityOut=dict( + V=dict(min=v_min, nominal=v_min), + I=dict(min=0.0, max=i_max, nominal=i_nom), + Power=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + + if asset.asset_type in ["ElectricityProducer", "Import"]: + return ElectricitySource, modifiers + if asset.asset_type in ["WindPark", "WindTurbine"]: + return WindPark, modifiers + if asset.asset_type == "PVInstallation": + return SolarPV, modifiers + + def convert_electricity_storage( + self, asset: Asset + ) -> Tuple[Type[ElectricityStorage], MODIFIERS]: + """ + This function converts the ElectricityStorage object in esdl to a set of modifiers that can + be used in a pycml object. Most important: + + - Setting the electrical power caps + + Parameters: + asset : The asset object with its properties. + + Returns: + ElectricityStorage class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"Battery"} + + max_capacity = asset.attributes.get("capacity") + i_max, i_nom = self._get_connected_i_nominal_and_max(asset) + v_min = asset.in_ports[0].carrier.voltage + max_charge = asset.attributes.get("maxChargeRate", max_capacity / 3600) + max_discharge = asset.attributes.get("maxDischargeRate", max_capacity / 3600) + discharge_efficiency = asset.attributes.get("dischargeEfficiency", 1) + charge_efficiency = asset.attributes.get("chargeEfficiency", 1) + + modifiers = dict( + charge_efficiency=charge_efficiency, + discharge_efficiency=discharge_efficiency, + min_voltage=v_min, + max_capacity=max_capacity, + Stored_electricity=dict(min=0.0, max=max_capacity), + ElectricityIn=dict( + V=dict(min=v_min, nominal=v_min), + I=dict(min=-i_max, max=i_max, nominal=i_nom), + Power=dict(min=-max_discharge, max=max_charge, nominal=max_charge / 2.0), + ), + Effective_power_charging=dict( + min=-max_discharge, max=max_charge, nominal=max_charge / 2.0 + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + + return ElectricityStorage, modifiers + + def convert_electricity_node(self, asset: Asset) -> Tuple[Type[ElectricityNode], MODIFIERS]: + """ + This function converts the ElectricityNode object in esdl to a set of modifiers that can be + used in a pycml object. Most important: + + - Setting the number of connections + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo (allowed to have multiple connections) + - carrier with voltage specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + ElectricityNode class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"Bus"} + + sum_in = 0 + sum_out = 0 + + node_carrier = None + for x in asset.attributes["port"].items: + if node_carrier is None: + node_carrier = x.carrier.name + nominal_voltage = x.carrier.voltage + else: + if node_carrier != x.carrier.name: + raise _ESDLInputException( + f"{asset.name} has multiple carriers mixing which is not allowed. " + ) + if isinstance(x, esdl.esdl.InPort): + sum_in += len(x.connectedTo) + if isinstance(x, esdl.esdl.OutPort): + sum_out += len(x.connectedTo) + + modifiers = dict( + voltage_nominal=nominal_voltage, + n=sum_in + sum_out, + state=self.get_state(asset), + ) + + return ElectricityNode, modifiers + + def convert_electricity_cable(self, asset: Asset) -> Tuple[Type[ElectricityCable], MODIFIERS]: + """ + This function converts the ElectricityCable object in esdl to a set of modifiers that can be + used in a pycml object. Most important: + + - Setting the length of the cable used for power loss computation. + - setting the min and max current. + + Required ESDL fields: + - length + - capacity + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with voltage specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + ElectricityCable class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"ElectricityCable"} + + max_power = asset.attributes["capacity"] + min_voltage = asset.in_ports[0].carrier.voltage + max_current = max_power / min_voltage + self._set_electricity_current_nominal_and_max(asset, max_current / 2.0, max_current) + + bi_direct = True if asset.attributes["assetType"] != "unidirectional" else False + + length = asset.attributes["length"] + if length == 0.0: + length = 10.0 + logger.warning(f"{asset.name} had a length of 0.0m, thus is set to " f"{length} meter") + res_ohm_per_m = self._cable_get_resistance(asset) + res_ohm = res_ohm_per_m * length + + min_current = -max_current if bi_direct else 0.0 + min_power = -max_power if bi_direct else 0.0 + + modifiers = dict( + max_current=max_current, + min_voltage=min_voltage, + nominal_current=max_current / 2.0, + nominal_voltage=min_voltage, + length=length, + r=res_ohm, + ElectricityOut=dict( + V=dict(min=min_voltage, nominal=min_voltage), + I=dict(min=min_current, max=max_current, nominal=max_current / 2.0), + Power=dict(min=min_power, max=max_power, nominal=max_power / 2.0), + ), + ElectricityIn=dict( + V=dict(min=min_voltage, nominal=min_voltage), + I=dict(min=min_current, max=max_current, nominal=max_current / 2.0), + Power=dict(min=min_power, max=max_power, nominal=max_power / 2.0), + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + return ElectricityCable, modifiers + + def convert_transformer(self, asset: Asset) -> Tuple[Type[Transformer], MODIFIERS]: + """ + This function converts the Transformer object in esdl to a set of modifiers that can be + used in a pycml object. Most important: + + - Setting the length of the cable used for power loss computation. + - setting the min and max current. + + Parameters: + asset : The asset object with its properties. + + Returns: + ElectricityCable class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"Transformer", "GenericConversion"} + self._get_connected_i_nominal_and_max(asset) + i_max_in, i_nom_in, i_max_out, i_nom_out = self._get_connected_i_nominal_and_max(asset) + min_voltage_in = asset.in_ports[0].carrier.voltage + min_voltage_out = asset.out_ports[0].carrier.voltage + max_power = min_voltage_in * i_max_in + + modifiers = dict( + power_nominal=max_power / 2.0, + min_voltage=min_voltage_in, + ElectricityIn=dict( + V=dict(min=min_voltage_in, nominal=min_voltage_in), + I=dict(min=0.0, max=i_max_in, nominal=i_nom_in), + Power=dict(min=0.0, max=max_power, nominal=max_power / 2.0), + ), + ElectricityOut=dict( + V=dict(nominal=min_voltage_out), + I=dict(min=0.0, max=i_max_out, nominal=i_nom_out), + Power=dict(min=0.0, max=max_power, nominal=max_power / 2.0), + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + return Transformer, modifiers + + def convert_gas_demand(self, asset: Asset) -> Tuple[Type[GasDemand], MODIFIERS]: + """ + This function converts the GasDemand object in esdl to a set of modifiers that can be + used in a pycml object. Most important: + + - Setting a cap on the mass flow produced. + - Setting the state (enabled, disabled, optional) + - Setting the relevant cost figures. + + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with pressure specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + GasDemand class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"GasDemand", "Export"} + + id_mapping = asset.global_properties["carriers"][asset.in_ports[0].carrier.id][ + "id_number_mapping" + ] + # DO not remove due usage in future + # hydrogen_specfic_energy = 20.0 / 1.0e6 + specific_energy = get_energy_content(asset.name, asset.in_ports[0].carrier) # J/kg + # TODO: the value being used is the internal energy and not the HHV (higher + # heating value) for hydrogen, therefore it does not represent the energy per weight. + # This still needs to be updated + density = get_density(asset.name, asset.in_ports[0].carrier) + pressure = asset.in_ports[0].carrier.pressure * 1.0e5 + q_nominal = self._get_connected_q_nominal(asset) + q_max = self._get_connected_q_max(asset) + # [g/s] = [J/s] * [J/kg]^-1 *1000 + max_mass_flow_g_per_s = min( + asset.attributes["power"] / specific_energy * 1000.0, q_max * density + ) + mass_flow_nominal_g_per_s = min(q_nominal * density, max_mass_flow_g_per_s / 2) + + modifiers = dict( + Q_nominal=q_nominal, + id_mapping_carrier=id_mapping, + # Gas_demand_mass_flow=dict(min=0., max=asset.attributes["power"] + # *hydrogen_specfic_energy), + density=density, + GasIn=dict( + Q=dict(min=0.0, nominal=q_nominal), + mass_flow=dict(nominal=mass_flow_nominal_g_per_s, max=max_mass_flow_g_per_s), + Hydraulic_power=dict(min=0.0, max=0.0, nominal=q_nominal * pressure), + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + + return GasDemand, modifiers + + def convert_gas_source(self, asset: Asset) -> Tuple[Type[GasSource], MODIFIERS]: + """ + This function converts the GasDemand object in esdl to a set of modifiers that can be + used in a pycml object. Most important: + + - Setting a cap on the mass flow produced. + - Setting the state (enabled, disabled, optional) + - Setting the relevant cost figures. + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with pressure specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + GasDemand class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"GasProducer", "Import"} + + q_nominal = self._get_connected_q_nominal(asset) + density_value = get_density(asset.name, asset.out_ports[0].carrier) + pressure = asset.out_ports[0].carrier.pressure * 1.0e5 + # J/kg #TODO: is not the HHV for hydrogen, so is off + specific_energy = get_energy_content(asset.name, asset.out_ports[0].carrier) + # [g/s] = [J/s] * [J/kg]^-1 *1000 + max_mass_flow_g_per_s = asset.attributes["power"] / specific_energy * 1000.0 + + bounds_nominals_mass_flow_g_per_s = dict( + min=0.0, + max=min(self._get_connected_q_max(asset) * density_value, max_mass_flow_g_per_s), + nominal=q_nominal * density_value, + ) + + modifiers = dict( + Q_nominal=q_nominal, + density=density_value, + Gas_source_mass_flow=bounds_nominals_mass_flow_g_per_s, + GasOut=dict( + Q=dict(nominal=q_nominal), + mass_flow=bounds_nominals_mass_flow_g_per_s, + Hydraulic_power=dict(nominal=q_nominal * pressure), + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + + return GasSource, modifiers + + def convert_electrolyzer(self, asset: Asset) -> Tuple[Type[Electrolyzer], MODIFIERS]: + """ + This function converts the Electrolyzer object in esdl to a set of modifiers that can be + used in a pycml object. + + Required ESDL fields: + - power + - minLoad + - maxLoad + - effMinLoad + - effMaxLoad + - efficiency + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with voltage/pressure specified + + Optional ESDL fields: + - technicalLifetime + - powerFactor + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + Electrolyzer class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"Electrolyzer"} + + i_max, i_nom = self._get_connected_i_nominal_and_max(asset) + v_min = asset.in_ports[0].carrier.voltage + max_power = asset.attributes.get("power", math.inf) + min_load = float(asset.attributes["minLoad"]) + max_load = float(asset.attributes["maxLoad"]) + if not max_power == max_load: + max_power = max_load + logger.warning( + f"The maximum load and the power of the electrolyzer did not match for " + f"{asset.name}. The maximum load of {max_load}W is now used as maximum " + f"power." + ) + eff_min_load = asset.attributes["effMinLoad"] # Wh/g + eff_max_load = asset.attributes["effMaxLoad"] # Wh/g + eff_max = asset.attributes["efficiency"] # Wh/g + + power_factor = ( + asset.attributes["powerFactor"] if asset.attributes["powerFactor"] != 0.0 else 2.5 + ) + + def equations(x): + a, b, c = x + eq1 = a / min_load + b * min_load + c - eff_min_load + eq2 = a / max_load + b * max_load + c - eff_max_load + eq3 = a / (min_load * power_factor) + b * (min_load * power_factor) + c - eff_max + return [eq1, eq2, eq3] + + # Here we approximate the efficiency curve of the electrolyzer with the function: + # 1/eff = a/P_e + b*P_e + c. We find the coefficients with a simple solve function. + # At the moment we abbuse the efficiency attribute of esdl to quantify the maximum + # operational efficiency. + a, b, c = fsolve(equations, (0, 0, 0)) + + q_nominal = self._get_connected_q_nominal(asset) + density = get_density(asset.name, asset.out_ports[0].carrier) + # [g/s] = [W] * [kWh/kg]^-1 * 1/3600 = [g/h] * 1/3600 + mass_flow_max_g_per_s = max_power / eff_max_load / 3600 + mass_flow_nominal_g_per_s = min(density * q_nominal, mass_flow_max_g_per_s / 2) + + modifiers = dict( + min_voltage=v_min, + a_eff_coefficient=a, + b_eff_coefficient=b, + c_eff_coefficient=c, + minimum_load=min_load, + nominal_power_consumed=max_power / 2.0, + nominal_gass_mass_out=mass_flow_nominal_g_per_s, + Q_nominal=q_nominal, + density=density, + efficiency=eff_max, + GasOut=dict( + Q=dict( + min=0.0, + max=self._get_connected_q_max(asset), + nominal=q_nominal, + ), + mass_flow=dict(nominal=mass_flow_nominal_g_per_s, max=mass_flow_max_g_per_s), + ), + ElectricityIn=dict( + Power=dict(min=0.0, max=max_power, nominal=max_power / 2.0), + I=dict(min=0.0, max=i_max, nominal=i_nom), + V=dict(min=v_min, nominal=v_min), + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + + return Electrolyzer, modifiers + + def convert_gas_tank_storage(self, asset: Asset) -> Tuple[Type[GasTankStorage], MODIFIERS]: + """ + This function converts the GasTankStorage object in esdl to a set of modifiers that can be + used in a pycml object. + + Required ESDL fields: + - workingVolume + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with pressure specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + GasTankStorage class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"GasStorage"} + + # DO not remove due usage in future + # hydrogen_specific_energy = 20.0 / 1.0e6 # kg/Wh + q_nominal = self._get_connected_q_nominal(asset) + density = get_density(asset.name, asset.in_ports[0].carrier) + pressure = asset.in_ports[0].carrier.pressure * 1.0e5 + + modifiers = dict( + Q_nominal=q_nominal, + density=density, + volume=asset.attributes["workingVolume"], + # Gas_tank_flow=dict(min=-hydrogen_specific_energy*asset.attributes["maxDischargeRate"], + # max=hydrogen_specific_energy*asset.attributes["maxChargeRate"]), + # TODO: Fix -> Gas network is currenlty non-limiting, mass flow is decoupled from the + # volumetric flow + # Gas_tank_flow=dict( + # min=-self._get_connected_q_max(asset), max=self._get_connected_q_max(asset), + # nominal=self._get_connected_q_nominal(asset), + # ) + GasIn=dict( + Q=dict(nominal=q_nominal), + mass_flow=dict(nominal=q_nominal * density), + Hydraulic_power=dict(nominal=q_nominal * pressure), + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + + return GasTankStorage, modifiers + + def convert_gas_substation(self, asset: Asset) -> Tuple[Type[GasSubstation], MODIFIERS]: + """ + This function converts the PressureReducingValve object in esdl to a set of modifiers that + can be used in a pycml object. + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with pressure specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + GasSubstation class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"GasConversion", "PressureReducingValve"} + + q_nom_in, q_nom_out = self._get_connected_q_nominal(asset) + density_in = get_density(asset.name, asset.in_ports[0].carrier) + density_out = get_density(asset.name, asset.out_ports[0].carrier) + pressure_in = asset.in_ports[0].carrier.pressure * 1.0e5 + pressure_out = asset.out_ports[0].carrier.pressure * 1.0e5 + + assert density_in >= density_out + + modifiers = dict( + Q_nominal_in=q_nom_in, + Q_nominal_out=q_nom_out, + density_in=density_in, + density_out=density_out, + GasIn=dict( + Q=dict(nominal=q_nom_in), + mass_flow=dict(nominal=q_nom_in * density_in), + Hydraulic_power=dict(nominal=q_nom_in * pressure_in), + ), + GasOut=dict( + Q=dict(nominal=q_nom_out), + mass_flow=dict(nominal=q_nom_out * density_out), + Hydraulic_power=dict(nominal=q_nom_out * pressure_out), + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + + return GasSubstation, modifiers + + def convert_compressor(self, asset: Asset) -> Tuple[Type[Compressor], MODIFIERS]: + """ + This function converts the Compressor object in esdl to a set of modifiers that can be + used in a pycml object. + + Required ESDL fields: + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with pressure specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + Compressor class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"Compressor"} + + q_nom_in, q_nom_out = self._get_connected_q_nominal(asset) + density_in = get_density(asset.name, asset.in_ports[0].carrier) + density_out = get_density(asset.name, asset.out_ports[0].carrier) + pressure_in = asset.in_ports[0].carrier.pressure * 1.0e5 + pressure_out = asset.out_ports[0].carrier.pressure * 1.0e5 + + assert density_out >= density_in + + modifiers = dict( + Q_nominal_in=q_nom_in, + Q_nominal_out=q_nom_out, + density_in=density_in, + density_out=density_out, + GasIn=dict( + Q=dict(nominal=q_nom_in), + mass_flow=dict(nominal=q_nom_in * density_in), + Hydraulic_power=dict(nominal=q_nom_in * pressure_in), + ), + GasOut=dict( + Q=dict(nominal=q_nom_out), + mass_flow=dict(nominal=q_nom_out * density_out), + Hydraulic_power=dict(nominal=q_nom_out * pressure_out), + ), + state=self.get_state(asset), + **self._get_cost_figure_modifiers(asset), + ) + + return Compressor, modifiers + + def convert_gas_boiler(self, asset: Asset) -> Tuple[GasBoiler, MODIFIERS]: + """ + This function converts the GasHeater object in esdl to a set of modifiers that can be + used in a pycml object. + + Required ESDL fields: + - power + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with pressure/temperature specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + GasBoiler class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"GasHeater"} + + max_supply = asset.attributes["power"] + + if not max_supply: + logger.error(f"{asset.asset_type} '{asset.name}' has no max power specified. ") + assert max_supply > 0.0 + + if len(asset.in_ports) == 1: + heat_source_object, modifiers = self.convert_heat_source(asset) + return heat_source_object, modifiers + + id_mapping = asset.global_properties["carriers"][asset.in_ports[0].carrier.id][ + "id_number_mapping" + ] + + for port in asset.in_ports: + if isinstance(port.carrier, esdl.GasCommodity): + density = get_density(asset.name, port.carrier) + energy_content = get_energy_content(asset.name, port.carrier) + + # TODO: CO2 coefficient + + q_nominals = self._get_connected_q_nominal(asset) + + modifiers = dict( + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + Heat_source=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + Heat_flow=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominals["Q_nominal"] * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominals["Q_nominal"] * 16.0e5)), + id_mapping_carrier=id_mapping, + density=density, + energy_content=energy_content, + GasIn=dict(Q=dict(min=0.0, nominal=q_nominals["Q_nominal_gas"])), + state=self.get_state(asset), + **q_nominals, + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + **self._get_cost_figure_modifiers(asset), + ) + + return GasBoiler, modifiers + + def convert_elec_boiler(self, asset: Asset) -> Tuple[ElecBoiler, MODIFIERS]: + """ + This function converts the ElectricBoiler object in esdl to a set of modifiers that can be + used in a pycml object. + + Required ESDL fields: + - power + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with voltage/temperature specified + + Optional ESDL fields: + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + GasBoiler class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"ElectricBoiler"} + + max_supply = asset.attributes["power"] + + if not max_supply: + logger.error(f"{asset.asset_type} '{asset.name}' has no max power specified. ") + assert max_supply > 0.0 + + if len(asset.in_ports) == 1: + heat_source_object, modifiers = self.convert_heat_source(asset) + return heat_source_object, modifiers + + id_mapping = asset.global_properties["carriers"][asset.in_ports[0].carrier.id][ + "id_number_mapping" + ] + + # TODO: CO2 coefficient + + q_nominal = self._get_connected_q_nominal(asset) + for port in asset.in_ports: + if isinstance(port.carrier, esdl.ElectricityCommodity): + min_voltage = port.carrier.voltage + i_max, i_nom = self._get_connected_i_nominal_and_max(asset) + eff = asset.attributes["efficiency"] if asset.attributes["efficiency"] else 1.0 + + modifiers = dict( + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + Heat_source=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + Heat_flow=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal["Q_nominal"] * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal["Q_nominal"] * 16.0e5)), + id_mapping_carrier=id_mapping, + ElectricityIn=dict( + Power=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + I=dict(min=0.0, max=i_max, nominal=i_nom), + V=dict(min=min_voltage, nominal=min_voltage), + ), + min_voltage=min_voltage, + elec_power_nominal=max_supply, + efficiency=eff, + state=self.get_state(asset), + **q_nominal, + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + **self._get_cost_figure_modifiers(asset), + ) + + return ElecBoiler, modifiers + + def convert_air_water_heat_pump_elec( + self, asset: Asset + ) -> Tuple[AirWaterHeatPumpElec, MODIFIERS]: + """ + This function converts the ElectricBoiler object in esdl to a set of modifiers that can be + used in a pycml object. + + Required ESDL fields: + - power + - id (this id must be unique) + - name (this name must be unique) + - xsi:type + - State + - InPort and OutPort with: + - xsi:type + - id + - name + - connectedTo + - carrier with voltage/temperature specified + + Optional ESDL fields: + - COP + - technicalLifetime + - CostInformation: discountRate + - CostInformation: marginalCost + - CostInformation: installationCost + - CostInformation: investmentCost + - CostInformation: fixedOperationalCost + - CostInformation: variableOperationalCost + + Parameters: + asset : The asset object with its properties. + + Returns: + AirWaterHeatPumpElec class with modifiers: + {automatically_add_modifiers_here} + """ + assert asset.asset_type in {"HeatPump"} + + max_supply = asset.attributes["power"] + + if not max_supply: + logger.error(f"{asset.asset_type} '{asset.name}' has no max power specified. ") + assert max_supply > 0.0 + + id_mapping = asset.global_properties["carriers"][asset.in_ports[0].carrier.id][ + "id_number_mapping" + ] + + # TODO: CO2 coefficient + + q_nominal = self._get_connected_q_nominal(asset) + for port in asset.in_ports: + if isinstance(port.carrier, esdl.ElectricityCommodity): + min_voltage = port.carrier.voltage + i_max, i_nom = self._get_connected_i_nominal_and_max(asset) + cop = asset.attributes["COP"] if asset.attributes["COP"] else 1.0 + + modifiers = dict( + technical_life=self.get_asset_attribute_value( + asset, + "technicalLifetime", + default_value=30.0, + min_value=1.0, + max_value=50.0, + ), + discount_rate=self.get_asset_attribute_value( + asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 + ), + Heat_source=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + Heat_flow=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal["Q_nominal"] * 16.0e5)), + HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal["Q_nominal"] * 16.0e5)), + id_mapping_carrier=id_mapping, + ElectricityIn=dict( + Power=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), + I=dict(min=0.0, max=i_max, nominal=i_nom), + V=dict(min=min_voltage, nominal=min_voltage), + ), + min_voltage=min_voltage, + elec_power_nominal=max_supply, + cop=cop, + state=self.get_state(asset), + **q_nominal, + **self._supply_return_temperature_modifiers(asset), + **self._rho_cp_modifiers, + **self._get_cost_figure_modifiers(asset), + ) + + return AirWaterHeatPumpElec, modifiers + + +class ESDLHeatModel(_ESDLModelBase): + """ + This class is used to convert the esdl Assets to PyCML assets this class only exists to specify + the specific objects used in the conversion step. Note there is no __init__ in the base class. + This probably could be standardized in that case this class would become obsolete. + """ + + def __init__( + self, + assets: Dict[str, Asset], + name_to_id_map: Dict[str, str], + converter_class=AssetToHeatComponent, + **kwargs, + ): + super().__init__(None) + + converter = converter_class( + **{ + **kwargs, + **{ + "primary_port_name_convention": self.primary_port_name_convention, + "secondary_port_name_convention": self.secondary_port_name_convention, + }, + } + ) + + self._esdl_convert(converter, assets, name_to_id_map, "MILP") diff --git a/src/rtctools_heat_network/esdl/esdl_mixin.py b/src/mesido/esdl/esdl_mixin.py similarity index 95% rename from src/rtctools_heat_network/esdl/esdl_mixin.py rename to src/mesido/esdl/esdl_mixin.py index 4b9e3796a..10a21743e 100644 --- a/src/rtctools_heat_network/esdl/esdl_mixin.py +++ b/src/mesido/esdl/esdl_mixin.py @@ -7,7 +7,22 @@ from typing import Any, Dict, Optional import esdl.esdl_handler -from esdl.resources.xmlresource import XMLResource + +from mesido.component_type_mixin import ( + ModelicaComponentTypeMixin, +) +from mesido.esdl.asset_to_component_base import _AssetToComponentBase +from mesido.esdl.common import Asset +from mesido.esdl.edr_pipe_class import EDRGasPipeClass, EDRPipeClass +from mesido.esdl.esdl_heat_model import ESDLHeatModel +from mesido.esdl.esdl_model_base import _ESDLModelBase +from mesido.esdl.esdl_parser import ESDLStringParser +from mesido.esdl.esdl_qth_model import ESDLQTHModel +from mesido.esdl.profile_parser import BaseProfileReader, InfluxDBProfileReader +from mesido.physics_mixin import PhysicsMixin +from mesido.pipe_class import GasPipeClass, PipeClass +from mesido.pycml.pycml_mixin import PyCMLMixin +from mesido.qth_not_maintained.qth_mixin import QTHMixin import numpy as np @@ -17,25 +32,8 @@ ) from rtctools.optimization.io_mixin import IOMixin -from rtctools_heat_network.component_type_mixin import ( - ModelicaComponentTypeMixin, -) -from rtctools_heat_network.esdl.asset_to_component_base import _AssetToComponentBase -from rtctools_heat_network.esdl.edr_pipe_class import EDRGasPipeClass, EDRPipeClass -from rtctools_heat_network.esdl.esdl_parser import ESDLStringParser -from rtctools_heat_network.esdl.profile_parser import BaseProfileReader, InfluxDBProfileReader -from rtctools_heat_network.physics_mixin import PhysicsMixin -from rtctools_heat_network.pipe_class import GasPipeClass, PipeClass -from rtctools_heat_network.pycml.pycml_mixin import PyCMLMixin -from rtctools_heat_network.qth_not_maintained.qth_mixin import QTHMixin - -from .common import Asset -from .esdl_heat_model import ESDLHeatModel -from .esdl_model_base import _ESDLModelBase -from .esdl_qth_model import ESDLQTHModel - -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") ns = {"fews": "http://www.wldelft.nl/fews", "pi": "http://www.wldelft.nl/fews/PI"} @@ -119,9 +117,10 @@ def __init__(self, *args, **kwargs) -> None: # Although we work with the names, the FEWS import data uses the component IDs self.__timeseries_id_map = {a.id: a.name for a in assets.values()} + name_to_id_map = {a.name: a.id for a in assets.values()} if isinstance(self, PhysicsMixin): - self.__model = ESDLHeatModel(assets, **self.esdl_heat_model_options()) + self.__model = ESDLHeatModel(assets, name_to_id_map, **self.esdl_heat_model_options()) else: assert isinstance(self, QTHMixin) @@ -364,9 +363,10 @@ def convert_energy_system_to_string(energy_system: esdl.esdl.EnergySystem) -> st ------- An XML string representing the energy system """ - esh = esdl.esdl_handler.EnergySystemHandler(energy_system=energy_system) - esh.resource = XMLResource(uri=esdl.esdl_handler.StringURI("to_string.esdl")) - return esh.to_string() + + uri = esdl.esdl_handler.StringURI("to_string.esdl") + energy_system.eResource.save(uri) + return uri.getvalue() @staticmethod def save_energy_system_to_file(energy_system: esdl.esdl.EnergySystem, file_path: Path) -> None: @@ -421,7 +421,7 @@ def get_asset_from_asset_name(self, asset_name: str) -> esdl.Asset: def esdl_heat_model_options(self) -> Dict: """ - function to spedifically return the needed HeatMixin options needed for the conversion + function to spedifically return the needed PhysicsMixin options needed for the conversion from ESDL to pycml. This case velocities used to set nominals and caps on the milp. Returns @@ -431,7 +431,8 @@ def esdl_heat_model_options(self) -> Dict: energy_system_options = self.energy_system_options() v_nominal = energy_system_options["estimated_velocity"] v_max = self.heat_network_settings["maximum_velocity"] - return dict(v_nominal=v_nominal, v_max=v_max) + v_max_gas = self.gas_network_settings["maximum_velocity"] + return dict(v_nominal=v_nominal, v_max=v_max, v_max_gas=v_max_gas) def esdl_qth_model_options(self) -> Dict: """ diff --git a/src/mesido/esdl/esdl_model_base.py b/src/mesido/esdl/esdl_model_base.py new file mode 100644 index 000000000..73fa09b3b --- /dev/null +++ b/src/mesido/esdl/esdl_model_base.py @@ -0,0 +1,507 @@ +import logging +from typing import Dict + +import esdl +from esdl import InPort, OutPort + +from mesido.esdl.asset_to_component_base import _AssetToComponentBase +from mesido.pycml import Model as _Model + +logger = logging.getLogger("mesido") + + +RETRY_LOOP_LIMIT = 100 + + +class _ESDLModelBase(_Model): + """ + This is the ESDL base class that is used to convert from the esdl parsed assets to the pycml + model description. In the base class we specify how the network is connected, meaning which + asset is connected to which asset as this is the same for different model types (both + Heat and QTH). Per model type we have a specialization for the converting of the assets as + different models might need different information from the esdl file. + """ + + primary_port_name_convention = "prim" + secondary_port_name_convention = "sec" + + def _esdl_convert( + self, converter: _AssetToComponentBase, assets: Dict, name_to_id_map: Dict, prefix: str + ) -> None: + """ + In this function we convert the esdl parsed assets and instantiate the pycml objects for + those assets. We use the converter to create those pycml objects and the same time we look + at the connections specified in the esdl and create the relevant maps between ports to then + also connect the pycml ports of the assets. + + Parameters: + converter : class with the different converter functions for all asset types. + assets : a dict with all the parsed esdl assets and their attributes + prefix : prefix for the name of the model type Heat or QTH at the moment + + """ + # Sometimes we need information of one component in order to convert + # another. For example, the nominal discharge of a pipe is used to set + # the nominal discharge of its connected components. + skip_assets = list() + + transport_asset_types = ["Pipe", "ElectricityCable"] + assets_transport = {} + assets_other = {} + + for name, properties in assets.items(): + if properties.asset_type in transport_asset_types: + assets_transport[name] = properties + else: + assets_other[name] = properties + + # We create an assets sorted to first loop over specific assets (the transport assets), + # before parsing the other assets. This is because the properties of the transport assets + # are used to set nominals for other assets that are then parsed later. + assets_sorted = {} + assets_sorted.update(assets_transport) + assets_sorted.update(assets_other) + # TODO: replace when python 3.8 is no longer supported + # assets_sorted = assets_transport | assets_other + + for asset in list(assets.values()): + converter.port_asset_type_connections(asset) + + for asset in list(assets_sorted.values()): + pycml_type, modifiers = converter.convert(asset) + self.add_variable(pycml_type, asset.name, **modifiers) + + in_suf = "HeatIn" + out_suf = "HeatOut" + node_suf = "HeatConn" + elec_in_suf = "ElectricityIn" + elec_out_suf = "ElectricityOut" + elec_node_suf = "ElectricityConn" + gas_in_suf = "GasIn" + gas_out_suf = "GasOut" + gas_node_suf = "GasConn" + + # TODO: check but I think the skip_assets is no longer needed + skip_asset_ids = {a.id for a in skip_assets} + + node_assets = [ + a + for a in assets.values() + if ( + (a.asset_type == "Joint") + and a.id not in skip_asset_ids + and ( + (isinstance(a.in_ports[0].carrier, esdl.HeatCommodity)) + or isinstance(a.out_ports[0].carrier, esdl.HeatCommodity) + ) + ) + ] + gas_node_assets = [ + a + for a in assets.values() + if ( + (a.asset_type == "Joint") + and a.id not in skip_asset_ids + and ( + (isinstance(a.in_ports[0].carrier, esdl.GasCommodity)) + or isinstance(a.out_ports[0].carrier, esdl.GasCommodity) + ) + ) + ] + bus_assets = [ + a for a in assets.values() if ((a.asset_type == "Bus") and a.id not in skip_asset_ids) + ] + non_node_assets = [ + a + for a in assets.values() + if (a.asset_type != "Joint" and a.asset_type != "Bus") and a.id not in skip_asset_ids + ] + + # First we map all port ids to their respective PyCML ports. We only + # do this for non-nodes, as for nodes we don't quite know what port + # index a connection has to use yet. + port_map = {} + + for asset in non_node_assets: + component = getattr(self, asset.name) + # We assume that every component has 2 ports. Essentially meaning that we are dealing + # with a single commodity for a component. Exceptions, assets that deal with multiple + # have to be specifically specified what port configuration is expected in the model. + if ( + asset.asset_type == "GenericConversion" + or asset.asset_type == "HeatExchange" + or asset.asset_type == "HeatPump" + ): + if prefix != "MILP": + raise Exception( + "Hydraulically decoulpled systems are not yet supported for nonlinear (QTH)" + "optimization" + ) + # check for expected number of ports + if len(asset.in_ports) == 2 and len(asset.out_ports) == 2: + for p in [*asset.in_ports, *asset.out_ports]: + if isinstance(p.carrier, esdl.HeatCommodity): + if isinstance(p, InPort): + if self.secondary_port_name_convention in p.name.lower(): + port_map[p.id] = getattr(component.Secondary, in_suf) + else: + port_map[p.id] = getattr(component.Primary, in_suf) + else: # OutPort + if self.primary_port_name_convention in p.name.lower(): + port_map[p.id] = getattr(component.Primary, out_suf) + else: + port_map[p.id] = getattr(component.Secondary, out_suf) + else: + raise Exception( + f"{asset.name} has does not have 2 Heat in_ports and 2 Heat " + f"out_ports " + ) + elif ( + len(asset.in_ports) == 3 + and len(asset.out_ports) == 2 + and asset.asset_type == "HeatPump" + ): + p_heat = 0 + p_elec = 0 + for p in [*asset.in_ports, *asset.out_ports]: + if isinstance(p.carrier, esdl.HeatCommodity) and p_heat <= 3: + if isinstance(p, InPort): + if self.secondary_port_name_convention in p.name.lower(): + port_map[p.id] = getattr(component.Secondary, in_suf) + else: + port_map[p.id] = getattr(component.Primary, in_suf) + else: # OutPort + if self.primary_port_name_convention in p.name.lower(): + port_map[p.id] = getattr(component.Primary, out_suf) + else: + port_map[p.id] = getattr(component.Secondary, out_suf) + p_heat += 1 + elif isinstance(p.carrier, esdl.ElectricityCommodity) and p_elec == 0: + port_map[p.id] = getattr(component, elec_in_suf) + p_elec += 1 + else: + raise Exception( + f"{asset.name} has total of 5 ports, but no proper split between " + f"milp(4) and electricity (1) ports" + ) + elif ( + asset.asset_type == "HeatPump" + and len(asset.out_ports) == 1 + and len(asset.in_ports) in [1, 2] + ): + for p in [*asset.in_ports, *asset.out_ports]: + + if isinstance(p, InPort) and isinstance( + p.carrier, esdl.ElectricityCommodity + ): + port_map[p.id] = getattr(component, elec_in_suf) + elif isinstance(p, InPort) and isinstance(p.carrier, esdl.HeatCommodity): + port_map[p.id] = getattr(component, in_suf) + elif isinstance(p, OutPort): # OutPort + port_map[p.id] = getattr(component, out_suf) + else: + raise Exception( + f"{asset.name} has does not have (1 electricity in_port) 1 heat " + f"in port and 1 Heat out_ports " + ) + else: + raise Exception( + f"{asset.name} has incorrect number of in/out ports. HeatPumps are allows " + f"to have 1 in and 1 out port for air-water HP, 2 in ports and 2 out ports " + f"when modelling a water-water HP, or 3 in ports and 2 out ports when the " + f"electricity connection of the water-water HP is modelled." + ) + elif ( + asset.asset_type == "GasHeater" + and len(asset.out_ports) == 1 + and len(asset.in_ports) == 2 + ): + for p in [*asset.in_ports, *asset.out_ports]: + + if isinstance(p, InPort) and isinstance(p.carrier, esdl.GasCommodity): + port_map[p.id] = getattr(component, gas_in_suf) + elif isinstance(p, InPort) and isinstance(p.carrier, esdl.HeatCommodity): + port_map[p.id] = getattr(component, in_suf) + elif isinstance(p, OutPort): # OutPort + port_map[p.id] = getattr(component, out_suf) + else: + raise Exception( + f"{asset.name} has does not have 1 Heat in_port 1 gas in port and 1" + f"Heat out_ports " + ) + elif ( + asset.asset_type == "ElectricBoiler" + and len(asset.out_ports) == 1 + and len(asset.in_ports) == 2 + ): + for p in [*asset.in_ports, *asset.out_ports]: + + if isinstance(p, InPort) and isinstance(p.carrier, esdl.ElectricityCommodity): + port_map[p.id] = getattr(component, elec_in_suf) + elif isinstance(p, InPort) and isinstance(p.carrier, esdl.HeatCommodity): + port_map[p.id] = getattr(component, in_suf) + elif isinstance(p, OutPort): # OutPort + port_map[p.id] = getattr(component, out_suf) + else: + raise Exception( + f"{asset.name} has does not have 1 electricity in_port 1 gas in port " + f"and 1 Heat out_ports " + ) + elif asset.asset_type == "Electrolyzer": + if len(asset.out_ports) == 1 and len(asset.in_ports) == 1: + if isinstance(asset.out_ports[0].carrier, esdl.GasCommodity): + port_map[asset.out_ports[0].id] = getattr(component, gas_out_suf) + else: + raise Exception(f"{asset.name} must have a gas commodity on the outport") + if isinstance(asset.in_ports[0].carrier, esdl.ElectricityCommodity): + port_map[asset.in_ports[0].id] = getattr(component, elec_in_suf) + else: + raise Exception( + f"{asset.name} must have a electricity commodity on the inport " + ) + else: + raise Exception( + f"{asset.name} must have one inport for electricity and one outport for gas" + ) + elif ( + asset.in_ports is None + and isinstance(asset.out_ports[0].carrier, esdl.ElectricityCommodity) + and len(asset.out_ports) == 1 + ): + port_map[asset.out_ports[0].id] = getattr(component, elec_out_suf) + elif ( + asset.in_ports is None + and isinstance(asset.out_ports[0].carrier, esdl.GasCommodity) + and len(asset.out_ports) == 1 + ): + port_map[asset.out_ports[0].id] = getattr(component, gas_out_suf) + elif ( + len(asset.in_ports) == 1 + and isinstance(asset.in_ports[0].carrier, esdl.ElectricityCommodity) + and asset.out_ports is None + ): + port_map[asset.in_ports[0].id] = getattr(component, elec_in_suf) + elif ( + len(asset.in_ports) == 1 + and isinstance(asset.in_ports[0].carrier, esdl.GasCommodity) + and asset.out_ports is None + ): + port_map[asset.in_ports[0].id] = getattr(component, gas_in_suf) + elif ( + len(asset.in_ports) == 1 + and isinstance(asset.in_ports[0].carrier, esdl.HeatCommodity) + and len(asset.out_ports) == 1 + ): + port_map[asset.in_ports[0].id] = getattr(component, in_suf) + port_map[asset.out_ports[0].id] = getattr(component, out_suf) + elif ( + len(asset.in_ports) == 1 + and isinstance(asset.in_ports[0].carrier, esdl.ElectricityCommodity) + and len(asset.out_ports) == 1 + ): + port_map[asset.in_ports[0].id] = getattr(component, elec_in_suf) + port_map[asset.out_ports[0].id] = getattr(component, elec_out_suf) + elif ( + len(asset.in_ports) == 1 + and isinstance(asset.in_ports[0].carrier, esdl.GasCommodity) + and len(asset.out_ports) == 1 + ): + port_map[asset.in_ports[0].id] = getattr(component, gas_in_suf) + port_map[asset.out_ports[0].id] = getattr(component, gas_out_suf) + else: + raise Exception(f"Unsupported ports for asset type {asset.name}.") + + # Nodes are special in that their in/out ports can have multiple + # connections. This means we have some bookkeeping to do per node. We + # therefore do the nodes first, and do all remaining connections + # after. + connections = set() + + for asset in [*node_assets, *bus_assets, *gas_node_assets]: + component = getattr(self, asset.name) + + i = 1 + if len(asset.in_ports) != 1 or len(asset.out_ports) != 1: + Exception( + f"{asset.name} has !=1 in or out ports, please only use one, " + f"multiple connections to a single joint port are allowed" + ) + for port in (asset.in_ports[0], asset.out_ports[0]): + for connected_to in port.connectedTo.items: + conn = (port.id, connected_to.id) + # Here we skip the adding of the connection if we already had the reverse + # connection. Note that we don't do that for logical links between nodes, as we + # need both connections in order to make the topology object in + # component_type_mixin.py. + if connected_to.id in list(port_map.keys()) and ( + conn in connections or tuple(reversed(conn)) in connections + ): + continue + if isinstance(port.carrier, esdl.HeatCommodity): + # First we check if the connected_to.id is in the port_map and if the + # connected aasset is of type Pipe. In this case we want to fully connect + # the model with head losses and hydraulic power. + if ( + connected_to.id in list(port_map.keys()) + and assets[ + name_to_id_map[port_map[connected_to.id].name.split(".")[0]] + ].asset_type + == "Pipe" + ): + self.connect(getattr(component, node_suf)[i], port_map[connected_to.id]) + elif connected_to.id not in list(port_map.keys()): + # If The asset is not in the + # port map means that there is a direct node to node connection with a + # logical link. Here we need to do some tricks to recover the correct + # port index of the node. + for node in node_assets: + if connected_to.id in [node.in_ports[0].id, node.out_ports[0].id]: + connected_node_asset = node + count = 1 + for ct in [ + *list(node.in_ports[0].connectedTo), + *list(node.out_ports[0].connectedTo), + ]: + if ct.id == port.id: + idx = count + else: + count += 1 + self.connect_logical_links( + getattr(component, node_suf)[i], + getattr(getattr(self, connected_node_asset.name), node_suf)[idx], + ) + else: + # If the Connected asset is not of type pipe, there might be + # logical link like source to node. + self.connect_logical_links( + getattr(component, node_suf)[i], port_map[connected_to.id] + ) + connections.add(conn) + i += 1 + elif isinstance(port.carrier, esdl.ElectricityCommodity): + # Same logic as for heat see comments there + if ( + connected_to.id in list(port_map.keys()) + and assets[ + name_to_id_map[port_map[connected_to.id].name.split(".")[0]] + ].asset_type + == "ElectricityCable" + ): + self.connect( + getattr(component, elec_node_suf)[i], port_map[connected_to.id] + ) + elif connected_to.id not in list(port_map.keys()): + for node in bus_assets: + if connected_to.id in [node.in_ports[0].id, node.out_ports[0].id]: + connected_node_asset = node + count = 1 + for ct in [ + *list(node.in_ports[0].connectedTo), + *list(node.out_ports[0].connectedTo), + ]: + if ct.id == port.id: + idx = count + else: + count += 1 + self.connect_logical_links( + getattr(component, elec_node_suf)[i], + getattr(getattr(self, connected_node_asset.name), elec_node_suf)[ + idx + ], + ) + else: + self.connect_logical_links( + getattr(component, elec_node_suf)[i], + port_map[connected_to.id], + ) + connections.add(conn) + i += 1 + elif isinstance(port.carrier, esdl.GasCommodity): + # Same logic as for heat see comments there + if ( + connected_to.id in list(port_map.keys()) + and assets[ + name_to_id_map[port_map[connected_to.id].name.split(".")[0]] + ].asset_type + == "Pipe" + ): + self.connect( + getattr(component, gas_node_suf)[i], port_map[connected_to.id] + ) + elif connected_to.id not in list(port_map.keys()): + for node in gas_node_assets: + if connected_to.id in [node.in_ports[0].id, node.out_ports[0].id]: + connected_node_asset = node + count = 1 + for ct in [ + *list(node.in_ports[0].connectedTo), + *list(node.out_ports[0].connectedTo), + ]: + if ct.id == port.id: + idx = count + else: + count += 1 + self.connect_logical_links( + getattr(component, gas_node_suf)[i], + getattr(getattr(self, connected_node_asset.name), gas_node_suf)[ + idx + ], + ) + else: + self.connect_logical_links( + getattr(component, gas_node_suf)[i], port_map[connected_to.id] + ) + connections.add(conn) + i += 1 + else: + logger.error( + f"asset {asset.name} has an unsupported carrier type for a node" + ) + + skip_port_ids = set() + for a in skip_assets: + if a.in_ports is not None: + for port in a.in_ports: + skip_port_ids.add(port.id) + if a.out_ports is not None: + for port in a.out_ports: + skip_port_ids.add(port.id) + + # All non-Joints/nodes + for asset in non_node_assets: + ports = [] + if asset.in_ports is not None: + ports.extend(asset.in_ports) + if asset.out_ports is not None: + ports.extend(asset.out_ports) + assert len(ports) > 0 + for port in ports: + connected_ports = [p for p in port.connectedTo.items if p.id not in skip_port_ids] + if len(connected_ports) != 1: + logger.warning( + f"{asset.asset_type} '{asset.name}' has multiple connections" + f" to a single port. " + ) + + assert len(connected_ports) == 1 + + for connected_to in connected_ports: + conn = (port.id, connected_to.id) + if conn in connections or tuple(reversed(conn)) in connections: + continue + if ( + asset.asset_type == "Pipe" + or asset.asset_type == "ElectricityCable" + or assets[ + name_to_id_map[port_map[connected_to.id].name.split(".")[0]] + ].asset_type + == "Pipe" + or assets[ + name_to_id_map[port_map[connected_to.id].name.split(".")[0]] + ].asset_type + == "ElectricityCable" + ): + self.connect(port_map[port.id], port_map[connected_to.id]) + else: + self.connect_logical_links(port_map[port.id], port_map[connected_to.id]) + connections.add(conn) diff --git a/src/rtctools_heat_network/esdl/esdl_parser.py b/src/mesido/esdl/esdl_parser.py similarity index 99% rename from src/rtctools_heat_network/esdl/esdl_parser.py rename to src/mesido/esdl/esdl_parser.py index bbed8d0e5..1a1707ee9 100644 --- a/src/rtctools_heat_network/esdl/esdl_parser.py +++ b/src/mesido/esdl/esdl_parser.py @@ -4,7 +4,7 @@ import esdl.esdl_handler -from .common import Asset +from mesido.esdl.common import Asset class _ESDLInputException(Exception): diff --git a/src/rtctools_heat_network/esdl/esdl_qth_model.py b/src/mesido/esdl/esdl_qth_model.py similarity index 97% rename from src/rtctools_heat_network/esdl/esdl_qth_model.py rename to src/mesido/esdl/esdl_qth_model.py index 651d05d80..6490b2c13 100644 --- a/src/rtctools_heat_network/esdl/esdl_qth_model.py +++ b/src/mesido/esdl/esdl_qth_model.py @@ -4,8 +4,11 @@ import esdl -from rtctools_heat_network.pycml import SymbolicParameter -from rtctools_heat_network.pycml.component_library.qth import ( +from mesido.esdl.asset_to_component_base import MODIFIERS, _AssetToComponentBase +from mesido.esdl.common import Asset +from mesido.esdl.esdl_model_base import _ESDLModelBase +from mesido.pycml import SymbolicParameter +from mesido.pycml.component_library.qth import ( Buffer, CheckValve, ControlValve, @@ -17,11 +20,7 @@ Source, ) -from .asset_to_component_base import MODIFIERS, _AssetToComponentBase -from .common import Asset -from .esdl_model_base import _ESDLModelBase - -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") class AssetToQTHComponent(_AssetToComponentBase): diff --git a/src/rtctools_heat_network/esdl/profile_parser.py b/src/mesido/esdl/profile_parser.py similarity index 66% rename from src/rtctools_heat_network/esdl/profile_parser.py rename to src/mesido/esdl/profile_parser.py index 712fa6906..9ca69d5ff 100644 --- a/src/rtctools_heat_network/esdl/profile_parser.py +++ b/src/mesido/esdl/profile_parser.py @@ -1,5 +1,6 @@ import datetime import logging +import sys from collections import defaultdict from pathlib import Path from typing import Dict, Optional, Set @@ -9,6 +10,9 @@ from esdl.profiles.influxdbprofilemanager import InfluxDBProfileManager from esdl.units.conversion import ENERGY_IN_J, POWER_IN_W, convert_to_unit +from mesido.esdl.common import Asset +from mesido.potential_errors import MesidoAssetIssueType, get_potential_errors + import numpy as np import pandas as pd @@ -16,8 +20,6 @@ import rtctools.data.pi from rtctools.data.storage import DataStore -from rtctools_heat_network.esdl.common import Asset - logger = logging.getLogger() @@ -30,6 +32,7 @@ class _ProfileParserException(Exception): class BaseProfileReader: component_type_to_var_name_map: dict = { + "cold_demand": ".target_cold_demand", "heat_demand": ".target_heat_demand", "heat_source": ".maximum_heat_source", "electricity_demand": ".target_electricity_demand", @@ -37,6 +40,7 @@ class BaseProfileReader: "gas_demand": ".target_gas_demand", "gas_source": ".maximum_gas_source", } + carrier_profile_var_name: str = ".price_profile" def __init__(self, energy_system: esdl.EnergySystem, file_path: Optional[Path]): @@ -103,6 +107,9 @@ def read_profiles( for component_type, var_name in self.component_type_to_var_name_map.items(): for component in energy_system_components.get(component_type, []): profile = self._profiles[ensemble_member].get(component + var_name, None) + asset_power = esdl_assets[esdl_asset_names_to_ids[component]].attributes[ + "power" + ] if profile is not None: values = profile else: @@ -113,9 +120,6 @@ def read_profiles( f"No profile provided for {component=} and " f"{ensemble_member=}, using the assets power value instead" ) - asset_power = esdl_assets[esdl_asset_names_to_ids[component]].attributes[ - "power" - ] values = np.array([asset_power] * len(self._reference_datetimes)) io.set_timeseries( @@ -124,6 +128,36 @@ def read_profiles( values=values, ensemble_member=ensemble_member, ) + # Check if that the installed heat/cool demand capacity is sufficient + if component_type in ["heat_demand", "cold_demand"]: + max_profile_value = max(values) + if asset_power < max_profile_value and asset_power != 0.0: + asset_id = esdl_asset_names_to_ids[component] + get_potential_errors().add_potential_issue( + ( + MesidoAssetIssueType.HEAT_DEMAND_POWER + if component_type == "heat_demand" + else MesidoAssetIssueType.COLD_DEMAND_POWER + ), + asset_id, + f"Asset named {component}: The installed capacity of" + f" {round(asset_power / 1.0e6, 3)}MW should be larger than the" + " maximum of the heat demand profile " + f"{round(max_profile_value / 1.0e6, 3)}MW", + ) + elif component_type in ["heat_source"]: + max_profile_value = max(values) + if asset_power < max_profile_value: + asset_id = esdl_asset_names_to_ids[component] + get_potential_errors().add_potential_issue( + MesidoAssetIssueType.HEAT_PRODUCER_POWER, + asset_id, + f"Asset named {component}: The installed capacity of" + f" {round(asset_power / 1.0e6, 3)}MW should be equal or larger than" + " the maximum of the heat producer maximum profile constraint" + f" {round(max_profile_value / 1.0e6, 3)}MW", + ) + for properties in carrier_properties.values(): carrier_name = properties["name"] profile = self._profiles[ensemble_member].get( @@ -174,6 +208,7 @@ def _load_profiles_from_source( class InfluxDBProfileReader(BaseProfileReader): asset_type_to_variable_name_conversion = { esdl.esdl.HeatingDemand: ".target_heat_demand", + esdl.esdl.GenericConsumer: ".target_heat_demand", esdl.esdl.HeatProducer: ".maximum_heat_source", esdl.esdl.ElectricityDemand: ".target_electricity_demand", esdl.esdl.ElectricityProducer: ".maximum_electricity_source", @@ -195,42 +230,122 @@ def _load_profiles_from_source( profiles: Dict[str, np.ndarray] = dict() logger.info("Reading profiles from InfluxDB") self._reference_datetimes = None + + # Get list of unique profiles and associated series based on specific profile attributes + unique_profiles = [] + unique_profiles_attributes = [] # a list containning lists of attributes + unique_series = [] + for profile in [ + x for x in self._energy_system.eAllContents() if isinstance(x, esdl.InfluxDBProfile) + ]: + if [ + profile.database, + profile.field, + profile.host, + profile.startDate, + profile.endDate, + profile.measurement, + profile.port, + ] not in unique_profiles_attributes: + unique_profiles_attributes.append( + [ + profile.database, + profile.field, + profile.host, + profile.startDate, + profile.endDate, + profile.measurement, + profile.port, + ] + ) + unique_profiles.append(profile) + + unique_series.append( + self._load_profile_timeseries_from_database(profile=unique_profiles[-1]) + ) + self._check_profile_time_series( + profile_time_series=unique_series[-1], profile=unique_profiles[-1] + ) + if self._reference_datetimes is None: + # TODO: since the previous function ensures it's a date time index, I'm not sure + # how to get rid of this type checking warning + self._reference_datetimes = unique_series[-1].index + else: + if not all(unique_series[-1].index == self._reference_datetimes): + raise RuntimeError( + f"Obtained a profile for asset {profile.field} with a " + f"timeseries index that doesn't match the timeseries of " + f"other assets. Please ensure that the profile that is " + f"specified to be loaded for each asset covers exactly the " + f"same timeseries. " + ) + # Loop trough all the requried profiles in the energy system and assign the profile data: + # - series: use the unique series data, without reading from the database again + # - other profile info: get it from the specific profile for profile in [ x for x in self._energy_system.eAllContents() if isinstance(x, esdl.InfluxDBProfile) ]: - series = self._load_profile_timeseries_from_database(profile=profile) + index_of_unique_profile = unique_profiles_attributes.index( + [ + profile.database, + profile.field, + profile.host, + profile.startDate, + profile.endDate, + profile.measurement, + profile.port, + ] + ) + series = unique_series[index_of_unique_profile] self._check_profile_time_series(profile_time_series=series, profile=profile) - if self._reference_datetimes is None: - # TODO: since the previous function ensures it's a date time index, I'm not sure - # how to get rid of this type checking warning - self._reference_datetimes = series.index - else: - if not all(series.index == self._reference_datetimes): - raise RuntimeError( - f"Obtained a profile for asset {profile.field} with a " - f"timeseries index that doesn't match the timeseries of " - f"other assets. Please ensure that the profile that is " - f"specified to be loaded for each asset covers exactly the " - f"same timeseries. " - ) converted_dataframe = self._convert_profile_to_correct_unit( profile_time_series=series, profile=profile ) container = profile.eContainer() - if isinstance(container, esdl.Commodity): + if isinstance(container, esdl.ProfileConstraint): + asset = container.eContainer() + variable_suffix = self.asset_type_to_variable_name_conversion[type(asset)] + var_base_name = asset.name + if variable_suffix in [ + self.asset_type_to_variable_name_conversion[esdl.esdl.GasProducer], + self.asset_type_to_variable_name_conversion[esdl.esdl.ElectricityProducer], + ]: + logger.error( + f"Profiles for {var_base_name} from esdl has not been tested yet but only" + " for heat sources" + ) + sys.exit(1) + + elif isinstance(container, esdl.Commodity): variable_suffix = self.carrier_profile_var_name var_base_name = container.name elif isinstance(container, esdl.Port): asset = container.energyasset var_base_name = asset.name + if var_base_name in [ + self.asset_type_to_variable_name_conversion[esdl.esdl.GasProducer], + self.asset_type_to_variable_name_conversion[esdl.esdl.ElectricityProducer], + ]: + logger.error(f"Profiles for {var_base_name} from esdl has not been tested yet") + sys.exit(1) try: variable_suffix = self.asset_type_to_variable_name_conversion[type(asset)] + # For multicommidity work profiles need to be assigned to GenericConsumer, but + # not for heat network (this asset_potential_errors is used in grow_workflow) + if type(asset) is esdl.GenericConsumer: + get_potential_errors().add_potential_issue( + MesidoAssetIssueType.HEAT_DEMAND_TYPE, + asset.id, + f"Asset named {asset.name}: This asset is currently a GenericConsumer" + " please change it to a HeatingDemand", + ) except KeyError: - raise RuntimeError( - f"The asset {profile.field} is of type {type(asset)} which is " - f"currently not supported to have a profile to be loaded " - f"from the database." + get_potential_errors().add_potential_issue( + MesidoAssetIssueType.ASSET_PROFILE_CAPABILITY, + asset.id, + f"Asset named {asset.name}: The assigment of profile field {profile.field}" + f" is not possible for this asset type {type(asset)}", ) else: raise RuntimeError( @@ -290,7 +405,7 @@ def _load_profile_timeseries_from_database(self, profile: esdl.InfluxDBProfile) time_series_data = InfluxDBProfileManager(conn_settings) time_series_data.load_influxdb( - '"' + profile.measurement + '"', + profile.measurement, [profile.field], profile.startDate, profile.endDate, @@ -303,7 +418,15 @@ def _load_profile_timeseries_from_database(self, profile: esdl.InfluxDBProfile) "profile for each asset" ) - index = pd.DatetimeIndex(data=[x[0] for x in time_series_data.profile_data_list]) + if not time_series_data.profile_data_list[0][0].tzinfo: + index = pd.DatetimeIndex( + data=[x[0] for x in time_series_data.profile_data_list], + tz=datetime.timezone.utc, + ) + logger.warning("No timezone specified for the input profile: default UTC has been used") + else: + index = pd.DatetimeIndex(data=[x[0] for x in time_series_data.profile_data_list]) + data = [x[1] for x in time_series_data.profile_data_list] series = pd.Series(data=data, index=index) self._df[profile.id] = series @@ -347,6 +470,11 @@ def _check_profile_time_series( f"The timestep for variable {profile.field} between {d1} and {d2} isn't " f"exactly 1 hour" ) + # Check if any NaN values exist + if profile_time_series.isnull().any().any(): + raise Exception( + f"Nan value was encountered in the profile data for variable {profile.field}" + ) def _convert_profile_to_correct_unit( self, profile_time_series: pd.Series, profile: esdl.InfluxDBProfile @@ -365,8 +493,23 @@ def _convert_profile_to_correct_unit( converted to either Watt or Joules, depending on the quantity used in the profile. """ profile_quantity_and_unit = self._get_profile_quantity_and_unit(profile=profile) - if profile_quantity_and_unit.physicalQuantity == esdl.PhysicalQuantityEnum.POWER: - target_unit = POWER_IN_W + if ( + profile_quantity_and_unit.physicalQuantity == esdl.PhysicalQuantityEnum.POWER + or profile_quantity_and_unit.physicalQuantity == esdl.PhysicalQuantityEnum.COEFFICIENT + ): + if profile_quantity_and_unit.unit == esdl.UnitEnum.WATT: + target_unit = POWER_IN_W + elif profile_quantity_and_unit.unit == esdl.UnitEnum.PERCENT: # values 0-100% + # TODO: in the future change to ratios if needed + return profile_time_series # These profiles are scaled in asset sizing + elif profile_quantity_and_unit.unit == esdl.UnitEnum.NONE: # ratio 0-1 + return profile_time_series + else: + raise RuntimeError( + f"Power profiles currently only support units" + f"specified in Watts or Percentage," + f"{profile} doesn't follow this convention." + ) elif profile_quantity_and_unit.physicalQuantity == esdl.PhysicalQuantityEnum.ENERGY: target_unit = ENERGY_IN_J elif profile_quantity_and_unit.physicalQuantity == esdl.PhysicalQuantityEnum.COST: @@ -386,10 +529,11 @@ def _convert_profile_to_correct_unit( f"either power, energy values or euros per Wh, not " f"{profile_quantity_and_unit.physicalQuantity}." ) - return profile_time_series.apply( - func=lambda x: convert_to_unit( - value=x, source_unit=profile_quantity_and_unit, target_unit=target_unit - ) + # The vectorized method below is used instead of profile_time_series.apply(), due to a + # computational cost reduction (order of 2000 times faster for a profile with 8760 + # timesteps) + return profile_time_series * convert_to_unit( + value=1.0, source_unit=profile_quantity_and_unit, target_unit=target_unit ) @staticmethod @@ -437,32 +581,54 @@ def _load_csv( ensemble_size: int, ) -> None: data = pd.read_csv(self._file_path) + + if len(data.filter(like="Unnamed").columns) > 0: + raise Exception( + f"An unnamed column has been found in profile source file: {self._file_path}" + ) + try: timeseries_import_times = [ - datetime.datetime.strptime(entry.replace("Z", ""), "%Y-%m-%d %H:%M:%S") + datetime.datetime.strptime(entry.replace("Z", ""), "%Y-%m-%d %H:%M:%S").replace( + tzinfo=datetime.timezone.utc + ) for entry in data["DateTime"].to_numpy() ] except ValueError: try: timeseries_import_times = [ - datetime.datetime.strptime(entry.replace("Z", ""), "%Y-%m-%dT%H:%M:%S") + datetime.datetime.strptime(entry.replace("Z", ""), "%Y-%m-%dT%H:%M:%S").replace( + tzinfo=datetime.timezone.utc + ) for entry in data["DateTime"].to_numpy() ] except ValueError: try: timeseries_import_times = [ - datetime.datetime.strptime(entry.replace("Z", ""), "%d-%m-%Y %H:%M") + datetime.datetime.strptime( + entry.replace("Z", ""), "%d-%m-%Y %H:%M" + ).replace(tzinfo=datetime.timezone.utc) for entry in data["DateTime"].to_numpy() ] except ValueError: raise _ProfileParserException("Date time string is not in a supported format") + logger.warning("Timezone specification not supported yet: default UTC has been used") + self._reference_datetimes = timeseries_import_times + for ensemble_member in range(ensemble_size): for component_type, var_name in self.component_type_to_var_name_map.items(): for component_name in energy_system_components.get(component_type, []): try: - values = data[f"{component_name.replace(' ', '')}"].to_numpy() + column_name = f"{component_name.replace(' ', '')}" + values = data[column_name].to_numpy() + if np.isnan(values).any(): + raise Exception( + f"Column name: {column_name}, NaN exists in the profile source" + f" file {self._file_path}." + f" Detials: {data[data[column_name].isnull()]}" + ) except KeyError: pass else: @@ -471,6 +637,11 @@ def _load_csv( carrier_name = properties.get("name") try: values = data[carrier_name].to_numpy() + if np.isnan(values).any(): + raise Exception( + f"Carrier name: {carrier_name}, NaN exists in the profile source file" + f" {self._file_path}. Details: {data[data[carrier_name].isnull()]}" + ) except KeyError: pass else: @@ -498,6 +669,11 @@ def _load_xml(self, energy_system_components, esdl_asset_id_to_name_map): ) # Convert timeseries timestamps to seconds since t0 for internal use + if not data.times[0].tzinfo: + for ii in range(len(data.times)): + data.times[ii] = data.times[ii].replace(tzinfo=datetime.timezone.utc) + logger.warning("No timezone specified for the input profile: default UTC has been used") + self._reference_datetimes = data.times # Offer input timeseries to IOMixin diff --git a/src/mesido/exceptions.py b/src/mesido/exceptions.py new file mode 100644 index 000000000..853706b20 --- /dev/null +++ b/src/mesido/exceptions.py @@ -0,0 +1,63 @@ +from typing import Dict, TYPE_CHECKING, Tuple, Type + +if TYPE_CHECKING: # This prevents circular referencing between this file and potential_errors.py + from mesido.potential_errors import ErrorMessage, MesidoAssetIssueType + + +class MesidoAssetIssueError(Exception): + """ + This class is used as a MESIDO defined exception class. + """ + + error_type: "MesidoAssetIssueType" + general_issue: str + message_per_asset_id: Dict[str, "ErrorMessage"] + + def __init__( + self, + general_issue: str, + error_type: "MesidoAssetIssueType", + message_per_asset_id: Dict[str, "ErrorMessage"], + ): + + self.error_type = error_type + self.general_issue = general_issue + self.message_per_asset_id = message_per_asset_id + + def __str__(self) -> str: + """ + Returns + ------- + A string containing the following: + - Error type (e.g.HEAT_DEMAND_POWER) + - General meassage about the group of error messages per asset id + - Asset id + - Error message for the applicable asset + """ + return_string = f"{self.error_type}: {self.general_issue}" + for keys, values in self.message_per_asset_id.items(): + return_string += f"\nAsset id: {keys}" + return_string += f" {values}" + + return return_string + + # Currently this function has been added for Design Toolkit back end purposes + def __reduce__( + self, + ) -> Tuple[ + Type["MesidoAssetIssueError"], Tuple[str, "MesidoAssetIssueType", Dict[str, "ErrorMessage"]] + ]: + """Reduce an instance of this class to pickable components. + + This is required so the class can be serialized and deserialized in the pickle format. + + Returns + ------- + A tuple containing: + - The class + - Separate arguments of this instance + """ + return ( + MesidoAssetIssueError, + (self.general_issue, self.error_type, self.message_per_asset_id), + ) diff --git a/src/rtctools_heat_network/financial_mixin.py b/src/mesido/financial_mixin.py similarity index 87% rename from src/rtctools_heat_network/financial_mixin.py rename to src/mesido/financial_mixin.py index e016f0cbb..53fbee500 100644 --- a/src/rtctools_heat_network/financial_mixin.py +++ b/src/mesido/financial_mixin.py @@ -3,6 +3,8 @@ import casadi as ca +from mesido.base_component_type_mixin import BaseComponentTypeMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -10,9 +12,7 @@ ) from rtctools.optimization.timeseries import Timeseries -from .base_component_type_mixin import BaseComponentTypeMixin - -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") class FinancialMixin(BaseComponentTypeMixin, CollocatedIntegratedOptimizationProblem): @@ -113,6 +113,22 @@ def pre(self): continue elif asset_name in [*self.energy_system_components.get("ates", [])]: nominal_fixed_operational = self.variable_nominal(f"{asset_name}.Heat_ates") + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) + nominal_variable_operational = nominal_fixed_operational + nominal_investment = nominal_fixed_operational + elif asset_name in [*self.energy_system_components.get("low_temperature_ates", [])]: + nominal_fixed_operational = self.variable_nominal( + f"{asset_name}.Heat_low_temperature_ates" + ) + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = nominal_fixed_operational nominal_investment = nominal_fixed_operational elif asset_name in [*self.energy_system_components.get("heat_demand", [])]: @@ -121,26 +137,56 @@ def pre(self): if not np.isinf(bounds[f"{asset_name}.Heat_demand"][1]) else bounds[f"{asset_name}.HeatIn.Heat"][1] ) + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = nominal_fixed_operational nominal_investment = nominal_fixed_operational elif asset_name in [*self.energy_system_components.get("heat_source", [])]: nominal_fixed_operational = self.variable_nominal(f"{asset_name}.Heat_source") + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = nominal_fixed_operational nominal_investment = nominal_fixed_operational elif asset_name in [*self.energy_system_components.get("heat_pipe", [])]: nominal_fixed_operational = max(parameters[f"{asset_name}.length"], 1.0) + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = nominal_fixed_operational nominal_investment = nominal_fixed_operational elif asset_name in [*self.energy_system_components.get("electricity_cable", [])]: nominal_fixed_operational = max(parameters[f"{asset_name}.length"], 1.0) + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = nominal_fixed_operational nominal_investment = nominal_fixed_operational elif asset_name in [*self.energy_system_components.get("gas_pipe", [])]: nominal_fixed_operational = max(parameters[f"{asset_name}.length"], 1.0) + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = nominal_fixed_operational nominal_investment = nominal_fixed_operational elif asset_name in [*self.energy_system_components.get("heat_buffer", [])]: nominal_fixed_operational = self.variable_nominal(f"{asset_name}.Stored_heat") + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = self.variable_nominal(f"{asset_name}.Heat_buffer") nominal_investment = nominal_fixed_operational elif asset_name in [ @@ -153,18 +199,63 @@ def pre(self): # TODO: set the nominal values below elif asset_name in [*self.energy_system_components.get("gas_tank_storage", [])]: nominal_fixed_operational = bounds[f"{asset_name}.Stored_gas_mass"][1] + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = nominal_fixed_operational nominal_investment = nominal_fixed_operational elif asset_name in [*self.energy_system_components.get("electricity_demand", [])]: nominal_fixed_operational = bounds[f"{asset_name}.Electricity_demand"][1] + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = nominal_fixed_operational nominal_investment = nominal_fixed_operational elif asset_name in [*self.energy_system_components.get("electrolyzer", [])]: nominal_fixed_operational = bounds[f"{asset_name}.Power_consumed"][1] + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = nominal_fixed_operational nominal_investment = nominal_fixed_operational - elif asset_name in [*self.energy_system_components.get("wind_park", [])]: - nominal_fixed_operational = bounds[f"{asset_name}.Set_point"][1] + elif asset_name in [*self.energy_system_components.get("electricity_source", [])]: + max_power = ( + bounds[f"{asset_name}.ElectricityOut.Power"][1] + if (isinstance(bounds[f"{asset_name}.ElectricityOut.Power"][1], float)) + else max(bounds[f"{asset_name}.ElectricityOut.Power"][1].values) + ) + nominal_fixed_operational = max_power + nominal_variable_operational = nominal_fixed_operational + nominal_investment = nominal_fixed_operational + elif asset_name in [*self.energy_system_components.get("electricity_storage", [])]: + nominal_fixed_operational = bounds[f"{asset_name}.Stored_electricity"][1] + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) + nominal_variable_operational = nominal_fixed_operational + nominal_investment = nominal_fixed_operational + elif asset_name in [ + *self.energy_system_components.get("gas_demand", []), + *self.energy_system_components.get("gas_source", []), + ]: + if asset_name in [*self.energy_system_components.get("gas_demand", [])]: + nominal_fixed_operational = bounds[f"{asset_name}.Gas_demand_mass_flow"][1] + elif asset_name in [*self.energy_system_components.get("gas_source", [])]: + nominal_fixed_operational = bounds[f"{asset_name}.Gas_source_mass_flow"][1] + + nominal_fixed_operational = ( + nominal_fixed_operational + if isinstance(nominal_fixed_operational, float) + else max(nominal_fixed_operational.values) + ) nominal_variable_operational = nominal_fixed_operational nominal_investment = nominal_fixed_operational else: @@ -342,6 +433,7 @@ def pre(self): *self.energy_system_components.get("heat_source", []), *self.energy_system_components.get("heat_demand", []), *self.energy_system_components.get("ates", []), + *self.energy_system_components.get("low_temperature_ates", []), *self.energy_system_components.get("heat_buffer", []), *self.energy_system_components.get("heat_pipe", []), *self.energy_system_components.get("heat_exchanger", []), @@ -367,6 +459,7 @@ def pre(self): *self.energy_system_components.get("heat_source", []), *self.energy_system_components.get("heat_demand", []), *self.energy_system_components.get("ates", []), + *self.energy_system_components.get("low_temperature_ates", []), *self.energy_system_components.get("heat_buffer", []), *self.energy_system_components.get("heat_exchanger", []), *self.energy_system_components.get("heat_pump", []), @@ -784,6 +877,7 @@ def __variable_operational_cost_constraints(self, ensemble_member): for asset in [ *self.energy_system_components.get("ates", []), + *self.energy_system_components.get("low_temperature_ates", []), *self.energy_system_components.get("heat_buffer", []), *self.energy_system_components.get("pump", []), *self.energy_system_components.get("heat_exchanger", []), @@ -838,15 +932,28 @@ def __variable_operational_cost_constraints(self, ensemble_member): assert len(self.get_electricity_carriers().keys()) <= 1 if len(self.get_electricity_carriers().keys()) == 1: - price_profile = self.get_timeseries( - f"{list(self.get_electricity_carriers().values())[0]['name']}.price_profile" - ) + try: + price_profile = self.get_timeseries( + f"{list(self.get_electricity_carriers().values())[0]['name']}.price_profile" + ) + except KeyError: + price_profile = Timeseries(self.times(), np.zeros(len(self.times()))) else: price_profile = Timeseries(self.times(), np.zeros(len(self.times()))) + denominator = 1.0 + if s in self.energy_system_components.get( + "air_water_heat_pump", [] + ) or s in self.energy_system_components.get("air_water_heat_pump_elec", []): + denominator = parameters[f"{s}.cop"] sum = 0.0 for i in range(1, len(self.times())): - sum += variable_operational_cost_coefficient * heat_source[i] * timesteps[i - 1] + sum += ( + variable_operational_cost_coefficient + * heat_source[i] + * timesteps[i - 1] + / denominator + ) sum += price_profile.values[i] * pump_power[i] * timesteps[i - 1] / eff constraints.append(((variable_operational_cost - sum) / nominal, 0.0, 0.0)) @@ -916,6 +1023,46 @@ def __variable_operational_cost_constraints(self, ensemble_member): constraints.append(((variable_operational_cost - sum) / nominal, 0.0, 0.0)) + for gs in self.energy_system_components.get("gas_source", []): + gas_produced_g_s = self.__state_vector_scaled( + f"{gs}.Gas_source_mass_flow", ensemble_member + ) + variable_operational_cost_var = self._asset_variable_operational_cost_map[gs] + variable_operational_cost = self.extra_variable( + variable_operational_cost_var, ensemble_member + ) + nominal = self.variable_nominal(variable_operational_cost_var) + variable_operational_cost_coefficient = parameters[ # euro / g + f"{gs}.variable_operational_cost_coefficient" + ] + timesteps = np.diff(self.times()) + sum = 0.0 + for i in range(1, len(self.times())): + sum += ( + variable_operational_cost_coefficient * gas_produced_g_s[i] * timesteps[i - 1] + ) # [euro/g] * [g/s] * [s] + constraints.append(((variable_operational_cost - sum) / nominal, 0.0, 0.0)) + + for es in self.energy_system_components.get("electricity_source", []): + elec_produced_w = self.__state_vector_scaled( + f"{es}.Electricity_source", ensemble_member + ) + variable_operational_cost_var = self._asset_variable_operational_cost_map[es] + variable_operational_cost = self.extra_variable( + variable_operational_cost_var, ensemble_member + ) + nominal = self.variable_nominal(variable_operational_cost_var) + variable_operational_cost_coefficient = parameters[ # euro / Wh + f"{es}.variable_operational_cost_coefficient" + ] + timesteps = np.diff(self.times()) / 3600.0 # convert dt from [s] to [hr] + sum = 0.0 + for i in range(1, len(self.times())): + sum += ( + variable_operational_cost_coefficient * elec_produced_w[i] * timesteps[i - 1] + ) # [euro/Wh] * [W] * [hr] + constraints.append(((variable_operational_cost - sum) / nominal, 0.0, 0.0)) + # for a in self.heat_network_components.get("ates", []): # TODO: needs to be replaced with the positive or abs value of this, see varOPEX, # then ates varopex also needs to be added to the mnimize_tco_goal @@ -1048,9 +1195,10 @@ def __cumulative_investments_made_in_eur_path_constraints(self, ensemble_member) options = self.energy_system_options() if options["include_asset_is_realized"]: for asset in [ - *self.energy_system_components.get("heat_demand", []), + # *self.energy_system_components.get("heat_demand", []), *self.energy_system_components.get("heat_source", []), *self.energy_system_components.get("ates", []), + *self.energy_system_components.get("low_temperature_ates", []), *self.energy_system_components.get("heat_buffer", []), *self.energy_system_components.get("heat_exchanger", []), *self.energy_system_components.get("heat_pump", []), @@ -1060,12 +1208,8 @@ def __cumulative_investments_made_in_eur_path_constraints(self, ensemble_member) nominal = self.variable_nominal(var_name) var_name = self.__asset_is_realized_map[asset] asset_is_realized = self.state(var_name) - installation_cost_sym = self.__asset_installation_cost_var[ - self._asset_installation_cost_map[asset] - ] - investment_cost_sym = self.__asset_investment_cost_var[ - self._asset_investment_cost_map[asset] - ] + installation_cost_sym = self.variable(self._asset_installation_cost_map[asset]) + investment_cost_sym = self.variable(self._asset_investment_cost_map[asset]) # TODO: add insulation class cost to the investments made. # if asset in self.heat_network_components.get("demand", []): # for insulation_class in self.__get_insulation_classes(asset): @@ -1158,6 +1302,7 @@ def __annualized_capex_constraints(self, ensemble_member): asset_categories = [ "heat_source", "ates", + "low_temperature_ates", "heat_buffer", "heat_pipe", "heat_exchanger", @@ -1229,9 +1374,11 @@ def __revenue_constraints(self, ensemble_member): for _id, attr in self.get_electricity_carriers().items(): if attr["id_number_mapping"] == parameters[f"{demand}.id_mapping_carrier"]: carrier_name = attr["name"] + cost_multiplier = 1 / 3600.0 # priceprofile electricity is EUR/Wh for _id, attr in self.get_gas_carriers().items(): if attr["id_number_mapping"] == parameters[f"{demand}.id_mapping_carrier"]: carrier_name = attr["name"] + cost_multiplier = 1.0 # priceprofile gas is in EUR/g if carrier_name is not None: price_profile = self.get_timeseries(f"{carrier_name}.price_profile").values @@ -1250,7 +1397,7 @@ def __revenue_constraints(self, ensemble_member): nominal = self.variable_nominal(variable_revenue_var) sum = 0.0 - timesteps = np.diff(self.times()) / 3600.0 + timesteps = np.diff(self.times()) * cost_multiplier for i in range(1, len(self.times())): sum += price_profile[i] * energy_flow[i] * timesteps[i - 1] diff --git a/src/rtctools_heat_network/gas_physics_mixin.py b/src/mesido/gas_physics_mixin.py similarity index 72% rename from src/rtctools_heat_network/gas_physics_mixin.py rename to src/mesido/gas_physics_mixin.py index 008f87ec8..b9efb5f51 100644 --- a/src/rtctools_heat_network/gas_physics_mixin.py +++ b/src/mesido/gas_physics_mixin.py @@ -1,7 +1,12 @@ +import copy import logging import casadi as ca +from mesido.base_component_type_mixin import BaseComponentTypeMixin +from mesido.head_loss_class import HeadLossClass, HeadLossOption +from mesido.network_common import NetworkSettings + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -9,11 +14,7 @@ ) from rtctools.optimization.timeseries import Timeseries -from .base_component_type_mixin import BaseComponentTypeMixin -from .head_loss_class import HeadLossClass, HeadLossOption -from .network_common import NetworkSettings - -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") class GasPhysicsMixin(BaseComponentTypeMixin, CollocatedIntegratedOptimizationProblem): @@ -109,7 +110,7 @@ def __init__(self, *args, **kwargs): self.__gas_pipe_head_loss_bounds = {} self.__gas_pipe_head_loss_nominals = {} self.__gas_pipe_head_loss_zero_bounds = {} - self._hn_gas_pipe_to_head_loss_map = {} + self._gn_pipe_to_head_loss_map = {} # Boolean path-variable for the direction of the flow, inport to outport is positive flow. self.__gas_flow_direct_var = {} @@ -132,6 +133,19 @@ def __init__(self, *args, **kwargs): self._gas_pipe_topo_pipe_class_map = {} + # self.__gas_pipe_disconnect_var = {} + # self.__gas_pipe_disconnect_var_bounds = {} + self._gas_pipe_disconnect_map = {} + + self.__gas_storage_discharge_var = {} + self.__gas_storage_discharge_bounds = {} + self.__gas_storage_discharge_nominals = {} + self.__gas_storage_discharge_map = {} + + # Map for setting port variable nominals in the case they were not set during the model + # parsing (logical links). + self.__gas_node_variable_nominal = {} + def gas_carriers(self): """ This function should be overwritten by the problem and should give a dict with the @@ -147,6 +161,8 @@ def pre(self): """ super().pre() + options = self.energy_system_options() + def _get_max_bound(bound): if isinstance(bound, np.ndarray): return max(bound) @@ -167,23 +183,23 @@ def _get_min_bound(bound): for pipe_name in self.energy_system_components.get("gas_pipe", []): head_loss_var = f"{pipe_name}.__head_loss" + commodity = self.energy_system_components_commodity.get(pipe_name) # Note we always use the gas network type for the naming of variables, independent of # the gas mixture used. initialized_vars = self._gn_head_loss_class.initialize_variables_nominals_and_bounds( - self, NetworkSettings.NETWORK_TYPE_GAS, pipe_name, self.gas_network_settings + self, + commodity, + pipe_name, + self.gas_network_settings, ) if initialized_vars[0] != {}: - self.__gas_pipe_head_bounds[ - f"{pipe_name}.{NetworkSettings.NETWORK_TYPE_GAS}In.H" - ] = initialized_vars[0] + self.__gas_pipe_head_bounds[f"{pipe_name}.{commodity}In.H"] = initialized_vars[0] if initialized_vars[1] != {}: - self.__gas_pipe_head_bounds[ - f"{pipe_name}.{NetworkSettings.NETWORK_TYPE_GAS}Out.H" - ] = initialized_vars[1] + self.__gas_pipe_head_bounds[f"{pipe_name}.{commodity}Out.H"] = initialized_vars[1] if initialized_vars[2] != {}: self.__gas_pipe_head_loss_zero_bounds[f"{pipe_name}.dH"] = initialized_vars[2] if initialized_vars[3] != {}: - self._hn_gas_pipe_to_head_loss_map[pipe_name] = initialized_vars[3] + self._gn_pipe_to_head_loss_map[pipe_name] = initialized_vars[3] if initialized_vars[4] != {}: self.__gas_pipe_head_loss_var[head_loss_var] = initialized_vars[4] if initialized_vars[5] != {}: @@ -233,7 +249,7 @@ def _get_min_bound(bound): else: self.__gas_flow_direct_bounds[flow_dir_var] = (0.0, 1.0) - # Still to be added in the future + # # Still to be added in the future # if parameters[f"{pipe_name}.disconnectable"]: # disconnected_var = f"{pipe_name}__is_disconnected" # self._gas_pipe_disconnect_map[pipe_name] = disconnected_var @@ -242,15 +258,66 @@ def _get_min_bound(bound): self.__maximum_total_head_loss = self.__get_maximum_total_head_loss() + if options["gas_storage_discharge_variables"]: + for storage in self.energy_system_components.get("gas_tank_storage", []): + bound_storage_q = -self.bounds()[f"{storage}.GasIn.Q"][0] + if isinstance(bound_storage_q, Timeseries): + bound_storage_q = copy.deepcopy(bound_storage_q) + bound_storage_q.values[bound_storage_q.values < 0] = 0.0 + var_name = f"{storage}__Q_discharge" + self.__gas_storage_discharge_map[storage] = var_name + self.__gas_storage_discharge_var[var_name] = ca.MX.sym(var_name) + self.__gas_storage_discharge_bounds[var_name] = (0, bound_storage_q) + self.__gas_storage_discharge_nominals[var_name] = self.variable_nominal( + f"{storage}.GasIn.Q" + ) + + # Setting the node nominals using the connected assets. + for node, connected_assets in self.energy_system_topology.gas_nodes.items(): + nominals = {} + for var in ["Q", "H", "Hydraulic_power"]: + nominals[var] = [] + for _, (asset, _orientation) in connected_assets.items(): + var_nom = self.variable_nominal(f"{asset}.GasOut.{var}") + if var_nom != 1: + nominals[var].append(var_nom) + elif self.variable_nominal(f"{asset}.GasIn.{var}") != 1: + nominals[var].append(self.variable_nominal(f"{asset}.GasIn.{var}")) + else: + nominals[var].append(1) + + for i in range(len(connected_assets)): + if self.variable_nominal(f"{node}.GasConn[{i + 1}].{var}") == 1: + if nominals[var][i] != 1: + # Here we set a nominal based directly on the connected asset. + self.__gas_node_variable_nominal[f"{node}.GasConn[{i + 1}].{var}"] = ( + nominals[var][i] + ) + else: + # Here we set a nominal based on median of all the connected assets to + # the node. This is specifically done when we have a logical link for + # node to node. In this case we cannot set the nominal based on the + # connected node, hence we assume a node has at least one not node + # asset connected to it. + self.__gas_node_variable_nominal[f"{node}.GasConn[{i + 1}].{var}"] = ( + np.median([x for x in nominals[var] if x != 1]) + if np.sum(nominals[var]) != len(nominals[var]) + else 1.0 + ) + def energy_system_options(self): r""" Returns a dictionary of milp network specific options. + gas_storage_discharge_variables: creates separate variables for the discharge of the + gas_storages, only required when using the multicommodity simulator as this requires + separate variables to create goals with. """ options = self._gn_head_loss_class.head_loss_network_options() options["minimum_pressure_far_point"] = 1.0 + options["gas_storage_discharge_variables"] = False return options @@ -276,6 +343,7 @@ def path_variables(self): variables.extend(self.__gas_flow_direct_var.values()) # variables.extend(self.__gas_pipe_disconnect_var.values()) # still to be implemented variables.extend(self.__gas_pipe_linear_line_segment_var.values()) + variables.extend(self.__gas_storage_discharge_var.values()) return variables @@ -298,6 +366,10 @@ def variable_nominal(self, variable): if variable in self.__gas_pipe_head_loss_nominals: return self.__gas_pipe_head_loss_nominals[variable] + elif variable in self.__gas_storage_discharge_nominals: + return self.__gas_storage_discharge_nominals[variable] + elif variable in self.__gas_node_variable_nominal: + return self.__gas_node_variable_nominal[variable] else: return super().variable_nominal(variable) @@ -313,6 +385,7 @@ def bounds(self): bounds.update(self.__gas_pipe_head_loss_bounds) bounds.update(self.__gas_pipe_head_loss_zero_bounds) bounds.update(self.__gas_pipe_linear_line_segment_var_bounds) + bounds.update(self.__gas_storage_discharge_bounds) for k, v in self.__gas_pipe_head_bounds.items(): bounds[k] = self.merge_bounds(bounds[k], v) @@ -336,6 +409,18 @@ def path_goals(self): self, self.gas_network_settings ) ) + if ( + self.gas_network_settings["head_loss_option"] + == HeadLossOption.LINEARIZED_ONE_LINE_EQUALITY + or self.gas_network_settings["head_loss_option"] + == HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY + ): + g.append( + self._gn_head_loss_class._hpwr_minimization_goal_class( + self, + self.gas_network_settings, + ) + ) return g @@ -375,7 +460,7 @@ def __get_maximum_total_head_loss(self): self.gas_network_settings, parameters, max_discharge, - network_type=self.gas_network_settings["network_type"], + # network_type=self.gas_network_settings["network_type"], pressure=parameters[f"{pipe}.pressure"], ) @@ -411,13 +496,24 @@ def __gas_node_mixing_path_constraints(self, ensemble_member): q_nominal = np.median(q_nominals) constraints.append((q_sum / q_nominal, 0.0, 0.0)) + return constraints + + def __gas_node_hydraulic_power_mixing_path_constraints(self, ensemble_member): + """ + This function adds constraints to ensure that the incoming hydraulic power equals the + outgoing hydraulic power. We assume constant density throughout a hydraulically coupled + system and thus these constraints are needed for mass conservation. + """ + constraints = [] + + for node, connected_pipes in self.energy_system_topology.gas_nodes.items(): q_sum = 0.0 q_nominals = [] for i_conn, (_pipe, orientation) in connected_pipes.items(): - gas_conn = f"{node}.GasConn[{i_conn + 1}].Q_shadow" - q_sum += orientation * self.state(gas_conn) - q_nominals.append(self.variable_nominal(gas_conn)) + q_conn = f"{node}.GasConn[{i_conn + 1}].Hydraulic_power" + q_sum += orientation * self.state(q_conn) + q_nominals.append(self.variable_nominal(q_conn)) q_nominal = np.median(q_nominals) constraints.append((q_sum / q_nominal, 0.0, 0.0)) @@ -496,192 +592,29 @@ def __flow_direction_path_constraints(self, ensemble_member): return constraints - def _hn_gas_pipe_head_loss_constraints(self, ensemble_member): + def __gas_storage_discharge_path_constraints(self, ensemble_member): """ - This function adds the head loss constraints for pipes. There are two options namely with - and without pipe class optimization. In both cases we assume that disconnected pipes, pipes - without flow have no head loss. - - Under pipe-class optimization the head loss constraints per pipe class are added and - applied with the big_m method (is_topo_disconnected) to only activate the correct + The discharge variables are added such that two separate goals for charging and discharging + can be created. The discharging variable has a lower bound of 0 and should always be larger + or equal to the negative of the inflow variable. This allows for first a minimization of + the discharging and afterwards an maximisation of the charging without conflicting goals or constraints. - - Under constant pipe class constraints for only one diameter are added. """ constraints = [] - options = self.energy_system_options() - parameters = self.parameters(ensemble_member) - components = self.energy_system_components - # Set the head loss according to the direction in the pipes. Note that - # the `.__head_loss` symbol is always positive by definition, but that - # `.dH` is not (positive when flow is negative, and vice versa). - # If the pipe is disconnected, we leave the .__head_loss symbol free - # (and it has no physical meaning). We also do not set any discharge - # relationship in this case (but dH is still equal to Out - In of - # course). - - for pipe in components.get("gas_pipe", []): - if parameters[f"{pipe}.length"] == 0.0: - # If the pipe does not have a control valve, the head loss is - # forced to zero via bounds. If the pipe _does_ have a control - # valve, then there still is no relationship between the - # discharge and the head loss/dH. - continue - - head_loss_sym = self._hn_gas_pipe_to_head_loss_map[pipe] - - dh = self.__state_vector_scaled(f"{pipe}.dH", ensemble_member) - head_loss = self.__state_vector_scaled(head_loss_sym, ensemble_member) - discharge = self.__state_vector_scaled(f"{pipe}.Q", ensemble_member) - - # We need to make sure the dH is decoupled from the discharge when - # the pipe is disconnected. Simply put, this means making the - # below constraints trivial. - - # Still to be implemented - # is_disconnected_var = self._gas_pipe_disconnect_map.get(pipe) - is_disconnected_var = None - - if is_disconnected_var is None: - is_disconnected = 0.0 - else: - is_disconnected = self.__state_vector_scaled(is_disconnected_var, ensemble_member) - - max_discharge = None - max_head_loss = -np.inf - - if pipe in self._gas_pipe_topo_pipe_class_map: - # Multiple diameter options for this pipe - pipe_classes = self._gas_pipe_topo_pipe_class_map[pipe] - max_discharge = max(c.maximum_discharge for c in pipe_classes) - - for pc, pc_var_name in pipe_classes.items(): - if pc.inner_diameter == 0.0: - continue - - head_loss_max_discharge = self._gn_head_loss_class._hn_pipe_head_loss( - pipe, - self, - options, - self.gas_network_settings, - parameters, - max_discharge, - pipe_class=pc, - network_type=self.gas_network_settings["network_type"], - pressure=parameters[f"{pipe}.pressure"], - ) - - big_m = max( - 2.0 * 2.0 * self.__maximum_total_head_loss, 2 * head_loss_max_discharge - ) - - is_topo_disconnected = 1 - self.extra_variable(pc_var_name, ensemble_member) - is_topo_disconnected = ca.repmat(is_topo_disconnected, dh.size1()) - - # Note that we add the two booleans `is_disconnected` and - # `is_topo_disconnected`. This is allowed because of the way the - # resulting expression is used in the Big-M formulation. We only care - # that the expression (i.e. a single boolean or the sum of the two - # booleans) is either 0 when the pipe is connected, or >= 1 when it - # is disconnected. - constraints.extend( - self._gn_head_loss_class._hn_pipe_head_loss( - pipe, - self, - options, - self.gas_network_settings, - parameters, - discharge, - head_loss, - dh, - is_disconnected + is_topo_disconnected, - big_m, - pc, - network_type=self.gas_network_settings["network_type"], - pressure=parameters[f"{pipe}.pressure"], - ) - ) - - # Contrary to the Big-M calculation above, the relation - # between dH and the head loss symbol requires the - # maximum head loss that can be realized effectively. So - # we pass the current pipe class's maximum discharge. - max_head_loss = max( - max_head_loss, - self._gn_head_loss_class._hn_pipe_head_loss( - pipe, - self, - options, - self.gas_network_settings, - parameters, - pc.maximum_discharge, - pipe_class=pc, - network_type=self.gas_network_settings["network_type"], - pressure=parameters[f"{pipe}.pressure"], - ), - ) - else: - # Only a single diameter for this pipe. Note that we rely on - # the diameter parameter being overridden automatically if a - # single pipe class is set by the user. - area = parameters[f"{pipe}.area"] - max_discharge = self.gas_network_settings["maximum_velocity"] * area - is_topo_disconnected = int(parameters[f"{pipe}.diameter"] == 0.0) + if options["gas_storage_discharge_variables"]: + for storage in self.energy_system_components.get("gas_tank_storage", []): + storage_charge_var = self.state(f"{storage}.GasIn.Q") + storage_discharge_var_name = f"{storage}__Q_discharge" + storage_discharge_var = self.state(storage_discharge_var_name) + nominal = self.variable_nominal(storage_discharge_var_name) - constraints.extend( - self._gn_head_loss_class._hn_pipe_head_loss( - pipe, - self, - options, - self.gas_network_settings, - parameters, - discharge, - head_loss, - dh, - is_disconnected + is_topo_disconnected, - 2.0 * 2.0 * self.__maximum_total_head_loss, - network_type=self.gas_network_settings["network_type"], - pressure=parameters[f"{pipe}.pressure"], - ) + # Q_discharge >= -Q + constraints.append( + ((storage_discharge_var + storage_charge_var) / nominal, 0.0, np.inf) ) - max_head_loss = self._gn_head_loss_class._hn_pipe_head_loss( - pipe, - self, - options, - self.gas_network_settings, - parameters, - max_discharge, - network_type=self.gas_network_settings["network_type"], - pressure=parameters[f"{pipe}.pressure"], - ) - - # Relate the head loss symbol to the pipe's dH symbol. - - # FIXME: Ugly hack. Cold pipes should be modelled completely with - # their own integers as well. - flow_dir = self.__state_vector_scaled( - self._gas_pipe_to_flow_direct_map[pipe], ensemble_member - ) - - # Note that the Big-M should _at least_ cover the maximum - # distance between `head_loss` and `dh`. If `head_loss` can be at - # most 1.0 (= `max_head_loss`), that means our Big-M should be at - # least double (i.e. >= 2.0). And because we do not want Big-Ms to - # be overly tight, we include an additional factor of 2. - big_m = 2.0 * 2.0 * max_head_loss - - constraints.append( - ( - (-dh - head_loss + (1 - flow_dir) * big_m) / big_m, - 0.0, - np.inf, - ) - ) - constraints.append(((dh - head_loss + flow_dir * big_m) / big_m, 0.0, np.inf)) - return constraints def path_constraints(self, ensemble_member): @@ -699,8 +632,14 @@ def path_constraints(self, ensemble_member): constraints.extend( self._gn_head_loss_class._pipe_head_loss_path_constraints(self, ensemble_member) ) - + constraints.extend( + self._gn_head_loss_class._pipe_hydraulic_power_path_constraints( + self, self.__maximum_total_head_loss, ensemble_member + ) + ) constraints.extend(self.__flow_direction_path_constraints(ensemble_member)) + constraints.extend(self.__gas_node_hydraulic_power_mixing_path_constraints(ensemble_member)) + constraints.extend(self.__gas_storage_discharge_path_constraints(ensemble_member)) return constraints @@ -714,7 +653,11 @@ def constraints(self, ensemble_member): constraints = super().constraints(ensemble_member) if self.gas_network_settings["head_loss_option"] != HeadLossOption.NO_HEADLOSS: - constraints.extend(self._hn_gas_pipe_head_loss_constraints(ensemble_member)) + constraints.extend( + self._gn_head_loss_class._pipe_head_loss_constraints( + self, self.__maximum_total_head_loss, ensemble_member + ) + ) return constraints @@ -793,7 +736,7 @@ def priority_completed(self, priority): parameters, q, None, - network_type=self.gas_network_settings["network_type"], + # network_type=self.gas_network_settings["network_type"], pressure=parameters[f"{pipe}.pressure"], ) if ( @@ -802,7 +745,7 @@ def priority_completed(self, priority): ): head_loss = np.abs(results[f"{pipe}.dH"][inds]) else: - head_loss = results[self._hn_gas_pipe_to_head_loss_map[pipe]][inds] + head_loss = results[self._gn_pipe_to_head_loss_map[pipe]][inds] if not np.allclose(head_loss, head_loss_target, rtol=rtol, atol=atol): logger.warning( diff --git a/src/rtctools_heat_network/head_loss_class.py b/src/mesido/head_loss_class.py similarity index 65% rename from src/rtctools_heat_network/head_loss_class.py rename to src/mesido/head_loss_class.py index e8e502692..c6c7abc13 100644 --- a/src/rtctools_heat_network/head_loss_class.py +++ b/src/mesido/head_loss_class.py @@ -5,19 +5,31 @@ import casadi as ca +import mesido._darcy_weisbach as darcy_weisbach +from mesido.constants import GRAVITATIONAL_CONSTANT +from mesido.network_common import NetworkSettings +from mesido.pipe_class import PipeClass + import numpy as np from rtctools.optimization.goal_programming_mixin_base import Goal from rtctools.optimization.optimization_problem import BT -import rtctools_heat_network._darcy_weisbach as darcy_weisbach -from .constants import GRAVITATIONAL_CONSTANT -from .network_common import NetworkSettings -from .pipe_class import PipeClass +logger = logging.getLogger("mesido") -logger = logging.getLogger("rtctools_heat_network") +def _state_vector_scaled(optimization_problem, variable, ensemble_member): + """ + This functions returns the casadi symbols scaled with their nominal for the entire time + horizon. + """ + canonical, sign = optimization_problem.alias_relation.canonical_signed(variable) + return ( + optimization_problem.state_vector(canonical, ensemble_member) + * optimization_problem.variable_nominal(canonical) + * sign + ) class HeadLossOption(IntEnum): @@ -147,10 +159,13 @@ def function(self, optimization_problem, ensemble_member): ): sym_name = optimization_problem._hn_pipe_to_head_loss_map[p] sum_ += optimization_problem.state(sym_name) - elif self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_GAS: + elif ( + self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_GAS + or self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_HYDROGEN + ): for p in optimization_problem.energy_system_components.get("gas_pipe", []): if not parameters[f"{p}.length"] == 0.0: - sym_name = optimization_problem._hn_gas_pipe_to_head_loss_map[p] + sym_name = optimization_problem._gn_pipe_to_head_loss_map[p] sum_ += optimization_problem.state(sym_name) return sum_ @@ -207,7 +222,6 @@ def __init__(self, input_network_settings, *args, **kwargs): self.__pipe_head_loss_zero_bounds = {} self._hn_pipe_to_head_loss_map = {} - # Kvr # Boolean variables for the linear line segment options per pipe. self.__pipe_linear_line_segment_var = {} # value 0/1: line segment - not active/active self.__pipe_linear_line_segment_var_bounds = {} @@ -370,7 +384,7 @@ def initialize_variables_nominals_and_bounds( network_settings, parameters, q_nominal, - network_type=self.network_settings["network_type"], + # network_type=self.network_settings["network_type"], pressure=parameters[f"{pipe_name}.pressure"], ) @@ -394,30 +408,28 @@ def initialize_variables_nominals_and_bounds( # We need to creat linear line segments for the - and + volumetric flow rate # possibilites. Line number 1, 2, N for the - & + side is created discharge_type = ["neg_discharge", "pos_discharge"] - line_number = 0 - for dtype in discharge_type: - for ii_line in range(network_settings["n_linearization_lines"] * 2): - if ii_line < network_settings["n_linearization_lines"]: - dtype = discharge_type[0] - line_number = ii_line + 1 - else: - dtype = discharge_type[1] - line_number = ii_line + 1 - network_settings["n_linearization_lines"] - - # start line segment numbering from 1 up to "n_linearization_lines" - pipe_linear_line_segment_var_name = ( - f"{pipe_name}__pipe_linear_line_segment_num_{line_number}_{dtype}" - ) + for ii_line in range(network_settings["n_linearization_lines"] * 2): + if ii_line < network_settings["n_linearization_lines"]: + dtype = discharge_type[0] + line_number = ii_line + 1 + else: + dtype = discharge_type[1] + line_number = ii_line + 1 - network_settings["n_linearization_lines"] + + # start line segment numbering from 1 up to "n_linearization_lines" + pipe_linear_line_segment_var_name = ( + f"{pipe_name}__pipe_linear_line_segment_num_{line_number}_{dtype}" + ) - self._pipe_linear_line_segment_map[pipe_name][ - ii_line - ] = pipe_linear_line_segment_var_name - self.__pipe_linear_line_segment_var[pipe_name][ - pipe_linear_line_segment_var_name - ] = ca.MX.sym(pipe_linear_line_segment_var_name) - self.__pipe_linear_line_segment_var_bounds[pipe_name][ - pipe_linear_line_segment_var_name - ] = (0.0, 1.0) + self._pipe_linear_line_segment_map[pipe_name][ + ii_line + ] = pipe_linear_line_segment_var_name + self.__pipe_linear_line_segment_var[pipe_name][ + pipe_linear_line_segment_var_name + ] = ca.MX.sym(pipe_linear_line_segment_var_name) + self.__pipe_linear_line_segment_var_bounds[pipe_name][ + pipe_linear_line_segment_var_name + ] = (0.0, 1.0) return ( ( @@ -496,7 +508,7 @@ def _hn_pipe_head_loss( is_disconnected: Union[ca.MX, int] = 0, big_m: Optional[float] = None, pipe_class: Optional[PipeClass] = None, - network_type: NetworkSettings = NetworkSettings.NETWORK_TYPE_HEAT, + # network_type: NetworkSettings = NetworkSettings.NETWORK_TYPE_HEAT, pressure: float = 0.0, ) -> Union[List[Tuple[ca.MX, BT, BT]], float, np.ndarray]: """ @@ -523,6 +535,8 @@ def _hn_pipe_head_loss( itself then also needs to be passed via the `big_m` keyword argument. """ + network_type = network_settings["network_type"] + if head_loss is None and dh is None: symbolic = False else: @@ -574,7 +588,7 @@ def _hn_pipe_head_loss( maximum_velocity = network_settings["maximum_velocity"] try: - # Only milp networks have a temperature attribute in the pipes, otherwise we will use + # Only heat networks have a temperature attribute in the pipes, otherwise we will use # a default temperature for gas networks temperature = parameters[f"{pipe}.temperature"] for _id, attr in optimization_problem.temperature_carriers().items(): @@ -750,7 +764,9 @@ def _hn_pipe_head_loss( big_m_lin = 0.0 else: big_m_lin = big_m - constraint_nominal = (constraint_nominal * big_m_lin) ** 0.5 + constraint_nominal = np.abs( + head_loss_nominal * (a_vec * q_nominal + b_vec) * big_m + ) ** (1.0 / 3.0) constraints = [] @@ -805,55 +821,43 @@ def _hn_pipe_head_loss( ) # Add equality constraint, value == 0.0 for all linear lines - # Loop twice due to linear lines exsiting for negative and positive discharge - # ii==0: this is the linear lines for the negative discharge possibility - # ii==1: this is the linear lines for the postive discharge possibility - for ii in range(2): - for ii_line in range(n_linear_lines): - ii_line_used = (ii * 2) + ii_line - - ii_start = (ii_line + 2 * ii) * n_timesteps - ii_end = ii_start + n_timesteps - constraints.append( + for ii_line_used in range(len(pipe_linear_line_segment)): + ii_start = ii_line_used * n_timesteps + ii_end = ii_start + n_timesteps + constraints.append( + ( ( - ( - head_loss_vec[ii_start:ii_end] - - ( - a_vec[ii_start:ii_end] * discharge_vec[ii_start:ii_end] - + b_vec[ii_start:ii_end] - ) - + is_disconnected_vec[ii_start:ii_end] * big_m_lin - + big_m_lin - * (1 - is_line_segment_active[ii_line_used][0:n_timesteps]) + head_loss_vec[ii_start:ii_end] + - ( + a_vec[ii_start:ii_end] * discharge_vec[ii_start:ii_end] + + b_vec[ii_start:ii_end] ) - / constraint_nominal[ii_start:ii_end], - 0.0, - np.inf, - ), - ) - for ii in range(2): - for ii_line in range(n_linear_lines): - ii_line_used = (ii * 2) + ii_line - - ii_start = (ii_line + 2 * ii) * n_timesteps - ii_end = ii_start + n_timesteps - constraints.append( + + is_disconnected_vec[ii_start:ii_end] * big_m_lin + + big_m_lin + * (1 - is_line_segment_active[ii_line_used][0:n_timesteps]) + ) + / constraint_nominal[ii_start:ii_end], + 0.0, + np.inf, + ), + ) + constraints.append( + ( ( - ( - head_loss_vec[ii_start:ii_end] - - ( - a_vec[ii_start:ii_end] * discharge_vec[ii_start:ii_end] - + b_vec[ii_start:ii_end] - ) - - is_disconnected_vec[ii_start:ii_end] * big_m_lin - - big_m_lin - * (1 - is_line_segment_active[ii_line_used][0:n_timesteps]) + head_loss_vec[ii_start:ii_end] + - ( + a_vec[ii_start:ii_end] * discharge_vec[ii_start:ii_end] + + b_vec[ii_start:ii_end] ) - / constraint_nominal[ii_start:ii_end], - -np.inf, - 0.0, - ), - ) + - is_disconnected_vec[ii_start:ii_end] * big_m_lin + - big_m_lin + * (1 - is_line_segment_active[ii_line_used][0:n_timesteps]) + ) + / constraint_nominal[ii_start:ii_end], + -np.inf, + 0.0, + ), + ) return constraints else: ret = np.amax(a * np.tile(discharge, (len(a), 1)).transpose() + b, axis=1) @@ -875,7 +879,6 @@ def _hydraulic_power( big_m: Optional[float] = None, pipe_class: Optional[PipeClass] = None, flow_dir: Union[ca.MX, int] = 0, - network_type: NetworkSettings = NetworkSettings.NETWORK_TYPE_HEAT, pressure: float = 0.0, ) -> Union[List[Tuple[ca.MX, BT, BT]], float, np.ndarray]: """ @@ -905,6 +908,8 @@ def _hydraulic_power( itself then also needs to be passed via the `big_m` keyword argument. """ + network_type = network_settings["network_type"] + if hydraulic_power is None: symbolic = False else: @@ -944,16 +949,22 @@ def _hydraulic_power( assert big_m != 0.0 wall_roughness = energy_system_options["wall_roughness"] - temperature = parameters[f"{pipe}.temperature"] - for _id, attr in optimization_problem.temperature_carriers().items(): - if ( - parameters[f"{pipe}.carrier_id"] == attr["id_number_mapping"] - and len(optimization_problem.temperature_regimes(parameters[f"{pipe}.carrier_id"])) - > 0 - ): - temperature = min( - optimization_problem.temperature_regimes(parameters[f"{pipe}.carrier_id"]) - ) + if network_type == NetworkSettings.NETWORK_TYPE_HEAT: + temperature = parameters[f"{pipe}.temperature"] + for _id, attr in optimization_problem.temperature_carriers().items(): + if ( + parameters[f"{pipe}.carrier_id"] == attr["id_number_mapping"] + and len( + optimization_problem.temperature_regimes(parameters[f"{pipe}.carrier_id"]) + ) + > 0 + ): + temperature = min( + optimization_problem.temperature_regimes(parameters[f"{pipe}.carrier_id"]) + ) + else: + # A default temperature of 20 degrees celcius is used for gas networks. + temperature = 20.0 rho = parameters[f"{pipe}.rho"] if pipe_class is not None: @@ -1135,11 +1146,20 @@ def _pipe_head_loss_path_constraints(self, optimization_problem, _ensemble_membe """ constraints = [] - pipe_type = "heat_pipe" - commodity = "Heat" - if len(optimization_problem.energy_system_components.get(pipe_type, [])) == 0: + if self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_HEAT: + commodity = "Heat" + pipe_type = "heat_pipe" + elif ( + self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_GAS + or self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_HYDROGEN + ): + commodity = "Gas" pipe_type = "gas_pipe" - commodity = NetworkSettings.NETWORK_TYPE_GAS + else: + raise Exception( + f"hydraulic power can not be calculated for network type of " + f"{self.network_settings['network_type']}" + ) for pipe in optimization_problem.energy_system_components.get(pipe_type, []): dh = optimization_problem.state(f"{pipe}.dH") @@ -1179,3 +1199,388 @@ def _demand_head_loss_path_constraints(self, optimization_problem, _ensemble_mem ) return constraints + + def _pipe_head_loss_constraints( + self, optimization_problem, _maximum_total_head_loss, ensemble_member + ): + """ + This function adds the head loss constraints for pipes. There are two options namely with + and without pipe class optimization. In both cases we assume that disconnected pipes, pipes + without flow have no head loss. + + Under pipe-class optimization the head loss constraints per pipe class are added and + applied with the big_m method (is_topo_disconnected) to only activate the correct + constraints. + + Under constant pipe class constraints for only one diameter are added. + """ + constraints = [] + + options = optimization_problem.energy_system_options() + parameters = optimization_problem.parameters(ensemble_member) + components = optimization_problem.energy_system_components + # Set the head loss according to the direction in the pipes. Note that + # the `.__head_loss` symbol is always positive by definition, but that + # `.dH` is not (positive when flow is negative, and vice versa). + # If the pipe is disconnected, we leave the .__head_loss symbol free + # (and it has no physical meaning). We also do not set any discharge + # relationship in this case (but dH is still equal to Out - In of + # course). + + if self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_HEAT: + commodity = "heat" + n_type = "hn" + elif ( + self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_GAS + or self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_HYDROGEN + ): + commodity = "gas" + n_type = "gn" + else: + raise Exception( + f"hydraulic power can not be calculated for network type of " + f"{self.network_settings['network_type']}" + ) + pipe_type = f"{commodity}_pipe" + + pipe_head_loss_map = getattr(optimization_problem, f"_{n_type}_pipe_to_head_loss_map") + is_disconnected_map = getattr(optimization_problem, f"_{commodity}_pipe_disconnect_map") + pipe_topo_class_map = getattr( + optimization_problem, f"_{commodity}_pipe_topo_pipe_class_map" + ) + pipe_to_flow_direct_map = getattr( + optimization_problem, f"_{commodity}_pipe_to_flow_direct_map" + ) + + for pipe in components.get(pipe_type, []): + if parameters[f"{pipe}.length"] == 0.0: + # If the pipe does not have a control valve, the head loss is + # forced to zero via bounds. If the pipe _does_ have a control + # valve, then there still is no relationship between the + # discharge and the head loss/dH. + continue + + head_loss_sym = pipe_head_loss_map[pipe] + + dh = _state_vector_scaled(optimization_problem, f"{pipe}.dH", ensemble_member) + head_loss = _state_vector_scaled(optimization_problem, head_loss_sym, ensemble_member) + discharge = _state_vector_scaled(optimization_problem, f"{pipe}.Q", ensemble_member) + + # We need to make sure the dH is decoupled from the discharge when + # the pipe is disconnected. Simply put, this means making the + # below constraints trivial. + is_disconnected_var = is_disconnected_map.get(pipe) + + if is_disconnected_var is None: + is_disconnected = 0.0 + else: + is_disconnected = _state_vector_scaled( + optimization_problem, is_disconnected_var, ensemble_member + ) + + max_discharge = None + max_head_loss = -np.inf + + if pipe in pipe_topo_class_map: + # Multiple diameter options for this pipe + pipe_classes = pipe_topo_class_map[pipe] + max_discharge = max(c.maximum_discharge for c in pipe_classes) + + for pc, pc_var_name in pipe_classes.items(): + if pc.inner_diameter == 0.0: + continue + + head_loss_max_discharge = self._hn_pipe_head_loss( + pipe, + optimization_problem, + options, + self.network_settings, + parameters, + max_discharge, + pipe_class=pc, + pressure=parameters[f"{pipe}.pressure"], + ) + + if self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_HEAT: + big_m = max(1.1 * _maximum_total_head_loss, 2 * head_loss_max_discharge) + elif ( + self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_GAS + or self.network_settings["network_type"] + == NetworkSettings.NETWORK_TYPE_HYDROGEN + ): + big_m = max( + 2.0 * 2.0 * _maximum_total_head_loss, 2 * head_loss_max_discharge + ) + else: + raise RuntimeError( + f"{self.network_settings['network_type']} is not of type Gas or Heat " + f"thus no maximum total headloss is given" + ) + + is_topo_disconnected = 1 - optimization_problem.extra_variable( + pc_var_name, ensemble_member + ) + is_topo_disconnected = ca.repmat(is_topo_disconnected, dh.size1()) + + # Note that we add the two booleans `is_disconnected` and + # `is_topo_disconnected`. This is allowed because of the way the + # resulting expression is used in the Big-M formulation. We only care + # that the expression (i.e. a single boolean or the sum of the two + # booleans) is either 0 when the pipe is connected, or >= 1 when it + # is disconnected. + constraints.extend( + self._hn_pipe_head_loss( + pipe, + optimization_problem, + options, + self.network_settings, + parameters, + discharge, + head_loss, + dh, + is_disconnected + is_topo_disconnected, + big_m, + pc, + pressure=parameters[f"{pipe}.pressure"], + ) + ) + + # Contrary to the Big-M calculation above, the relation + # between dH and the head loss symbol requires the + # maximum head loss that can be realized effectively. So + # we pass the current pipe class's maximum discharge. + max_head_loss = max( + max_head_loss, + self._hn_pipe_head_loss( + pipe, + optimization_problem, + options, + self.network_settings, + parameters, + pc.maximum_discharge, + pipe_class=pc, + pressure=parameters[f"{pipe}.pressure"], + ), + ) + else: + # Only a single diameter for this pipe. Note that we rely on + # the diameter parameter being overridden automatically if a + # single pipe class is set by the user. + area = parameters[f"{pipe}.area"] + max_discharge = self.network_settings["maximum_velocity"] * area + + is_topo_disconnected = int(parameters[f"{pipe}.diameter"] == 0.0) + + if self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_HEAT: + big_m = 1.1 * _maximum_total_head_loss + elif ( + self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_GAS + or self.network_settings["network_type"] + == NetworkSettings.NETWORK_TYPE_HYDROGEN + ): + big_m = 2.0 * 2.0 * _maximum_total_head_loss + else: + raise RuntimeError( + f"{self.network_settings['network_type']} is not of type Gas or Heat thus " + f"no maximum total headloss is given" + ) + + constraints.extend( + self._hn_pipe_head_loss( + pipe, + optimization_problem, + options, + self.network_settings, + parameters, + discharge, + head_loss, + dh, + is_disconnected + is_topo_disconnected, + big_m=big_m, + pressure=parameters[f"{pipe}.pressure"], + ) + ) + + max_head_loss = self._hn_pipe_head_loss( + pipe, + optimization_problem, + options, + self.network_settings, + parameters, + max_discharge, + pressure=parameters[f"{pipe}.pressure"], + ) + + # Relate the head loss symbol to the pipe's dH symbol. + + # FIXME: Ugly hack. Cold pipes should be modelled completely with + # their own integers as well. + flow_dir = _state_vector_scaled( + optimization_problem, pipe_to_flow_direct_map[pipe], ensemble_member + ) + + # Note that the Big-M should _at least_ cover the maximum + # distance between `head_loss` and `dh`. If `head_loss` can be at + # most 1.0 (= `max_head_loss`), that means our Big-M should be at + # least double (i.e. >= 2.0). And because we do not want Big-Ms to + # be overly tight, we include an additional factor of 2. + big_m = 2 * 2 * max_head_loss + + constraints.append( + ( + (-dh - head_loss + (1 - flow_dir) * big_m) / big_m, + 0.0, + np.inf, + ) + ) + constraints.append(((dh - head_loss + flow_dir * big_m) / big_m, 0.0, np.inf)) + + constraints.append( + ( + (-dh - head_loss - (1 - flow_dir) * big_m) / big_m, + -np.inf, + 0.0, + ) + ) + constraints.append(((dh - head_loss - flow_dir * big_m) / big_m, -np.inf, 0.0)) + + return constraints + + def _pipe_hydraulic_power_path_constraints( + self, optimization_problem, _maximum_total_head_loss, ensemble_member + ): + """ + This function adds constraints to compute the hydraulic power that is needed to realize the + flow, compensating the pressure drop through the pipe. Similar to the head loss constraints + we allow two supported methods. 1) a single linear line between 0 to max velocity. 2) A + multiple line inequality approach where one can use the minimize_head_losses == True option + to drag down the solution to the actual physical solution. + + Note that the linearizations are made separately from the pressure drop constraints, this is + done to avoid "stacked" overestimations. + """ + constraints = [] + options = optimization_problem.energy_system_options() + + if self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_HEAT: + commodity = "heat" + elif ( + self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_GAS + or self.network_settings["network_type"] == NetworkSettings.NETWORK_TYPE_HYDROGEN + ): + commodity = "gas" + else: + raise Exception( + f"hydraulic power can not be calculated for network type of " + f"{self.network_settings['network_type']}" + ) + pipe_type = f"{commodity}_pipe" + + pipe_topo_class_map = getattr( + optimization_problem, f"_{commodity}_pipe_topo_pipe_class_map" + ) + + if self.network_settings["head_loss_option"] != HeadLossOption.NO_HEADLOSS: + parameters = optimization_problem.parameters(ensemble_member) + components = optimization_problem.energy_system_components + + for pipe in components.get(pipe_type, []): + if parameters[f"{pipe}.length"] == 0.0: + # If the pipe does not have a control valve, the head loss is + # forced to zero via bounds. If the pipe _does_ have a control + # valve, then there still is no relationship between the + # discharge and the hydraulic_power. + continue + + # TODO: I think the upcomming 8 lines can be removed (e.g. head_loss_option) + if pipe_type == "heat_pipe": + head_loss_option = optimization_problem._hn_get_pipe_head_loss_option( + pipe, self.network_settings, parameters + ) + else: + head_loss_option = self.network_settings["head_loss_option"] + assert ( + head_loss_option != HeadLossOption.NO_HEADLOSS + ), "This method should be skipped when NO_HEADLOSS is set." + + discharge = optimization_problem.state(f"{pipe}.Q") + hydraulic_power = optimization_problem.state(f"{pipe}.Hydraulic_power") + rho = parameters[f"{pipe}.rho"] + + # 0: pipe is connected, 1: pipe is disconnected + is_disconnected_var = getattr( + optimization_problem, f"_{commodity}_pipe_disconnect_map" + ).get(pipe) + # optimization_problem._pipe_disconnect_map.get(pipe) + if is_disconnected_var is None: + is_disconnected = 0.0 + else: + is_disconnected = optimization_problem.state(is_disconnected_var) + + flow_dir_var = getattr( + optimization_problem, f"_{commodity}_pipe_to_flow_direct_map" + ).get(pipe) + flow_dir = optimization_problem.state( + flow_dir_var + ) # 0/1: negative/positive flow direction + + if pipe in pipe_topo_class_map: + # Multiple diameter options for this pipe + pipe_classes = pipe_topo_class_map[pipe] + max_discharge = max(c.maximum_discharge for c in pipe_classes) + for pc, pc_var_name in pipe_classes.items(): + if pc.inner_diameter == 0.0: + continue + + # Calc max hydraulic power based on maximum_total_head_loss = + # f(max_sum_dh_pipes, max_dh_network_options) + max_total_hydraulic_power = 2.0 * ( + rho * GRAVITATIONAL_CONSTANT * _maximum_total_head_loss * max_discharge + ) + + # is_topo_disconnected - 0: pipe selected, 1: pipe disconnected/not selected + # self.__pipe_topo_pipe_class_var - value 0: pipe is not selected, 1: pipe + # is selected + is_topo_disconnected = 1 - optimization_problem.variable(pc_var_name) + + constraints.extend( + self._hydraulic_power( + pipe, + optimization_problem, + options, + self.network_settings, + parameters, + discharge, + hydraulic_power, + is_disconnected=is_topo_disconnected + is_disconnected, + big_m=max_total_hydraulic_power, + pipe_class=pc, + flow_dir=flow_dir, + pressure=parameters[f"{pipe}.pressure"], + ) + ) + else: + is_topo_disconnected = int(parameters[f"{pipe}.diameter"] == 0.0) + max_total_hydraulic_power = 2.0 * ( + rho + * GRAVITATIONAL_CONSTANT + * _maximum_total_head_loss + * parameters[f"{pipe}.area"] + * self.network_settings["maximum_velocity"] + ) + constraints.extend( + self._hydraulic_power( + pipe, + optimization_problem, + options, + self.network_settings, + parameters, + discharge, + hydraulic_power, + is_disconnected=is_disconnected + is_topo_disconnected, + big_m=max_total_hydraulic_power, + flow_dir=flow_dir, + pressure=parameters[f"{pipe}.pressure"], + ) + ) + return constraints diff --git a/src/rtctools_heat_network/heat_network_common.py b/src/mesido/heat_network_common.py similarity index 100% rename from src/rtctools_heat_network/heat_network_common.py rename to src/mesido/heat_network_common.py diff --git a/src/rtctools_heat_network/heat_physics_mixin.py b/src/mesido/heat_physics_mixin.py similarity index 84% rename from src/rtctools_heat_network/heat_physics_mixin.py rename to src/mesido/heat_physics_mixin.py index 0825df5d1..eb4c7cfba 100644 --- a/src/rtctools_heat_network/heat_physics_mixin.py +++ b/src/mesido/heat_physics_mixin.py @@ -4,6 +4,12 @@ import casadi as ca +from mesido._heat_loss_u_values_pipe import pipe_heat_loss +from mesido.base_component_type_mixin import BaseComponentTypeMixin +from mesido.demand_insulation_class import DemandInsulationClass +from mesido.head_loss_class import HeadLossClass, HeadLossOption +from mesido.network_common import NetworkSettings + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,28 +17,20 @@ ) from rtctools.optimization.timeseries import Timeseries -from rtctools_heat_network._heat_loss_u_values_pipe import pipe_heat_loss - - -from .base_component_type_mixin import BaseComponentTypeMixin -from .constants import GRAVITATIONAL_CONSTANT -from .demand_insulation_class import DemandInsulationClass -from .head_loss_class import HeadLossClass, HeadLossOption -from .network_common import NetworkSettings - -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") class HeatPhysicsMixin(BaseComponentTypeMixin, CollocatedIntegratedOptimizationProblem): + """ + This class is used to model the physics of a heat district network with its assets. We model + the different components with a variety of linearization strategies. + """ + __allowed_head_loss_options = { HeadLossOption.NO_HEADLOSS, HeadLossOption.LINEARIZED_ONE_LINE_EQUALITY, HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY, } - """ - This class is used to model the physics of a milp district network with its assets. We model - the different components with variety of linearization strategies. - """ def __init__(self, *args, **kwargs): r""" @@ -109,6 +107,7 @@ def __init__(self, *args, **kwargs): "n_linearization_lines": 5, "pipe_minimum_pressure": -np.inf, "pipe_maximum_pressure": np.inf, + "heat_exchanger_bypass": False, } self._hn_head_loss_class = HeadLossClass(self.heat_network_settings) self.__pipe_head_bounds = {} @@ -119,14 +118,14 @@ def __init__(self, *args, **kwargs): self._hn_pipe_to_head_loss_map = {} # Boolean path-variable for the direction of the flow, inport to outport is positive flow. - self.__flow_direct_var = {} - self.__flow_direct_bounds = {} - self._pipe_to_flow_direct_map = {} + self.__heat_flow_direct_var = {} + self.__heat_flow_direct_bounds = {} + self._heat_pipe_to_flow_direct_map = {} # Boolean path-variable to determine whether flow is going through a pipe. - self.__pipe_disconnect_var = {} - self.__pipe_disconnect_var_bounds = {} - self._pipe_disconnect_map = {} + self.__heat_pipe_disconnect_var = {} + self.__heat_pipe_disconnect_var_bounds = {} + self._heat_pipe_disconnect_map = {} # Boolean path-variable for the status of the check valve self.__check_valve_status_var = {} @@ -146,7 +145,7 @@ def __init__(self, *args, **kwargs): # To avoid artificial energy generation at t0 self.__buffer_t0_bounds = {} - # Variable for the milp-loss, note that we make the bounds, and nominals not protected as + # Variable for the heat-loss, note that we make the bounds, and nominals not protected as # we need to adapt these in case of pipe sizing in the AssetSizingMixin. self.__pipe_heat_loss_var = {} self.__pipe_heat_loss_path_var = {} @@ -202,7 +201,10 @@ def __init__(self, *args, **kwargs): # these variables do not exist here, we instead only instantiate the maps to allow the # physics mixin to have the logic in place. The creation of the actual variables and filling # of these maps is in the AssetSizingMixin. - self._pipe_topo_pipe_class_map = {} + self._heat_pipe_topo_pipe_class_map = {} + + # Map for setting node nominals in case of logical links. + self.__heat_node_variable_nominal = {} super().__init__(*args, **kwargs) @@ -248,19 +250,20 @@ def _get_min_bound(bound): bounds = self.bounds() + # Set structure used instead of list. Purpose: to make lookup faster when there are many + # pipes in the network. + set_self_hot_pipes = set(self.hot_pipes) + for pipe_name in self.energy_system_components.get("heat_pipe", []): + commodity = self.energy_system_components_commodity.get(pipe_name) head_loss_var = f"{pipe_name}.__head_loss" initialized_vars = self._hn_head_loss_class.initialize_variables_nominals_and_bounds( - self, NetworkSettings.NETWORK_TYPE_HEAT, pipe_name, self.heat_network_settings + self, commodity, pipe_name, self.heat_network_settings ) if initialized_vars[0] != {}: - self.__pipe_head_bounds[f"{pipe_name}.{NetworkSettings.NETWORK_TYPE_HEAT}In.H"] = ( - initialized_vars[0] - ) + self.__pipe_head_bounds[f"{pipe_name}.{commodity}In.H"] = initialized_vars[0] if initialized_vars[1] != {}: - self.__pipe_head_bounds[f"{pipe_name}.{NetworkSettings.NETWORK_TYPE_HEAT}Out.H"] = ( - initialized_vars[1] - ) + self.__pipe_head_bounds[f"{pipe_name}.{commodity}Out.H"] = initialized_vars[1] if initialized_vars[2] != {}: self.__pipe_head_loss_zero_bounds[f"{pipe_name}.dH"] = initialized_vars[2] if initialized_vars[3] != {}: @@ -293,17 +296,17 @@ def _get_min_bound(bound): ] = initialized_vars[10][pipe_linear_line_segment_var_name] neighbour = self.has_related_pipe(pipe_name) - if neighbour and pipe_name not in self.hot_pipes: + if neighbour and pipe_name not in set_self_hot_pipes: flow_dir_var = f"{self.cold_to_hot_pipe(pipe_name)}__flow_direct_var" else: flow_dir_var = f"{pipe_name}__flow_direct_var" - self._pipe_to_flow_direct_map[pipe_name] = flow_dir_var - self.__flow_direct_var[flow_dir_var] = ca.MX.sym(flow_dir_var) + self._heat_pipe_to_flow_direct_map[pipe_name] = flow_dir_var + self.__heat_flow_direct_var[flow_dir_var] = ca.MX.sym(flow_dir_var) - # Fix the directions that are already implied by the bounds on milp - # Nonnegative milp implies that flow direction Boolean is equal to one. - # Nonpositive milp implies that flow direction Boolean is equal to zero. + # Fix the directions that are already implied by the bounds on heat + # Nonnegative heat implies that flow direction Boolean is equal to one. + # Nonpositive heat implies that flow direction Boolean is equal to zero. heat_in_lb = _get_min_bound(bounds[f"{pipe_name}.HeatIn.Heat"][0]) heat_in_ub = _get_max_bound(bounds[f"{pipe_name}.HeatIn.Heat"][1]) @@ -313,24 +316,24 @@ def _get_min_bound(bound): if (heat_in_lb >= 0.0 and heat_in_ub >= 0.0) or ( heat_out_lb >= 0.0 and heat_out_ub >= 0.0 ): - self.__flow_direct_bounds[flow_dir_var] = (1.0, 1.0) + self.__heat_flow_direct_bounds[flow_dir_var] = (1.0, 1.0) elif (heat_in_lb <= 0.0 and heat_in_ub <= 0.0) or ( heat_out_lb <= 0.0 and heat_out_ub <= 0.0 ): - self.__flow_direct_bounds[flow_dir_var] = (0.0, 0.0) + self.__heat_flow_direct_bounds[flow_dir_var] = (0.0, 0.0) else: - self.__flow_direct_bounds[flow_dir_var] = (0.0, 1.0) + self.__heat_flow_direct_bounds[flow_dir_var] = (0.0, 1.0) if parameters[f"{pipe_name}.disconnectable"]: neighbour = self.has_related_pipe(pipe_name) - if neighbour and pipe_name not in self.hot_pipes: + if neighbour and pipe_name not in set_self_hot_pipes: disconnected_var = f"{self.cold_to_hot_pipe(pipe_name)}__is_disconnected" else: disconnected_var = f"{pipe_name}__is_disconnected" - self._pipe_disconnect_map[pipe_name] = disconnected_var - self.__pipe_disconnect_var[disconnected_var] = ca.MX.sym(disconnected_var) - self.__pipe_disconnect_var_bounds[disconnected_var] = (0.0, 1.0) + self._heat_pipe_disconnect_map[pipe_name] = disconnected_var + self.__heat_pipe_disconnect_var[disconnected_var] = ca.MX.sym(disconnected_var) + self.__heat_pipe_disconnect_var_bounds[disconnected_var] = (0.0, 1.0) if heat_in_ub <= 0.0 and heat_out_lb >= 0.0: raise Exception(f"Heat flow rate in/out of pipe '{pipe_name}' cannot be zero.") @@ -364,6 +367,9 @@ def _get_min_bound(bound): (_cold_pipe, _cold_pipe_orientation), ) in self.energy_system_topology.ates.items(): + if ates in self.energy_system_components.get("low_temperature_ates", []): + continue + ates_temp_disc_var_name = f"{ates}__temperature_ates_disc" self.__ates_temperature_disc_var[ates_temp_disc_var_name] = ca.MX.sym( ates_temp_disc_var_name @@ -458,8 +464,8 @@ def _get_min_bound(bound): self.__pipe_heat_loss_parameters.append({}) for pipe in self.energy_system_components.get("heat_pipe", []): - # For similar reasons as for the diameter, we always make a milp - # loss symbol, even if the milp loss is fixed. Note that we also + # For similar reasons as for the diameter, we always make a heat + # loss symbol, even if the heat loss is fixed. Note that we also # override the .Heat_loss parameter for cold pipes, even though # it is not actually used in the optimization problem. heat_loss_var_name = f"{pipe}__hn_heat_loss" @@ -471,7 +477,7 @@ def _get_min_bound(bound): self._pipe_heat_loss_map[pipe] = heat_loss_var_name if options["neglect_pipe_heat_losses"]: - # No decision to make for this pipe w.r.t. milp loss + # No decision to make for this pipe w.r.t. heat loss self._pipe_heat_loss_var_bounds[heat_loss_var_name] = ( 0.0, 0.0, @@ -487,12 +493,16 @@ def _get_min_bound(bound): else: heat_loss = pipe_heat_loss(self, options, parameters, pipe) + if parameters[f"{pipe}.temperature"] > parameters[f"{pipe}.T_ground"]: + lb = 0.0 + else: + lb = 2.0 * heat_loss self._pipe_heat_loss_var_bounds[heat_loss_var_name] = ( - 0.0, - 2.0 * heat_loss, + lb, + 2.0 * abs(heat_loss), ) self._pipe_heat_loss_nominals[heat_loss_var_name] = max( - heat_loss, + abs(heat_loss), 1.0, ) @@ -531,15 +541,48 @@ def _get_min_bound(bound): ] = (0.0, 1.0) # Check that buffer information is logical and - # set the stored milp at t0 in the buffer(s) via bounds + # set the stored heat at t0 in the buffer(s) via bounds if len(self.times()) > 2: self.__check_buffer_values_and_set_bounds_at_t0() self.__maximum_total_head_loss = self.__get_maximum_total_head_loss() + # Setting the node nominals using the connected assets. + for node, connected_assets in self.energy_system_topology.nodes.items(): + nominals = {} + for var in ["Q", "H", "Heat", "Hydraulic_power"]: + nominals[var] = [] + for _, (asset, _orientation) in connected_assets.items(): + var_nom = self.variable_nominal(f"{asset}.HeatOut.{var}") + if var_nom != 1: + nominals[var].append(var_nom) + elif self.variable_nominal(f"{asset}.HeatIn.{var}") != 1: + nominals[var].append(self.variable_nominal(f"{asset}.HeatIn.{var}")) + else: + nominals[var].append(1) + + for i in range(len(connected_assets)): + if self.variable_nominal(f"{node}.HeatConn[{i + 1}].{var}") == 1: + if nominals[var][i] != 1: + # Here we set a nominal based directly on the connected asset. + self.__heat_node_variable_nominal[f"{node}.HeatConn[{i + 1}].{var}"] = ( + nominals[var][i] + ) + else: + # Here we set a nominal based on median of all the connected assets to + # the node. This is specifically done when we have a logical link for + # node to node. In this case we cannot set the nominal based on the + # connected node, hence we assume a node has at least one not node + # asset connected to it. + self.__heat_node_variable_nominal[f"{node}.HeatConn[{i + 1}].{var}"] = ( + np.median([x for x in nominals[var] if x != 1]) + if np.sum(nominals[var]) != len(nominals[var]) + else 1.0 + ) + def energy_system_options(self): r""" - Returns a dictionary of milp network physics specific options. + Returns a dictionary of heat network physics specific options. +--------------------------------------+-----------+-----------------------------+ | Option | Type | Default value | @@ -560,25 +603,25 @@ def energy_system_options(self): The ``maximum_temperature_der`` gives the maximum temperature change per hour. Similarly, the ``maximum_flow_der`` parameter gives the maximum flow change per hour. These options together are used to - constrain the maximum milp change per hour allowed in the entire + constrain the maximum heat change per hour allowed in the entire network. Note the unit for flow is m3/s, but the change is expressed on an hourly basis leading to the ``m3/s/hour`` unit. The ``heat_loss_disconnected_pipe`` option decides whether a - disconnectable pipe has milp loss or not when it is disconnected on - that particular time step. By default, a pipe has milp loss even if + disconnectable pipe has heat loss or not when it is disconnected on + that particular time step. By default, a pipe has heat loss even if it is disconnected, as it would still contain relatively hot water in - reality. We also do not want minimization of milp production to lead + reality. We also do not want minimization of heat production to lead to overly disconnecting pipes. In some scenarios it is hydraulically - impossible to supply milp to these disconnected pipes (Q is forced to + impossible to supply heat to these disconnected pipes (Q is forced to zero), in which case this option can be set to ``False``. - The ``neglect_pipe_heat_losses`` option sets the milp loss in pipes to + The ``neglect_pipe_heat_losses`` option sets the heat loss in pipes to zero. This can be useful when the insulation properties are unknown. - Note that other components can still have milp loss, e.g. a buffer. + Note that other components can still have heat loss, e.g. a buffer. The ``include_demand_insulation_options`` options is used, when insulations options per - demand is specificied, to include milp demand and supply matching via constraints for all + demand is specificied, to include heat demand and supply matching via constraints for all possible insulation options. """ @@ -631,8 +674,8 @@ def path_variables(self): """ variables = super().path_variables.copy() variables.extend(self.__pipe_head_loss_var.values()) - variables.extend(self.__flow_direct_var.values()) - variables.extend(self.__pipe_disconnect_var.values()) + variables.extend(self.__heat_flow_direct_var.values()) + variables.extend(self.__heat_pipe_disconnect_var.values()) variables.extend(self.__check_valve_status_var.values()) variables.extend(self.__control_valve_direction_var.values()) variables.extend(self.__demand_insulation_class_var.values()) @@ -653,8 +696,8 @@ def variable_is_discrete(self, variable): All variables that only can take integer values should be added to this function. """ if ( - variable in self.__flow_direct_var - or variable in self.__pipe_disconnect_var + variable in self.__heat_flow_direct_var + or variable in self.__heat_pipe_disconnect_var or variable in self.__check_valve_status_var or variable in self.__control_valve_direction_var or variable in self.__demand_insulation_class_var @@ -680,6 +723,8 @@ def variable_nominal(self, variable): return self.__pipe_head_loss_nominals[variable] elif variable in self.__ates_max_stored_heat_nominals: return self.__ates_max_stored_heat_nominals[variable] + elif variable in self.__heat_node_variable_nominal: + return self.__heat_node_variable_nominal[variable] else: return super().variable_nominal(variable) @@ -689,8 +734,8 @@ def bounds(self): the HeatMixin. """ bounds = super().bounds() - bounds.update(self.__flow_direct_bounds) - bounds.update(self.__pipe_disconnect_var_bounds) + bounds.update(self.__heat_flow_direct_bounds) + bounds.update(self.__heat_pipe_disconnect_var_bounds) bounds.update(self.__check_valve_status_var_bounds) bounds.update(self.__control_valve_direction_var_bounds) bounds.update(self.__buffer_t0_bounds) @@ -811,7 +856,7 @@ def __check_buffer_values_and_set_bounds_at_t0(self): """ In this function we force the buffer at t0 to have a certain amount of set energy in it. We do this via the bounds, by providing the bounds with a time-series where the first - element is the initial milp in the buffer. + element is the initial heat in the buffer. """ t = self.times() # We assume that t0 is always equal to self.times()[0] @@ -838,7 +883,7 @@ def __check_buffer_values_and_set_bounds_at_t0(self): stored_heat = f"{b}.Stored_heat" if not np.isnan(vol_t0) and not np.isnan(heat_t0): raise Exception( - f"At most one between the initial milp and volume of {b} should be prescribed." + f"At most one between the initial heat and volume of {b} should be prescribed." ) if np.isnan(heat_t0): @@ -851,14 +896,14 @@ def __check_buffer_values_and_set_bounds_at_t0(self): default_vol_t0 = min_fract_vol * volume heat_t0 = default_vol_t0 * dt * cp * rho - # Check that volume/initial stored milp at t0 is within bounds + # Check that volume/initial stored heat at t0 is within bounds lb_heat, ub_heat = bounds[stored_heat] lb_heat_t0 = np.inf ub_heat_t0 = -np.inf for bound in [lb_heat, ub_heat]: assert not isinstance( bound, np.ndarray - ), f"{b} stored milp cannot be a vector state" + ), f"{b} stored heat cannot be a vector state" if isinstance(bound, Timeseries): bound_t0 = bound.values[0] else: @@ -867,9 +912,9 @@ def __check_buffer_values_and_set_bounds_at_t0(self): ub_heat_t0 = max(ub_heat_t0, bound_t0) if heat_t0 < lb_heat_t0 or heat_t0 > ub_heat_t0: - raise Exception(f"Initial milp of {b} is not within bounds.") + raise Exception(f"Initial heat of {b} is not within bounds.") - # Set milp at t0 + # Set heat at t0 lb = np.full_like(t, -np.inf) ub = np.full_like(t, np.inf) lb[0] = heat_t0 @@ -879,16 +924,16 @@ def __check_buffer_values_and_set_bounds_at_t0(self): def __heat_matching_demand_insulation_constraints(self, ensemble_member): """ - Consider all possible milp demand insulation options (each options has an assosiated unique + Consider all possible heat demand insulation options (each options has an assosiated unique demand profile for the specific demand) and add constraints such that only one insulation options is activated per demand. The constraints will then ensure aim to match the supply and demand. Note: - This function is only active when the "include_demand_insulation_options" (False by - default) has been set to True in the milp network options. + default) has been set to True in the heat network options. - Currently this functional requires that all demands have at least one insualtion option is - specified for every demand in the milp network. + specified for every demand in the heat network. """ constraints = [] @@ -970,7 +1015,7 @@ def __heat_matching_demand_insulation_constraints(self, ensemble_member): def __pipe_rate_heat_change_constraints(self, ensemble_member): """ - To avoid sudden change in milp from a timestep to the next, + To avoid sudden change in heat from a timestep to the next, constraints on d(Heat)/dt are introduced. Information of restrictions on dQ/dt and dT/dt are used, as d(Heat)/dt is proportional to average_temperature * dQ/dt + average_discharge * dT/dt. @@ -986,8 +1031,8 @@ def __pipe_rate_heat_change_constraints(self, ensemble_member): if np.isfinite(t_change) and np.isfinite(q_change): assert ( - not self._pipe_topo_pipe_class_map - ), "milp rate change constraints not allowed with topology optimization" + not self._heat_pipe_topo_pipe_class_map + ), "heat rate change constraints not allowed with topology optimization" for p in self.energy_system_components.get("heat_pipe", []): variable = f"{p}.HeatIn.Heat" @@ -1027,7 +1072,7 @@ def __pipe_rate_heat_change_constraints(self, ensemble_member): def __node_heat_mixing_path_constraints(self, ensemble_member): """ - This function adds constraints for each milp network node/joint to have as much + This function adds constraints for each heat network node/joint to have as much thermal power (Heat variable) going in as out. Effectively, it is setting the sum of thermal powers to zero. """ @@ -1093,21 +1138,21 @@ def __node_hydraulic_power_mixing_path_constraints(self, ensemble_member): def __heat_loss_path_constraints(self, ensemble_member): """ - This function adds the constraints to subtract the milp losses from the thermal power that + This function adds the constraints to subtract the heat losses from the thermal power that propagates through the network. Note that this is done only on the thermal power, as such only energy losses are accounted for, temperature losses are not considered. - There are a few cases for the milp loss constraints + There are a few cases for the heat loss constraints - Heat losses are constant: This is the case when the pipe class is constant and the - network temperature is constant. In this case the symbol for the milp-loss is fixed by its + network temperature is constant. In this case the symbol for the heat-loss is fixed by its lower and upper bound to a value. - - Heat losses depend on pipe_class: In this case the milp loss depend on the pipe class - selected by the optimization. In this case the milp losses can vary due to the varying + - Heat losses depend on pipe_class: In this case the heat loss depend on the pipe class + selected by the optimization. In this case the heat losses can vary due to the varying radiation surface and different insulation materials applied to the pipe. Note that the - influences of varying pipe class are taken into account while setting the milp-loss + influences of varying pipe class are taken into account while setting the heat-loss variable in topology constraints. - - Heat losses depend on varying network temperature: In this case the milp loss varies due - to the different delta temperature with ambient. Note that the milp loss symbol does not + - Heat losses depend on varying network temperature: In this case the heat loss varies due + to the different delta temperature with ambient. Note that the heat loss symbol does not account for the varying temperature. Therefore, the big_m formulation is needed in these constraints. - Heat losses depend both on varying network temperature and pipe classes: In this case @@ -1131,7 +1176,7 @@ def __heat_loss_path_constraints(self, ensemble_member): ) ) - is_disconnected_var = self._pipe_disconnect_map.get(p) + is_disconnected_var = self._heat_pipe_disconnect_map.get(p) if is_disconnected_var is None: is_disconnected = 0.0 @@ -1157,11 +1202,11 @@ def __heat_loss_path_constraints(self, ensemble_member): ) ) else: - # Force milp loss to `heat_loss` when pipe is connected, and zero otherwise. + # Force heat loss to `heat_loss` when pipe is connected, and zero otherwise. heat_loss_nominal = self._pipe_heat_loss_nominals[heat_loss_sym_name] constraint_nominal = (big_m * heat_loss_nominal) ** 0.5 - # Force milp loss to `heat_loss` when pipe is connected. + # Force heat loss to `heat_loss` when pipe is connected. constraints.append( ( (heat_in - heat_out - heat_loss - is_disconnected * big_m) @@ -1207,7 +1252,7 @@ def __flow_direction_path_constraints(self, ensemble_member): The directions are set based upon the directions of how thermal power propegates. This is done based upon the sign of the Heat variable. Where positive Heat means a positive - direction and negative milp means a negative direction. By default, positive is defined from + direction and negative heat means a negative direction. By default, positive is defined from HeatIn to HeatOut. Finally, a minimum flow can be set. This can sometimes be useful for numerical stability. @@ -1218,12 +1263,12 @@ def __flow_direction_path_constraints(self, ensemble_member): minimum_velocity = self.heat_network_settings["minimum_velocity"] maximum_velocity = self.heat_network_settings["maximum_velocity"] - # Also ensure that the discharge has the same sign as the milp. + # Also ensure that the discharge has the same sign as the heat. for p in self.energy_system_components.get("heat_pipe", []): - flow_dir_var = self._pipe_to_flow_direct_map[p] + flow_dir_var = self._heat_pipe_to_flow_direct_map[p] flow_dir = self.state(flow_dir_var) - is_disconnected_var = self._pipe_disconnect_map.get(p) + is_disconnected_var = self._heat_pipe_disconnect_map.get(p) if is_disconnected_var is None: is_disconnected = 0.0 @@ -1235,9 +1280,9 @@ def __flow_direction_path_constraints(self, ensemble_member): heat_out = self.state(f"{p}.HeatOut.Heat") try: - pipe_classes = self._pipe_topo_pipe_class_map[p].keys() + pipe_classes = self._heat_pipe_topo_pipe_class_map[p].keys() maximum_discharge = max([c.maximum_discharge for c in pipe_classes]) - var_names = self._pipe_topo_pipe_class_map[p].values() + var_names = self._heat_pipe_topo_pipe_class_map[p].values() dn_none = 0.0 for i, pc in enumerate(pipe_classes): if pc.inner_diameter == 0.0: @@ -1297,7 +1342,7 @@ def __flow_direction_path_constraints(self, ensemble_member): ) ) ) - # Note we only need one on the milp as the desired behaviour is propegated by the + # Note we only need one on the heat as the desired behaviour is propegated by the # constraints heat_in - heat_out - heat_loss == 0. constraints.append( ( @@ -1338,7 +1383,7 @@ def __flow_direction_path_constraints(self, ensemble_member): ((heat_out + (1 - is_disconnected) * big_m) / big_m, 0.0, np.inf) ) - # Pipes that are connected in series should have the same milp direction. + # Pipes that are connected in series should have the same heat direction. for pipes in self.energy_system_topology.pipe_series: if len(pipes) <= 1: continue @@ -1347,10 +1392,10 @@ def __flow_direction_path_constraints(self, ensemble_member): len({p for p in pipes if self.is_cold_pipe(p)}) == 0 ), "Pipe series for Heat models should only contain hot pipes" - base_flow_dir_var = self.state(self._pipe_to_flow_direct_map[pipes[0]]) + base_flow_dir_var = self.state(self._heat_pipe_to_flow_direct_map[pipes[0]]) for p in pipes[1:]: - flow_dir_var = self.state(self._pipe_to_flow_direct_map[p]) + flow_dir_var = self.state(self._heat_pipe_to_flow_direct_map[p]) constraints.append((base_flow_dir_var - flow_dir_var, 0.0, 0.0)) return constraints @@ -1359,20 +1404,21 @@ def __demand_heat_to_discharge_path_constraints(self, ensemble_member): """ This function adds constraints linking the flow to the thermal power at the demand assets. We use an equality constraint on the outgoing flow for every non-pipe asset. Meaning that we - equate Q * rho * cp * T == Heat for outgoing flows, and inequalities for the milp carried - in the pipes. This means that the milp can decrease in the network to compensate losses, + equate Q * rho * cp * T == Heat for outgoing flows, and inequalities for the heat carried + in the pipes. This means that the heat can decrease in the network to compensate losses, but that the losses and thus flow will always be over-estimated with the temperature for which no temperature drops are modelled. """ constraints = [] parameters = self.parameters(ensemble_member) - for d in self.energy_system_components.get("heat_demand", []): + for d in [ + *self.energy_system_components.get("heat_demand", []), + *self.energy_system_components.get("airco", []), + ]: heat_nominal = parameters[f"{d}.Heat_nominal"] cp = parameters[f"{d}.cp"] rho = parameters[f"{d}.rho"] - # TODO: future work - some sort of correction factor to account for temp drop n pipe: - # (maximum/average lenght fromm source to demand) * V_nominal * temperature_loss_factor discharge = self.state(f"{d}.Q") heat_out = self.state(f"{d}.HeatOut.Heat") @@ -1423,8 +1469,8 @@ def __source_heat_to_discharge_path_constraints(self, ensemble_member): """ This function adds constraints linking the flow to the thermal power at the demand assets. We use an equality constraint on the outgoing flow for every non-pipe asset. Meaning that we - equate Q * rho * cp * T == Heat for outgoing flows, and inequalities for the milp carried - in the pipes. This means that the milp can decrease in the network to compensate losses, + equate Q * rho * cp * T == Heat for outgoing flows, and inequalities for the heat carried + in the pipes. This means that the heat can decrease in the network to compensate losses, but that the losses and thus flow will always be over-estimated with the temperature for which no temperature drops are modelled. """ @@ -1446,6 +1492,11 @@ def __source_heat_to_discharge_path_constraints(self, ensemble_member): sup_carrier = parameters[f"{s}.T_supply_id"] supply_temperatures = self.temperature_regimes(sup_carrier) big_m = 2.0 * self.bounds()[f"{s}.HeatOut.Heat"][1] + big_m = ( + big_m + if big_m != np.inf + else 2.0 * self.bounds()[f"{s}.Heat_source"][1] * parameters[f"{s}.T_supply"] / dt + ) if len(supply_temperatures) == 0: constraints.append( @@ -1487,126 +1538,84 @@ def __source_heat_to_discharge_path_constraints(self, ensemble_member): return constraints - def __pipe_hydraulic_power_path_constraints(self, ensemble_member): + def __cold_demand_heat_to_discharge_path_constraints(self, ensemble_member): """ - This function adds constraints to compute the hydraulic power that is needed to realize the - flow, compensating the pressure drop through the pipe. Similar to the head loss constraints - we allow two supported methods. 1) a single linear line between 0 to max velocity. 2) A - multiple line inequality approach where one can use the minimize_head_losses == True option - to drag down the solution to the actual physical solution. + This function adds constraints linking the flow to the thermal power at the cold demand + assets. We use an equality constraint on the outgoing flow for every non-pipe asset. + Meaning that we equate Q * rho * cp * T == Heat for outgoing flows, and inequalities for + the heat carried in the pipes. This means that the heat can decrease in the network to + compensate losses, but that the losses and thus flow will always be over-estimated with the + temperature for which no temperature drops are modelled. - Note that the linearizations are made separately from the pressure drop constraints, this is - done to avoid "stacked" overestimations. + In the specific case of cold demand the temperature in the network can be below the ground + temperature. This causes negative heat losses as the flow is heated up by the ground, we + therefore constrain the discharge with the theoretical maximum temperature, which is the + ground temperature. """ constraints = [] - options = self.energy_system_options() - - if self.heat_network_settings["head_loss_option"] != HeadLossOption.NO_HEADLOSS: - parameters = self.parameters(ensemble_member) - components = self.energy_system_components + parameters = self.parameters(ensemble_member) - for pipe in components.get("heat_pipe", []): - if parameters[f"{pipe}.length"] == 0.0: - # If the pipe does not have a control valve, the head loss is - # forced to zero via bounds. If the pipe _does_ have a control - # valve, then there still is no relationship between the - # discharge and the hydraulic_power. - continue - - head_loss_option = self._hn_get_pipe_head_loss_option( - pipe, self.heat_network_settings, parameters - ) - assert ( - head_loss_option != HeadLossOption.NO_HEADLOSS - ), "This method should be skipped when NO_HEADLOSS is set." - - discharge = self.state(f"{pipe}.Q") - hydraulic_power = self.state(f"{pipe}.Hydraulic_power") - rho = parameters[f"{pipe}.rho"] - - # 0: pipe is connected, 1: pipe is disconnected - is_disconnected_var = self._pipe_disconnect_map.get(pipe) - if is_disconnected_var is None: - is_disconnected = 0.0 - else: - is_disconnected = self.state(is_disconnected_var) - - flow_dir_var = self._pipe_to_flow_direct_map[pipe] - flow_dir = self.state(flow_dir_var) # 0/1: negative/positive flow direction - - if pipe in self._pipe_topo_pipe_class_map: - # Multiple diameter options for this pipe - pipe_classes = self._pipe_topo_pipe_class_map[pipe] - max_discharge = max(c.maximum_discharge for c in pipe_classes) - for pc, pc_var_name in pipe_classes.items(): - if pc.inner_diameter == 0.0: - continue - - # Calc max hydraulic power based on maximum_total_head_loss = - # f(max_sum_dh_pipes, max_dh_network_options) - max_total_hydraulic_power = 2.0 * ( - rho - * GRAVITATIONAL_CONSTANT - * self.__maximum_total_head_loss - * max_discharge - ) + for d in self.energy_system_components.get("cold_demand", []): + heat_nominal = parameters[f"{d}.Heat_nominal"] + cp = parameters[f"{d}.cp"] + rho = parameters[f"{d}.rho"] + discharge = self.state(f"{d}.Q") + heat_out = self.state(f"{d}.HeatOut.Heat") - # is_topo_disconnected - 0: pipe selected, 1: pipe disconnected/not selected - # self.__pipe_topo_pipe_class_var - value 0: pipe is not selected, 1: pipe - # is selected - is_topo_disconnected = 1 - self.variable(pc_var_name) + sup_carrier = parameters[f"{d}.T_supply_id"] + supply_temperatures = self.temperature_regimes(sup_carrier) + big_m = 2.0 * self.bounds()[f"{d}.HeatOut.Heat"][1] - constraints.extend( - self._hn_head_loss_class._hydraulic_power( - pipe, - self, - options, - self.heat_network_settings, - parameters, - discharge, - hydraulic_power, - is_disconnected=is_topo_disconnected + is_disconnected, - big_m=max_total_hydraulic_power, - pipe_class=pc, - flow_dir=flow_dir, + if len(supply_temperatures) == 0: + constraints.append( + ( + (heat_out - discharge * cp * rho * parameters[f"{d}.T_supply"]) + / heat_nominal, + 0.0, + 0.0, + ) + ) + else: + for sup_temperature in supply_temperatures: + sup_temperature_is_selected = self.state(f"{sup_carrier}_{sup_temperature}") + constraints.append( + ( + ( + heat_out + - discharge * cp * rho * sup_temperature + + (1.0 - sup_temperature_is_selected) * big_m ) + / heat_nominal, + 0.0, + np.inf, ) - else: - is_topo_disconnected = int(parameters[f"{pipe}.diameter"] == 0.0) - max_total_hydraulic_power = 2.0 * ( - rho - * GRAVITATIONAL_CONSTANT - * self.__maximum_total_head_loss - * parameters[f"{pipe}.area"] - * self.heat_network_settings["maximum_velocity"] ) - constraints.extend( - self._hn_head_loss_class._hydraulic_power( - pipe, - self, - options, - self.heat_network_settings, - parameters, - discharge, - hydraulic_power, - is_disconnected=is_disconnected + is_topo_disconnected, - big_m=max_total_hydraulic_power, - flow_dir=flow_dir, + constraints.append( + ( + ( + heat_out + - discharge * cp * rho * sup_temperature + - (1.0 - sup_temperature_is_selected) * big_m + ) + / heat_nominal, + -np.inf, + 0.0, ) ) + return constraints def __pipe_heat_to_discharge_path_constraints(self, ensemble_member): """ This function adds constraints linking the flow to the thermal power at the pipe assets. We use an equality constraint on the outgoing flow for every non-pipe asset. Meaning that we - equate Q * rho * cp * T == Heat for outgoing flows, and inequalities for the milp carried - in the pipes. This means that the milp can decrease in the network to compensate losses, + equate Q * rho * cp * T == Heat for outgoing flows, and inequalities for the heat carried + in the pipes. This means that the heat can decrease in the network to compensate losses, but that the losses and thus flow will always be over-estimated with the temperature for which no temperature drops are modelled. There are three cases for the constraint, namely: - - no milp losses: In this case a single equality constraint can be used. + - no heat losses: In this case a single equality constraint can be used. - constant network temperature: In this case there is a single set inequality constraints - varying network temperature: In this case a set of big_m constraints is used to "activate" only the constraints with the selected network temperature. @@ -1627,9 +1636,8 @@ def __pipe_heat_to_discharge_path_constraints(self, ensemble_member): for p in self.energy_system_components.get("heat_pipe", []): cp = parameters[f"{p}.cp"] rho = parameters[f"{p}.rho"] - temp = parameters[f"{p}.temperature"] - flow_dir_var = self._pipe_to_flow_direct_map[p] + flow_dir_var = self._heat_pipe_to_flow_direct_map[p] flow_dir = self.state(flow_dir_var) scaled_heat_in = self.state(f"{p}.HeatIn.Heat") # * heat_to_discharge_fac scaled_heat_out = self.state(f"{p}.HeatOut.Heat") # * heat_to_discharge_fac @@ -1649,6 +1657,7 @@ def __pipe_heat_to_discharge_path_constraints(self, ensemble_member): for heat in [scaled_heat_in, scaled_heat_out]: if self.energy_system_options()["neglect_pipe_heat_losses"]: + temp = parameters[f"{p}.temperature"] if len(temperatures) == 0: constraints.append( ( @@ -1685,6 +1694,12 @@ def __pipe_heat_to_discharge_path_constraints(self, ensemble_member): ) ) else: + # Note that during cold delivery the line can be colder than the ground + # temperature. + # In this case we have to bound the heat flowing in the line with the ground + # temperature instead, as the line can heat up to at maximum the ground + # temperature. + temp = max(parameters[f"{p}.temperature"], parameters[f"{p}.T_ground"]) assert big_m > 0.0 carrier = parameters[f"{p}.carrier_id"] @@ -1708,6 +1723,7 @@ def __pipe_heat_to_discharge_path_constraints(self, ensemble_member): elif len(temperatures) > 0: for temperature in temperatures: temperature_is_selected = self.state(f"{carrier}_{temperature}") + temperature = max(temperature, parameters[f"{p}.T_ground"]) constraints.append( ( ( @@ -1787,7 +1803,10 @@ def __ates_temperature_path_constraints(self, ensemble_member): (_cold_pipe, _cold_pipe_orientation), ) in {**self.energy_system_topology.ates}.items(): - flow_dir_var = self._pipe_to_flow_direct_map[hot_pipe] + if ates_asset in self.energy_system_components.get("low_temperature_ates", []): + continue + + flow_dir_var = self._heat_pipe_to_flow_direct_map[hot_pipe] is_buffer_charging = self.state(flow_dir_var) * _hot_pipe_orientation sup_carrier = parameters[f"{ates_asset}.T_supply_id"] @@ -2055,20 +2074,22 @@ def __ates_temperature_changing_path_constraints(self, ensemble_member): (_cold_pipe, _cold_pipe_orientation), ) in {**self.energy_system_topology.ates}.items(): + if ates in self.energy_system_components.get("low_temperature_ates", []): + continue + ates_dt_charging = self.state(f"{ates}.Temperature_change_charging") ates_dt_loss = self.state(f"{ates}.Temperature_loss") + ates_temperature_loss_nominal = self.variable_nominal(f"{ates}.Temperature_loss") + ates_dt_charging_nominal = self.variable_nominal(f"{ates}.Temperature_change_charging") + sup_carrier = parameters[f"{ates}.T_supply_id"] supply_temperatures = self.temperature_regimes(sup_carrier) if options["include_ates_temperature_options"] and len(supply_temperatures) != 0: soil_temperature = parameters[f"{ates}.T_amb"] - ates_temperature_loss_nominal = self.variable_nominal(f"{ates}.Temperature_loss") - ates_dt_charging_nominal = self.variable_nominal( - f"{ates}.Temperature_change_charging" - ) - flow_dir_var = self._pipe_to_flow_direct_map[hot_pipe] + flow_dir_var = self._heat_pipe_to_flow_direct_map[hot_pipe] is_buffer_charging = self.state(flow_dir_var) * _hot_pipe_orientation heat_stored_max = bounds[f"{ates}.Stored_heat"][1] heat_ates_max = bounds[f"{ates}.Heat_ates"][1] @@ -2182,8 +2203,8 @@ def __ates_temperature_changing_path_constraints(self, ensemble_member): ) ) else: - constraints.append((ates_dt_charging, 0.0, 0.0)) - constraints.append((ates_dt_loss, 0.0, 0.0)) + constraints.append((ates_dt_charging / ates_dt_charging_nominal, 0.0, 0.0)) + constraints.append((ates_dt_loss / ates_temperature_loss_nominal, 0.0, 0.0)) return constraints def __ates_heat_losses_path_constraints(self, ensemble_member): @@ -2202,7 +2223,10 @@ def __ates_heat_losses_path_constraints(self, ensemble_member): bounds = self.bounds() options = self.energy_system_options() - for ates in self.energy_system_components.get("ates", []): + for ates in [ + *self.energy_system_components.get("ates", []), + *self.energy_system_components.get("low_temperature_ates", []), + ]: heat_loss_nominal = self.variable_nominal(f"{ates}.Heat_loss") soil_temperature = parameters[f"{ates}.T_amb"] heat_stored_max = bounds[f"{ates}.Stored_heat"][1] @@ -2213,7 +2237,11 @@ def __ates_heat_losses_path_constraints(self, ensemble_member): sup_carrier = parameters[f"{ates}.T_supply_id"] supply_temperatures = self.temperature_regimes(sup_carrier) - if options["include_ates_temperature_options"] and len(supply_temperatures) != 0: + if ( + options["include_ates_temperature_options"] + and len(supply_temperatures) != 0 + and ates in self.energy_system_components.get("ates", []) + ): big_m_heatloss = 2 * heat_loss_nominal for ates_temperature in supply_temperatures: ates_temperature_is_selected = self.state( @@ -2265,8 +2293,8 @@ def __storage_heat_to_discharge_path_constraints(self, ensemble_member): """ This function adds constraints linking the flow to the thermal power at the pipe assets. We use an equality constraint on the outgoing flow for every non-pipe asset. Meaning that we - equate Q * rho * cp * T == Heat for outgoing flows, and inequalities for the milp carried - in the pipes. This means that the milp can decrease in the network to compensate losses, + equate Q * rho * cp * T == Heat for outgoing flows, and inequalities for the heat carried + in the pipes. This means that the heat can decrease in the network to compensate losses, but that the losses and thus flow will always be over-estimated with the temperature for which no temperature drops are modelled. @@ -2286,6 +2314,10 @@ def __storage_heat_to_discharge_path_constraints(self, ensemble_member): (hot_pipe, _hot_pipe_orientation), (_cold_pipe, _cold_pipe_orientation), ) in {**self.energy_system_topology.buffers, **self.energy_system_topology.ates}.items(): + if hot_pipe not in self.energy_system_components.get("heat_pipe", []): + # We skip the constraints in case their is a logical link to the storage. + continue + heat_nominal = parameters[f"{b}.Heat_nominal"] q_nominal = self.variable_nominal(f"{b}.Q") cp = parameters[f"{b}.cp"] @@ -2294,17 +2326,17 @@ def __storage_heat_to_discharge_path_constraints(self, ensemble_member): discharge = self.state(f"{b}.HeatIn.Q") # Note that `heat_hot` can be negative for the buffer; in that case we - # are extracting milp from it. + # are extracting heat from it. heat_out = self.state(f"{b}.HeatOut.Heat") heat_in = self.state(f"{b}.HeatIn.Heat") - # We want an _equality_ constraint between discharge and milp if the buffer is + # We want an _equality_ constraint between discharge and heat if the buffer is # consuming (i.e. behaving like a "demand"). We want an _inequality_ - # constraint (`|milp| >= |f(Q)|`) just like a "heat_source" component if milp is + # constraint (`|heat| >= |f(Q)|`) just like a "heat_source" component if heat is # extracted from the buffer. We accomplish this by disabling one of # the constraints with a boolean. Note that `discharge` and `heat_hot` # are guaranteed to have the same sign. - flow_dir_var = self._pipe_to_flow_direct_map[hot_pipe] + flow_dir_var = self._heat_pipe_to_flow_direct_map[hot_pipe] is_buffer_charging = self.state(flow_dir_var) big_m = 2.0 * np.max( @@ -2318,7 +2350,7 @@ def __storage_heat_to_discharge_path_constraints(self, ensemble_member): if len(supply_temperatures) == 0: constraint_nominal = (heat_nominal * cp * rho * dt * q_nominal) ** 0.5 - # only when discharging the heat_in should match the milp excactly (like producer) + # only when discharging the heat_in should match the heat excactly (like producer) constraints.append( ( ( @@ -2480,29 +2512,31 @@ def __network_temperature_path_constraints(self, ensemble_member): def __heat_exchanger_heat_to_discharge_path_constraints(self, ensemble_member): """ - This function adds the milp to discharge constraints of components that connect two + This function adds the heat to discharge constraints of components that connect two hydraulically decoupled networks. We assume that there is a dedicated primary side and secondary side and that Thermal power can only flow from primary to secondary. - Following this assumption we use the demand logic to relate milp to discharge at the - primary side and the source logic for relating milp to discharge at the secondary side. + Following this assumption we use the demand logic to relate heat to discharge at the + primary side and the source logic for relating heat to discharge at the secondary side. This function also adds constraints to ensure physically logical temperatures between the primary and secondary side when varying temperature is applied to the optimization. - Assuming a counter flow milp exchanger, this means that the secondary supply temperature + Assuming a counter flow heat exchanger, this means that the secondary supply temperature will always be below the primary supply temperature and that the primary return temperature has to be above the secondary return temperature. - Finally, an is disabled variable is set for when the milp exchanger is not used. This is - needed to allow disabling of the HEX temperature constraints when no milp is flowing + Finally, an is disabled variable is set for when the heat exchanger is not used. This is + needed to allow disabling of the HEX temperature constraints when no heat is flowing through the HEX. """ constraints = [] parameters = self.parameters(ensemble_member) - # The primary side of the milp exchanger acts like a milp consumer, and the secondary side - # acts as a milp producer. Essentially using equality constraints to set the milp leaving - # the secondary side based on the secondary Supply temperature and the milp leaving the + hn_settings = self.heat_network_settings + + # The primary side of the heat exchanger acts like a heat consumer, and the secondary side + # acts as a heat producer. Essentially using equality constraints to set the heat leaving + # the secondary side based on the secondary Supply temperature and the heat leaving the # primary side based on the primary Return temperature. for heat_exchanger in [ @@ -2519,7 +2553,9 @@ def __heat_exchanger_heat_to_discharge_path_constraints(self, ensemble_member): discharge_secondary = self.state(f"{heat_exchanger}.Secondary.HeatOut.Q") heat_primary = self.state(f"{heat_exchanger}.Primary_heat") heat_out_prim = self.state(f"{heat_exchanger}.Primary.HeatOut.Heat") + heat_in_prim = self.state(f"{heat_exchanger}.Primary.HeatIn.Heat") heat_out_sec = self.state(f"{heat_exchanger}.Secondary.HeatOut.Heat") + heat_in_sec = self.state(f"{heat_exchanger}.Secondary.HeatIn.Heat") constraint_nominal = ( cp_prim @@ -2536,51 +2572,227 @@ def __heat_exchanger_heat_to_discharge_path_constraints(self, ensemble_member): big_m = 2.0 * self.bounds()[f"{heat_exchanger}.Primary.HeatOut.Heat"][1] - # primary side - if len(return_temperatures_prim) == 0: + def __constraints_temperature_heat_to_discharge_bypass( + heat_out, expr, sum_temp_selec, big_m: float, constraint_nominal: float + ): + """ + Generic setup of the constraints for the heat to discharge of a heat exchanger. + Ensuring that + - when bypass is allowed, heatout = heatin + - otherwise heatout = Q*cp*rho*Tout + - based on the selected temperatures the approriate expression is added. + + Args: + heat_out: HeatOut variable + exp: expression for heatout + sum_temp_selec: sum of two binary variables and or floats (1.0 or 2.0) to + identify if the temperature for this constraint is selected + big_m: float to activate/deactive this constraint + constraint_nominal: nominal to scale the constraint + + Returns: + + """ + constraints = [] constraints.append( ( - ( - heat_out_prim - - discharge_primary - * cp_prim - * rho_prim - * parameters[f"{heat_exchanger}.Primary.T_return"] - ) - / constraint_nominal, + (heat_out - expr + (2.0 - sum_temp_selec) * big_m) / constraint_nominal, 0.0, + np.inf, + ) + ) + constraints.append( + ( + (heat_out - expr - (2.0 - sum_temp_selec) * big_m) / constraint_nominal, + -np.inf, 0.0, ) ) + return constraints + + def __constraints_temperature_heat_to_discharge_bypass_primary( + temp_prim_in: float, + temp_prim_out: float, + discharge, + cp: float, + rho: float, + heat_in, + heat_out, + temp_high_selec, + temp_low_selec, + big_m: float, + constraint_nominal: float, + ): + """ + Generic setup of the constraints for the primary side of the heat exchanger for + heat to discharge. + Ensuring that + - when bypass is allowed, heatout = heatin + - otherwise heatout = Q*cp*rho*Tout + - based on the selected temperatures + + Args: + temp_prim_in: Primary temperature in + temp_prim_out: Primary temperature out + discharge: Casadi variable for primary volumetric flow + cp: specific heat capacity + rho: density + heat_in: Casadi variable for primary heat in + heat_out: Casadi variable for primary heat out + temp_high_selec: is_selected variable for the primary in temperature or 1.0 + if temperature is fixed + temp_low_selec: is_selected variable for the primary out temperature or 1.0 + if temperature is fixed + big_m: float to activate/deactive this constraint + constraint_nominal: nominal to scale the constraint + + Returns: + + """ + + if temp_prim_out >= temp_prim_in: + expr = heat_in + else: + expr = discharge * cp * rho * temp_prim_out + + return __constraints_temperature_heat_to_discharge_bypass( + heat_out, expr, temp_high_selec + temp_low_selec, big_m, constraint_nominal + ) + + def __constraints_temperature_heat_to_discharge_bypass_secondary( + temp_sec_in: float, + temp_sec_out: float, + discharge, + cp: float, + rho: float, + heat_in, + heat_out, + temp_high_selec, + temp_low_selec, + big_m: float, + constraint_nominal: float, + ): + """ + Generic setup of the constraints for the primary side of the heat exchanger for + heat to discharge. + Ensuring that + - when bypass is allowed, heatout = heatin + - otherwise heatout = Q*cp*rho*Tout + - based on the selected temperatures + + Args: + temp_sec_in: Secondary temperature in + temp_sec_out: Secondary temperature out + discharge: Casadi variable for secondary volumetric flow + cp: specific heat capacity + rho: density + heat_in: Casadi variable for secondary heat in + heat_out: Casadi variable for secondary heat out + temp_high_selec: is_selected variable for the secondary out temperature or 1.0 + if temperature is fixed + temp_low_selec: is_selected variable for the secondary in temperature or + 1.0 if temperature is fixed + big_m: float to activate/deactive this constraint + constraint_nominal: nominal to scale the constraint + + Returns: + + """ + + if temp_sec_in >= temp_sec_out: + expr = heat_in + else: + expr = discharge * cp * rho * temp_sec_out + + return __constraints_temperature_heat_to_discharge_bypass( + heat_out, expr, temp_high_selec + temp_low_selec, big_m, constraint_nominal + ) + + # primary side + if len(return_temperatures_prim) == 0: + return_temperature = parameters[f"{heat_exchanger}.Primary.T_return"] + if len(supply_temperatures_prim) != 0 and hn_settings["heat_exchanger_bypass"]: + for sup_temp in supply_temperatures_prim: + sup_temperature_is_selected = self.state(f"{sup_carrier_prim}_{sup_temp}") + constraints.extend( + __constraints_temperature_heat_to_discharge_bypass_primary( + sup_temp, + return_temperature, + discharge_primary, + cp_prim, + rho_prim, + heat_in_prim, + heat_out_prim, + sup_temperature_is_selected, + 1.0, + big_m, + constraint_nominal, + ) + ) + else: + sup_temp = parameters[f"{heat_exchanger}.Primary.T_supply"] + assert sup_temp >= return_temperature + constraints.extend( + __constraints_temperature_heat_to_discharge_bypass_primary( + sup_temp, + return_temperature, + discharge_primary, + cp_prim, + rho_prim, + heat_in_prim, + heat_out_prim, + 1.0, + 1.0, + big_m, + constraint_nominal, + ) + ) + else: for return_temperature in return_temperatures_prim: ret_temperature_is_selected = self.state( f"{ret_carrier_prim}_{return_temperature}" ) - constraints.append( - ( - ( - heat_out_prim - - discharge_primary * cp_prim * rho_prim * return_temperature - + (1.0 - ret_temperature_is_selected) * big_m + if hn_settings["heat_exchanger_bypass"] and len(supply_temperatures_prim) != 0: + # if bypass of heat exchanger is allowed and the primary in temperature + # is also a variable + for sup_temp in supply_temperatures_prim: + sup_temperature_is_selected = self.state( + f"{sup_carrier_prim}_{sup_temp}" ) - / constraint_nominal, - 0.0, - np.inf, - ) - ) - constraints.append( - ( - ( - heat_out_prim - - discharge_primary * cp_prim * rho_prim * return_temperature - - (1.0 - ret_temperature_is_selected) * big_m + constraints.extend( + __constraints_temperature_heat_to_discharge_bypass_primary( + sup_temp, + return_temperature, + discharge_primary, + cp_prim, + rho_prim, + heat_in_prim, + heat_out_prim, + sup_temperature_is_selected, + ret_temperature_is_selected, + big_m, + constraint_nominal, + ) + ) + + else: + sup_temp = parameters[(f"{heat_exchanger}.Primary.T_supply")] + constraints.extend( + __constraints_temperature_heat_to_discharge_bypass_primary( + sup_temp, + return_temperature, + discharge_primary, + cp_prim, + rho_prim, + heat_in_prim, + heat_out_prim, + 1.0, + ret_temperature_is_selected, + big_m, + constraint_nominal, ) - / constraint_nominal, - -np.inf, - 0.0, ) - ) # Secondary side sup_carrier_sec = parameters[f"{heat_exchanger}.Secondary.T_supply_id"] @@ -2594,49 +2806,87 @@ def __heat_exchanger_heat_to_discharge_path_constraints(self, ensemble_member): ) if len(supply_temperatures_sec) == 0: - constraints.append( - ( - ( - heat_out_sec - - discharge_secondary - * cp_sec - * rho_sec - * parameters[f"{heat_exchanger}.Secondary.T_supply"] + supply_temperature = parameters[f"{heat_exchanger}.Secondary.T_supply"] + if len(return_temperatures_sec) != 0 and hn_settings["heat_exchanger_bypass"]: + for ret_temperature in return_temperatures_sec: + ret_temperature_is_selected = self.state( + f"{ret_carrier_sec}_{ret_temperature}" + ) + constraints.extend( + __constraints_temperature_heat_to_discharge_bypass_secondary( + ret_temperature, + supply_temperature, + discharge_secondary, + cp_sec, + rho_sec, + heat_in_sec, + heat_out_sec, + ret_temperature_is_selected, + 1.0, + big_m, + constraint_nominal, + ) + ) + else: + ret_temperature = parameters[f"{heat_exchanger}.Secondary.T_return"] + assert supply_temperature >= ret_temperature + constraints.extend( + __constraints_temperature_heat_to_discharge_bypass_secondary( + ret_temperature, + supply_temperature, + discharge_secondary, + cp_sec, + rho_sec, + heat_in_sec, + heat_out_sec, + 1.0, + 1.0, + big_m, + constraint_nominal, ) - / constraint_nominal, - 0.0, - 0.0, ) - ) else: for supply_temperature in supply_temperatures_sec: sup_temperature_is_selected = self.state( f"{sup_carrier_sec}_{supply_temperature}" ) - constraints.append( - ( - ( - heat_out_sec - - discharge_secondary * cp_sec * rho_sec * supply_temperature - - (1.0 - sup_temperature_is_selected) * big_m + if len(return_temperatures_sec) != 0 and hn_settings["heat_exchanger_bypass"]: + for ret_temperature in return_temperatures_sec: + ret_temperature_is_selected = self.state( + f"{ret_carrier_sec}_{ret_temperature}" ) - / constraint_nominal, - -np.inf, - 0.0, - ) - ) - constraints.append( - ( - ( - heat_out_sec - - discharge_secondary * cp_sec * rho_sec * supply_temperature - + (1.0 - sup_temperature_is_selected) * big_m + constraints.extend( + __constraints_temperature_heat_to_discharge_bypass_secondary( + ret_temperature, + supply_temperature, + discharge_secondary, + cp_sec, + rho_sec, + heat_in_sec, + heat_out_sec, + ret_temperature_is_selected, + sup_temperature_is_selected, + big_m, + constraint_nominal, + ) + ) + else: + ret_temperature = parameters[f"{heat_exchanger}.Secondary.T_return"] + constraints.extend( + __constraints_temperature_heat_to_discharge_bypass_secondary( + ret_temperature, + supply_temperature, + discharge_secondary, + cp_sec, + rho_sec, + heat_in_sec, + heat_out_sec, + 1.0, + sup_temperature_is_selected, + big_m, + constraint_nominal, ) - / constraint_nominal, - 0.0, - np.inf, ) - ) # disconnect HEX # Getting var for disabled constraints @@ -2686,8 +2936,8 @@ def __heat_exchanger_heat_to_discharge_path_constraints(self, ensemble_member): constraints.append( ( ( - t_sup_prim * sup_prim_t_is_selected - - t_sup_sec * sup_sec_t_is_selected + t_sup_prim + - t_sup_sec + ( is_disabled + (1.0 - sup_prim_t_is_selected) @@ -2788,7 +3038,7 @@ def _hn_pipe_nominal_discharge(self, energy_system_options, parameters, pipe: st This functions returns a nominal for the discharge of pipes under topology optimization. """ try: - pipe_classes = self._pipe_topo_pipe_class_map[pipe].keys() + pipe_classes = self._heat_pipe_topo_pipe_class_map[pipe].keys() area = np.median(c.area for c in pipe_classes) except KeyError: area = parameters[f"{pipe}.area"] @@ -2813,174 +3063,6 @@ def _hn_get_pipe_head_loss_option(pipe, heat_network_settings, parameters): return head_loss_option - def _hn_pipe_head_loss_constraints(self, ensemble_member): - """ - This function adds the head loss constraints for pipes. There are two options namely with - and without pipe class optimization. In both cases we assume that disconnected pipes, pipes - without flow have no head loss. - - Under pipe-class optimization the head loss constraints per pipe class are added and - applied with the big_m method (is_topo_disconnected) to only activate the correct - constraints. - - Under constant pipe class constraints for only one diameter are added. - """ - constraints = [] - - options = self.energy_system_options() - parameters = self.parameters(ensemble_member) - components = self.energy_system_components - # Set the head loss according to the direction in the pipes. Note that - # the `.__head_loss` symbol is always positive by definition, but that - # `.dH` is not (positive when flow is negative, and vice versa). - # If the pipe is disconnected, we leave the .__head_loss symbol free - # (and it has no physical meaning). We also do not set any discharge - # relationship in this case (but dH is still equal to Out - In of - # course). - - for pipe in components.get("heat_pipe", []): - if parameters[f"{pipe}.length"] == 0.0: - # If the pipe does not have a control valve, the head loss is - # forced to zero via bounds. If the pipe _does_ have a control - # valve, then there still is no relationship between the - # discharge and the head loss/dH. - continue - - head_loss_sym = self._hn_pipe_to_head_loss_map[pipe] - - dh = self.__state_vector_scaled(f"{pipe}.dH", ensemble_member) - head_loss = self.__state_vector_scaled(head_loss_sym, ensemble_member) - discharge = self.__state_vector_scaled(f"{pipe}.Q", ensemble_member) - - # We need to make sure the dH is decoupled from the discharge when - # the pipe is disconnected. Simply put, this means making the - # below constraints trivial. - is_disconnected_var = self._pipe_disconnect_map.get(pipe) - - if is_disconnected_var is None: - is_disconnected = 0.0 - else: - is_disconnected = self.__state_vector_scaled(is_disconnected_var, ensemble_member) - - max_discharge = None - max_head_loss = -np.inf - - if pipe in self._pipe_topo_pipe_class_map: - # Multiple diameter options for this pipe - pipe_classes = self._pipe_topo_pipe_class_map[pipe] - max_discharge = max(c.maximum_discharge for c in pipe_classes) - - for pc, pc_var_name in pipe_classes.items(): - if pc.inner_diameter == 0.0: - continue - - head_loss_max_discharge = self._hn_head_loss_class._hn_pipe_head_loss( - pipe, - self, - options, - self.heat_network_settings, - parameters, - max_discharge, - pipe_class=pc, - ) - - big_m = max(1.1 * self.__maximum_total_head_loss, 2 * head_loss_max_discharge) - - is_topo_disconnected = 1 - self.extra_variable(pc_var_name, ensemble_member) - is_topo_disconnected = ca.repmat(is_topo_disconnected, dh.size1()) - - # Note that we add the two booleans `is_disconnected` and - # `is_topo_disconnected`. This is allowed because of the way the - # resulting expression is used in the Big-M formulation. We only care - # that the expression (i.e. a single boolean or the sum of the two - # booleans) is either 0 when the pipe is connected, or >= 1 when it - # is disconnected. - constraints.extend( - self._hn_head_loss_class._hn_pipe_head_loss( - pipe, - self, - options, - self.heat_network_settings, - parameters, - discharge, - head_loss, - dh, - is_disconnected + is_topo_disconnected, - big_m, - pc, - ) - ) - - # Contrary to the Big-M calculation above, the relation - # between dH and the head loss symbol requires the - # maximum head loss that can be realized effectively. So - # we pass the current pipe class's maximum discharge. - max_head_loss = max( - max_head_loss, - self._hn_head_loss_class._hn_pipe_head_loss( - pipe, - self, - options, - self.heat_network_settings, - parameters, - pc.maximum_discharge, - pipe_class=pc, - ), - ) - else: - # Only a single diameter for this pipe. Note that we rely on - # the diameter parameter being overridden automatically if a - # single pipe class is set by the user. - area = parameters[f"{pipe}.area"] - max_discharge = self.heat_network_settings["maximum_velocity"] * area - - is_topo_disconnected = int(parameters[f"{pipe}.diameter"] == 0.0) - - constraints.extend( - self._hn_head_loss_class._hn_pipe_head_loss( - pipe, - self, - options, - self.heat_network_settings, - parameters, - discharge, - head_loss, - dh, - is_disconnected + is_topo_disconnected, - 1.1 * self.__maximum_total_head_loss, - ) - ) - - max_head_loss = self._hn_head_loss_class._hn_pipe_head_loss( - pipe, self, options, self.heat_network_settings, parameters, max_discharge - ) - - # Relate the head loss symbol to the pipe's dH symbol. - - # FIXME: Ugly hack. Cold pipes should be modelled completely with - # their own integers as well. - flow_dir = self.__state_vector_scaled( - self._pipe_to_flow_direct_map[pipe], ensemble_member - ) - - # Note that the Big-M should _at least_ cover the maximum - # distance between `head_loss` and `dh`. If `head_loss` can be at - # most 1.0 (= `max_head_loss`), that means our Big-M should be at - # least double (i.e. >= 2.0). And because we do not want Big-Ms to - # be overly tight, we include an additional factor of 2. - big_m = 2 * 2 * max_head_loss - - constraints.append( - ( - (-dh - head_loss + (1 - flow_dir) * big_m) / big_m, - 0.0, - np.inf, - ) - ) - constraints.append(((dh - head_loss + flow_dir * big_m) / big_m, 0.0, np.inf)) - - return constraints - def __check_valve_head_discharge_path_constraints(self, ensemble_member): """ This function adds constraints for the check valve functionality. Meaning that the flow can @@ -3011,7 +3093,7 @@ def __check_valve_head_discharge_path_constraints(self, ensemble_member): for p in connected_pipes: try: - pipe_classes = self._pipe_topo_pipe_class_map[p].keys() + pipe_classes = self._heat_pipe_topo_pipe_class_map[p].keys() max_discharge_pipe = max(c.maximum_discharge for c in pipe_classes) except KeyError: max_discharge_pipe = maximum_velocity * parameters[f"{p}.area"] @@ -3058,7 +3140,7 @@ def __control_valve_head_discharge_path_constraints(self, ensemble_member): for p in connected_pipes: try: - pipe_classes = self._pipe_topo_pipe_class_map[p].keys() + pipe_classes = self._heat_pipe_topo_pipe_class_map[p].keys() max_discharge_pipe = max(c.maximum_discharge for c in pipe_classes) except KeyError: max_discharge_pipe = maximum_velocity * parameters[f"{p}.area"] @@ -3082,16 +3164,14 @@ def __control_valve_head_discharge_path_constraints(self, ensemble_member): def __heat_loss_variable_constraints(self, ensemble_member): """ - Furthermore, the __hn_heat_loss symbol is set, as the milp loss depends on the chosen pipe + Furthermore, the __hn_heat_loss symbol is set, as the heat loss depends on the chosen pipe class and the selected temperature in the network. - Parameters - ---------- - ensemble_member : The ensemble of the optimizaton + Parameters: + ensemble_member : The ensemble of the optimizaton - Returns - ------- - list of the added constraints + Returns: + list of the added constraints """ constraints = [] @@ -3109,7 +3189,7 @@ class and the selected temperature in the network. heat_loss_sym = self.extra_variable(heat_loss_sym_name, ensemble_member) try: heat_losses = self._pipe_heat_losses[p] - pipe_classes = self._pipe_topo_pipe_class_map[p] + pipe_classes = self._heat_pipe_topo_pipe_class_map[p] variables = [ self.extra_variable(var_name, ensemble_member) for pc, var_name in pipe_classes.items() @@ -3220,7 +3300,9 @@ class and the selected temperature in the network. def __ates_max_stored_heat_constriants(self, ensemble_member): constraints = [] - for ates in self.energy_system_components.get("ates", []): + for ates in [ + *self.energy_system_components.get("ates", []), + ]: max_var_name = f"{ates}__max_stored_heat" max_var = self.extra_variable(max_var_name, ensemble_member) stored_heat = self.__state_vector_scaled(f"{ates}.Stored_heat", ensemble_member) @@ -3413,7 +3495,7 @@ def __storage_hydraulic_power_path_constraints(self, ensemble_member): pump_power = self.state(f"{b}.Pump_power") min_dp = parameters[f"{b}.minimum_pressure_drop"] - flow_dir_var = self._pipe_to_flow_direct_map[hot_pipe] + flow_dir_var = self._heat_pipe_to_flow_direct_map[hot_pipe] is_buffer_charging = self.state(flow_dir_var) * hot_pipe_orientation big_m = ( @@ -3488,13 +3570,18 @@ def path_constraints(self, ensemble_member): self._hn_head_loss_class._demand_head_loss_path_constraints(self, ensemble_member) ) - constraints.extend(self.__pipe_hydraulic_power_path_constraints(ensemble_member)) + constraints.extend( + self._hn_head_loss_class._pipe_hydraulic_power_path_constraints( + self, self.__maximum_total_head_loss, ensemble_member + ) + ) constraints.extend(self.__flow_direction_path_constraints(ensemble_member)) constraints.extend(self.__node_heat_mixing_path_constraints(ensemble_member)) constraints.extend(self.__node_hydraulic_power_mixing_path_constraints(ensemble_member)) constraints.extend(self.__heat_loss_path_constraints(ensemble_member)) constraints.extend(self.__node_discharge_mixing_path_constraints(ensemble_member)) constraints.extend(self.__demand_heat_to_discharge_path_constraints(ensemble_member)) + constraints.extend(self.__cold_demand_heat_to_discharge_path_constraints(ensemble_member)) constraints.extend(self.__source_heat_to_discharge_path_constraints(ensemble_member)) constraints.extend(self.__pipe_heat_to_discharge_path_constraints(ensemble_member)) constraints.extend(self.__storage_heat_to_discharge_path_constraints(ensemble_member)) @@ -3523,7 +3610,12 @@ def constraints(self, ensemble_member): constraints = super().constraints(ensemble_member) if self.heat_network_settings["head_loss_option"] != HeadLossOption.NO_HEADLOSS: - constraints.extend(self._hn_pipe_head_loss_constraints(ensemble_member)) + # constraints.extend(self._hn_pipe_head_loss_constraints(ensemble_member)) + constraints.extend( + self._hn_head_loss_class._pipe_head_loss_constraints( + self, self.__maximum_total_head_loss, ensemble_member + ) + ) constraints.extend(self.__heat_loss_variable_constraints(ensemble_member)) constraints.extend(self.__pipe_rate_heat_change_constraints(ensemble_member)) @@ -3549,9 +3641,9 @@ def history(self, ensemble_member): hist_heat_buffer = history.get(f"{b}.Heat_buffer", empty_timeseries).values hist_stored_heat = history.get(f"{b}.Stored_heat", empty_timeseries).values - # One has to provide information of what Heat_buffer (i.e., the milp + # One has to provide information of what Heat_buffer (i.e., the heat # added/extracted from the buffer at that timestep) is at t0. - # Else the solution will always extract milp from the buffer at t0. + # Else the solution will always extract heat from the buffer at t0. # This information can be passed in two ways: # - non-trivial history of Heat_buffer at t0; # - non-trivial history of Stored_heat. @@ -3672,7 +3764,7 @@ def post(self): In this post function we check the optimization results for accurately solving the constraints. We do this for the head losses and check if they are consistent with the flow direction. Whether, the minimum velocity is actually met. And whether, the directions of - milp match the directions of the flow. + heat match the directions of the flow. """ super().post() @@ -3680,15 +3772,6 @@ def post(self): parameters = self.parameters(0) options = self.energy_system_options() - # The flow directions are the same as the milp directions if the - # return (i.e. cold) line has zero milp throughout. Here we check that - # this is indeed the case. - for p in self.cold_pipes: - heat_in = results[f"{p}.HeatIn.Heat"] - heat_out = results[f"{p}.HeatOut.Heat"] - if np.any(heat_in > 1.0) or np.any(heat_out > 1.0): - logger.warning(f"Heat directions of pipes might be wrong. Check {p}.") - if self.heat_network_settings["head_loss_option"] != HeadLossOption.NO_HEADLOSS: for p in self.energy_system_components.get("heat_pipe", []): head_diff = results[f"{p}.HeatIn.H"] - results[f"{p}.HeatOut.H"] @@ -3699,7 +3782,7 @@ def post(self): q = results[f"{p}.Q"] try: - is_disconnected = np.round(results[self._pipe_disconnect_map[p]]) + is_disconnected = np.round(results[self._heat_pipe_disconnect_map[p]]) except KeyError: is_disconnected = np.zeros_like(q) @@ -3719,9 +3802,9 @@ def post(self): q = results[f"{p}.Q"] v = q / area - flow_dir = np.round(results[self._pipe_to_flow_direct_map[p]]) + flow_dir = np.round(results[self._heat_pipe_to_flow_direct_map[p]]) try: - is_disconnected = np.round(results[self._pipe_disconnect_map[p]]) + is_disconnected = np.round(results[self._heat_pipe_disconnect_map[p]]) except KeyError: is_disconnected = np.zeros_like(q) diff --git a/src/rtctools_heat_network/influxdb/__init__.py b/src/mesido/influxdb/__init__.py similarity index 100% rename from src/rtctools_heat_network/influxdb/__init__.py rename to src/mesido/influxdb/__init__.py diff --git a/src/rtctools_heat_network/influxdb/profile.py b/src/mesido/influxdb/profile.py similarity index 100% rename from src/rtctools_heat_network/influxdb/profile.py rename to src/mesido/influxdb/profile.py diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Buffer.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Buffer.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Buffer.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Buffer.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/CheckValve.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/CheckValve.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/CheckValve.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/CheckValve.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/ControlValve.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/ControlValve.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/ControlValve.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/ControlValve.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Demand.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Demand.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Demand.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Demand.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/GeothermalSource.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/GeothermalSource.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/GeothermalSource.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/GeothermalSource.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/HeatPort.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/HeatPort.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/HeatPort.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/HeatPort.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/HeatTwoPort.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/HeatTwoPort.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/HeatTwoPort.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/HeatTwoPort.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Node.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Node.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Node.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Node.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Pipe.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Pipe.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Pipe.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Pipe.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Pump.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Pump.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Pump.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Pump.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Source.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Source.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/Source.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/Source.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/_NonStorageComponent.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/_NonStorageComponent.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/_NonStorageComponent.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/_NonStorageComponent.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/package.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/Heat/package.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/Heat/package.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/Heat/package.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Buffer.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Buffer.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Buffer.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Buffer.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/CheckValve.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/CheckValve.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/CheckValve.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/CheckValve.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/ControlValve.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/ControlValve.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/ControlValve.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/ControlValve.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Demand.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Demand.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Demand.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Demand.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/GeothermalSource.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/GeothermalSource.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/GeothermalSource.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/GeothermalSource.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Node.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Node.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Node.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Node.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Pipe.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Pipe.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Pipe.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Pipe.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Pump.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Pump.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Pump.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Pump.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/QTHPort.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/QTHPort.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/QTHPort.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/QTHPort.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/QTHTwoPort.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/QTHTwoPort.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/QTHTwoPort.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/QTHTwoPort.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Source.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Source.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/Source.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/Source.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/_FluidPropertiesComponent.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/_FluidPropertiesComponent.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/_FluidPropertiesComponent.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/_FluidPropertiesComponent.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/_NonStorageComponent.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/_NonStorageComponent.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/_NonStorageComponent.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/_NonStorageComponent.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/package.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/QTH/package.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/QTH/package.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/QTH/package.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/package.mo b/src/mesido/modelica/WarmingUp/HeatNetwork/package.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/HeatNetwork/package.mo rename to src/mesido/modelica/WarmingUp/HeatNetwork/package.mo diff --git a/src/rtctools_heat_network/modelica/WarmingUp/package.mo b/src/mesido/modelica/WarmingUp/package.mo similarity index 100% rename from src/rtctools_heat_network/modelica/WarmingUp/package.mo rename to src/mesido/modelica/WarmingUp/package.mo diff --git a/src/rtctools_heat_network/network_common.py b/src/mesido/network_common.py similarity index 100% rename from src/rtctools_heat_network/network_common.py rename to src/mesido/network_common.py diff --git a/src/rtctools_heat_network/physics_mixin.py b/src/mesido/physics_mixin.py similarity index 97% rename from src/rtctools_heat_network/physics_mixin.py rename to src/mesido/physics_mixin.py index ba84881c3..f147ba8ce 100644 --- a/src/rtctools_heat_network/physics_mixin.py +++ b/src/mesido/physics_mixin.py @@ -2,21 +2,20 @@ import casadi as ca +from mesido.base_component_type_mixin import BaseComponentTypeMixin +from mesido.control_variables import map_comp_type_to_control_variable +from mesido.electricity_physics_mixin import ElectricityPhysicsMixin +from mesido.gas_physics_mixin import GasPhysicsMixin +from mesido.heat_physics_mixin import HeatPhysicsMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( CollocatedIntegratedOptimizationProblem, ) -from rtctools_heat_network.control_variables import map_comp_type_to_control_variable - - -from .base_component_type_mixin import BaseComponentTypeMixin -from .electricity_physics_mixin import ElectricityPhysicsMixin -from .gas_physics_mixin import GasPhysicsMixin -from .heat_physics_mixin import HeatPhysicsMixin -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") class PhysicsMixin( diff --git a/src/rtctools_heat_network/pipe_class.py b/src/mesido/pipe_class.py similarity index 100% rename from src/rtctools_heat_network/pipe_class.py rename to src/mesido/pipe_class.py diff --git a/src/rtctools_heat_network/pycml/component_library/__init__.py b/src/mesido/post_processing/__init__.py similarity index 100% rename from src/rtctools_heat_network/pycml/component_library/__init__.py rename to src/mesido/post_processing/__init__.py diff --git a/src/mesido/post_processing/post_processing_utils.py b/src/mesido/post_processing/post_processing_utils.py new file mode 100644 index 000000000..d18f2b3bf --- /dev/null +++ b/src/mesido/post_processing/post_processing_utils.py @@ -0,0 +1,130 @@ +import json +import os +from typing import Dict, Union + +from mesido.constants import GRAVITATIONAL_CONSTANT +from mesido.network_common import NetworkSettings + +import numpy as np + +from rtctools._internal.alias_tools import AliasDict + + +class AliasDictResults: + """ + This class allows for the handling of the result data created by MESIDO. + In MESIDO aliasing of variables is used to reduce computational effort. This results in fewer + variables being saved with their own names. + This class takes the loaded jsons of the results and aliases to be converted to an alias + dictionary. + Using the get_results method the result of each original variable name can be accessed. + """ + + def __init__(self, results: Dict, aliases: Dict): + self.results = results + self._aliases = aliases + + def __getitem__(self, name: str) -> list: + if name in self.results.keys(): + return self.results[name] + else: + alias = self._aliases[name] + return alias[1] * self.results[alias[0]] + + def get_results_as_array(self, name: str) -> np.array: + return np.array(self.results[name]) + + +def extract_data_results_alias(data_path: str) -> [AliasDictResults, Dict]: + """ + Extracts the data in the provided path to create an alias dictionary of the results + Args: + data_path: path to the folder with the jsons saved after a MESIDO run + + Returns: an alias dictionary of the results, and the raw data extracted in the path. + + """ + raw_data = extract_data_results(data_path) + results_alias_dict = create_alias_dict(raw_data) + return results_alias_dict, raw_data + + +def create_alias_dict(data: Dict) -> AliasDictResults: + """ + Creates the alias dict from the dictionary which contains the aliases and results. + :param data: + :return: + """ + return AliasDictResults(data["results"], data["aliases"]) + + +def extract_data_results(data_path: str) -> Dict: + """ + Extracts the data from the json files created after a run with MESIDO + :param data_path: String containing the absolute path to the folder with the json files created + by MESIDO. + :return: dictionary with the data from the json files + """ + file_names = ["results", "parameters", "bounds", "aliases", "solver_stats"] + data = {} + for f in file_names: + input_path = os.path.join(data_path, f"{f}.json") + try: + with open(input_path) as file: + data_file = json.load(file) + data[f] = data_file + except IOError: + pass + + return data + + +def pipe_velocity( + asset_name: str, commodity: str, results: Union[AliasDictResults, AliasDict], parameters: Dict +) -> np.array: + """ + Post-processing to determine the pipe_velocity. + To be used in code and as post-processing from jsons. + Args: + asset_name: asset_name of gas or heat pipe + commodity: commodity type to select the correct port name "Heat" or "Gas" + results: AliasDict with results + parameters: Dict with results + + Returns: + + """ + post_processed_velocity = ( + results[f"{asset_name}.{commodity}Out.Q"] / parameters[f"{asset_name}.area"] + ) + return post_processed_velocity + + +def pipe_pressure( + asset_name: str, commodity: str, results: Union[AliasDictResults, AliasDict], parameters: Dict +) -> np.array: + """ + Post-processing to determine the pipe_velocity. + To be used in code and as post-processing from jsons. + Args: + asset_name: asset_name of gas or heat pipe + commodity: commodity type to select the correct port name "Heat" or "Gas" + results: AliasDict with results + parameters: Dict with results + + Returns: + + """ + if commodity == NetworkSettings.NETWORK_TYPE_HEAT: + scale_factor = 1.0 + elif commodity in [NetworkSettings.NETWORK_TYPE_GAS, NetworkSettings.NETWORK_TYPE_HYDROGEN]: + scale_factor = 1.0e3 + else: + exit("Unkown commodity type used for pipe pressure") + post_processed_pressure = ( + results[f"{asset_name}.{commodity}In.H"] # m + * GRAVITATIONAL_CONSTANT # m/s2 + * parameters[f"{asset_name}.rho"] # Heat kg/m3, non-heat related g/m3 + / scale_factor + ) # Pa + return post_processed_pressure diff --git a/src/mesido/potential_errors.py b/src/mesido/potential_errors.py new file mode 100644 index 000000000..3fe155f31 --- /dev/null +++ b/src/mesido/potential_errors.py @@ -0,0 +1,76 @@ +from enum import Enum +from typing import Dict, List, NoReturn + +from mesido.exceptions import MesidoAssetIssueError + +AssetId = str +ErrorMessage = str + + +# Asset error type that can occur +class MesidoAssetIssueType(Enum): + HEAT_PRODUCER_POWER = "heat_producer.power" + HEAT_DEMAND_POWER = "heat_demand.power" + COLD_DEMAND_POWER = "cold_demand.power" + HEAT_DEMAND_TYPE = "heat_demand.type" + ASSET_PROFILE_CAPABILITY = "asset_profile.capability" + HEAT_EXCHANGER_TEMPERATURES = "heat_exchanger.temperature" + + +class PotentialErrors: + """Singleton, do not instantiate. Use POTENTIAL_ERRORS.""" + + _gathered_potential_issues: Dict[MesidoAssetIssueType, Dict[AssetId, List[ErrorMessage]]] + + def __init__(self): + self._gathered_potential_issues = {} + + def add_potential_issue( + self, issue_type: MesidoAssetIssueType, asset_id: AssetId, error_message: ErrorMessage + ) -> None: + """ + Add potential issues to _gathered_potential_issues. + + """ + self._gathered_potential_issues.setdefault(issue_type, {}) + self._gathered_potential_issues[issue_type][asset_id] = error_message + + def have_issues_for(self, issue_type: MesidoAssetIssueType) -> bool: + """ + Check if the potential issue exists. + + """ + result = False + if issue_type in self._gathered_potential_issues: + result = True + + return result + + def convert_to_exception( + self, issue_type: MesidoAssetIssueType, general_issue: str + ) -> NoReturn: + """ + Raise a MESIDO exception if the issue exists. + + """ + if issue_type not in self._gathered_potential_issues: + raise RuntimeError("Something very wrong. Issue type not in potential errors") + + raise MesidoAssetIssueError( + general_issue=general_issue, + error_type=issue_type, + message_per_asset_id=self._gathered_potential_issues[issue_type], + ) + + +# When adding POTENTIAL_ERRORS to a workflow a reset thereof is required due to it being a +# persistent object +POTENTIAL_ERRORS = PotentialErrors() + + +def get_potential_errors() -> PotentialErrors: + return POTENTIAL_ERRORS + + +def reset_potential_errors() -> None: + POTENTIAL_ERRORS._gathered_potential_issues = {} diff --git a/src/rtctools_heat_network/pycml/__init__.py b/src/mesido/pycml/__init__.py similarity index 100% rename from src/rtctools_heat_network/pycml/__init__.py rename to src/mesido/pycml/__init__.py diff --git a/src/rtctools_heat_network/qth_not_maintained/__init__.py b/src/mesido/pycml/component_library/__init__.py similarity index 100% rename from src/rtctools_heat_network/qth_not_maintained/__init__.py rename to src/mesido/pycml/component_library/__init__.py diff --git a/src/rtctools_heat_network/pycml/component_library/milp/__init__.py b/src/mesido/pycml/component_library/milp/__init__.py similarity index 69% rename from src/rtctools_heat_network/pycml/component_library/milp/__init__.py rename to src/mesido/pycml/component_library/milp/__init__.py index d9e6a2e80..0b562377d 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/__init__.py +++ b/src/mesido/pycml/component_library/milp/__init__.py @@ -2,16 +2,23 @@ from .electricity.electricity_demand import ElectricityDemand from .electricity.electricity_node import ElectricityNode from .electricity.electricity_source import ElectricitySource +from .electricity.electricity_storage import ElectricityStorage from .electricity.heat_pump_elec import HeatPumpElec +from .electricity.solarpv import SolarPV +from .electricity.transformer import Transformer from .electricity.windpark import WindPark +from .gas.compressor import Compressor from .gas.gas_demand import GasDemand from .gas.gas_node import GasNode from .gas.gas_pipe import GasPipe from .gas.gas_source import GasSource from .gas.gas_substation import GasSubstation from .gas.gas_tank_storage import GasTankStorage +from .heat.air_water_heat_pump import AirWaterHeatPump +from .heat.airco import Airco from .heat.ates import ATES from .heat.check_valve import CheckValve +from .heat.cold_demand import ColdDemand from .heat.control_valve import ControlValve from .heat.geothermal_source import GeothermalSource from .heat.heat_buffer import HeatBuffer @@ -23,21 +30,33 @@ from .heat.heat_pump import HeatPump from .heat.heat_source import HeatSource from .heat.heat_two_port import HeatTwoPort +from .heat.low_temperature_ates import LowTemperatureATES from .heat.node import Node from .heat.pump import Pump +from .multicommodity.airwater_heat_pump_elec import AirWaterHeatPumpElec +from .multicommodity.electro_boiler import ElecBoiler from .multicommodity.electrolyzer import Electrolyzer +from .multicommodity.gas_boiler import GasBoiler __all__ = [ + "Airco", + "AirWaterHeatPump", + "AirWaterHeatPumpElec", "ATES", "HeatBuffer", "CheckValve", + "ColdDemand", + "Compressor", "ControlValve", "HeatDemand", + "ElecBoiler", "ElectricityCable", "ElectricityDemand", "ElectricityNode", "ElectricitySource", + "ElectricityStorage", "Electrolyzer", + "GasBoiler", "GasDemand", "GasNode", "GasPipe", @@ -47,13 +66,16 @@ "GeothermalSource", "HeatExchanger", "HeatFourPort", + "HeatPipe", "HeatPort", "HeatPump", "HeatPumpElec", "HeatTwoPort", + "LowTemperatureATES", "Node", - "HeatPipe", "Pump", "HeatSource", + "SolarPV", + "Transformer", "WindPark", ] diff --git a/src/rtctools_heat_network/pycml/component_library/milp/_internal/__init__.py b/src/mesido/pycml/component_library/milp/_internal/__init__.py similarity index 100% rename from src/rtctools_heat_network/pycml/component_library/milp/_internal/__init__.py rename to src/mesido/pycml/component_library/milp/_internal/__init__.py diff --git a/src/rtctools_heat_network/pycml/component_library/milp/_internal/heat_component.py b/src/mesido/pycml/component_library/milp/_internal/base_component.py similarity index 71% rename from src/rtctools_heat_network/pycml/component_library/milp/_internal/heat_component.py rename to src/mesido/pycml/component_library/milp/_internal/base_component.py index f93d4ca62..63f7af606 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/_internal/heat_component.py +++ b/src/mesido/pycml/component_library/milp/_internal/base_component.py @@ -1,31 +1,22 @@ -from numpy import nan - -from rtctools_heat_network.pycml import Component - - -class HeatComponent(Component): - """ - Base milp component nothing to add here yet. - """ - - def __init__(self, name, **modifiers): - super().__init__(name, **modifiers) - - -class BaseAsset(Component): - """ - A base asset that carries properties used throughout the different commodities. In this case - only the financial structure is used in all commodities. - """ - - def __init__(self, name, **modifiers): - super().__init__(name, **modifiers) - self.state = 1 - - self.variable_operational_cost_coefficient = 0.0 - self.fixed_operational_cost_coefficient = 0.0 - self.investment_cost_coefficient = 0.0 - self.installation_cost = 0.0 - - self.technical_life = nan - self.discount_rate = nan +from mesido.pycml import Component + +from numpy import nan + + +class BaseAsset(Component): + """ + A base asset that carries properties used throughout the different commodities. In this case + only the financial structure is used in all commodities. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + self.state = 1 + + self.variable_operational_cost_coefficient = 0.0 + self.fixed_operational_cost_coefficient = 0.0 + self.investment_cost_coefficient = 0.0 + self.installation_cost = 0.0 + + self.technical_life = nan + self.discount_rate = nan diff --git a/src/mesido/pycml/component_library/milp/_internal/electricity_component.py b/src/mesido/pycml/component_library/milp/_internal/electricity_component.py new file mode 100644 index 000000000..f01767bb5 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/_internal/electricity_component.py @@ -0,0 +1,12 @@ +from mesido.network_common import NetworkSettings +from mesido.pycml.component_library.milp._internal.base_component import BaseAsset + + +class ElectricityComponent(BaseAsset): + """ + Base electricity component nothing to add here yet. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + self.network_type = NetworkSettings.NETWORK_TYPE_ELECTRICITY diff --git a/src/mesido/pycml/component_library/milp/_internal/gas_component.py b/src/mesido/pycml/component_library/milp/_internal/gas_component.py new file mode 100644 index 000000000..b002dbd73 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/_internal/gas_component.py @@ -0,0 +1,12 @@ +from mesido.network_common import NetworkSettings +from mesido.pycml.component_library.milp._internal.base_component import BaseAsset + + +class GasComponent(BaseAsset): + """ + Base gas component nothing to add here yet. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + self.network_type = NetworkSettings.NETWORK_TYPE_GAS diff --git a/src/mesido/pycml/component_library/milp/_internal/heat_component.py b/src/mesido/pycml/component_library/milp/_internal/heat_component.py new file mode 100644 index 000000000..6e1a4d064 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/_internal/heat_component.py @@ -0,0 +1,12 @@ +from mesido.network_common import NetworkSettings +from mesido.pycml.component_library.milp._internal.base_component import BaseAsset + + +class HeatComponent(BaseAsset): + """ + Base milp component nothing to add here yet. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + self.network_type = NetworkSettings.NETWORK_TYPE_HEAT diff --git a/src/rtctools_heat_network/pycml/component_library/milp/electricity/__init__.py b/src/mesido/pycml/component_library/milp/electricity/__init__.py similarity index 86% rename from src/rtctools_heat_network/pycml/component_library/milp/electricity/__init__.py rename to src/mesido/pycml/component_library/milp/electricity/__init__.py index cd65110e7..d6592bb8f 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/electricity/__init__.py +++ b/src/mesido/pycml/component_library/milp/electricity/__init__.py @@ -3,6 +3,7 @@ from .electricity_node import ElectricityNode from .electricity_source import ElectricitySource from .heat_pump_elec import HeatPumpElec +from .transformer import Transformer __all__ = [ "ElectricityNode", @@ -10,4 +11,5 @@ "ElectricitySource", "ElectricityDemand", "HeatPumpElec", + "Transformer", ] diff --git a/src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_base.py b/src/mesido/pycml/component_library/milp/electricity/electricity_base.py similarity index 62% rename from src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_base.py rename to src/mesido/pycml/component_library/milp/electricity/electricity_base.py index 2072ca02a..26f60828d 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_base.py +++ b/src/mesido/pycml/component_library/milp/electricity/electricity_base.py @@ -1,26 +1,43 @@ -from rtctools_heat_network.pycml import Connector, Variable +from mesido.pycml import Connector, Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically from .._internal.electricity_component import ElectricityComponent +@add_variables_documentation_automatically class ElectricityPort(ElectricityComponent, Connector): """ The electricity port is used to model the variables at a port where two assets are connected. For electricity networks we model the electrical power (P), the voltage (V) and the current (I). + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): super().__init__(name, **modifiers) self.add_variable(Variable, "Power") - self.add_variable(Variable, "V", min=0.0) self.add_variable(Variable, "I") + self.add_variable(Variable, "V", min=0.0) +@add_variables_documentation_automatically class ElectricityTwoPort(ElectricityComponent): """ For electricity components that transport power we have a two port component to allow for electricity flow in and out of the component. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): diff --git a/src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_cable.py b/src/mesido/pycml/component_library/milp/electricity/electricity_cable.py similarity index 69% rename from src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_cable.py rename to src/mesido/pycml/component_library/milp/electricity/electricity_cable.py index 014d4008e..07006cc47 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_cable.py +++ b/src/mesido/pycml/component_library/milp/electricity/electricity_cable.py @@ -1,17 +1,26 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable +from numpy import nan from .electricity_base import ElectricityTwoPort from .._internal import BaseAsset +@add_variables_documentation_automatically class ElectricityCable(ElectricityTwoPort, BaseAsset): """ The electricity cable component is used to model voltage and power drops in the electricity lines. We model the power losses by over estimating them with the maximum current. We ensure that the power is always less than what the current is able to carry by an equality constraint at the demand where we enforce the minimum voltage. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -30,9 +39,14 @@ def __init__(self, name, **modifiers): self.max_voltage = self.min_voltage * 2.0 self.nominal_current = nan self.nominal_voltage = nan - self.r = 1.0e-6 * self.length # TODO: temporary value - self.nominal_voltage_loss = (self.nominal_current * self.r * self.nominal_current) ** 0.5 - self.add_variable(Variable, "Power_loss", min=0.0, nominal=self.r * self.max_current**2) + self.r = nan + self.nominal_voltage_loss = (self.nominal_current * self.r * self.nominal_voltage) ** 0.5 + self.power_loss_nominal = self.r * self.max_current * self.nominal_current + # We accept lower accuracy in the loss computation to improve scaling in case the nominals + # are very far apart. Typically, when a short cable has a very high max capacity. + if self.power_loss_nominal / self.ElectricityIn.Power.nominal < 1.0e-4: + self.power_loss_nominal = self.ElectricityIn.Power.nominal * 1.0e-4 + self.add_variable(Variable, "Power_loss", min=0.0, nominal=self.power_loss_nominal) self.add_variable(Variable, "I", nominal=self.nominal_current) self.add_variable(Variable, "V_loss", nominal=self.nominal_voltage_loss) @@ -50,6 +64,6 @@ def __init__(self, name, **modifiers): self.add_equation( ( (self.ElectricityOut.Power - (self.ElectricityIn.Power - self.Power_loss)) - / (self.nominal_voltage * self.nominal_current * self.r * self.max_current) ** 0.5 + / (self.ElectricityIn.Power.nominal * self.Power_loss.nominal) ** 0.5 ) ) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_demand.py b/src/mesido/pycml/component_library/milp/electricity/electricity_demand.py similarity index 75% rename from src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_demand.py rename to src/mesido/pycml/component_library/milp/electricity/electricity_demand.py index 43b7ec2b3..bd379dcc9 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_demand.py +++ b/src/mesido/pycml/component_library/milp/electricity/electricity_demand.py @@ -1,17 +1,26 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable +from numpy import nan from .electricity_base import ElectricityPort from .._internal import BaseAsset from .._internal.electricity_component import ElectricityComponent +@add_variables_documentation_automatically class ElectricityDemand(ElectricityComponent, BaseAsset): """ The electricity demand models consumption of electrical power. We set an equality constriant in to enforce the minimum voltage and the associated power at the demand. This allows us to overestimate the power losses in the rest of the network. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): diff --git a/src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_node.py b/src/mesido/pycml/component_library/milp/electricity/electricity_node.py similarity index 78% rename from src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_node.py rename to src/mesido/pycml/component_library/milp/electricity/electricity_node.py index e8b6deab1..bfa371533 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_node.py +++ b/src/mesido/pycml/component_library/milp/electricity/electricity_node.py @@ -1,18 +1,27 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable +from numpy import nan from .electricity_base import ElectricityPort from .._internal import BaseAsset from .._internal.electricity_component import ElectricityComponent +@add_variables_documentation_automatically class ElectricityNode(ElectricityComponent, BaseAsset): """ The electricity node or bus is a component where we model multiple currents coming together, this is the only component where it is allowed that 3 or more currents come together. This means that a node is always connected to cables. We set constraints for equal voltage at all ports. Furthermore, we set constraints for conservation of power and current. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): diff --git a/src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_source.py b/src/mesido/pycml/component_library/milp/electricity/electricity_source.py similarity index 74% rename from src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_source.py rename to src/mesido/pycml/component_library/milp/electricity/electricity_source.py index 4c2792fef..8772939ff 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/electricity/electricity_source.py +++ b/src/mesido/pycml/component_library/milp/electricity/electricity_source.py @@ -1,17 +1,26 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable +from numpy import nan from .electricity_base import ElectricityPort from .._internal import BaseAsset from .._internal.electricity_component import ElectricityComponent +@add_variables_documentation_automatically class ElectricitySource(ElectricityComponent, BaseAsset): """ The electricity source component is used to generate electrical power and provide that to the network. As we set the equality constraint on the demand side we do not have to set any constraint at the source side. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): diff --git a/src/mesido/pycml/component_library/milp/electricity/electricity_storage.py b/src/mesido/pycml/component_library/milp/electricity/electricity_storage.py new file mode 100644 index 000000000..5f3a22fa7 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/electricity/electricity_storage.py @@ -0,0 +1,59 @@ +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from numpy import nan + +from .electricity_base import ElectricityPort +from .._internal import BaseAsset +from .._internal.electricity_component import ElectricityComponent + + +@add_variables_documentation_automatically +class ElectricityStorage(ElectricityComponent, BaseAsset): + """ + The electricity storage component is used to store electrical power of a network. + The change in stored electrical power should be equal to the electricity entering and leaving + the component multiplied with its efficiency. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + + self.component_type = "electricity_storage" + + self.max_capacity = nan + self.min_voltage = nan + self.charge_efficiency = 1.0 + self.discharge_efficiency = 1.0 + + self.add_variable(ElectricityPort, "ElectricityIn") + + self._typical_fill_time = 3600.0 + self._nominal_stored_electricity = self.ElectricityIn.Power.max * self._typical_fill_time + self.add_variable( + Variable, + "Stored_electricity", + min=0.0, + max=self.max_capacity, + nominal=self._nominal_stored_electricity, + ) + self.add_variable( + Variable, + "Effective_power_charging", + nominal=self.ElectricityIn.Power.nominal, + max=self.ElectricityIn.Power.max, + ) + + self.add_equation( + ( + (self.der(self.Stored_electricity) - self.Effective_power_charging) + / self.ElectricityIn.Power.nominal + ) + ) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/electricity/heat_pump_elec.py b/src/mesido/pycml/component_library/milp/electricity/heat_pump_elec.py similarity index 65% rename from src/rtctools_heat_network/pycml/component_library/milp/electricity/heat_pump_elec.py rename to src/mesido/pycml/component_library/milp/electricity/heat_pump_elec.py index dfc1faa0f..b183d2ff5 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/electricity/heat_pump_elec.py +++ b/src/mesido/pycml/component_library/milp/electricity/heat_pump_elec.py @@ -1,16 +1,25 @@ -from rtctools_heat_network.pycml.component_library.milp.electricity.electricity_base import ( +from mesido.pycml.component_library.milp.electricity.electricity_base import ( ElectricityPort, ) -from rtctools_heat_network.pycml.component_library.milp.heat.heat_pump import HeatPump +from mesido.pycml.component_library.milp.heat.heat_pump import HeatPump +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically # TODO: for now in the electricity folder, but maybe we can make a multicommodity folder, # where this is then placed. +@add_variables_documentation_automatically class HeatPumpElec(HeatPump): """ The heat pump elec is to model a water-water heatpump where we explicitly model its connection to the electricity grid. This allows to potentially optimize for electricity network constraints in the optimization of the heat network and vice-versa. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): diff --git a/src/mesido/pycml/component_library/milp/electricity/solarpv.py b/src/mesido/pycml/component_library/milp/electricity/solarpv.py new file mode 100644 index 000000000..362684237 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/electricity/solarpv.py @@ -0,0 +1,23 @@ +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from .. import ElectricitySource + + +@add_variables_documentation_automatically +class SolarPV(ElectricitySource): + """ + The solar pv asset is an electricity source component used to generate electrical power and + provide that to the network, which can handle production profiles. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + + self.component_subtype = "solar_pv" diff --git a/src/mesido/pycml/component_library/milp/electricity/transformer.py b/src/mesido/pycml/component_library/milp/electricity/transformer.py new file mode 100644 index 000000000..a1b6ff71f --- /dev/null +++ b/src/mesido/pycml/component_library/milp/electricity/transformer.py @@ -0,0 +1,37 @@ +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from numpy import nan + +from .electricity_base import ElectricityTwoPort +from .._internal import BaseAsset + + +@add_variables_documentation_automatically +class Transformer(ElectricityTwoPort, BaseAsset): + """ + The transformer component is used to change the voltage level of the network whilst conserving + the power. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + + self.component_type = "transformer" + self.meret_place = 1 + + self.price = nan + + self.min_voltage = nan + + self.power_nominal = nan + + self.add_equation( + ((self.ElectricityIn.Power - self.ElectricityOut.Power) / self.power_nominal) + ) diff --git a/src/mesido/pycml/component_library/milp/electricity/windpark.py b/src/mesido/pycml/component_library/milp/electricity/windpark.py new file mode 100644 index 000000000..13b7503ea --- /dev/null +++ b/src/mesido/pycml/component_library/milp/electricity/windpark.py @@ -0,0 +1,23 @@ +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from .. import ElectricitySource + + +@add_variables_documentation_automatically +class WindPark(ElectricitySource): + """ + The windpark is an electricity source component used to generate electrical power and + provide that to the network, which can handle production profiles. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + + self.component_subtype = "wind_park" diff --git a/src/rtctools_heat_network/pycml/component_library/milp/gas/__init__.py b/src/mesido/pycml/component_library/milp/gas/__init__.py similarity index 83% rename from src/rtctools_heat_network/pycml/component_library/milp/gas/__init__.py rename to src/mesido/pycml/component_library/milp/gas/__init__.py index 1aac45553..baa4fe707 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/gas/__init__.py +++ b/src/mesido/pycml/component_library/milp/gas/__init__.py @@ -1,3 +1,4 @@ +from .compressor import Compressor from .gas_demand import GasDemand from .gas_node import GasNode from .gas_pipe import GasPipe @@ -5,6 +6,7 @@ from .gas_substation import GasSubstation __all__ = [ + "Compressor", "GasNode", "GasPipe", "GasSource", diff --git a/src/mesido/pycml/component_library/milp/gas/compressor.py b/src/mesido/pycml/component_library/milp/gas/compressor.py new file mode 100644 index 000000000..88dc04d83 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/gas/compressor.py @@ -0,0 +1,47 @@ +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from numpy import nan + +from .gas_base import GasTwoPort +from .._internal import BaseAsset + + +@add_variables_documentation_automatically +class Compressor(GasTwoPort, BaseAsset): + """ + A gas compressor increases the pressure level of the flow. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + + self.component_type = "compressor" + self.min_head = 30.0 + + self.Q_nominal_in = nan + self.Q_nominal_out = nan + + self.density_in = 2.5e3 # H2 density [g/m3] at 30bar + self.density_out = 2.5e3 # H2 density [g/m3] at 30bar + + self.add_equation( + ( + (self.GasIn.Q * self.density_in - self.GasOut.Q * self.density_out) + / (self.Q_nominal_in * self.density_in * self.Q_nominal_out * self.density_out) + ** 0.5 + ) + ) + + self.add_equation( + ((self.GasIn.Q - self.GasIn.mass_flow / self.density_in) / self.Q_nominal_in) + ) + self.add_equation( + ((self.GasOut.Q - self.GasOut.mass_flow / self.density_out) / self.Q_nominal_out) + ) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_base.py b/src/mesido/pycml/component_library/milp/gas/gas_base.py similarity index 72% rename from src/rtctools_heat_network/pycml/component_library/milp/gas/gas_base.py rename to src/mesido/pycml/component_library/milp/gas/gas_base.py index afa19b088..aea786d36 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_base.py +++ b/src/mesido/pycml/component_library/milp/gas/gas_base.py @@ -1,13 +1,22 @@ -from rtctools_heat_network.pycml import Connector, Variable +from mesido.pycml import Connector, Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically from .._internal.gas_component import GasComponent +@add_variables_documentation_automatically class GasPort(GasComponent, Connector): """ The gas port is used to model the variables at a port where two assets are connected. For the gas network we model flow (Q [m3/s]) and head (H [m]). The Q_shadow variable is only used for correctly connecting ports of assets later on. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -15,9 +24,9 @@ def __init__(self, name, **modifiers): # TODO: think of more elegant approach for Q_shadow, currently required to ensure that # every port has a unique variable to make the correct port mapping self.add_variable(Variable, "Q") # [m3/s] - self.add_variable(Variable, "Q_shadow") self.add_variable(Variable, "mass_flow") # [g/s] self.add_variable(Variable, "H") # [m] + self.add_variable(Variable, "Hydraulic_power") # [W] class GasTwoPort(GasComponent): diff --git a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_demand.py b/src/mesido/pycml/component_library/milp/gas/gas_demand.py similarity index 61% rename from src/rtctools_heat_network/pycml/component_library/milp/gas/gas_demand.py rename to src/mesido/pycml/component_library/milp/gas/gas_demand.py index 24f7f2043..11d17069a 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_demand.py +++ b/src/mesido/pycml/component_library/milp/gas/gas_demand.py @@ -1,15 +1,24 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable +from numpy import nan from .gas_base import GasPort from .._internal import BaseAsset from .._internal.gas_component import GasComponent +@add_variables_documentation_automatically class GasDemand(GasComponent, BaseAsset): """ A gas demand consumes flow from the network. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -20,7 +29,7 @@ def __init__(self, name, **modifiers): self.Q_nominal = nan - self.density = 2.5e3 # H2 density [kg/m3] at 30bar + self.density = 2.5e3 # H2 density [g/m3] at 30bar self.id_mapping_carrier = -1 @@ -32,3 +41,5 @@ def __init__(self, name, **modifiers): self.add_equation( ((self.GasIn.mass_flow - self.Gas_demand_mass_flow) / (self.Q_nominal * self.density)) ) + + self.add_equation(((self.GasIn.Q - self.GasIn.mass_flow / self.density) / self.Q_nominal)) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_node.py b/src/mesido/pycml/component_library/milp/gas/gas_node.py similarity index 75% rename from src/rtctools_heat_network/pycml/component_library/milp/gas/gas_node.py rename to src/mesido/pycml/component_library/milp/gas/gas_node.py index 0b2817cca..e7142defa 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_node.py +++ b/src/mesido/pycml/component_library/milp/gas/gas_node.py @@ -1,16 +1,25 @@ -from rtctools_heat_network.pycml import Variable +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically from .gas_base import GasPort from .._internal import BaseAsset from .._internal.gas_component import GasComponent +@add_variables_documentation_automatically class GasNode(GasComponent, BaseAsset): """ The gas node is a component where we model multiple flows coming together, this is the only component where it is allowed that 3 or more flows come together. This means that a node is always connected to gas pipes. We set constraints for equal head at all ports. Furthermore, we set constraints for conservation of flow. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): diff --git a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_pipe.py b/src/mesido/pycml/component_library/milp/gas/gas_pipe.py similarity index 61% rename from src/rtctools_heat_network/pycml/component_library/milp/gas/gas_pipe.py rename to src/mesido/pycml/component_library/milp/gas/gas_pipe.py index 68b8a489e..c9f4ddece 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_pipe.py +++ b/src/mesido/pycml/component_library/milp/gas/gas_pipe.py @@ -1,15 +1,24 @@ -from numpy import nan, pi +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable +from numpy import nan, pi from .gas_base import GasTwoPort from .._internal import BaseAsset +@add_variables_documentation_automatically class GasPipe(GasTwoPort, BaseAsset): """ The gas_pipe component is used to model head loss through the pipe. At the moment we only have a placeholder linear head loss formulation in place. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -20,17 +29,19 @@ def __init__(self, name, **modifiers): self.v_max = 15.0 self.density = 2.5e3 # [g/m3] + self.rho = self.density self.diameter = nan self.area = 0.25 * pi * self.diameter**2 self.Q_nominal = self.v_max / 2.0 * self.area self.pressure = 16.0e5 + self.id_mapping_carrier = -1 self.nominal_head = 30.0 self.length = nan self.r = 1.0e-6 * self.length # TODO: temporary value self.nominal_head_loss = (self.Q_nominal * self.r * self.nominal_head) ** 0.5 - self.add_variable(Variable, "dH", nominal=self.Q_nominal * self.r) + self.add_variable(Variable, "dH") self.add_variable(Variable, "Q", nominal=self.Q_nominal) # Flow should be preserved @@ -42,5 +53,15 @@ def __init__(self, name, **modifiers): self.add_equation( ((self.GasIn.mass_flow - self.GasOut.mass_flow) / (self.Q_nominal * self.density)) ) - # # shadow Q for aliases - self.add_equation(((self.GasOut.Q_shadow - (self.GasIn.Q_shadow - 1.0e-3)))) + + # Hydraulic power + # TODO replace value + # rho * ff * length * area / 2 / diameter * velocity**3 + self.add_variable( + Variable, "Hydraulic_power", min=0.0, nominal=self.GasIn.Hydraulic_power.nominal + ) # [W] + + self.add_equation( + (self.Hydraulic_power - (self.GasIn.Hydraulic_power - self.GasOut.Hydraulic_power)) + / self.GasIn.Hydraulic_power.nominal + ) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_source.py b/src/mesido/pycml/component_library/milp/gas/gas_source.py similarity index 61% rename from src/rtctools_heat_network/pycml/component_library/milp/gas/gas_source.py rename to src/mesido/pycml/component_library/milp/gas/gas_source.py index 313003b0b..a4f6e5a36 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_source.py +++ b/src/mesido/pycml/component_library/milp/gas/gas_source.py @@ -1,15 +1,24 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable +from numpy import nan from .gas_base import GasPort from .._internal import BaseAsset from .._internal.gas_component import GasComponent +@add_variables_documentation_automatically class GasSource(GasComponent, BaseAsset): """ A gas source generates gas flow for the network. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -29,3 +38,5 @@ def __init__(self, name, **modifiers): self.add_equation( ((self.GasOut.mass_flow - self.Gas_source_mass_flow) / (self.Q_nominal * self.density)) ) + + self.add_equation(((self.GasOut.Q - self.GasOut.mass_flow / self.density) / self.Q_nominal)) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_substation.py b/src/mesido/pycml/component_library/milp/gas/gas_substation.py similarity index 51% rename from src/rtctools_heat_network/pycml/component_library/milp/gas/gas_substation.py rename to src/mesido/pycml/component_library/milp/gas/gas_substation.py index 534d37247..f7ff6378e 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_substation.py +++ b/src/mesido/pycml/component_library/milp/gas/gas_substation.py @@ -1,13 +1,25 @@ +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + from numpy import nan from .gas_base import GasTwoPort from .._internal import BaseAsset +@add_variables_documentation_automatically class GasSubstation(GasTwoPort, BaseAsset): """ A gas substation that reduces the pressure level of the flow (basically pressure reducinng valve). + + .__disabled + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -19,8 +31,8 @@ def __init__(self, name, **modifiers): self.Q_nominal_in = nan self.Q_nominal_out = nan - self.density_in = 2.5e3 # H2 density [kg/m3] at 30bar - self.density_out = 2.5e3 # H2 density [kg/m3] at 30bar + self.density_in = 2.5e3 # H2 density [g/m3] at 30bar + self.density_out = 2.5e3 # H2 density [g/m3] at 30bar self.add_equation( ( @@ -29,3 +41,10 @@ def __init__(self, name, **modifiers): ** 0.5 ) ) + + self.add_equation( + ((self.GasIn.Q - self.GasIn.mass_flow / self.density_in) / self.Q_nominal_in) + ) + self.add_equation( + ((self.GasOut.Q - self.GasOut.mass_flow / self.density_out) / self.Q_nominal_out) + ) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_tank_storage.py b/src/mesido/pycml/component_library/milp/gas/gas_tank_storage.py similarity index 69% rename from src/rtctools_heat_network/pycml/component_library/milp/gas/gas_tank_storage.py rename to src/mesido/pycml/component_library/milp/gas/gas_tank_storage.py index 007742556..7e791bef4 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/gas/gas_tank_storage.py +++ b/src/mesido/pycml/component_library/milp/gas/gas_tank_storage.py @@ -1,15 +1,25 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.component_library.milp._internal import BaseAsset +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable -from rtctools_heat_network.pycml.component_library.milp._internal import BaseAsset +from numpy import nan from .gas_base import GasPort from .._internal.gas_component import GasComponent +@add_variables_documentation_automatically class GasTankStorage(GasComponent, BaseAsset): """ - ... + A gas tank storages can storage gas from the network, thereby allowing both charging and + discharging, thus both flow directions. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -42,6 +52,8 @@ def __init__(self, name, **modifiers): ((self.GasIn.mass_flow - self.Gas_tank_flow) / (self.Q_nominal * self.density)) ) + self.add_equation(((self.GasIn.Q - self.GasIn.mass_flow / self.density) / self.Q_nominal)) + self.add_equation( ( (self.der(self.Stored_gas_mass) - (self.Gas_tank_flow)) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/__init__.py b/src/mesido/pycml/component_library/milp/heat/__init__.py similarity index 76% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/__init__.py rename to src/mesido/pycml/component_library/milp/heat/__init__.py index d027d0980..b03cc2159 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/__init__.py +++ b/src/mesido/pycml/component_library/milp/heat/__init__.py @@ -1,5 +1,8 @@ +from .air_water_heat_pump import AirWaterHeatPump +from .airco import Airco from .ates import ATES from .check_valve import CheckValve +from .cold_demand import ColdDemand from .control_valve import ControlValve from .geothermal_source import GeothermalSource from .heat_buffer import HeatBuffer @@ -11,13 +14,17 @@ from .heat_pump import HeatPump from .heat_source import HeatSource from .heat_two_port import HeatTwoPort +from .low_temperature_ates import LowTemperatureATES from .node import Node from .pump import Pump __all__ = [ + "Airco", + "AirWaterHeatPump", "ATES", "HeatBuffer", "CheckValve", + "ColdDemand", "ControlValve", "HeatDemand", "GeothermalSource", @@ -26,8 +33,9 @@ "HeatPort", "HeatPump", "HeatTwoPort", - "Node", "HeatPipe", - "Pump", "HeatSource", + "LowTemperatureATES", + "Node", + "Pump", ] diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/_non_storage_component.py b/src/mesido/pycml/component_library/milp/heat/_non_storage_component.py similarity index 72% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/_non_storage_component.py rename to src/mesido/pycml/component_library/milp/heat/_non_storage_component.py index 67f87d5fc..2c83481b5 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/_non_storage_component.py +++ b/src/mesido/pycml/component_library/milp/heat/_non_storage_component.py @@ -1,16 +1,25 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.component_library.milp._internal.heat_component import BaseAsset +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable -from rtctools_heat_network.pycml.component_library.milp._internal.heat_component import BaseAsset +from numpy import nan from .heat_two_port import HeatTwoPort +@add_variables_documentation_automatically class _NonStorageComponent(HeatTwoPort, BaseAsset): """ A non storage component is an asset type that does not have states that have interdependent time-steps, it does have time-varying states like Heat_flow. In the NonStorageComponent we define most of the properties being utilized by all components, like rho and cp. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -26,10 +35,10 @@ def __init__(self, name, **modifiers): self.rho = 988.0 self.nominal_pressure = 16.0e5 - # NOTE: We move a factor of 100.0 of the milp to the state entry, to - # reduce the coefficient in front of the milp variables. This + # NOTE: We move a factor of 100.0 of the heat to the state entry, to + # reduce the coefficient in front of the heat variables. This # particularly helps the scaling/range of the constraints that relate - # the milp loss (if it is variable/optional) to the milp in- and out + # the milp loss (if it is variable/optional) to the heat in- and out # of a component. self.Heat_nominal = self.cp * self.rho * self.Q_nominal * 100.0 diff --git a/src/mesido/pycml/component_library/milp/heat/air_water_heat_pump.py b/src/mesido/pycml/component_library/milp/heat/air_water_heat_pump.py new file mode 100644 index 000000000..88ee3e0d6 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/heat/air_water_heat_pump.py @@ -0,0 +1,23 @@ +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from .heat_source import HeatSource + + +@add_variables_documentation_automatically +class AirWaterHeatPump(HeatSource): + """ + The air water heat pump component is used to model the source behaviour of air water heat pumps. + For now, it is just a source, but in the future this can be expanded. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + self.cop = modifiers["cop"] + self.component_subtype = "air_water_heat_pump" diff --git a/src/mesido/pycml/component_library/milp/heat/airco.py b/src/mesido/pycml/component_library/milp/heat/airco.py new file mode 100644 index 000000000..6f8c24502 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/heat/airco.py @@ -0,0 +1,62 @@ +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from ._non_storage_component import _NonStorageComponent + + +@add_variables_documentation_automatically +class Airco(_NonStorageComponent): + """ + The airco component is there to extract thermal power (Heat) out of the network. This component + can also be used to model cold producers, e.g. dry coolers. + + The heat to discharge constraints are set in the HeatPhysicsMixin. We enforce that the outgoing + temperature of the airco matches the absolute thermal power, Q * cp * rho * T_ret == Heat, + similar as with the sources. This allows us to guarantee that the flow can always carry the + heat and that thermal losses are always estimated conservatively, as the heat losses further + downstream in the network are over-estimated with T_ret where in reality this temperature + drops. It also implicitly assumes that the temperature drops in the network are small and thus + satisfy minimum temperature requirements. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__( + name, + **self.merge_modifiers( + dict( + HeatIn=dict(Heat=dict(min=0.0)), + HeatOut=dict(Heat=dict(min=0.0)), + ), + modifiers, + ), + ) + + self.component_type = "airco" + + self.minimum_pressure_drop = 1.0e5 # 1 bar of pressure drop + + # Assumption: heat in/out and extracted is nonnegative + # Heat in the return (i.e. cold) line is zero + self.add_variable(Variable, "Heat_airco", min=0.0, nominal=self.Heat_nominal) + self.add_variable(Variable, "dH", max=0.0) + self.add_equation(self.dH - (self.HeatOut.H - self.HeatIn.H)) + self.add_equation( + ( + self.minimum_pressure_drop * self.Q + - (self.HeatIn.Hydraulic_power - self.HeatOut.Hydraulic_power) + ) + / (self.Q_nominal * self.minimum_pressure_drop) + ) + + self.add_equation( + (self.HeatOut.Heat - (self.HeatIn.Heat - self.Heat_airco)) / self.Heat_nominal + ) + + self.add_equation((self.Heat_flow - self.Heat_airco) / self.Heat_nominal) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/ates.py b/src/mesido/pycml/component_library/milp/heat/ates.py similarity index 81% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/ates.py rename to src/mesido/pycml/component_library/milp/heat/ates.py index 0930234aa..e1a2dfa26 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/ates.py +++ b/src/mesido/pycml/component_library/milp/heat/ates.py @@ -1,26 +1,34 @@ -from numpy import nan - +from mesido.pycml import Variable +from mesido.pycml.component_library.milp._internal.heat_component import BaseAsset +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable -from rtctools_heat_network.pycml.component_library.milp._internal.heat_component import BaseAsset +from numpy import nan from .heat_two_port import HeatTwoPort +@add_variables_documentation_automatically class ATES(HeatTwoPort, BaseAsset): """ - An Ates is a storage component that is used to model milp storage underground. Typically, this + An Ates is a storage component that is used to model heat storage underground. Typically, this is done by storing hot water in an underground aquifier. We model this with an energy storage where the energy loss is modelled as a fraction of the Stored energy for each time-step. - Like all storage assets we enforce that they must be connected as a demand. The milp to - discharge constraints are set in the HeatMixin, where we use a big_m formulation to enforce the - correct constraints depending on whether the ates is charging or discharging. + Like all storage assets we enforce that they must be connected as a demand. The heat to + discharge constraints are set in the HeatPhysicsMixin, where we use a big_m formulation to + enforce the correct constraints depending on whether the ates is charging or discharging. Please note that: The user is responsible to implement the cyclic behaviour in their workflow constraints. - Meaning that the milp stored at the 1st and last time step should be equal. Furthermore, due + Meaning that the heat stored at the 1st and last time step should be equal. Furthermore, due to the implicit solving note that the energy out of the ATES should be 0 for the 1st time step. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -63,14 +71,14 @@ def __init__(self, name, **modifiers): # Meaning that they might always be, for e.g., 5% full. self.min_fraction_tank_volume = 0.05 - # Stored_heat is the milp that is contained in the ates. - # Heat_ates is the amount of milp added to or extracted from the buffer + # Stored_heat is the heat that is contained in the ates. + # Heat_ates is the amount of heat added to or extracted from the buffer # per timestep. # Thus Heat_buffer = HeatHot = der(Stored_heat). # We connect an ATES as an demand, meaning that flow and Heat_ates are positive under # charging and negative under discharge - self.add_variable(Variable, "Heat_ates", nominal=self.Heat_nominal) - self.add_variable(Variable, "Heat_flow", nominal=self.Heat_nominal) + self.add_variable(Variable, "Heat_ates", nominal=self.Heat_nominal) # [W] + self.add_variable(Variable, "Heat_flow", nominal=self.Heat_nominal) # [W] # Assume the storage fills in about 3 months at typical rate self._typical_fill_time = 3600.0 * 24.0 * 90.0 self._nominal_stored_heat = self.Heat_nominal * self._typical_fill_time @@ -91,6 +99,9 @@ def __init__(self, name, **modifiers): Variable, "Pump_power", min=0.0, nominal=self.Q_nominal * self.nominal_pressure ) + self.add_variable(Variable, "dH") + self.add_equation(self.dH - (self.HeatOut.H - self.HeatIn.H)) + self._heat_loss_error_to_state_factor = 1 self._nominal_heat_loss = ( self.Stored_heat.nominal * self.heat_loss_coeff * self._heat_loss_error_to_state_factor diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/check_valve.py b/src/mesido/pycml/component_library/milp/heat/check_valve.py similarity index 68% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/check_valve.py rename to src/mesido/pycml/component_library/milp/heat/check_valve.py index c5cdc961d..e34acef6d 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/check_valve.py +++ b/src/mesido/pycml/component_library/milp/heat/check_valve.py @@ -1,12 +1,22 @@ -from rtctools_heat_network.pycml import Variable +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically from ._non_storage_component import _NonStorageComponent +@add_variables_documentation_automatically class CheckValve(_NonStorageComponent): """ The check valve allows the fluid to flow in only one direction. This is done with constraints in the HeatMixin. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ def __init__(self, name, **modifiers): diff --git a/src/mesido/pycml/component_library/milp/heat/cold_demand.py b/src/mesido/pycml/component_library/milp/heat/cold_demand.py new file mode 100644 index 000000000..3e1a5fd0c --- /dev/null +++ b/src/mesido/pycml/component_library/milp/heat/cold_demand.py @@ -0,0 +1,63 @@ +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from ._non_storage_component import _NonStorageComponent + + +@add_variables_documentation_automatically +class ColdDemand(_NonStorageComponent): + """ + The cold demand component is there to add thermal power (Heat) out of the network. Typically, + this component is used to model aggregated demands. + + The heat to discharge constraints are set in the HeatPhysicsMixin. We enforce that the outgoing + temperature of the demand matches the absolute thermal power, Q * cp * rho * T_ret == Heat, + similar as with the sources. This allows us to guarantee that the flow can always carry the + heat and that thermal losses are always estimated conservatively, as the heat losses further + downstream in the network are over-estimated with T_ret where in reality this temperature + drops. It also implicitly assumes that the temperature drops in the network are small and thus + satisfy minimum temperature requirements. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + + """ + + def __init__(self, name, **modifiers): + super().__init__( + name, + **self.merge_modifiers( + dict( + HeatIn=dict(Heat=dict(min=0.0)), + HeatOut=dict(Heat=dict(min=0.0)), + ), + modifiers, + ), + ) + + self.component_type = "cold_demand" + + self.minimum_pressure_drop = 1.0e5 # 1 bar of pressure drop + + # Assumption: heat in/out and extracted is nonnegative + # Heat in the return (i.e. cold) line is zero + self.add_variable(Variable, "Cold_demand", min=0.0, nominal=self.Heat_nominal) + self.add_variable(Variable, "dH", max=0.0) + self.add_equation(self.dH - (self.HeatOut.H - self.HeatIn.H)) + self.add_equation( + ( + self.minimum_pressure_drop * self.Q + - (self.HeatIn.Hydraulic_power - self.HeatOut.Hydraulic_power) + ) + / (self.Q_nominal * self.minimum_pressure_drop) + ) + + self.add_equation( + (self.HeatOut.Heat - (self.HeatIn.Heat + self.Cold_demand)) / self.Heat_nominal + ) + + self.add_equation((self.Heat_flow - self.Cold_demand) / self.Heat_nominal) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/control_valve.py b/src/mesido/pycml/component_library/milp/heat/control_valve.py similarity index 70% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/control_valve.py rename to src/mesido/pycml/component_library/milp/heat/control_valve.py index f968ba3a6..324d86a4a 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/control_valve.py +++ b/src/mesido/pycml/component_library/milp/heat/control_valve.py @@ -1,13 +1,22 @@ -from rtctools_heat_network.pycml import Variable +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically from ._non_storage_component import _NonStorageComponent +@add_variables_documentation_automatically class ControlValve(_NonStorageComponent): """ The control valve is a component to create pressure drop. We allow the control valve to create pressure drop for flow in both directions. Note that we set the absolute head loss symbol in the HeatMixin. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/geothermal_source.py b/src/mesido/pycml/component_library/milp/heat/geothermal_source.py similarity index 74% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/geothermal_source.py rename to src/mesido/pycml/component_library/milp/heat/geothermal_source.py index f2c93a13c..a91a4099e 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/geothermal_source.py +++ b/src/mesido/pycml/component_library/milp/heat/geothermal_source.py @@ -1,8 +1,11 @@ +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + from numpy import nan from .heat_source import HeatSource +@add_variables_documentation_automatically class GeothermalSource(HeatSource): """ The geothermal source component is used to model geothermal doublets. It is equivilent to a @@ -11,6 +14,14 @@ class GeothermalSource(HeatSource): increasing the amount of doublets. In the HeatMixin an integer is created _aggregation_count to model the amount of doublets and the maximum power will scale with this integer instead of continuous. This will also ensure that the cost will scale with this integer. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ def __init__(self, name, **modifiers): diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_buffer.py b/src/mesido/pycml/component_library/milp/heat/heat_buffer.py similarity index 79% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/heat_buffer.py rename to src/mesido/pycml/component_library/milp/heat/heat_buffer.py index 149d5fcfe..ee674b441 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_buffer.py +++ b/src/mesido/pycml/component_library/milp/heat/heat_buffer.py @@ -1,22 +1,32 @@ import math -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.component_library.milp._internal.heat_component import BaseAsset +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable -from rtctools_heat_network.pycml.component_library.milp._internal.heat_component import BaseAsset +from numpy import nan from .heat_two_port import HeatTwoPort +@add_variables_documentation_automatically class HeatBuffer(HeatTwoPort, BaseAsset): """ The buffer component is to model milp storage in a tank. This means that we model a tank of hot - water being filled and radiating milp away (milp loss) over the hot surfaces. We assume that the + water being filled and radiating milp away (heat loss) over the hot surfaces. We assume that the hot surfaces are those in contact with hot water. - Like all storage assets we enforce that they must be connected as a demand. The milp to - discharge constraints are set in the HeatMixin, where we use a big_m formulation to enforce the - correct constraints depending on whether the buffer is charging or discharging. + Like all storage assets we enforce that they must be connected as a demand. The heat to + discharge constraints are set in the HeatPhysicsMixin, where we use a big_m formulation to + enforce the correct constraints depending on whether the buffer is charging or discharging. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ def __init__(self, name, **modifiers): @@ -58,12 +68,12 @@ def __init__(self, name, **modifiers): self.volume * (1 - self.min_fraction_tank_volume) * self.dT * self.cp * self.rho ) - # Stored_heat is the milp that is contained in the buffer. - # Heat_buffer is the amount of milp added to or extracted from the buffer + # Stored_heat is the heat that is contained in the buffer. + # Heat_buffer is the amount of heat added to or extracted from the buffer # per timestep. - # HeatHot (resp. HeatCold) is the amount of milp added or extracted from + # HeatHot (resp. HeatCold) is the amount of heat added or extracted from # the hot (resp. cold) line. - # As by construction the cold line should have zero milp, we fix HeatCold to zero. + # As by construction the cold line should have zero heat, we fix HeatCold to zero. # Thus Heat_buffer = HeatHot = der(Stored_heat). # We connect a buffer as an demand, meaning that flow and Heat_buffer are positive under # charging and negative under discharge @@ -94,6 +104,9 @@ def __init__(self, name, **modifiers): self._heat_loss_eq_nominal_buf = (self.Heat_nominal * self._nominal_heat_loss) ** 0.5 + self.add_variable(Variable, "dH") + self.add_equation(self.dH - (self.HeatOut.H - self.HeatIn.H)) + self.add_equation(self.HeatIn.Q - self.HeatOut.Q) self.add_equation(self.Q - self.HeatOut.Q) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_demand.py b/src/mesido/pycml/component_library/milp/heat/heat_demand.py similarity index 75% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/heat_demand.py rename to src/mesido/pycml/component_library/milp/heat/heat_demand.py index 1c5d7ecce..ffeae480d 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_demand.py +++ b/src/mesido/pycml/component_library/milp/heat/heat_demand.py @@ -1,20 +1,29 @@ -from rtctools_heat_network.pycml import Variable +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically from ._non_storage_component import _NonStorageComponent +@add_variables_documentation_automatically class HeatDemand(_NonStorageComponent): """ The demand component is there to extract thermal power (Heat) out of the network. Typically, this component is used to model aggregated demands. - The milp to discharge constraints are set in the HeatMixin. We enforce that the outgoing + The heat to discharge constraints are set in the HeatPhysicsMixin. We enforce that the outgoing temperature of the demand matches the absolute thermal power, Q * cp * rho * T_ret == Heat, similar as with the sources. This allows us to guarantee that the flow can always carry the - milp and that thermal losses are always estimated conservatively, as the milp losses further + heatf and that thermal losses are always estimated conservatively, as the heat losses further downstream in the network are over-estimated with T_ret where in reality this temperature drops. It also implicitly assumes that the temperature drops in the network are small and thus satisfy minimum temperature requirements. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -33,7 +42,7 @@ def __init__(self, name, **modifiers): self.minimum_pressure_drop = 1.0e5 # 1 bar of pressure drop - # Assumption: milp in/out and extracted is nonnegative + # Assumption: heat in/out and extracted is nonnegative # Heat in the return (i.e. cold) line is zero self.add_variable(Variable, "Heat_demand", min=0.0, nominal=self.Heat_nominal) self.add_variable(Variable, "dH", max=0.0) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_exchanger.py b/src/mesido/pycml/component_library/milp/heat/heat_exchanger.py similarity index 75% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/heat_exchanger.py rename to src/mesido/pycml/component_library/milp/heat/heat_exchanger.py index 9403da960..a8c45231e 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_exchanger.py +++ b/src/mesido/pycml/component_library/milp/heat/heat_exchanger.py @@ -1,25 +1,34 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.component_library.milp._internal import BaseAsset +from mesido.pycml.component_library.milp.heat.heat_four_port import HeatFourPort +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable -from rtctools_heat_network.pycml.component_library.milp._internal import BaseAsset -from rtctools_heat_network.pycml.component_library.milp.heat.heat_four_port import HeatFourPort +from numpy import nan +@add_variables_documentation_automatically class HeatExchanger(HeatFourPort, BaseAsset): """ - The milp exchanger component is used to model the exchange of thermal power between two + The heat exchanger component is used to model the exchange of thermal power between two hydraulically decoupled systems. A constant efficiency is used to model milp losses and a - maximum power is set on the primary side to model physical constraints on the amount of milp + maximum power is set on the primary side to model physical constraints on the amount of heat transfer. - The milp to discharge constraints are set in the HeatMixin. The primary side is modelled as a + The heat to discharge constraints are set in the HeatMixin. The primary side is modelled as a demand, meaning it consumes energy from the primary network and gives it to the secondary side, - where the secondary side acts like a source to the secondary network. This also means that milp + where the secondary side acts like a source to the secondary network. This also means that heat can only flow from primary to secondary. - To avoid unphysical milp transfer the HeatMixin sets constraints on the temperatures on both - sides in the case of varying temperature. We also allow a heat_exchanger to be disabled on + To avoid unphysical heat transfer the HeatPhysicsMixin sets constraints on the temperatures on + both sides in the case of varying temperature. We also allow a heat_exchanger to be disabled on certain time-steps to then allow these temperature constraints to be also disabled. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -42,7 +51,7 @@ def __init__(self, name, **modifiers): self.minimum_pressure_drop = 1.0e5 # 1 bar of pressure drop self.pump_efficiency = 0.5 - # Assumption: milp in/out and added is nonnegative + # Assumption: heat in/out and added is nonnegative self.add_variable(Variable, "Primary_heat", min=0.0) self.add_variable(Variable, "Secondary_heat", min=0.0) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_four_port.py b/src/mesido/pycml/component_library/milp/heat/heat_four_port.py similarity index 65% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/heat_four_port.py rename to src/mesido/pycml/component_library/milp/heat/heat_four_port.py index 743e74ab9..36cf03339 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_four_port.py +++ b/src/mesido/pycml/component_library/milp/heat/heat_four_port.py @@ -1,13 +1,22 @@ -from rtctools_heat_network.pycml import Variable -from rtctools_heat_network.pycml.component_library.milp._internal import HeatComponent +from mesido.pycml import Variable +from mesido.pycml.component_library.milp._internal import HeatComponent +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically from ._non_storage_component import _NonStorageComponent +@add_variables_documentation_automatically class HeatFourPort(HeatComponent): """ The HeatFourPort is used as a base component to model assets that interact with two hydraulically decoupled systems. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_pipe.py b/src/mesido/pycml/component_library/milp/heat/heat_pipe.py similarity index 78% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/heat_pipe.py rename to src/mesido/pycml/component_library/milp/heat/heat_pipe.py index 431106dc6..b1d345e25 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_pipe.py +++ b/src/mesido/pycml/component_library/milp/heat/heat_pipe.py @@ -1,24 +1,34 @@ -from numpy import nan, pi +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable +from numpy import nan, pi from ._non_storage_component import _NonStorageComponent +@add_variables_documentation_automatically class HeatPipe(_NonStorageComponent): """ The pipe component is to model the pressure drop (and optionally hydraulic power) and - milp losses over a pipe. Three options for head loss computation are available in the HeatMixin + heat losses over a pipe. Three options for head loss computation are available in the HeatMixin options: No_HeadLoss, Linear, DW_Linearized. The hydraulic power computation can only be done reasonably if DW_linearized is selected as otherwise head_losses are significantly over-estimated. - The milp to discharge constraints are set in the HeatMixin. Where we ensure that the milp must - be smaller than the flow can carry, as we overestimate the milp losses with the outgoing + The heat to discharge constraints are set in the HeatMixin. Where we ensure that the heat must + be smaller than the flow can carry, as we overestimate the heat losses with the outgoing temperature at the demand/source/storage assets where in reality this temperature drops throughout the network. Meaning that the flow does lose energy but not temperature. In this manner the energy losses will always be overestimated as in reality the flow will also have a temperature drop. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ def __init__(self, name, **modifiers): @@ -36,7 +46,7 @@ def __init__(self, name, **modifiers): self.carrier_id = -1 self.pressure = 16.0e5 - # Parameters determining the milp loss + # Parameters determining the heat loss # All of these have default values in the library function self.insulation_thickness = nan self.conductivity_insulation = nan @@ -69,4 +79,4 @@ def __init__(self, name, **modifiers): self.add_equation(((self.Heat_flow - self.HeatIn.Heat) / self.Heat_nominal)) # Note: Heat loss is added in the mixin, because it depends on the flow direction - # * milp loss equation: (HeatOut.Heat - (HeatIn.Heat +/- Heat_loss)) = 0. + # * heat loss equation: (HeatOut.Heat - (HeatIn.Heat +/- Heat_loss)) = 0. diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_port.py b/src/mesido/pycml/component_library/milp/heat/heat_port.py similarity index 55% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/heat_port.py rename to src/mesido/pycml/component_library/milp/heat/heat_port.py index cf819b330..c6f795650 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_port.py +++ b/src/mesido/pycml/component_library/milp/heat/heat_port.py @@ -1,12 +1,21 @@ -from rtctools_heat_network.pycml import Connector, Variable -from rtctools_heat_network.pycml.component_library.milp._internal import HeatComponent +from mesido.pycml import Connector, Variable +from mesido.pycml.component_library.milp._internal import HeatComponent +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically +@add_variables_documentation_automatically class HeatPort(HeatComponent, Connector): """ The HeatPort is used to model the variables at an in or outgoing port of a component. For the HeatMixin we model thermal Power (Heat [W]), flow (Q [m3/s]) and head (H [m]) at every port in the network. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_pump.py b/src/mesido/pycml/component_library/milp/heat/heat_pump.py similarity index 75% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/heat_pump.py rename to src/mesido/pycml/component_library/milp/heat/heat_pump.py index 0db1800e6..23d4e7ed2 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_pump.py +++ b/src/mesido/pycml/component_library/milp/heat/heat_pump.py @@ -1,20 +1,30 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.component_library.milp._internal import BaseAsset +from mesido.pycml.component_library.milp.heat.heat_four_port import HeatFourPort +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable -from rtctools_heat_network.pycml.component_library.milp._internal import BaseAsset -from rtctools_heat_network.pycml.component_library.milp.heat.heat_four_port import HeatFourPort +from numpy import nan +@add_variables_documentation_automatically class HeatPump(HeatFourPort, BaseAsset): """ The heatpump component is used to model a water-water heatpump. A constant COP is used to model the electricity use of the heatpump. A power cap is set - on the primary side to model physical constraints on the amount of milp transfer. + on the primary side to model physical constraints on the amount of heat transfer. + + The heat to discharge constraints are set in the HeatPhysicsMixin. The primary side is modelled + as a demand, meaning it consumes energy from the primary network and gives it to the secondary + side, where the secondary side acts like a source to the secondary network. This also means + that heat can only flow from primary to secondary. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. - The milp to discharge constraints are set in the HeatMixin. The primary side is modelled as a - demand, meaning it consumes energy from the primary network and gives it to the secondary side, - where the secondary side acts like a source to the secondary network. This also means that milp - can only flow from primary to secondary. """ def __init__(self, name, **modifiers): @@ -36,7 +46,7 @@ def __init__(self, name, **modifiers): self.pump_efficiency = 0.5 self.elec_power_nominal = self.nominal / self.COP - # Assumption: milp in/out and added is nonnegative + # Assumption: heat in/out and added is nonnegative self.add_variable(Variable, "Primary_heat", min=0.0) self.add_variable(Variable, "Secondary_heat", min=0.0) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_source.py b/src/mesido/pycml/component_library/milp/heat/heat_source.py similarity index 80% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/heat_source.py rename to src/mesido/pycml/component_library/milp/heat/heat_source.py index aa2f3adcc..f2d16eb33 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_source.py +++ b/src/mesido/pycml/component_library/milp/heat/heat_source.py @@ -1,20 +1,30 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable +from numpy import nan from ._non_storage_component import _NonStorageComponent +@add_variables_documentation_automatically class HeatSource(_NonStorageComponent): """ The source component is there to insert thermal power (Heat) into the network. - The milp to discharge constraints are set in the HeatMixin. We enforce that the outgoing + The heat to discharge constraints are set in the HeatMixin. We enforce that the outgoing temperature of the source matches the absolute thermal power, Q * cp * rho * T_sup == Heat, similar as with the demands. This allows us to guarantee that the flow can always carry, as - the milp losses further downstream in the network are over-estimated with T_ret where in + the heat losses further downstream in the network are over-estimated with T_ret where in reality this temperature drops. It also implicitly assumes that the temperature drops in the network are small and thus satisfy minimum temperature requirements. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ def __init__(self, name, **modifiers): @@ -35,7 +45,7 @@ def __init__(self, name, **modifiers): self.co2_coeff = 1.0 self.pump_efficiency = 0.5 - # Assumption: milp in/out and added is nonnegative + # Assumption: heat in/out and added is nonnegative # Heat in the return (i.e. cold) line is zero self.add_variable(Variable, "Heat_source", min=0.0, nominal=self.Heat_nominal) self.add_variable(Variable, "Emission", min=0.0, nominal=self.Heat_nominal) diff --git a/src/mesido/pycml/component_library/milp/heat/heat_two_port.py b/src/mesido/pycml/component_library/milp/heat/heat_two_port.py new file mode 100644 index 000000000..c4061e6fe --- /dev/null +++ b/src/mesido/pycml/component_library/milp/heat/heat_two_port.py @@ -0,0 +1,26 @@ +from mesido.pycml.component_library.milp._internal import HeatComponent +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from .heat_port import HeatPort + + +@add_variables_documentation_automatically +class HeatTwoPort(HeatComponent): + """ + The HeatTwoPort component is used as a base for interaction with one hydraulically coupled + system. As heat networks are closed systems we always need two ports to model both the in and + out going flow in the system. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + + self.add_variable(HeatPort, "HeatIn") + self.add_variable(HeatPort, "HeatOut") diff --git a/src/mesido/pycml/component_library/milp/heat/low_temperature_ates.py b/src/mesido/pycml/component_library/milp/heat/low_temperature_ates.py new file mode 100644 index 000000000..6e4255f71 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/heat/low_temperature_ates.py @@ -0,0 +1,110 @@ +from mesido.pycml import Variable +from mesido.pycml.component_library.milp._internal.heat_component import BaseAsset +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from numpy import nan + +from .heat_two_port import HeatTwoPort + + +@add_variables_documentation_automatically +class LowTemperatureATES(HeatTwoPort, BaseAsset): + """ + TODO: This model is still under developement. + A low temperature ates is a underground aquifier in which heat can be stored. + + Like all storage assets we enforce that they must be connected as a demand. The heat to + discharge constraints are set in the HeatPhysicsMixin, where we use a big_m formulation to + enforce the correct constraints depending on whether the ates is charging or discharging. + + Please note that: + The user is responsible to implement the cyclic behaviour in their workflow constraints. + Meaning that the milp stored at the 1st and last time step should be equal. Furthermore, due + to the implicit solving note that the energy out of the ATES should be 0 for the 1st time step. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information.. + """ + + def __init__(self, name, **modifiers): + super().__init__(name, **modifiers) + + self.component_type = "low_temperature_ates" + + self.Q_nominal = 1.0 + self.T_amb = 10 + self.T_supply = nan + self.T_return = nan + self.T_supply_id = -1 + self.T_return_id = -1 + self.dT = self.T_supply - self.T_return + self.cp = 4200.0 + self.rho = 988.0 + self.Heat_nominal = self.cp * self.rho * self.dT * self.Q_nominal + self.nominal_pressure = 16.0e5 + self.minimum_pressure_drop = 1.0e5 # 1 bar of pressure drop + self.pump_efficiency = 0.5 + + self.heat_loss_coeff = 0.005 / (24.0 * 3600.0) + self.single_doublet_power = nan + self.nr_of_doublets = 1.0 + # The hot/cold tank can have a lower bound on its volume. + # Meaning that they might always be, for e.g., 5% full. + self.min_fraction_tank_volume = 0.05 + + # Stored_heat is the heat that is contained in the ates. + # Heat_low_temperature_ates is the amount of heat added to or extracted from the buffer + # per timestep. + # Thus Heat_buffer = HeatHot = der(Stored_heat). + # We connect an ATES as an demand, meaning that flow and Heat_low_temperature_ates are + # positive undercharging and negative under discharge + self.add_variable(Variable, "Heat_low_temperature_ates", nominal=self.Heat_nominal) # [W] + self.add_variable(Variable, "Heat_flow", nominal=self.Heat_nominal) # [W] + # Assume the storage fills in about 3 months at typical rate + self._typical_fill_time = 3600.0 * 24.0 * 90.0 + self._nominal_stored_heat = self.Heat_nominal * self._typical_fill_time + self.add_variable( + Variable, + "Stored_heat", + min=0.0, + nominal=self._nominal_stored_heat, + ) + self.add_variable( + Variable, + "Stored_volume", + min=0.0, + nominal=self._typical_fill_time * self.Q_nominal, + ) + + self.add_variable(Variable, "Q", nominal=self.Q_nominal) + self.add_variable( + Variable, "Pump_power", min=0.0, nominal=self.Q_nominal * self.nominal_pressure + ) + + self._heat_loss_error_to_state_factor = 1 + self._nominal_heat_loss = ( + self.Stored_heat.nominal * self.heat_loss_coeff * self._heat_loss_error_to_state_factor + ) + self.add_variable(Variable, "Heat_loss", min=0.0, nominal=self._nominal_heat_loss) + + self._heat_loss_eq_nominal_ates = (self.Heat_nominal * self._nominal_heat_loss) ** 0.5 + + self.add_equation(self.HeatIn.Q - self.HeatOut.Q) + self.add_equation(self.Q - self.HeatOut.Q) + + # Heat stored in the ates + self.add_equation( + (self.der(self.Stored_heat) - self.Heat_low_temperature_ates + self.Heat_loss) + / self._heat_loss_eq_nominal_ates + ) + self.add_equation((self.der(self.Stored_volume) - self.Q) / self.Q_nominal) + + self.add_equation( + (self.HeatIn.Heat - (self.HeatOut.Heat + self.Heat_low_temperature_ates)) + / self.Heat_nominal + ) + self.add_equation((self.Heat_flow - self.Heat_low_temperature_ates) / self.Heat_nominal) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/node.py b/src/mesido/pycml/component_library/milp/heat/node.py similarity index 58% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/node.py rename to src/mesido/pycml/component_library/milp/heat/node.py index 09ea3d5bc..6f9c765d2 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/node.py +++ b/src/mesido/pycml/component_library/milp/heat/node.py @@ -1,16 +1,28 @@ -from rtctools_heat_network.pycml import Variable -from rtctools_heat_network.pycml.component_library.milp._internal import BaseAsset, HeatComponent +from mesido.pycml import Variable +from mesido.pycml.component_library.milp._internal import BaseAsset, HeatComponent +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically from .heat_port import HeatPort +@add_variables_documentation_automatically class Node(HeatComponent, BaseAsset): """ A node is the only component in the network that allows to model 3 or more flows to come together. This essentially means that only pipes can be connected to ports and that it models - junctions where multiple pipes come together. The node ensures that the milp on all ports is - equal. Furthermore, it ensures that discharge and milp are conserved for which constraints in + junctions where multiple pipes come together. The node ensures that the heat on all ports is + equal. Furthermore, it ensures that discharge and heat are conserved for which constraints in the HeatMixin are set. + + port = HeatConn[i] (i is the index of the port) + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ def __init__(self, name, **modifiers): @@ -25,7 +37,7 @@ def __init__(self, name, **modifiers): self.add_variable(Variable, "H") # Because the orientation of the connected pipes are important to - # setup the milp conservation, these constraints are added in the + # setup the heat conservation, these constraints are added in the # mixin. for i in range(1, self.n + 1): diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/pump.py b/src/mesido/pycml/component_library/milp/heat/pump.py similarity index 74% rename from src/rtctools_heat_network/pycml/component_library/milp/heat/pump.py rename to src/mesido/pycml/component_library/milp/heat/pump.py index 45d70b1ca..6cd7f301b 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/pump.py +++ b/src/mesido/pycml/component_library/milp/heat/pump.py @@ -1,14 +1,23 @@ -from numpy import nan +from mesido.pycml import Variable +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically -from rtctools_heat_network.pycml import Variable +from numpy import nan from ._non_storage_component import _NonStorageComponent +@add_variables_documentation_automatically class Pump(_NonStorageComponent): """ The pump component is there to add head to the flow. We assume head can only be added for positive flow. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): diff --git a/src/mesido/pycml/component_library/milp/multicommodity/__init__.py b/src/mesido/pycml/component_library/milp/multicommodity/__init__.py new file mode 100644 index 000000000..056357d2e --- /dev/null +++ b/src/mesido/pycml/component_library/milp/multicommodity/__init__.py @@ -0,0 +1,11 @@ +from .airwater_heat_pump_elec import AirWaterHeatPumpElec +from .electro_boiler import ElecBoiler +from .electrolyzer import Electrolyzer +from .gas_boiler import GasBoiler + +__all__ = [ + "AirWaterHeatPumpElec", + "ElecBoiler", + "Electrolyzer", + "GasBoiler", +] diff --git a/src/mesido/pycml/component_library/milp/multicommodity/airwater_heat_pump_elec.py b/src/mesido/pycml/component_library/milp/multicommodity/airwater_heat_pump_elec.py new file mode 100644 index 000000000..7579ad34e --- /dev/null +++ b/src/mesido/pycml/component_library/milp/multicommodity/airwater_heat_pump_elec.py @@ -0,0 +1,51 @@ +from mesido.pycml import Variable +from mesido.pycml.component_library.milp.electricity.electricity_base import ElectricityPort +from mesido.pycml.component_library.milp.heat.air_water_heat_pump import AirWaterHeatPump +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from numpy import nan + + +@add_variables_documentation_automatically +class AirWaterHeatPumpElec(AirWaterHeatPump): + """ + The air-water heat pump component is there to insert thermal power (Heat) into the network. + + The heat to discharge constraints are set in the HeatMixin. We enforce that the outgoing + temperature of the source matches the absolute thermal power, Q * cp * rho * T_sup == Heat, + similar as with the demands. This allows us to guarantee that the flow can always carry, as + the heat losses further downstream in the network are over-estimated with T_ret where in + reality this temperature drops. It also implicitly assumes that the temperature drops in the + network are small and thus satisfy minimum temperature requirements. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__( + name, + **modifiers, + ) + + self.component_subtype = "air_water_heat_pump_elec" + + self.id_mapping_carrier = -1 + + self.min_voltage = nan + self.elec_power_nominal = nan + + # Assumption: heat in/out and added is nonnegative + # Heat in the return (i.e. cold) line is zero + self.add_variable(ElectricityPort, "ElectricityIn") + self.add_variable(Variable, "Power_consumed", min=0.0, nominal=self.elec_power_nominal) + + self.add_equation( + ((self.ElectricityIn.Power - self.Power_consumed) / self.elec_power_nominal) + ) + + self.add_equation(((self.Power_consumed * self.cop - self.Heat_source) / self.Heat_nominal)) diff --git a/src/mesido/pycml/component_library/milp/multicommodity/electro_boiler.py b/src/mesido/pycml/component_library/milp/multicommodity/electro_boiler.py new file mode 100644 index 000000000..b24c5b799 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/multicommodity/electro_boiler.py @@ -0,0 +1,54 @@ +from mesido.pycml import Variable +from mesido.pycml.component_library.milp.electricity.electricity_base import ElectricityPort +from mesido.pycml.component_library.milp.heat.heat_source import HeatSource +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from numpy import nan + + +@add_variables_documentation_automatically +class ElecBoiler(HeatSource): + """ + The e-boiler component is there to insert thermal power (Heat) into the network. + + The heat to discharge constraints are set in the HeatMixin. We enforce that the outgoing + temperature of the source matches the absolute thermal power, Q * cp * rho * T_sup == Heat, + similar as with the demands. This allows us to guarantee that the flow can always carry, as + the heat losses further downstream in the network are over-estimated with T_ret where in + reality this temperature drops. It also implicitly assumes that the temperature drops in the + network are small and thus satisfy minimum temperature requirements. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__( + name, + **modifiers, + ) + + self.component_subtype = "elec_boiler" + + self.id_mapping_carrier = -1 + + self.min_voltage = nan + self.elec_power_nominal = nan + self.efficiency = nan + + # Assumption: heat in/out and added is nonnegative + # Heat in the return (i.e. cold) line is zero + self.add_variable(ElectricityPort, "ElectricityIn") + self.add_variable(Variable, "Power_consumed", min=0.0, nominal=self.elec_power_nominal) + + self.add_equation( + ((self.ElectricityIn.Power - self.Power_consumed) / self.elec_power_nominal) + ) + + self.add_equation( + ((self.Power_consumed * self.efficiency - self.Heat_source) / self.Heat_nominal) + ) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/multicommodity/electrolyzer.py b/src/mesido/pycml/component_library/milp/multicommodity/electrolyzer.py similarity index 64% rename from src/rtctools_heat_network/pycml/component_library/milp/multicommodity/electrolyzer.py rename to src/mesido/pycml/component_library/milp/multicommodity/electrolyzer.py index 77029c152..08eade878 100644 --- a/src/rtctools_heat_network/pycml/component_library/milp/multicommodity/electrolyzer.py +++ b/src/mesido/pycml/component_library/milp/multicommodity/electrolyzer.py @@ -1,21 +1,30 @@ -from numpy import nan - -from rtctools_heat_network.pycml import Variable -from rtctools_heat_network.pycml.component_library.milp._internal import BaseAsset -from rtctools_heat_network.pycml.component_library.milp._internal.electricity_component import ( +from mesido.pycml import Variable +from mesido.pycml.component_library.milp._internal import BaseAsset +from mesido.pycml.component_library.milp._internal.electricity_component import ( ElectricityComponent, ) -from rtctools_heat_network.pycml.component_library.milp.electricity.electricity_base import ( +from mesido.pycml.component_library.milp.electricity.electricity_base import ( ElectricityPort, ) -from rtctools_heat_network.pycml.component_library.milp.gas.gas_base import ( +from mesido.pycml.component_library.milp.gas.gas_base import ( GasPort, ) +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from numpy import nan +@add_variables_documentation_automatically class Electrolyzer(ElectricityComponent, BaseAsset): """ - An electrolyzer consumes electricity and produces hydrogen + An electrolyzer consumes electricity and produces hydrogen. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. """ def __init__(self, name, **modifiers): @@ -40,6 +49,8 @@ def __init__(self, name, **modifiers): self.Q_nominal = nan self.min_voltage = nan + self.efficiency = nan + self.nominal_gass_mass_out = self.Q_nominal * self.density self.nominal_power_consumed = nan @@ -52,7 +63,7 @@ def __init__(self, name, **modifiers): self.add_variable(GasPort, "GasOut") self.add_variable( Variable, "Gas_mass_flow_out", min=0.0, nominal=self.nominal_gass_mass_out - ) # [kg/hr] + ) # [g/s] self.add_equation( (self.GasOut.mass_flow - self.Gas_mass_flow_out) / self.nominal_gass_mass_out ) diff --git a/src/mesido/pycml/component_library/milp/multicommodity/gas_boiler.py b/src/mesido/pycml/component_library/milp/multicommodity/gas_boiler.py new file mode 100644 index 000000000..d3701eb82 --- /dev/null +++ b/src/mesido/pycml/component_library/milp/multicommodity/gas_boiler.py @@ -0,0 +1,63 @@ +from mesido.pycml import Variable +from mesido.pycml.component_library.milp.gas.gas_base import GasPort +from mesido.pycml.component_library.milp.heat.heat_source import HeatSource +from mesido.pycml.pycml_mixin import add_variables_documentation_automatically + +from numpy import nan + + +@add_variables_documentation_automatically +class GasBoiler(HeatSource): + """ + The source component is there to insert thermal power (Heat) into the network. + + The heat to discharge constraints are set in the HeatMixin. We enforce that the outgoing + temperature of the source matches the absolute thermal power, Q * cp * rho * T_sup == Heat, + similar as with the demands. This allows us to guarantee that the flow can always carry, as + the heat losses further downstream in the network are over-estimated with T_ret where in + reality this temperature drops. It also implicitly assumes that the temperature drops in the + network are small and thus satisfy minimum temperature requirements. + + Variables created: + {add_variable_names_for_documentation_here} + + Parameters: + name : The name of the asset. \n + modifiers : Dictionary with asset information. + """ + + def __init__(self, name, **modifiers): + super().__init__( + name, + **modifiers, + ) + + self.Q_nominal_gas = nan + + self.component_subtype = "gas_boiler" + + self.energy_content = nan + self.density = 2.5e3 # H2 density [g/m3] at 30bar + + self.id_mapping_carrier = -1 + + # Assumption: heat in/out and added is nonnegative + # Heat in the return (i.e. cold) line is zero + self.add_variable(GasPort, "GasIn") + self.add_variable( + Variable, "Gas_demand_mass_flow", min=0.0, nominal=self.Q_nominal_gas * self.density + ) + + self.add_equation( + ( + (self.GasIn.mass_flow - self.Gas_demand_mass_flow) + / (self.Q_nominal_gas * self.density) + ) + ) + + self.add_equation( + ( + (self.GasIn.mass_flow / 1000.0 * self.energy_content - self.Heat_source) + / self.Heat_nominal + ) + ) diff --git a/src/rtctools_heat_network/pycml/component_library/qth/__init__.py b/src/mesido/pycml/component_library/qth/__init__.py similarity index 100% rename from src/rtctools_heat_network/pycml/component_library/qth/__init__.py rename to src/mesido/pycml/component_library/qth/__init__.py diff --git a/src/rtctools_heat_network/pycml/component_library/qth/_fluid_properties_component.py b/src/mesido/pycml/component_library/qth/_fluid_properties_component.py similarity index 100% rename from src/rtctools_heat_network/pycml/component_library/qth/_fluid_properties_component.py rename to src/mesido/pycml/component_library/qth/_fluid_properties_component.py diff --git a/src/rtctools_heat_network/pycml/component_library/qth/_internal/__init__.py b/src/mesido/pycml/component_library/qth/_internal/__init__.py similarity index 100% rename from src/rtctools_heat_network/pycml/component_library/qth/_internal/__init__.py rename to src/mesido/pycml/component_library/qth/_internal/__init__.py diff --git a/src/mesido/pycml/component_library/qth/_internal/qth_component.py b/src/mesido/pycml/component_library/qth/_internal/qth_component.py new file mode 100644 index 000000000..1dd41cee6 --- /dev/null +++ b/src/mesido/pycml/component_library/qth/_internal/qth_component.py @@ -0,0 +1,5 @@ +from mesido.pycml import Component + + +class QTHComponent(Component): + pass diff --git a/src/rtctools_heat_network/pycml/component_library/qth/_non_storage_component.py b/src/mesido/pycml/component_library/qth/_non_storage_component.py similarity index 91% rename from src/rtctools_heat_network/pycml/component_library/qth/_non_storage_component.py rename to src/mesido/pycml/component_library/qth/_non_storage_component.py index 3456d62e6..ffdd605fc 100644 --- a/src/rtctools_heat_network/pycml/component_library/qth/_non_storage_component.py +++ b/src/mesido/pycml/component_library/qth/_non_storage_component.py @@ -1,4 +1,4 @@ -from rtctools_heat_network.pycml import Variable +from mesido.pycml import Variable from .qth_two_port import QTHTwoPort diff --git a/src/rtctools_heat_network/pycml/component_library/qth/buffer.py b/src/mesido/pycml/component_library/qth/buffer.py similarity index 98% rename from src/rtctools_heat_network/pycml/component_library/qth/buffer.py rename to src/mesido/pycml/component_library/qth/buffer.py index a2375dbc1..b708cf649 100644 --- a/src/rtctools_heat_network/pycml/component_library/qth/buffer.py +++ b/src/mesido/pycml/component_library/qth/buffer.py @@ -1,8 +1,8 @@ import math -from numpy import nan +from mesido.pycml import Variable -from rtctools_heat_network.pycml import Variable +from numpy import nan from ._fluid_properties_component import _FluidPropertiesComponent diff --git a/src/rtctools_heat_network/pycml/component_library/qth/check_valve.py b/src/mesido/pycml/component_library/qth/check_valve.py similarity index 91% rename from src/rtctools_heat_network/pycml/component_library/qth/check_valve.py rename to src/mesido/pycml/component_library/qth/check_valve.py index 2a50a0a66..ab5e1a174 100644 --- a/src/rtctools_heat_network/pycml/component_library/qth/check_valve.py +++ b/src/mesido/pycml/component_library/qth/check_valve.py @@ -1,4 +1,4 @@ -from rtctools_heat_network.pycml import Variable +from mesido.pycml import Variable from ._non_storage_component import _NonStorageComponent diff --git a/src/rtctools_heat_network/pycml/component_library/qth/control_valve.py b/src/mesido/pycml/component_library/qth/control_valve.py similarity index 89% rename from src/rtctools_heat_network/pycml/component_library/qth/control_valve.py rename to src/mesido/pycml/component_library/qth/control_valve.py index 2324eae60..53443c4d0 100644 --- a/src/rtctools_heat_network/pycml/component_library/qth/control_valve.py +++ b/src/mesido/pycml/component_library/qth/control_valve.py @@ -1,4 +1,4 @@ -from rtctools_heat_network.pycml import Variable +from mesido.pycml import Variable from ._non_storage_component import _NonStorageComponent diff --git a/src/rtctools_heat_network/pycml/component_library/qth/demand.py b/src/mesido/pycml/component_library/qth/demand.py similarity index 94% rename from src/rtctools_heat_network/pycml/component_library/qth/demand.py rename to src/mesido/pycml/component_library/qth/demand.py index 7aa696991..4e30483a1 100644 --- a/src/rtctools_heat_network/pycml/component_library/qth/demand.py +++ b/src/mesido/pycml/component_library/qth/demand.py @@ -1,4 +1,4 @@ -from rtctools_heat_network.pycml import SymbolicParameter, Variable +from mesido.pycml import SymbolicParameter, Variable from ._fluid_properties_component import _FluidPropertiesComponent from ._non_storage_component import _NonStorageComponent diff --git a/src/rtctools_heat_network/pycml/component_library/qth/geothermal_source.py b/src/mesido/pycml/component_library/qth/geothermal_source.py similarity index 100% rename from src/rtctools_heat_network/pycml/component_library/qth/geothermal_source.py rename to src/mesido/pycml/component_library/qth/geothermal_source.py diff --git a/src/rtctools_heat_network/pycml/component_library/qth/node.py b/src/mesido/pycml/component_library/qth/node.py similarity index 93% rename from src/rtctools_heat_network/pycml/component_library/qth/node.py rename to src/mesido/pycml/component_library/qth/node.py index c48805ae9..5ff3d7ead 100644 --- a/src/rtctools_heat_network/pycml/component_library/qth/node.py +++ b/src/mesido/pycml/component_library/qth/node.py @@ -1,4 +1,4 @@ -from rtctools_heat_network.pycml import Variable +from mesido.pycml import Variable from ._internal import QTHComponent from .qth_port import QTHPort diff --git a/src/rtctools_heat_network/pycml/component_library/qth/pipe.py b/src/mesido/pycml/component_library/qth/pipe.py similarity index 97% rename from src/rtctools_heat_network/pycml/component_library/qth/pipe.py rename to src/mesido/pycml/component_library/qth/pipe.py index aaf14345b..5209e4202 100644 --- a/src/rtctools_heat_network/pycml/component_library/qth/pipe.py +++ b/src/mesido/pycml/component_library/qth/pipe.py @@ -1,6 +1,6 @@ -from numpy import nan, pi +from mesido.pycml import Variable -from rtctools_heat_network.pycml import Variable +from numpy import nan, pi from ._fluid_properties_component import _FluidPropertiesComponent from ._non_storage_component import _NonStorageComponent diff --git a/src/rtctools_heat_network/pycml/component_library/qth/pump.py b/src/mesido/pycml/component_library/qth/pump.py similarity index 91% rename from src/rtctools_heat_network/pycml/component_library/qth/pump.py rename to src/mesido/pycml/component_library/qth/pump.py index 730be6555..852d0d622 100644 --- a/src/rtctools_heat_network/pycml/component_library/qth/pump.py +++ b/src/mesido/pycml/component_library/qth/pump.py @@ -1,4 +1,4 @@ -from rtctools_heat_network.pycml import Variable +from mesido.pycml import Variable from ._non_storage_component import _NonStorageComponent diff --git a/src/rtctools_heat_network/pycml/component_library/qth/qth_port.py b/src/mesido/pycml/component_library/qth/qth_port.py similarity index 88% rename from src/rtctools_heat_network/pycml/component_library/qth/qth_port.py rename to src/mesido/pycml/component_library/qth/qth_port.py index e0c2583ad..7a622d53a 100644 --- a/src/rtctools_heat_network/pycml/component_library/qth/qth_port.py +++ b/src/mesido/pycml/component_library/qth/qth_port.py @@ -1,4 +1,4 @@ -from rtctools_heat_network.pycml import Connector, Variable +from mesido.pycml import Connector, Variable from ._internal import QTHComponent diff --git a/src/rtctools_heat_network/pycml/component_library/qth/qth_two_port.py b/src/mesido/pycml/component_library/qth/qth_two_port.py similarity index 100% rename from src/rtctools_heat_network/pycml/component_library/qth/qth_two_port.py rename to src/mesido/pycml/component_library/qth/qth_two_port.py diff --git a/src/rtctools_heat_network/pycml/component_library/qth/source.py b/src/mesido/pycml/component_library/qth/source.py similarity index 94% rename from src/rtctools_heat_network/pycml/component_library/qth/source.py rename to src/mesido/pycml/component_library/qth/source.py index 1e69907e6..e14ce3ed7 100644 --- a/src/rtctools_heat_network/pycml/component_library/qth/source.py +++ b/src/mesido/pycml/component_library/qth/source.py @@ -1,6 +1,6 @@ -from numpy import nan +from mesido.pycml import SymbolicParameter, Variable -from rtctools_heat_network.pycml import SymbolicParameter, Variable +from numpy import nan from ._fluid_properties_component import _FluidPropertiesComponent from ._non_storage_component import _NonStorageComponent diff --git a/src/rtctools_heat_network/pycml/model_base.py b/src/mesido/pycml/model_base.py similarity index 89% rename from src/rtctools_heat_network/pycml/model_base.py rename to src/mesido/pycml/model_base.py index 3eb988cd9..4d011664f 100644 --- a/src/rtctools_heat_network/pycml/model_base.py +++ b/src/mesido/pycml/model_base.py @@ -225,6 +225,16 @@ def add_initial_equation(self, equation, lb=None, ub=None): self._initial_inequalities.append((equation, lb, ub)) def connect(self, a: "Connector", b: "Connector"): + """ + This function sets equality constraints to the variables of the two (connected) ports. + + Params: + a: port 1 + b: port 2 + + Return: + None + """ if not a.variables.keys() == b.variables.keys(): raise Exception( f"Cannot connect port {a} of type {type(a)} to port {b} " @@ -233,6 +243,35 @@ def connect(self, a: "Connector", b: "Connector"): self._equations.extend([a.variables[k] - b.variables[k] for k in a.variables.keys()]) + def connect_logical_links(self, a: "Connector", b: "Connector"): + """ + This function sets equality constraints to the variables of the two (connected) ports. Note + that this function is used for logical links, meaning that we only use this function for + models where the user defined direct connection between assets without the use of + "transport" assets in between. For that purpose we do not make equality constraints for + head, voltage and hydrualic power as these are inherent for the transport modelling. + + Params: + a: port 1 + b: port 2 + + Return: + None + """ + if not a.variables.keys() == b.variables.keys(): + raise Exception( + f"Cannot connect port {a} of type {type(a)} to port {b} " + f"of type {type(b)} as they have different variables." + ) + + self._equations.extend( + [ + a.variables[k] - b.variables[k] + for k in a.variables.keys() + if (k != "H" and k != "Hydraulic_power" and k != "V") + ] + ) + def der(self, var: Variable): return var.der() diff --git a/src/rtctools_heat_network/pycml/pycml_mixin.py b/src/mesido/pycml/pycml_mixin.py similarity index 59% rename from src/rtctools_heat_network/pycml/pycml_mixin.py rename to src/mesido/pycml/pycml_mixin.py index 647dbe332..1579dbe9f 100644 --- a/src/rtctools_heat_network/pycml/pycml_mixin.py +++ b/src/mesido/pycml/pycml_mixin.py @@ -1,7 +1,9 @@ +import ast +import inspect import itertools import logging from abc import abstractmethod -from typing import Dict, Union +from typing import Dict, List, Type, Union import casadi as ca @@ -15,7 +17,130 @@ from . import ConstantInput, ControlInput, Model, SymbolicParameter, Variable -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") + + +DYNAMIC_NAME_CACHE = {} + + +def add_variables_documentation_automatically(class_: Type): + """ + This function can be added as a decorator to asset classes. It will update the documentation + of that class with the variables that are created in it and the classes from which it inherits, + based on the self.add_variable() function. The string + "{add_variable_names_for_documentation_here}" in the asset documentation is then replaced by + a list of the variable names. + + Note: This decorator must be added to any class which may be referenced by `class_`. + + Note: This function will not work properly if 2 two port classes have the same name due to + the use of `DYNAMIC_NAME_CACHE`. + + Args: + class_: The asset class it is documenting + + Returns: updated documentation of the class. + + """ + + def get_names_for_class(current_class_: Type) -> List[str]: + """ + This function checks for the variables that are added using the add_variable function. + Using the cache the variable names that are created by inheritance and port names, + are tracked to recreate the full variable name. + + It will follow any classes up the inheritance tree and it will follow any Port classes + recursively. The variable name of port classes are added to the variable path while classes + up the inheritance tree only add their variable paths to the set of this class. + + Args: + current_class_: The class which is currently checked + + Returns: List of variable names + + """ + dynamic_names = [] + for class__ in inspect.getmro(current_class_): + if inspect.getmodule(class__).__name__ == "builtins": + break + ast_of_init: ast.Module = ast.parse(inspect.getsource(class__)) + for node in ast.walk(ast_of_init): + # Look for any function calls that fit self.add_variable + if ( + isinstance(node, ast.Call) + and isinstance(node.func, ast.Attribute) + and isinstance(node.func.value, ast.Name) + and node.func.value.id == "self" + and node.func.attr == "add_variable" + ): + # Now extract the first and second argument + # First argument decides if it is a port or variable name + # Second argument is the string name + if isinstance(node.args[0], ast.Name): + port_class_name = node.args[0].id + if port_class_name in [ + "HeatPort", + "ElectricityPort", + "GasPort", + "Primary", + "Secondary", + "_NonStorageComponent", + ]: + # Follow the port and retrieve all variable names for that port + port_name = node.args[1].value + + # We leverage Python's import structure here. If there is a reference + # to a class in another file, that file will already have imported + # the necessary class as well as run this function. + dynamic_names_of_port = DYNAMIC_NAME_CACHE[port_class_name] + for dynamic_name_of_port in dynamic_names_of_port: + dynamic_names.append(f"{port_name}.{dynamic_name_of_port}") + elif node.args[0].id == "Variable": + # This is a variable for this component, save its name. + dynamic_names.append(node.args[1].value) + else: + raise RuntimeError(f"Unknown case:\n{ast.dump(node)}") + else: + raise RuntimeError(f"Unknown case:\n{ast.dump(node)}") + + dynamic_names = sorted(dynamic_names) + if current_class_.__name__ in DYNAMIC_NAME_CACHE: + raise RuntimeError( + f"Unsupported situation. Already generated documentation for " + f"{current_class_.__name__} before. Possibly that 2 classes " + f"(in different modules) have the same class name? This is not " + f"supported by this function." + ) + DYNAMIC_NAME_CACHE[current_class_.__name__] = dynamic_names + return dynamic_names + + all_dynamic_names = get_names_for_class(class_) + + # Format the dynamic names properly + formatted_dynamic_names = [ + f"* {{name}}.{dynamic_name}" for dynamic_name in sorted(all_dynamic_names) + ] + + # Find the indent that should be used + line_with_hook = next( + ( + line + for line in class_.__doc__.splitlines() + if "{" "add_variable_names_for_documentation_here}" in line + ), + None, + ) + if line_with_hook is None: + indent = "" + else: + (indent, _) = line_with_hook.split("{add_variable_names_for_documentation_here}") + + # Insert the dynamic names into the documentation + class_.__doc__ = class_.__doc__.replace( + "{add_variable_names_for_documentation_here}", + f"\n{indent}".join(formatted_dynamic_names), + ) + return class_ class PyCMLMixin(OptimizationProblem): diff --git a/src/rtctools_heat_network/workflows/goals/__init__.py b/src/mesido/qth_not_maintained/__init__.py similarity index 100% rename from src/rtctools_heat_network/workflows/goals/__init__.py rename to src/mesido/qth_not_maintained/__init__.py diff --git a/src/rtctools_heat_network/qth_not_maintained/bounds_to_pipe_flow_directions_mixin.py b/src/mesido/qth_not_maintained/bounds_to_pipe_flow_directions_mixin.py similarity index 94% rename from src/rtctools_heat_network/qth_not_maintained/bounds_to_pipe_flow_directions_mixin.py rename to src/mesido/qth_not_maintained/bounds_to_pipe_flow_directions_mixin.py index b1583c857..cd2538377 100644 --- a/src/rtctools_heat_network/qth_not_maintained/bounds_to_pipe_flow_directions_mixin.py +++ b/src/mesido/qth_not_maintained/bounds_to_pipe_flow_directions_mixin.py @@ -1,12 +1,12 @@ from typing import Dict +from mesido.base_component_type_mixin import BaseComponentTypeMixin +from mesido.heat_network_common import PipeFlowDirection + import numpy as np from rtctools.optimization.timeseries import Timeseries -from rtctools_heat_network.base_component_type_mixin import BaseComponentTypeMixin -from rtctools_heat_network.heat_network_common import PipeFlowDirection - class BoundsToPipeFlowDirectionsMixin(BaseComponentTypeMixin): """ diff --git a/src/rtctools_heat_network/qth_not_maintained/head_loss_mixin.py b/src/mesido/qth_not_maintained/head_loss_mixin.py similarity index 99% rename from src/rtctools_heat_network/qth_not_maintained/head_loss_mixin.py rename to src/mesido/qth_not_maintained/head_loss_mixin.py index d492cc625..3feb4d33e 100644 --- a/src/rtctools_heat_network/qth_not_maintained/head_loss_mixin.py +++ b/src/mesido/qth_not_maintained/head_loss_mixin.py @@ -5,20 +5,20 @@ import casadi as ca +import mesido._darcy_weisbach as darcy_weisbach +from mesido.base_component_type_mixin import BaseComponentTypeMixin + import numpy as np from rtctools._internal.alias_tools import AliasDict from rtctools.optimization.goal_programming_mixin_base import Goal, _GoalProgrammingMixinBase from rtctools.optimization.optimization_problem import BT, OptimizationProblem -import rtctools_heat_network._darcy_weisbach as darcy_weisbach -from rtctools_heat_network.base_component_type_mixin import BaseComponentTypeMixin - from ..constants import GRAVITATIONAL_CONSTANT from ..pipe_class import PipeClass -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") class HeadLossOption(IntEnum): diff --git a/src/rtctools_heat_network/qth_not_maintained/qth_loop_mixin.py b/src/mesido/qth_not_maintained/qth_loop_mixin.py similarity index 99% rename from src/rtctools_heat_network/qth_not_maintained/qth_loop_mixin.py rename to src/mesido/qth_not_maintained/qth_loop_mixin.py index df7d60ea0..f59a8d40f 100644 --- a/src/rtctools_heat_network/qth_not_maintained/qth_loop_mixin.py +++ b/src/mesido/qth_not_maintained/qth_loop_mixin.py @@ -2,14 +2,14 @@ import casadi as ca +from mesido.qth_not_maintained.qth_mixin import HeadLossOption, QTHMixin + import numpy as np from rtctools._internal.alias_tools import AliasDict from rtctools.optimization.goal_programming_mixin_base import Goal from rtctools.optimization.timeseries import Timeseries -from rtctools_heat_network.qth_not_maintained.qth_mixin import HeadLossOption, QTHMixin - class BufferTargetDischargeGoal(Goal): def __init__( diff --git a/src/rtctools_heat_network/qth_not_maintained/qth_mixin.py b/src/mesido/qth_not_maintained/qth_mixin.py similarity index 99% rename from src/rtctools_heat_network/qth_not_maintained/qth_mixin.py rename to src/mesido/qth_not_maintained/qth_mixin.py index a3869647b..8f3063fed 100644 --- a/src/rtctools_heat_network/qth_not_maintained/qth_mixin.py +++ b/src/mesido/qth_not_maintained/qth_mixin.py @@ -5,30 +5,30 @@ import casadi as ca -import numpy as np - -from rtctools.optimization.collocated_integrated_optimization_problem import ( - CollocatedIntegratedOptimizationProblem, -) -from rtctools.optimization.homotopy_mixin import HomotopyMixin -from rtctools.optimization.timeseries import Timeseries - -from rtctools_heat_network._heat_loss_u_values_pipe import heat_loss_u_values_pipe -from rtctools_heat_network.base_component_type_mixin import BaseComponentTypeMixin -from rtctools_heat_network.heat_network_common import ( +from mesido._heat_loss_u_values_pipe import heat_loss_u_values_pipe +from mesido.base_component_type_mixin import BaseComponentTypeMixin +from mesido.heat_network_common import ( CheckValveStatus, ControlValveDirection, NodeConnectionDirection, PipeFlowDirection, ) -from rtctools_heat_network.qth_not_maintained.head_loss_mixin import ( +from mesido.qth_not_maintained.head_loss_mixin import ( HeadLossOption, _HeadLossMixin, _MinimizeHeadLosses as _MinimizeHeadLossesBase, _MinimizeHydraulicPower as _MinimizeHydraulicPowerBase, ) -logger = logging.getLogger("rtctools_heat_network") +import numpy as np + +from rtctools.optimization.collocated_integrated_optimization_problem import ( + CollocatedIntegratedOptimizationProblem, +) +from rtctools.optimization.homotopy_mixin import HomotopyMixin +from rtctools.optimization.timeseries import Timeseries + +logger = logging.getLogger("mesido") class _MinimizeHeadLosses(_MinimizeHeadLossesBase): diff --git a/src/rtctools_heat_network/qth_not_maintained/util.py b/src/mesido/qth_not_maintained/util.py similarity index 98% rename from src/rtctools_heat_network/qth_not_maintained/util.py rename to src/mesido/qth_not_maintained/util.py index fd42bcdd9..8f8edba68 100644 --- a/src/rtctools_heat_network/qth_not_maintained/util.py +++ b/src/mesido/qth_not_maintained/util.py @@ -15,7 +15,7 @@ def run_heat_network_optimization(heat_class, qht_class, *args, log_level=loggin given that the milp milp optimization is reasonably close and conservative it can guarantee feasibility. """ - logger = logging.getLogger("rtctools_heat_network") + logger = logging.getLogger("mesido") logger.setLevel(log_level) logger.info(f"Using RTC-Tools Heat Network {__version__}.") diff --git a/src/rtctools_heat_network/techno_economic_mixin.py b/src/mesido/techno_economic_mixin.py similarity index 93% rename from src/rtctools_heat_network/techno_economic_mixin.py rename to src/mesido/techno_economic_mixin.py index 22e090864..1a29cf093 100644 --- a/src/rtctools_heat_network/techno_economic_mixin.py +++ b/src/mesido/techno_economic_mixin.py @@ -1,15 +1,15 @@ import logging +from mesido.asset_sizing_mixin import AssetSizingMixin +from mesido.base_component_type_mixin import BaseComponentTypeMixin +from mesido.financial_mixin import FinancialMixin +from mesido.physics_mixin import PhysicsMixin + from rtctools.optimization.collocated_integrated_optimization_problem import ( CollocatedIntegratedOptimizationProblem, ) -from .asset_sizing_mixin import AssetSizingMixin -from .base_component_type_mixin import BaseComponentTypeMixin -from .financial_mixin import FinancialMixin -from .physics_mixin import PhysicsMixin - -logger = logging.getLogger("rtctools_heat_network") +logger = logging.getLogger("mesido") class TechnoEconomicMixin( @@ -54,7 +54,7 @@ def get_aggregation_count_max(self, asset_name): return self.bounds()[self._asset_aggregation_count_var_map[asset_name]][1] def get_pipe_class_map(self): - return self._pipe_topo_pipe_class_map + return self._heat_pipe_topo_pipe_class_map def get_gas_pipe_class_map(self): return self._gas_pipe_topo_pipe_class_map @@ -63,7 +63,7 @@ def get_electricity_cable_class_map(self): return self._electricity_cable_topo_cable_class_map def get_pipe_investment_cost_coefficient(self, asset_name, ensemble_member): - return self.extra_variable(self._pipe_topo_cost_map[asset_name], ensemble_member) + return self.extra_variable(self._heat_pipe_topo_cost_map[asset_name], ensemble_member) def get_electricity_carriers(self): return self.electricity_carriers() diff --git a/src/rtctools_heat_network/topology.py b/src/mesido/topology.py similarity index 72% rename from src/rtctools_heat_network/topology.py rename to src/mesido/topology.py index e6751a216..2b6fecb3a 100644 --- a/src/rtctools_heat_network/topology.py +++ b/src/mesido/topology.py @@ -1,11 +1,19 @@ from typing import Dict, List, Tuple -from .heat_network_common import NodeConnectionDirection +from mesido.heat_network_common import NodeConnectionDirection class Topology: def __init__( - self, nodes=None, gas_nodes=None, pipe_series=None, buffers=None, atess=None, busses=None + self, + nodes=None, + gas_nodes=None, + pipe_series=None, + buffers=None, + atess=None, + busses=None, + demands=None, + sources=None, ): if nodes is not None: self._nodes = nodes @@ -19,6 +27,10 @@ def __init__( self._busses = busses if atess is not None: self._atess = atess + if demands is not None: + self._demands = demands + if sources is not None: + self._sources = sources @property def nodes(self) -> Dict[str, Dict[int, Tuple[str, NodeConnectionDirection]]]: @@ -97,3 +109,31 @@ def ates( return self._atess except AttributeError: raise NotImplementedError + + @property + def demands( + self, + ) -> Dict[str, Tuple[str, NodeConnectionDirection]]: + """ + Maps an demand name to a dictionary of its in/out connections. Written out using + descriptive variable names the return type would be: + Dict[demand_name, Tuple[pipe/cable, orientation] + """ + try: + return self._demands + except AttributeError: + raise NotImplementedError + + @property + def sources( + self, + ) -> Dict[str, Tuple[str, NodeConnectionDirection]]: + """ + Maps a source name to a dictionary of its in/out connections. Written out using + descriptive variable names the return type would be: + Dict[source_name, Tuple[pipe/cable, orientation] + """ + try: + return self._sources + except AttributeError: + raise NotImplementedError diff --git a/src/mesido/util.py b/src/mesido/util.py new file mode 100644 index 000000000..c88d3ef43 --- /dev/null +++ b/src/mesido/util.py @@ -0,0 +1,57 @@ +from mesido.esdl.esdl_parser import BaseESDLParser +from mesido.esdl.profile_parser import BaseProfileReader, InfluxDBProfileReader + +from rtctools.optimization.collocated_integrated_optimization_problem import ( + CollocatedIntegratedOptimizationProblem, +) +from rtctools.util import run_optimization_problem + + +def run_esdl_mesido_optimization( + problem: CollocatedIntegratedOptimizationProblem, + esdl_parser: BaseESDLParser, + esdl_file_name: str = "", + base_folder: str = "", + esdl_string: str = "", + profile_reader: BaseProfileReader = InfluxDBProfileReader, + input_timeseries_file: str = "", + *args, + **kwargs, +): + """ + This function is used to execute an optimization on a MESIDO defined problem. Compared to the + standard rtc-tools run_optimization_problem() method extra checks can be included here. + + params: + Problem: The problem defined in the mesido + esdl_parser: How the ESDL will be provided to the problem, e.g. file or base64 string. + base_folder: The base folder from where the input, model, output folder are defined + esdl_file_name: The string of the esdl file in case the ESDLFileParser is used and placed in + the model folder. + esdl_string: the base64 string in case the ESDLStringParser is selected + profile_reader: The way the time-series profiles are read + input_timeseries_file: The file from which to read the time-series profiles in case the + FromFileReader is selected. + + Returns: + The solved full problem object with the solution in it. + + """ + + solution = run_optimization_problem( + problem, + *args, + base_folder=base_folder, + esdl_file_name=esdl_file_name, + esdl_string=esdl_string, + esdl_parser=esdl_parser, + profile_reader=profile_reader, + input_timeseries_file=input_timeseries_file, + **kwargs, + ) + + feasibility = solution.solver_stats["return_status"] + + assert feasibility.lower() in ["optimal", "finished", "integer optimal solution"] + + return solution diff --git a/src/rtctools_heat_network/workflows/__init__.py b/src/mesido/workflows/__init__.py similarity index 64% rename from src/rtctools_heat_network/workflows/__init__.py rename to src/mesido/workflows/__init__.py index 587b188db..1126a6ac1 100644 --- a/src/rtctools_heat_network/workflows/__init__.py +++ b/src/mesido/workflows/__init__.py @@ -1,9 +1,12 @@ from .grow_workflow import ( EndScenarioSizing, - EndScenarioSizingDiscountedHIGHS, + EndScenarioSizingDiscounted, + EndScenarioSizingDiscountedStaged, EndScenarioSizingHIGHS, + EndScenarioSizingHeadLossDiscounted, + EndScenarioSizingHeadLossDiscountedStaged, + EndScenarioSizingHeadLossStaged, EndScenarioSizingStaged, - EndScenarioSizingStagedHIGHS, SolverGurobi, SolverHIGHS, run_end_scenario_sizing, @@ -19,10 +22,13 @@ __all__ = [ "EndScenarioSizing", - "EndScenarioSizingDiscountedHIGHS", + "EndScenarioSizingDiscounted", + "EndScenarioSizingDiscountedStaged", "EndScenarioSizingHIGHS", + "EndScenarioSizingHeadLossDiscounted", + "EndScenarioSizingHeadLossDiscountedStaged", + "EndScenarioSizingHeadLossStaged", "EndScenarioSizingStaged", - "EndScenarioSizingStagedHIGHS", "SolverGurobi", "SolverHIGHS", "run_end_scenario_sizing", diff --git a/src/mesido/workflows/emerge.py b/src/mesido/workflows/emerge.py new file mode 100644 index 000000000..84862b9a2 --- /dev/null +++ b/src/mesido/workflows/emerge.py @@ -0,0 +1,253 @@ +import os +import time + +import casadi as ca + +from mesido.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.io.write_output import ScenarioOutput + +from rtctools.optimization.collocated_integrated_optimization_problem import ( + CollocatedIntegratedOptimizationProblem, +) +from rtctools.optimization.goal_programming_mixin_base import Goal +from rtctools.optimization.linearized_order_goal_programming_mixin import ( + LinearizedOrderGoalProgrammingMixin, +) +from rtctools.optimization.single_pass_goal_programming_mixin import SinglePassGoalProgrammingMixin +from rtctools.util import run_optimization_problem + + +class MaxRevenue(Goal): + + priority = 1 + + order = 1 + + def __init__(self, asset_name: str): + """ + The constructor of the goal. + + Parameters + ---------- + source : string of the source name that is going to be minimized + """ + + self.asset_name = asset_name + + def function( + self, optimization_problem: CollocatedIntegratedOptimizationProblem, ensemble_member: int + ) -> ca.MX: + """ + This function returns the state variable to be minimized. + + Parameters + ---------- + optimization_problem : The optimization class containing the variables'. + ensemble_member : the ensemble member. + + Returns + ------- + The negative revenue var of the optimization problem. + """ + return -optimization_problem.extra_variable(f"{self.asset_name}__revenue", ensemble_member) + + +class MinCost(Goal): + + priority = 1 + + order = 1 + + def __init__(self, asset_name: str): + # self.target_max = 0.0 + # self.function_range = (0.0, 1.0e9) + # self.function_nominal = 1.0e7 + + self.asset_name = asset_name + + def function( + self, optimization_problem: CollocatedIntegratedOptimizationProblem, ensemble_member: int + ) -> ca.MX: + + return optimization_problem.extra_variable( + f"{self.asset_name}__fixed_operational_cost", ensemble_member + ) + optimization_problem.extra_variable( + f"{self.asset_name}__variable_operational_cost", ensemble_member + ) + + +class EmergeWorkFlow( + ScenarioOutput, + ESDLAdditionalVarsMixin, + TechnoEconomicMixin, + LinearizedOrderGoalProgrammingMixin, + SinglePassGoalProgrammingMixin, + ESDLMixin, + CollocatedIntegratedOptimizationProblem, +): + """ + This problem class is for the absolute heat tests. Meaning that this problem class + is applied to an esdl where there is no dedicated supply or return line. For this test case + we just match heating demand (_GoalsAndOptions) and minimize the energy production to have a + representative result. + """ + + # TODO: this workflow is still work in progress and this part of code still needs to be + # finalised + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + self.gas_network_settings["head_loss_option"] = HeadLossOption.NO_HEADLOSS + + def goals(self): + + goals = super().goals().copy() + + for asset_name in [ + *self.energy_system_components.get("electricity_demand", []), + *self.energy_system_components.get("gas_demand", []), + ]: + goals.append(MaxRevenue(asset_name)) + goals.append(MinCost(asset_name)) + + for asset_name in [ + *self.energy_system_components.get("electricity_source", []), + *self.energy_system_components.get("gas_tank_storage", []), + *self.energy_system_components.get("electricity_storage", []), + *self.energy_system_components.get("electrolyzer", []), + *self.energy_system_components.get("heat_pump_elec", []), + ]: + goals.append(MinCost(asset_name)) + + return goals + + def constraints(self, ensemble_member): + constraints = super().constraints(ensemble_member) + + for gs in self.energy_system_components.get("gas_tank_storage", []): + canonical, sign = self.alias_relation.canonical_signed(f"{gs}.Stored_gas_mass") + storage_t0 = sign * self.state_vector(canonical, ensemble_member)[0] + constraints.append((storage_t0, 0.0, 0.0)) + canonical, sign = self.alias_relation.canonical_signed(f"{gs}.Gas_tank_flow") + gas_flow_t0 = sign * self.state_vector(canonical, ensemble_member)[0] + constraints.append((gas_flow_t0, 0.0, 0.0)) + + for es in self.energy_system_components.get("electricity_storage", []): + canonical, sign = self.alias_relation.canonical_signed(f"{es}.Stored_electricity") + storage_t0 = sign * self.state_vector(canonical, ensemble_member)[0] + constraints.append((storage_t0, 0.0, 0.0)) + + return constraints + + def solver_options(self): + """ + This function does not add anything at the moment but during debugging we use this. + + Returns + ------- + solver options dict + """ + options = super().solver_options() + options["solver"] = "highs" + highs_options = options["highs"] = {} + highs_options["presolve"] = "off" + + return options + + def times(self, variable=None): + return super().times(variable)[:25] + + def energy_system_options(self): + """ + This function does not add anything at the moment but during debugging we use this. + + Returns + ------- + Options dict for the physics modelling + """ + options = super().energy_system_options() + options["minimum_velocity"] = 0.0 + options["heat_loss_disconnected_pipe"] = False + options["neglect_pipe_heat_losses"] = False + options["include_asset_is_switched_on"] = True + options["include_electric_cable_power_loss"] = False + return options + + def post(self): + # In case the solver fails, we do not get in priority_completed(). We + # append this last priority's statistics here in post(). + # TODO: check if we still need this small part of code below + success, _ = self.solver_success(self.solver_stats, False) + # if not success: + # time_taken = time.time() - self.__priority_timer + # self._priorities_output.append( + # ( + # self.__priority, + # time_taken, + # False, + # self.objective_value, + # self.solver_stats, + # ) + # ) + + super().post() + + # Optimized ESDL + self._write_updated_esdl( + self._ESDLMixin__energy_system_handler.energy_system, add_kpis=False + ) + + self._save_json = False + + results = self.extract_results() + + if os.path.exists(self.output_folder) and self._save_json: + parameters = self.parameters(0) + bounds = self.bounds() + aliases = self.alias_relation._canonical_variables_map + solver_stats = self.solver_stats + self._write_json_output(results, parameters, bounds, aliases, solver_stats) + + for _type, assets in self.energy_system_components.items(): + for asset in assets: + print("----------------------------------") + print(f"{asset} financials:") + try: + print(f"revenue of {asset} in MEUR/day: ", results[f"{asset}__revenue"] / 1e6) + except KeyError: + print(f"{asset} does not have a revenue") + pass + try: + print( + f"fixed operational costs of {asset} in MEUR/yr : ", + results[f"{asset}__fixed_operational_cost"] / 1e6, + ) + print( + f"variable operational costs of {asset} : ", + results[f"{asset}__variable_operational_cost"] / 1e6, + ) # not yet all included in financialmixin + print(f"max size of {asset} : ", results[f"{asset}__max_size"]) + except KeyError: + print(f"{asset} does not have a costs") + pass + + +if __name__ == "__main__": + + tic = time.time() + elect = run_optimization_problem( + EmergeWorkFlow, + esdl_file_name="emerge_solar_battery.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_with_PV.csv", + ) + print(time.time() - tic) + results = elect.extract_results() + a = 1 diff --git a/src/mesido/workflows/gas_elect_workflow.py b/src/mesido/workflows/gas_elect_workflow.py new file mode 100644 index 000000000..6d204b201 --- /dev/null +++ b/src/mesido/workflows/gas_elect_workflow.py @@ -0,0 +1,208 @@ +import logging +import os + +from mesido.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.head_loss_class import HeadLossOption +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.goals.minimize_tco_goal import MinimizeTCO +from mesido.workflows.io.write_output import ScenarioOutput +from mesido.workflows.utils.helpers import main_decorator + +import numpy as np + +from rtctools.optimization.collocated_integrated_optimization_problem import ( + CollocatedIntegratedOptimizationProblem, +) +from rtctools.optimization.goal_programming_mixin import Goal +from rtctools.optimization.linearized_order_goal_programming_mixin import ( + LinearizedOrderGoalProgrammingMixin, +) +from rtctools.optimization.single_pass_goal_programming_mixin import ( + CachingQPSol, + SinglePassGoalProgrammingMixin, +) +from rtctools.util import run_optimization_problem + +logger = logging.getLogger("WarmingUP-MPC") +logger.setLevel(logging.INFO) + + +class TargetHeatGoal(Goal): + priority = 1 + + order = 2 + + def __init__(self, state, target): + self.state = state + + self.target_min = target + self.target_max = target + try: + self.function_range = (-1.0e6, max(2.0 * max(target.values), 1.0e6)) + self.function_nominal = max(np.median(target.values), 1.0e6) + except Exception: + self.function_range = (-1.0e6, max(2.0 * target, 1.0e6)) + self.function_nominal = max(target, 1.0e6) + + def function(self, optimization_problem, ensemble_member): + return optimization_problem.state(self.state) + + +class SolverCPLEX: + def solver_options(self): + options = super().solver_options() + options["casadi_solver"] = self._qpsol + options["solver"] = "cplex" + cplex_options = options["cplex"] = {} + cplex_options["CPX_PARAM_EPGAP"] = 0.00001 + + options["highs"] = None + + return options + + +class GasElectProblem( + ScenarioOutput, + ESDLAdditionalVarsMixin, + TechnoEconomicMixin, + LinearizedOrderGoalProgrammingMixin, + SinglePassGoalProgrammingMixin, + ESDLMixin, + CollocatedIntegratedOptimizationProblem, +): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + self._number_of_years = 1.0 + + self._save_json = True + + def energy_system_options(self): + options = super().energy_system_options() + options["neglect_pipe_heat_losses"] = True + options["include_electric_cable_power_loss"] = False + # TODO: determine why no heat pump (case with heat pumps & boilers) is used when pwer + # losses are included + # options["include_electric_cable_power_loss"] = True + + # Setting when started with head loss inclusions + self.gas_network_settings["minimum_velocity"] = 0.0 + self.gas_network_settings["maximum_velocity"] = 15.0 + + # TODO: resolve scaling and potential other issues preventing HIGHS to optimize the system + # when LINEARIZED_N_LINES_EQUALITY head loss setting is used + # self.gas_network_settings["n_linearization_lines"] = 3 + # self.gas_network_settings["minimize_head_losses"] = False + # self.gas_network_settings["head_loss_option"] = HeadLossOption.LINEARIZED_N_LINES_EQUALITY + + self.gas_network_settings["minimize_head_losses"] = True + self.gas_network_settings["head_loss_option"] = HeadLossOption.LINEARIZED_ONE_LINE_EQUALITY + + return options + + def solver_options(self): + options = super().solver_options() + options["casadi_solver"] = self._qpsol + options["solver"] = "highs" + highs_options = options["highs"] = {} + highs_options["mip_abs_gap"] = 1.0e-6 + + return options + + def read(self): + super().read() + + # Convert gas demand Nm3/h (data in timeseries source file) to heat demand in watts + # Assumumption: + # - gas heating value (LCV value) = 31.68 * 10^6 (J/m3) at 1bar, 273.15K + # - gas boiler efficiency 80% + # TODO: setup a standard way for gas usage and automate the link to heating value & boiler + # efficiency (if needed) + for demand in self.energy_system_components["heat_demand"]: + target = self.get_timeseries(f"{demand}.target_heat_demand") + + # Manually set heating demand values + boiler_efficiency = 0.8 + gas_heating_value_joule_m3 = 31.68 * 10**6 + for ii in range(len(target.values)): + target.values[ii] *= gas_heating_value_joule_m3 * boiler_efficiency + + self.io.set_timeseries( + f"{demand}.target_heat_demand", + self.io._DataStore__timeseries_datetimes, + target.values, + 0, + ) + + def pre(self): + super().pre() + + # variables for solver settings + self._qpsol = CachingQPSol() + + def parameters(self, ensemble_member): + parameters = super().parameters(ensemble_member) + parameters["number_of_years"] = self._number_of_years + return parameters + + def path_goals(self): + goals = super().path_goals().copy() + bounds = self.bounds() + + for demand in self.energy_system_components["heat_demand"]: + target = self.get_timeseries(f"{demand}.target_heat_demand") + if bounds[f"{demand}.HeatIn.Heat"][1] < max(target.values): + logger.warning( + f"{demand} has a flow limit, {bounds[f'{demand}.HeatIn.Heat'][1]}, " + f"lower that wat is required for the maximum demand {max(target.values)}" + ) + # TODO: update this caclulation to bounds[f"{demand}.HeatIn.Heat"][1]/ dT * Tsup & move + # to potential_errors variable + state = f"{demand}.Heat_demand" + + goals.append(TargetHeatGoal(state, target)) + + return goals + + def goals(self): + goals = super().goals().copy() + goals.append(MinimizeTCO(priority=2, number_of_years=self._number_of_years)) + + return goals + + # Do not delete. Temporary code to deactivate the heat pumps. Use for manual test/checking + # def path_constraints(self, ensemble_member): + # constraints = super().path_constraints(ensemble_member) + + # for eb in self.energy_system_components.get("air_water_heat_pump_elec", []): + # power_consumed = self.state(f"{eb}.Power_consumed") + # constraints.append((power_consumed, 0.0, 0.0)) + + # return constraints + + def post(self): + if os.path.exists(self.output_folder) and self._save_json: + self._write_json_output() + + +@main_decorator +def main(runinfo_path, log_level): + logger.info("Gas and electricity workflow") + + kwargs = { + "write_result_db_profiles": False, + "influxdb_host": "localhost", + "influxdb_port": 8086, + "influxdb_username": None, + "influxdb_password": None, + "influxdb_ssl": False, + "influxdb_verify_ssl": False, + } + + _ = run_optimization_problem( + GasElectProblem, + esdl_run_info_path=runinfo_path, + log_level=log_level, + **kwargs, + ) diff --git a/src/rtctools_heat_network/workflows/io/__init__.py b/src/mesido/workflows/goals/__init__.py similarity index 100% rename from src/rtctools_heat_network/workflows/io/__init__.py rename to src/mesido/workflows/goals/__init__.py diff --git a/src/rtctools_heat_network/workflows/goals/minimize_tco_goal.py b/src/mesido/workflows/goals/minimize_tco_goal.py similarity index 94% rename from src/rtctools_heat_network/workflows/goals/minimize_tco_goal.py rename to src/mesido/workflows/goals/minimize_tco_goal.py index f08944fbd..53eff5123 100644 --- a/src/rtctools_heat_network/workflows/goals/minimize_tco_goal.py +++ b/src/mesido/workflows/goals/minimize_tco_goal.py @@ -2,9 +2,9 @@ from casadi import MX -from rtctools.optimization.goal_programming_mixin_base import Goal +from mesido.techno_economic_mixin import TechnoEconomicMixin -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin +from rtctools.optimization.goal_programming_mixin_base import Goal class MinimizeTCO(Goal): @@ -43,6 +43,8 @@ def __init__( "pump", "heat_exchanger", "heat_buffer", + "gas_source", # TODO still to add other costs for this asset_type + "electricity_source", # TODO still to add other costs for this asset_type }, "fixed_operational": { "heat_source", @@ -50,7 +52,6 @@ def __init__( "heat_buffer", "heat_pump", "heat_exchanger", - "heat_exchanger_elec", "pump", }, "investment": { @@ -61,7 +62,6 @@ def __init__( "heat_exchanger", "heat_pump", "heat_pipe", - "heat_exchanger_elec", "pump", }, "installation": { @@ -72,7 +72,6 @@ def __init__( "heat_exchanger", "heat_pump", "heat_pipe", - "heat_exchanger_elec", "pump", }, "annualized": { @@ -83,9 +82,8 @@ def __init__( "heat_exchanger", "heat_pump", "heat_pipe", - "heat_exchanger_elec", "pump", - }, # TODO: confirm inclusion of "heat_exchanger_elec" & "pump" in "annualized" + }, } self.asset_type_maps = ( diff --git a/src/rtctools_heat_network/workflows/grow_workflow.py b/src/mesido/workflows/grow_workflow.py similarity index 66% rename from src/rtctools_heat_network/workflows/grow_workflow.py rename to src/mesido/workflows/grow_workflow.py index 8f5e04f88..f376c4d61 100644 --- a/src/rtctools_heat_network/workflows/grow_workflow.py +++ b/src/mesido/workflows/grow_workflow.py @@ -1,7 +1,22 @@ import locale import logging import os +import sys import time +from typing import Dict + +from mesido.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.head_loss_class import HeadLossOption +from mesido.potential_errors import reset_potential_errors +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.goals.minimize_tco_goal import MinimizeTCO +from mesido.workflows.io.write_output import ScenarioOutput +from mesido.workflows.utils.adapt_profiles import ( + adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day, +) +from mesido.workflows.utils.error_types import HEAT_NETWORK_ERRORS, potential_error_to_error +from mesido.workflows.utils.helpers import main_decorator, run_optimization_problem_solver import numpy as np @@ -17,18 +32,6 @@ CachingQPSol, SinglePassGoalProgrammingMixin, ) -from rtctools.util import run_optimization_problem - -from rtctools_heat_network.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.head_loss_class import HeadLossOption -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin -from rtctools_heat_network.workflows.goals.minimize_tco_goal import MinimizeTCO -from rtctools_heat_network.workflows.io.write_output import ScenarioOutput -from rtctools_heat_network.workflows.utils.adapt_profiles import ( - adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day, -) -from rtctools_heat_network.workflows.utils.helpers import main_decorator DB_HOST = "172.17.0.2" @@ -69,21 +72,85 @@ def function(self, optimization_problem, ensemble_member): return optimization_problem.state(self.state) +def _mip_gap_settings(mip_gap_name: str, problem) -> Dict[str, float]: + """Creating the same MIP gap settings for all solvers.""" + + options = {} + if hasattr(problem, "_stage"): + if problem._stage == 1: + options[mip_gap_name] = 0.005 + else: + options[mip_gap_name] = 0.02 + else: + options[mip_gap_name] = 0.02 + + return options + + +def estimate_and_update_progress_status(self, priority): + """Estimate the progress of the optimization workflow. Currently the tasks completed in this + workflow is used to estimate the progress (ratio between 0 and 1). The task completed ratio is + the number of tasks completed divided by the total number of tasks. The total number of tasks + is estimated based on the stage number and the priority of the task. The progress is then + passed to the workflow progress status function (OMOTES back end).""" + # TODO: the estimates below needs to be improved in the future instead of using task numbers + + if self._workflow_progress_status is None: + logger.error("The workflow progress status function is not set. Cannot estimate progress.") + exit(1) + + if self._total_stages == 1: + denominator = 2.0 + if priority == 1: # match heat demand + numerator = 1.0 + elif priority == 2: # minimize TCO + numerator = 2.0 + else: + sys.exit( + f"The function does not cater for stage number:{self._stage} & priority:{priority}" + ) + elif self._total_stages == 2: + denominator = 4.0 + 2.0 * self.heat_network_settings["minimize_head_losses"] + if priority == 1 and self._stage == 1: # match heat demand + numerator = 1.0 + elif priority == 2 and self._stage == 1: # minimize TCO + numerator = 2.0 + elif priority == 1 and self._stage == 2: # match heat demand + numerator = 3.0 + elif priority == 2 and self._stage == 2: # minimize TCO + numerator = 4.0 + elif priority == (2**31 - 2) and self._stage == 2: # head loss optimization + numerator = 5.0 + elif priority == (2**31 - 1) and self._stage == 2: # hydraulic power optimization + numerator = 6.0 + else: + sys.exit( + f"The function does not cater for stage number:{self._stage} & priority:{priority}" + ) + else: + sys.exit( + f"The stage number: {self._stage} is higher then the total stages" + f" expected: {self._total_stages}. Assuming the stage numbering starts at 1." + ) + + # This kwarg only exists when the code is used in OMOTES backend + task_quantity_perc_completed = numerator / denominator + self._workflow_progress_status( + task_quantity_perc_completed, + f"Optimization task {numerator} out of {denominator} has completed", + ) # In the future this ratio might differ from the step being completed + + class SolverHIGHS: def solver_options(self): options = super().solver_options() options["casadi_solver"] = self._qpsol options["solver"] = "highs" highs_options = options["highs"] = {} - if hasattr(self, "_stage"): - if self._stage == 1: - highs_options["mip_rel_gap"] = 0.005 - else: - highs_options["mip_rel_gap"] = 0.02 - else: - highs_options["mip_rel_gap"] = 0.02 + highs_options.update(_mip_gap_settings("mip_rel_gap", self)) options["gurobi"] = None + options["cplex"] = None return options @@ -94,12 +161,7 @@ def solver_options(self): options["casadi_solver"] = self._qpsol options["solver"] = "gurobi" gurobi_options = options["gurobi"] = {} - if hasattr(self, "_stage"): - if self._stage == 1: - gurobi_options["MIPgap"] = 0.005 - else: - gurobi_options["MIPgap"] = 0.02 - gurobi_options["MIPgap"] = 0.02 + gurobi_options.update(_mip_gap_settings("MIPgap", self)) gurobi_options["threads"] = 4 gurobi_options["LPWarmStart"] = 2 @@ -108,6 +170,19 @@ def solver_options(self): return options +class SolverCPLEX: + def solver_options(self): + options = super().solver_options() + options["casadi_solver"] = self._qpsol + options["solver"] = "cplex" + cplex_options = options["cplex"] = {} + cplex_options.update(_mip_gap_settings("CPX_PARAM_EPGAP", self)) + + options["highs"] = None + + return options + + class EndScenarioSizing( SolverHIGHS, ScenarioOutput, @@ -129,9 +204,13 @@ class EndScenarioSizing( """ def __init__(self, *args, **kwargs): + reset_potential_errors() # This needed to clear the Singleton which is persistent + super().__init__(*args, **kwargs) - self.heat_network_settings["minimum_velocity"] = 0.0 # 0.001 + # default setting to cater for ~ 10kW heat, DN800 pipe at dT = 40 degrees Celcuis + self.heat_network_settings["minimum_velocity"] = 1.0e-4 + self.heat_network_settings["maximum_velocity"] = 3.0 self.heat_network_settings["head_loss_option"] = HeadLossOption.NO_HEADLOSS @@ -159,6 +238,8 @@ def __init__(self, *args, **kwargs): self._save_json = False + self._workflow_progress_status = kwargs.get("update_progress_function", None) + def parameters(self, ensemble_member): parameters = super().parameters(ensemble_member) parameters["peak_day_index"] = self.__indx_max_peak @@ -178,9 +259,12 @@ def read(self): """ super().read() + potential_error_to_error(HEAT_NETWORK_ERRORS) + ( self.__indx_max_peak, self.__heat_demand_nominal, + _, ) = adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day(self, self.__day_steps) logger.info("HeatProblem read") @@ -202,7 +286,6 @@ def energy_system_options(self): options = super().energy_system_options() options["maximum_temperature_der"] = np.inf options["heat_loss_disconnected_pipe"] = True - # options.update(self._override_hn_options) return options def path_goals(self): @@ -210,13 +293,14 @@ def path_goals(self): bounds = self.bounds() for demand in self.energy_system_components["heat_demand"]: - # target = self.get_timeseries(f"{demand}.target_heat_demand_peak") target = self.get_timeseries(f"{demand}.target_heat_demand") if bounds[f"{demand}.HeatIn.Heat"][1] < max(target.values): logger.warning( f"{demand} has a flow limit, {bounds[f'{demand}.HeatIn.Heat'][1]}, " f"lower that wat is required for the maximum demand {max(target.values)}" ) + # TODO: update this caclulation to bounds[f"{demand}.HeatIn.Heat"][1]/ dT * Tsup & move + # to potential_errors variable state = f"{demand}.Heat_demand" goals.append(TargetHeatGoal(state, target)) @@ -266,6 +350,16 @@ def __state_vector_scaled(self, variable, ensemble_member): self.state_vector(canonical, ensemble_member) * self.variable_nominal(canonical) * sign ) + def solver_options(self): + options = super().solver_options() + if options["solver"] == "highs": + highs_options = options["highs"] + if self.__priority == 1: + highs_options["time_limit"] = 600 + else: + highs_options["time_limit"] = 100000 + return options + def solver_success(self, solver_stats, log_solver_failure_as_error): success, log_level = super().solver_success(solver_stats, log_solver_failure_as_error) @@ -309,6 +403,11 @@ def priority_completed(self, priority): self.solver_stats, ) ) + if priority == 1 and self.objective_value > 1e-6: + raise RuntimeError("The heating demand is not matched") + + if self._workflow_progress_status is not None: + estimate_and_update_progress_status(self, priority) def post(self): # In case the solver fails, we do not get in priority_completed(). We @@ -332,7 +431,32 @@ def post(self): parameters = self.parameters(0) # bounds = self.bounds() # Optimized ESDL - self._write_updated_esdl(self.get_energy_system_copy()) + # Assume there are either no stages (write updated ESDL) or a maximum of 2 stages + # (only write final results when the stage number is the final stage) + # TODO: once database testing has been added, check that the results have only been written + # once. + try: + if self._stage == 0: + logger.error( + f"The stage number is: {self._stage} and it is excpected that the" + " stage numbering starts at 1 instead" + ) + sys.exit(1) + if self._total_stages == self._stage: # When staging does exists + self._write_updated_esdl(self._ESDLMixin__energy_system_handler.energy_system) + elif self._total_stages < self._stage: + logger.error( + f"The stage number: {self._stage} is higher then the total stages" + " expected: {self._total_stages}. Assuming the stage numbering starts at 1" + ) + sys.exit(1) + + except AttributeError: + # Staging does not exist + self._write_updated_esdl(self._ESDLMixin__energy_system_handler.energy_system) + except Exception: + logger.error("Unkown error occured when evaluating self._stage for _write_updated_esdl") + sys.exit(1) for d in self.energy_system_components.get("heat_demand", []): realized_demand = results[f"{d}.Heat_demand"] @@ -344,7 +468,10 @@ def post(self): logger.warning(f"For demand {d} the target is not matched by {delta_energy} GJ") if os.path.exists(self.output_folder) and self._save_json: - self._write_json_output() + bounds = self.bounds() + aliases = self.alias_relation._canonical_variables_map + solver_stats = self.solver_stats + self._write_json_output(results, parameters, bounds, aliases, solver_stats) class EndScenarioSizingHIGHS(EndScenarioSizing): @@ -357,24 +484,16 @@ class EndScenarioSizingHIGHS(EndScenarioSizing): pass -class EndScenarioSizingGurobi(SolverGurobi, EndScenarioSizing): - """ - Uses Gurobi as the solver for the EndScenarioSizing problem. - """ - - pass - - class EndScenarioSizingDiscounted(EndScenarioSizing): """ - The discounted annualized is utilised as the objective function. - The change of the objective function is done by changing the option 'discounted_annulized_cost' + The Discounted Annualized Cost is used as the objective function. + Changing the objective function is done by setting the 'discounted_annualized_cost' option to True Goal priorities are: 1. Match heat demand with target - 2. minimize TCO = Anualized capex (function of technical lifetime of individual assets) + - Opex*timehorizon + 2. Minimize annualized TCO = discounted annualized CAPEX (function of technical lifetime + of each asset) + annual OPEX. """ def energy_system_options(self): @@ -385,14 +504,6 @@ def energy_system_options(self): return options -class EndScenarioSizingDiscountedHIGHS(EndScenarioSizingDiscounted): - pass - - -class EndScenarioSizingDiscountedGurobi(SolverGurobi, EndScenarioSizingDiscounted): - pass - - class EndScenarioSizingHeadLoss(EndScenarioSizing): """ EndScenarioSizing optimisation including the linearised inequality DarcyWeisbach Head loss @@ -426,11 +537,13 @@ class SettingsStaged: sizes and flow directions. """ - _stage = 0 + _stage = 0 # current stage that is being used + _total_stages = 0 # total number of stages to be used def __init__( self, stage=None, + total_stages=None, boolean_bounds: list = None, priorities_output: list = None, *args, @@ -439,6 +552,7 @@ def __init__( super().__init__(*args, **kwargs) self._stage = stage + self._total_stages = total_stages self.__boolean_bounds = boolean_bounds if self._stage == 1: @@ -470,48 +584,23 @@ class EndScenarioSizingStaged(SettingsStaged, EndScenarioSizing): pass -class EndScenarioSizingStagedHIGHS(EndScenarioSizingStaged): - pass - - -class EndScenarioSizingStagedGurobi(SolverGurobi, EndScenarioSizingStaged): - pass - - class EndScenarioSizingDiscountedStaged(SettingsStaged, EndScenarioSizingDiscounted): pass -class EndScenarioSizingDiscountedStagedHIGHS(EndScenarioSizingDiscountedStaged): - pass - - -class EndScenarioSizingDiscountedStagedGurobi(SolverGurobi, EndScenarioSizingDiscountedStaged): - pass - - class EndScenarioSizingHeadLossStaged(SettingsStaged, EndScenarioSizingHeadLoss): pass -class EndScenarioSizingHeadLossStagedGurobi(SolverGurobi, EndScenarioSizingHeadLossStaged): - pass - - class EndScenarioSizingHeadLossDiscountedStaged( SettingsStaged, EndScenarioSizingHeadLossDiscounted ): pass -class EndScenarioSizingHeadLossDiscountedStagedGurobi( - SolverGurobi, EndScenarioSizingHeadLossDiscountedStaged -): - pass - - def run_end_scenario_sizing_no_heat_losses( end_scenario_problem_class, + solver_class=SolverHIGHS, **kwargs, ): """ @@ -522,6 +611,7 @@ def run_end_scenario_sizing_no_heat_losses( Parameters ---------- end_scenario_problem_class : The end scenario problem class. + solver_class: The solver and its settings to be used to solve the problem. staged_pipe_optimization : Boolean to toggle between the staged or non-staged approach Returns @@ -535,9 +625,11 @@ def run_end_scenario_sizing_no_heat_losses( ), "A staged problem class is required as input for the sizing without heat_losses" start_time = time.time() - solution = run_optimization_problem( + solution = run_optimization_problem_solver( end_scenario_problem_class, + solver_class=solver_class, stage=1, + total_stages=1, **kwargs, ) @@ -548,6 +640,7 @@ def run_end_scenario_sizing_no_heat_losses( def run_end_scenario_sizing( end_scenario_problem_class, + solver_class=None, staged_pipe_optimization=True, **kwargs, ): @@ -564,6 +657,7 @@ def run_end_scenario_sizing( Parameters ---------- end_scenario_problem_class : The end scenario problem class. + solver_class: The solver and its settings to be used to solve the problem. staged_pipe_optimization : Boolean to toggle between the staged or non-staged approach Returns @@ -577,31 +671,52 @@ def run_end_scenario_sizing( start_time = time.time() if staged_pipe_optimization and issubclass(end_scenario_problem_class, SettingsStaged): - solution = run_optimization_problem( + solution = run_optimization_problem_solver( end_scenario_problem_class, + solver_class=solver_class, stage=1, + total_stages=2, **kwargs, ) + # Error checking + solver_success, _ = solution.solver_success(solution.solver_stats, False) + if not solver_success: + if ( + solution.solver_stats["return_status"] == "Time limit reached" + and solution.objective_value > 1e-6 + and solution._stage == 1 + ): + logger.error("Optimization maximum allowed time limit reached for stage_1, goal_1") + exit(1) + else: + logger.error("Unsuccessful: unexpected error for stage_1, goal_1") + exit(1) + results = solution.extract_results() parameters = solution.parameters(0) bounds = solution.bounds() # We give bounds for stage 2 by allowing one DN sizes larger than what was found in the - # stage 1 optimization. - pc_map = solution.get_pipe_class_map() + # stage 1 optimization. But if the pipe is not to be used class DN none should be used and + # all the following pipe clasess should have bounds (0, 0) + # Assumptions: + # - The fist pipe class in the list of pipe_classes is pipe DN none + pc_map = solution.get_pipe_class_map() # if disconnectable and not connected to source for pipe_classes in pc_map.values(): v_prev = 0.0 first_pipe_class = True + use_pipe_dn_none = False for var_name in pipe_classes.values(): - v = results[var_name][0] - if first_pipe_class and abs(v) == 1.0: - boolean_bounds[var_name] = (abs(v), abs(v)) - elif abs(v) == 1.0: - boolean_bounds[var_name] = (0.0, abs(v)) - elif v_prev == 1.0: + v = round(abs(results[var_name][0])) + if first_pipe_class and v == 1.0: + boolean_bounds[var_name] = (v, v) + use_pipe_dn_none = True + elif v == 1.0: + boolean_bounds[var_name] = (0.0, v) + elif not use_pipe_dn_none and v_prev == 1.0: # This allows one DN larger boolean_bounds[var_name] = (0.0, 1.0) else: - boolean_bounds[var_name] = (abs(v), abs(v)) + boolean_bounds[var_name] = (v, v) v_prev = v first_pipe_class = False @@ -610,10 +725,15 @@ def run_end_scenario_sizing( *solution.energy_system_components.get("heat_buffer", []), ]: var_name = f"{asset}_aggregation_count" - lb = results[var_name][0] + round_lb = round(results[var_name][0]) ub = solution.bounds()[var_name][1] - if round(lb) >= 1: - boolean_bounds[var_name] = (lb, ub) + if round_lb >= 1 and (round_lb <= ub): + boolean_bounds[var_name] = (round_lb, ub) + elif round_lb > ub: + logger.error( + f"{var_name}: The lower bound value {round_lb} > the upper bound {ub} value" + ) + exit(1) t = solution.times() from rtctools.optimization.timeseries import Timeseries @@ -643,11 +763,14 @@ def run_end_scenario_sizing( boolean_bounds[f"{p}__is_disconnected"] = (Timeseries(t, r), Timeseries(t, r)) except KeyError: pass + priorities_output = solution._priorities_output - solution = run_optimization_problem( + solution = run_optimization_problem_solver( end_scenario_problem_class, + solver_class=solver_class, stage=2, + total_stages=2, boolean_bounds=boolean_bounds, priorities_output=priorities_output, **kwargs, @@ -677,8 +800,9 @@ def main(runinfo_path, log_level): # user write-user # password nwn_write_test - _ = run_optimization_problem( - EndScenarioSizingHIGHS, + _ = run_optimization_problem_solver( + EndScenarioSizing, + solver_class=SolverHIGHS, esdl_run_info_path=runinfo_path, log_level=log_level, **kwargs, diff --git a/src/rtctools_heat_network/workflows/utils/__init__.py b/src/mesido/workflows/io/__init__.py similarity index 100% rename from src/rtctools_heat_network/workflows/utils/__init__.py rename to src/mesido/workflows/io/__init__.py diff --git a/src/rtctools_heat_network/workflows/io/read_files_and_create_influxdb.py b/src/mesido/workflows/io/read_files_and_create_influxdb.py similarity index 100% rename from src/rtctools_heat_network/workflows/io/read_files_and_create_influxdb.py rename to src/mesido/workflows/io/read_files_and_create_influxdb.py diff --git a/src/rtctools_heat_network/workflows/io/write_output.py b/src/mesido/workflows/io/write_output.py similarity index 57% rename from src/rtctools_heat_network/workflows/io/write_output.py rename to src/mesido/workflows/io/write_output.py index bbcdbadfd..73bc11665 100644 --- a/src/rtctools_heat_network/workflows/io/write_output.py +++ b/src/mesido/workflows/io/write_output.py @@ -1,36 +1,39 @@ +import datetime import json import logging +import math import numbers import os import sys import traceback import uuid +from collections import OrderedDict from pathlib import Path +from typing import Dict, Union import esdl from esdl.profiles.influxdbprofilemanager import ConnectionSettings from esdl.profiles.influxdbprofilemanager import InfluxDBProfileManager from esdl.profiles.profilemanager import ProfileManager +import mesido.esdl.esdl_parser +from mesido.constants import GRAVITATIONAL_CONSTANT +from mesido.esdl.edr_pipe_class import EDRPipeClass +from mesido.network_common import NetworkSettings +from mesido.post_processing.post_processing_utils import pipe_pressure, pipe_velocity +from mesido.workflows.utils.helpers import _sort_numbered + import numpy as np import pandas as pd -import pytz - +from rtctools._internal.alias_tools import AliasDict from rtctools.optimization.timeseries import Timeseries -import rtctools_heat_network.esdl.esdl_parser -from rtctools_heat_network.constants import GRAVITATIONAL_CONSTANT -from rtctools_heat_network.esdl.edr_pipe_class import EDRPipeClass -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin -from rtctools_heat_network.workflows.utils.helpers import _sort_numbered - +logger = logging.getLogger("mesido") -logger = logging.getLogger("rtctools_heat_network") - -class ScenarioOutput(TechnoEconomicMixin): +class ScenarioOutput: __optimized_energy_system_handler = None def __init__(self, **kwargs): @@ -296,48 +299,66 @@ def _write_html_output(self, template_name="mpc_buffer_sizing_output"): ) ) - def _write_updated_esdl(self, energy_system, optimizer_sim: bool = False): - from esdl.esdl_handler import EnergySystemHandler + def _add_kpis_to_energy_system(self, energy_system, optimizer_sim: bool = False): results = self.extract_results() parameters = self.parameters(0) - input_energy_system_id = energy_system.id - energy_system.id = str(uuid.uuid4()) - if optimizer_sim: - energy_system.name = energy_system.name + "_Simulation" - else: - energy_system.name = energy_system.name + "_GrowOptimized" - - def _name_to_asset(name): - return next( - (x for x in energy_system.eAllContents() if hasattr(x, "name") and x.name == name) - ) - # ------------------------------------------------------------------------------------------ # KPIs # General cost breakdowns # ------------------------------------------------------------------------------------------ kpis_top_level = esdl.KPIs(id=str(uuid.uuid4())) heat_source_energy_wh = {} - asset_capex_breakdown = {} - asset_opex_breakdown = {} - tot_install_cost_euro = 0.0 - tot_invest_cost_euro = 0.0 - tot_variable_opex_cost_euro = 0.0 - tot_fixed_opex_cost_euro = 0.0 + asset_opex_breakdown = {} # yearly cost + tot_variable_opex_cost_euro = 0.0 # yearly cost + tot_fixed_opex_cost_euro = 0.0 # yearly cost + + # cost over the total time horizon (number of year) being optimized: + # - parameters["number_of_years"] + # - these kpis are not created for the newtwork simualtor->optimizer_sim + asset_timehorizon_opex_breakdown = {} + tot_timehorizon_variable_opex_cost_euro = 0.0 + tot_timehorizon_fixed_opex_cost_euro = 0.0 + asset_timehorizon_capex_breakdown = {} + tot_timehorizon_install_cost_euro = 0.0 + tot_timehorizon_invest_cost_euro = 0.0 + + # Specify the correct time horizon: + # Optimization=number of year: since it is taken into account in TCO minimization + # Simulator=1: since 30 years of optimization is not applicable for the network simulator + if not optimizer_sim: # optimization mode + optim_time_horizon = parameters["number_of_years"] + elif optimizer_sim: # network simulator mode + optim_time_horizon = 1.0 + else: + logger.error("Variable optimizer_sim has not been set") for _key, asset in self.esdl_assets.items(): asset_placement_var = self._asset_aggregation_count_var_map[asset.name] placed = np.round(results[asset_placement_var][0]) >= 1.0 + + if np.isnan(parameters[f"{asset.name}.technical_life"]) or np.isclose( + parameters[f"{asset.name}.technical_life"], 0.0 + ): + capex_factor = 1.0 + else: + capex_factor = math.ceil( + optim_time_horizon / parameters[f"{asset.name}.technical_life"] + ) + if placed: try: - asset_capex_breakdown[asset.asset_type] += ( + asset_timehorizon_capex_breakdown[asset.asset_type] += ( results[f"{asset.name}__installation_cost"][0] + results[f"{asset.name}__investment_cost"][0] - ) - tot_install_cost_euro += results[f"{asset.name}__installation_cost"][0] - tot_invest_cost_euro += results[f"{asset.name}__investment_cost"][0] + ) * capex_factor + tot_timehorizon_install_cost_euro += ( + results[f"{asset.name}__installation_cost"][0] + ) * capex_factor + tot_timehorizon_invest_cost_euro += ( + results[f"{asset.name}__investment_cost"][0] + ) * capex_factor if ( results[f"{asset.name}__variable_operational_cost"][0] > 0.0 @@ -347,6 +368,10 @@ def _name_to_asset(name): results[f"{asset.name}__variable_operational_cost"][0] + results[f"{asset.name}__fixed_operational_cost"][0] ) + asset_timehorizon_opex_breakdown[asset.asset_type] += ( + results[f"{asset.name}__variable_operational_cost"][0] + + results[f"{asset.name}__fixed_operational_cost"][0] + ) * optim_time_horizon tot_variable_opex_cost_euro += results[ f"{asset.name}__variable_operational_cost" @@ -354,15 +379,26 @@ def _name_to_asset(name): tot_fixed_opex_cost_euro += results[ f"{asset.name}__fixed_operational_cost" ][0] + tot_timehorizon_variable_opex_cost_euro += ( + results[f"{asset.name}__variable_operational_cost"][0] + * optim_time_horizon + ) + tot_timehorizon_fixed_opex_cost_euro += ( + results[f"{asset.name}__fixed_operational_cost"][0] * optim_time_horizon + ) except KeyError: try: - asset_capex_breakdown[asset.asset_type] = ( + asset_timehorizon_capex_breakdown[asset.asset_type] = ( results[f"{asset.name}__installation_cost"][0] + results[f"{asset.name}__investment_cost"][0] - ) - tot_install_cost_euro += results[f"{asset.name}__installation_cost"][0] - tot_invest_cost_euro += results[f"{asset.name}__investment_cost"][0] + ) * capex_factor + tot_timehorizon_install_cost_euro += ( + results[f"{asset.name}__installation_cost"][0] + ) * capex_factor + tot_timehorizon_invest_cost_euro += ( + results[f"{asset.name}__investment_cost"][0] + ) * capex_factor if ( results[f"{asset.name}__variable_operational_cost"][0] > 0.0 @@ -372,6 +408,9 @@ def _name_to_asset(name): results[f"{asset.name}__variable_operational_cost"][0] + results[f"{asset.name}__fixed_operational_cost"][0] ) + asset_timehorizon_opex_breakdown[asset.asset_type] = ( + asset_opex_breakdown[asset.asset_type] * optim_time_horizon + ) tot_variable_opex_cost_euro += results[ f"{asset.name}__variable_operational_cost" @@ -379,6 +418,15 @@ def _name_to_asset(name): tot_fixed_opex_cost_euro += results[ f"{asset.name}__fixed_operational_cost" ][0] + tot_timehorizon_variable_opex_cost_euro += ( + results[f"{asset.name}__variable_operational_cost"][0] + * optim_time_horizon + ) + tot_timehorizon_fixed_opex_cost_euro += ( + results[f"{asset.name}__fixed_operational_cost"][0] + * optim_time_horizon + ) + except KeyError: # Do not add any costs. Items like joint pass @@ -412,12 +460,15 @@ def _name_to_asset(name): kpis_top_level.kpi.append( esdl.DistributionKPI( - name="High level cost breakdown [EUR]", + name="High level cost breakdown [EUR] (yearly averaged)", distribution=esdl.StringLabelDistribution( stringItem=[ esdl.StringItem( label="CAPEX", - value=tot_install_cost_euro + tot_invest_cost_euro, + value=( + tot_timehorizon_install_cost_euro + tot_timehorizon_invest_cost_euro + ) + / optim_time_horizon, ), esdl.StringItem( label="OPEX", @@ -431,13 +482,45 @@ def _name_to_asset(name): ) ) + if not optimizer_sim: + kpis_top_level.kpi.append( + esdl.DistributionKPI( + name=f"High level cost breakdown [EUR] ({optim_time_horizon} year period)", + distribution=esdl.StringLabelDistribution( + stringItem=[ + esdl.StringItem( + label="CAPEX", + value=tot_timehorizon_install_cost_euro + + tot_timehorizon_invest_cost_euro, + ), + esdl.StringItem( + label="OPEX", + value=( + tot_timehorizon_variable_opex_cost_euro + + tot_timehorizon_fixed_opex_cost_euro + ), + ), + ] + ), + quantityAndUnit=esdl.esdl.QuantityAndUnitType( + physicalQuantity=esdl.PhysicalQuantityEnum.COST, unit=esdl.UnitEnum.EURO + ), + ) + ) + kpis_top_level.kpi.append( esdl.DistributionKPI( - name="Overall cost breakdown [EUR]", + name="Overall cost breakdown [EUR] (yearly averaged)", distribution=esdl.StringLabelDistribution( stringItem=[ - esdl.StringItem(label="Installation", value=tot_install_cost_euro), - esdl.StringItem(label="Investment", value=tot_invest_cost_euro), + esdl.StringItem( + label="Installation", + value=(tot_timehorizon_install_cost_euro / optim_time_horizon), + ), + esdl.StringItem( + label="Investment", + value=(tot_timehorizon_invest_cost_euro / optim_time_horizon), + ), esdl.StringItem(label="Variable OPEX", value=tot_variable_opex_cost_euro), esdl.StringItem(label="Fixed OPEX", value=tot_fixed_opex_cost_euro), ] @@ -447,25 +530,52 @@ def _name_to_asset(name): ), ) ) + if not optimizer_sim: + kpis_top_level.kpi.append( + esdl.DistributionKPI( + name=f"Overall cost breakdown [EUR] ({optim_time_horizon} year period)", + distribution=esdl.StringLabelDistribution( + stringItem=[ + esdl.StringItem( + label="Installation", value=tot_timehorizon_install_cost_euro + ), + esdl.StringItem( + label="Investment", value=tot_timehorizon_invest_cost_euro + ), + esdl.StringItem( + label="Variable OPEX", + value=tot_timehorizon_variable_opex_cost_euro, + ), + esdl.StringItem( + label="Fixed OPEX", + value=tot_timehorizon_fixed_opex_cost_euro, + ), + ] + ), + quantityAndUnit=esdl.esdl.QuantityAndUnitType( + physicalQuantity=esdl.PhysicalQuantityEnum.COST, unit=esdl.UnitEnum.EURO + ), + ) + ) - kpis_top_level.kpi.append( - esdl.DistributionKPI( - name="CAPEX breakdown [EUR]", - distribution=esdl.StringLabelDistribution( - stringItem=[ - esdl.StringItem(label=key, value=value) - for key, value in asset_capex_breakdown.items() - ] - ), - quantityAndUnit=esdl.esdl.QuantityAndUnitType( - physicalQuantity=esdl.PhysicalQuantityEnum.COST, unit=esdl.UnitEnum.EURO - ), + kpis_top_level.kpi.append( + esdl.DistributionKPI( + name=f"CAPEX breakdown [EUR] ({optim_time_horizon} year period)", + distribution=esdl.StringLabelDistribution( + stringItem=[ + esdl.StringItem(label=key, value=value) + for key, value in asset_timehorizon_capex_breakdown.items() + ] + ), + quantityAndUnit=esdl.esdl.QuantityAndUnitType( + physicalQuantity=esdl.PhysicalQuantityEnum.COST, unit=esdl.UnitEnum.EURO + ), + ) ) - ) kpis_top_level.kpi.append( esdl.DistributionKPI( - name="OPEX breakdown [EUR]", + name="OPEX breakdown [EUR] (yearly averaged)", distribution=esdl.StringLabelDistribution( stringItem=[ esdl.StringItem(label=key, value=value) @@ -477,16 +587,34 @@ def _name_to_asset(name): ), ) ) + if not optimizer_sim: + kpis_top_level.kpi.append( + esdl.DistributionKPI( + name=f"OPEX breakdown [EUR] ({optim_time_horizon} year period)", + distribution=esdl.StringLabelDistribution( + stringItem=[ + esdl.StringItem(label=key, value=value) + for key, value in asset_timehorizon_opex_breakdown.items() + ] + ), + quantityAndUnit=esdl.esdl.QuantityAndUnitType( + physicalQuantity=esdl.PhysicalQuantityEnum.COST, unit=esdl.UnitEnum.EURO + ), + ) + ) kpis_top_level.kpi.append( esdl.DistributionKPI( - name="Energy production [Wh]", + name="Energy production [Wh] (yearly averaged)", distribution=esdl.StringLabelDistribution( stringItem=[ esdl.StringItem(label=key, value=value) for key, value in heat_source_energy_wh.items() ] ), + quantityAndUnit=esdl.esdl.QuantityAndUnitType( + physicalQuantity=esdl.PhysicalQuantityEnum.ENERGY, unit=esdl.UnitEnum.WATTHOUR + ), ) ) energy_system.instance[0].area.KPIs = kpis_top_level @@ -603,22 +731,36 @@ def _name_to_asset(name): # Calculate the estimated energy source [%] for an area try: - total_energy_produced_locally_wh_area = total_energy_produced_locally_wh[ - subarea.name - ] + if not np.isnan(total_energy_produced_locally_wh[subarea.name]): + total_energy_produced_locally_wh_area = total_energy_produced_locally_wh[ + subarea.name + ] + else: + total_energy_produced_locally_wh_area = 0.0 except KeyError: total_energy_produced_locally_wh_area = 0.0 try: - estimated_energy_from_local_source_perc[subarea.name] = min( - total_energy_produced_locally_wh_area - / total_energy_consumed_locally_wh[subarea.name] - * 100.0, - 100.0, - ) - estimated_energy_from_regional_source_perc[subarea.name] = min( - (100.0 - estimated_energy_from_local_source_perc[subarea.name]), 100.0 - ) + if not np.isnan(total_energy_consumed_locally_wh[subarea.name]) and np.isclose( + total_energy_consumed_locally_wh[subarea.name], 0.0 + ): + estimated_energy_from_local_source_perc[subarea.name] = min( + total_energy_produced_locally_wh_area + / total_energy_consumed_locally_wh[subarea.name] + * 100.0, + 100.0, + ) + estimated_energy_from_regional_source_perc[subarea.name] = min( + (100.0 - estimated_energy_from_local_source_perc[subarea.name]), 100.0 + ) + else: + estimated_energy_from_local_source_perc[subarea.name] = 0.0 + estimated_energy_from_regional_source_perc[subarea.name] = 0.0 + logger.warning( + f"KPI estimated energy from local & regional source have been set to 0.0" + f" in area {subarea.name}. Reason: area local energy" + f" consumption value is: {total_energy_consumed_locally_wh[subarea.name]}" + ) except KeyError: # Nothing to do, go on to next section of code pass @@ -656,7 +798,7 @@ def _name_to_asset(name): kpis.kpi.append( esdl.DoubleKPI( value=area_variable_opex_cost / 1.0e6, - name="Variable OPEX", + name="Variable OPEX (year 1)", quantityAndUnit=esdl.esdl.QuantityAndUnitType( physicalQuantity=esdl.PhysicalQuantityEnum.COST, unit=esdl.UnitEnum.EURO, @@ -667,7 +809,7 @@ def _name_to_asset(name): kpis.kpi.append( esdl.DoubleKPI( value=area_fixed_opex_cost / 1.0e6, - name="Fixed OPEX", + name="Fixed OPEX (year 1)", quantityAndUnit=esdl.esdl.QuantityAndUnitType( physicalQuantity=esdl.PhysicalQuantityEnum.COST, unit=esdl.UnitEnum.EURO, @@ -773,52 +915,96 @@ def _name_to_asset(name): # ebd sub-area loop # end KPIs + + def _write_updated_esdl( + self, + energy_system, + optimizer_sim: bool = False, + add_kpis: bool = True, + ): + from esdl.esdl_handler import EnergySystemHandler + + results = self.extract_results() + parameters = self.parameters(0) + + _ = energy_system.id # input energy system id. Kept here as not sure if still needed + energy_system.id = str(uuid.uuid4()) # output energy system id + output_energy_system_id = energy_system.id + # Currently the simulation_id is created here, but in the future this will probably move + # to account for 1 simulation/optimization/run potentialy generating more than 1 output + # energy system (ESDL) + simulation_id = str(uuid.uuid4()) # simulation (optimization/simulator etc) id + + if optimizer_sim: # network simulator + energy_system.name = energy_system.name + "_Simulation" + else: # network optimization + energy_system.name = energy_system.name + "_GrowOptimized" + + def _name_to_asset(name): + return next( + (x for x in energy_system.eAllContents() if hasattr(x, "name") and x.name == name) + ) + + if add_kpis: + self._add_kpis_to_energy_system(energy_system, optimizer_sim) + # ------------------------------------------------------------------------------------------ # Placement + heat_pipes = set(self.energy_system_components.get("heat_pipe", [])) for _, attributes in self.esdl_assets.items(): name = attributes.name if name in [ *self.energy_system_components.get("heat_source", []), *self.energy_system_components.get("ates", []), *self.energy_system_components.get("heat_buffer", []), + *self.energy_system_components.get("heat_pump", []), ]: asset = _name_to_asset(name) asset_placement_var = self._asset_aggregation_count_var_map[name] placed = np.round(results[asset_placement_var][0]) >= 1.0 max_size = results[self._asset_max_size_map[name]][0] - if asset in self.energy_system_components.get("heat_buffer", []): + if asset.name in self.energy_system_components.get("ates", []): + asset.maxChargeRate = results[f"{name}__max_size"][0] + asset.maxDischargeRate = results[f"{name}__max_size"][0] + elif asset.name in self.energy_system_components.get("heat_buffer", []): asset.capacity = max_size asset.volume = max_size / ( parameters[f"{name}.cp"] * parameters[f"{name}.rho"] * parameters[f"{name}.dT"] ) + elif asset.name in self.energy_system_components.get("heat_pump", []): + # Note: The heat capacity and not the electrical capacity + # TODO: in the future we need to cater for varying COP as well + asset.power = results[f"{name}__max_size"][0] else: asset.power = max_size if not placed: asset.delete(recursive=True) else: asset.state = esdl.AssetStateEnum.ENABLED + elif name not in heat_pipes: # because heat pipes are updated below + logger.warning(f"ESDL update: asset {name} has not been updated") # Pipes: edr_pipe_properties_to_copy = ["innerDiameter", "outerDiameter", "diameter", "material"] esh_edr = EnergySystemHandler() - for pipe in self.hot_pipes: + for pipe in self.energy_system_components.get("heat_pipe", []): + pipe_classes = self.pipe_classes(pipe) # When a pipe has not been optimized, enforce pipe to be shown in the simulator # ESDL. if not pipe_classes: - if optimizer_sim: + if not optimizer_sim: continue else: asset.state = esdl.AssetStateEnum.ENABLED - if optimizer_sim: + if not optimizer_sim: pipe_class = self.get_optimized_pipe_class(pipe) - cold_pipe = self.hot_to_cold_pipe(pipe) if parameters[f"{pipe}.diameter"] != 0.0 or any(np.abs(results[f"{pipe}.Q"]) > 1.0e-9): # if not isinstance(pipe_class, EDRPipeClass): @@ -828,77 +1014,66 @@ def _name_to_asset(name): # print(pipe + " has pipeclass: " + pipe_class.name ) # print(pipe + f" has diameter: " + pipe_class.name) - if optimizer_sim: + if not optimizer_sim: assert isinstance(pipe_class, EDRPipeClass) - asset_edr = esh_edr.load_from_string(pipe_class.xml_string) - for p in [pipe, cold_pipe]: - asset = _name_to_asset(p) - asset.state = esdl.AssetStateEnum.ENABLED + asset = _name_to_asset(pipe) + asset.state = esdl.AssetStateEnum.ENABLED - try: - asset.costInformation.investmentCosts.value = pipe_class.investment_costs - except AttributeError: - pass - # do nothing, in the case that no costs have been specified for the return - # pipe in the mapeditor - except UnboundLocalError: - pass + try: + asset.costInformation.investmentCosts.value = pipe_class.investment_costs + except AttributeError: + pass + # do nothing, in the case that no costs have been specified for the return + # pipe in the mapeditor + except UnboundLocalError: + pass - if optimizer_sim: - for prop in edr_pipe_properties_to_copy: - setattr(asset, prop, getattr(asset_edr, prop)) + if not optimizer_sim: + for prop in edr_pipe_properties_to_copy: + setattr(asset, prop, getattr(asset_edr, prop)) else: - for p in [pipe, cold_pipe]: - asset = _name_to_asset(p) - asset.delete(recursive=True) + asset = _name_to_asset(pipe) + asset.delete(recursive=True) # ------------------------------------------------------------------------------------------ # Important: This code below must be placed after the "Placement" code. Reason: it relies # on unplaced assets being deleted. # ------------------------------------------------------------------------------------------ - # Write asset result profile data to database. The datbase is setup as follows: - # - The each time step is represented by a row of data, with columns datetime, field + # Write asset result profile data to database. The database is setup as follows: + # - The each time step is represented by a row of data, with columns; datetime, field # values + # - The database contains columns based on the carrier connected for visualisation + # purposes + # - Assets with more than 1 carrier are looped over the time steps as many times as there + # are different carriers connected, to ensure the correct data is written to each carrier. # - Database name: input esdl id - # - Measurment: asset name + # - Measurment: carrier id # - Fields: profile value for the specific variable - # - Tags used as filters: output esdl id + # - Tags used as filters: simulationRun, assetClass, assetName, assetId, capability if self.write_result_db_profiles: logger.info("Writing asset result profile data to influxDB") results = self.extract_results() - # Note: when adding new variables to variables_one_hydraulic_system or" - # variables_two_hydraulic_system also add quantity and units to the ESDL for the new - # variables in the code lower down - variables_one_hydraulic_system = ["HeatIn.Q", "HeatIn.H", "Heat_flow"] - variables_two_hydraulic_system = [ - "Primary.HeatIn.Q", - "Primary.HeatIn.H", - "Secondary.HeatIn.Q", - "Secondary.HeatIn.H", - "Heat_flow", - ] influxdb_conn_settings = ConnectionSettings( host=self.influxdb_host, port=self.influxdb_port, username=self.influxdb_username, password=self.influxdb_password, - database=input_energy_system_id, + database=output_energy_system_id, ssl=self.influxdb_ssl, verify_ssl=self.influxdb_verify_ssl, ) - # influxdb_conn_settings = ConnectionSettings( - # host="omotes-poc-test.hesi.energy", #self.influxdb_host, - # port=8086, # self.influxdb_port, - # username="write-user", #self.influxdb_username, - # password="nwn_write_test", #self.influxdb_password, - # database="test_kvr", # input_energy_system_id, - # ssl=self.influxdb_ssl, - # verify_ssl=self.influxdb_verify_ssl, - # ) + + capabilities = [ + esdl.Transport, + esdl.Conversion, + esdl.Consumer, + esdl.Producer, + esdl.Storage, + ] for asset_name in [ *self.energy_system_components.get("heat_source", []), @@ -909,155 +1084,325 @@ def _name_to_asset(name): *self.energy_system_components.get("heat_exchanger", []), *self.energy_system_components.get("heat_pump", []), ]: - profiles = ProfileManager() - profiles.profile_type = "DATETIME_LIST" - profiles.profile_header = ["datetime"] try: # If the asset has been placed asset = _name_to_asset(asset_name) - - # Get index of outport which will be used to assign the profile data to - index_outport = -1 - for ip in range(len(asset.port)): - if isinstance(asset.port[ip], esdl.OutPort): - if index_outport == -1: - index_outport = ip - else: - logger.warning( - f"Asset {asset_name} has more than 1 OutPort, and the " - "profile data has been assigned to the 1st OutPort" - ) - break - - if index_outport == -1: - logger.error( - f"Variable {index_outport} has not been assigned to the asset OutPort" + asset_class = asset.__class__.__name__ + asset_id = asset.id + capability = [c for c in capabilities if c in asset.__class__.__mro__][ + 0 + ].__name__ + + # Generate three empty variables, + # For transport and consumer assets, 'port' is filled with the inport + # For producer assets, 'port' is filled with outport as this is linked to the + # same carrier as the inport of consumers (thus all info in one carrier) + # For conversion assets, the primary side is acting like a consumer, the + # secondary side as a producer, thus a similar port structure is assumed, but + # now port_prim and port_sec variable are set, such that data can be saved for + # both carriers. + port, port_prim, port_sec = 3 * [None] + if isinstance(asset, esdl.Transport) or isinstance(asset, esdl.Consumer): + port = [port for port in asset.port if isinstance(port, esdl.InPort)][0] + elif isinstance(asset, esdl.Producer): + port = [port for port in asset.port if isinstance(port, esdl.OutPort)][0] + elif isinstance(asset, esdl.Conversion): + port_prim = [ + port + for port in asset.port + if isinstance(port, esdl.InPort) and "Prim" in port.name + ][0] + port_sec = [ + port + for port in asset.port + if isinstance(port, esdl.OutPort) and "Sec" in port.name + ][0] + else: + NotImplementedError( + f"influxdb not included for assets of type {type(asset)}" ) - sys.exit(1) - for ii in range(len(self.times())): - if not self.io.datetimes[ii].tzinfo: - data_row = [pytz.utc.localize(self.io.datetimes[ii])] - else: - data_row = [self.io.datetimes[ii]] + # Note: when adding new variables to variables_one_hydraulic_system or" + # variables_two_hydraulic_system also add quantity and units to the ESDL for + # the new variables in the code lower down + # These variables exist for all the assets. Variables that only exist for + # specific + # assets are only added later, like Pump_power + commodity = self.energy_system_components_commodity.get(asset_name) + + variables_one_hydraulic_system = [f"{commodity}In.Q"] + variables_two_hydraulic_system = [ + f"Primary.{commodity}In.Q", + f"Secondary.{commodity}In.Q", + ] + if commodity == NetworkSettings.NETWORK_TYPE_HEAT: + variables_one_hydraulic_system.append("Heat_flow") + variables_two_hydraulic_system.append("Heat_flow") + elif commodity == NetworkSettings.NETWORK_TYPE_GAS: + variables_one_hydraulic_system.append(f"{commodity}In.mass_flow") + variables_two_hydraulic_system.append(f"{commodity}In.mass_flow") + + post_processed = {} + + # Update/overwrite each asset variable list due to: + # - the addition of head loss minimization: head variable and pump power + # - only a specific variable required for a specific asset: pump power + # - addition of post processed variables: pipe velocity + if self.heat_network_settings["minimize_head_losses"]: + variables_one_hydraulic_system.append(f"{commodity}In.H") + variables_two_hydraulic_system.append(f"Primary.{commodity}In.H") + variables_two_hydraulic_system.append(f"Secondary.{commodity}In.H") + if asset_name in [ + *self.energy_system_components.get("heat_source", []), + *self.energy_system_components.get("heat_buffer", []), + *self.energy_system_components.get("ates", []), + *self.energy_system_components.get("heat_exchanger", []), + *self.energy_system_components.get("heat_pump", []), + ]: + variables_one_hydraulic_system.append("Pump_power") + variables_two_hydraulic_system.append("Pump_power") + elif asset_name in [*self.energy_system_components.get("pump", [])]: + variables_one_hydraulic_system = ["Pump_power"] + variables_two_hydraulic_system = ["Pump_power"] + if asset_name in [ + *self.energy_system_components.get("heat_pipe", []), + *self.energy_system_components.get("gas_pipe", []), + ]: + variables_one_hydraulic_system.append("PostProc.Velocity") + variables_two_hydraulic_system.append("PostProc.Velocity") + # Velocity at the pipe outlet [m/s] + post_processed["PostProc.Velocity"] = pipe_velocity( + asset_name, commodity, results, parameters + ) + variables_one_hydraulic_system.append("PostProc.Pressure") + # TODO: seems unnecessary, pipes always only have 1 hydraulic system + variables_two_hydraulic_system.append("PostProc.Pressure") + post_processed["PostProc.Pressure"] = pipe_pressure( + asset_name, commodity, results, parameters + ) # Pa + + # Depending on the port set, different carriers are assigned + if port: + carrier_id_dict = {"single_carrier_id": port.carrier.id} + elif port_prim and port_sec: + carrier_id_dict = { + "primary_carrier_id": port_prim.carrier.id, + "secondary_carrier_id": port_sec.carrier.id, + } + else: + NotImplementedError( + "Unsuported types for the different port carrier combinations" + ) - try: - # For all components dealing with one hydraulic system - if isinstance( - results[f"{asset_name}." + variables_one_hydraulic_system[0]][ii], - numbers.Number, - ): - variables_names = variables_one_hydraulic_system - except Exception: - # For all components dealing with two hydraulic system - if isinstance( - results[f"{asset_name}." + variables_two_hydraulic_system[0]][ii], - numbers.Number, - ): - variables_names = variables_two_hydraulic_system - - for variable in variables_names: - if ii == 0: - # Set header for each column - profiles.profile_header.append(variable) - # Set profile database attributes for the esdl asset - if not self.io.datetimes[0].tzinfo: - start_date_time = pytz.utc.localize(self.io.datetimes[0]) - else: - start_date_time = self.io.datetimes[0] - if not self.io.datetimes[-1].tzinfo: - end_date_time = pytz.utc.localize(self.io.datetimes[-1]) + # Looping over the carrier_ids relevant for the asset + # If primary or secondary port are set, variables_to_hydraulic_system will be + # used, variable names linking to the secondary port are popped from the list + # when the primary port is selected and vice versa + variables_two_hydraulic_system_org = variables_two_hydraulic_system.copy() + for asset_side, carrier_id in carrier_id_dict.items(): + variables_two_hydraulic_system = variables_two_hydraulic_system_org.copy() + var_pops = [] + if asset_side == "primary_carrier_id": + var_pops = [ + v for v in variables_two_hydraulic_system if "Secondary" in v + ] + elif asset_side == "secondary_carrier_id": + var_pops = [v for v in variables_two_hydraulic_system if "Primary" in v] + for v in var_pops: + variables_two_hydraulic_system.remove(v) + + profiles = ProfileManager() + profiles.profile_type = "DATETIME_LIST" + profiles.profile_header = ["datetime"] # + general_headers + + # Get index of outport which will be used to assign the profile data to + index_outport = -1 + for ip in range(len(asset.port)): + if isinstance(asset.port[ip], esdl.OutPort): + if index_outport == -1: + index_outport = ip else: - end_date_time = self.io.datetimes[-1] - - profile_attributes = esdl.InfluxDBProfile( - database=input_energy_system_id, - measurement=asset_name, - field=profiles.profile_header[-1], - port=self.influxdb_port, - host=self.influxdb_host, - startDate=start_date_time, - endDate=end_date_time, - id=str(uuid.uuid4()), + logger.warning( + f"Asset {asset_name} has more than 1 OutPort, and the " + "profile data has been assigned to the 1st OutPort" + ) + break + + if index_outport == -1: + logger.error( + f"Variable {index_outport} has not been assigned to the asset " + f"OutPort" + ) + sys.exit(1) + + for ii in range(len(self.times())): + if not self.io.datetimes[ii].tzinfo: + data_row = [ + self.io.datetimes[ii].replace(tzinfo=datetime.timezone.utc) + ] + else: + data_row = [self.io.datetimes[ii]] + + try: + # For all components dealing with one hydraulic system + if isinstance( + results[f"{asset_name}." + variables_one_hydraulic_system[0]][ + ii + ], + numbers.Number, + ): + variables_names = variables_one_hydraulic_system + except KeyError: + # For all components dealing with two hydraulic system + if isinstance( + results[f"{asset_name}." + variables_two_hydraulic_system[0]][ + ii + ], + numbers.Number, + ): + variables_names = variables_two_hydraulic_system + except Exception: + logger.error( + f"During the influxDB profile writing for asset: {asset_name}," + f" the following error occured:" ) - # Assign quantity and units variable - if variable in ["Heat_flow"]: - profile_attributes.profileQuantityAndUnit = ( - esdl.esdl.QuantityAndUnitType( - physicalQuantity=esdl.PhysicalQuantityEnum.POWER, - unit=esdl.UnitEnum.WATT, - multiplier=esdl.MultiplierEnum.NONE, + traceback.print_exc() + sys.exit(1) + + for variable in variables_names: + if ii == 0: + # Set header for each column + profiles.profile_header.append(variable) + # Set profile database attributes for the esdl asset + if not self.io.datetimes[0].tzinfo: + start_date_time = self.io.datetimes[0].replace( + tzinfo=datetime.timezone.utc ) - ) - elif variable in [ - "HeatIn.H", - "Primary.HeatIn.H", - "Secondary.HeatIn.H", - ]: - profile_attributes.profileQuantityAndUnit = ( - esdl.esdl.QuantityAndUnitType( - physicalQuantity=esdl.PhysicalQuantityEnum.PRESSURE, - unit=esdl.UnitEnum.PASCAL, - multiplier=esdl.MultiplierEnum.NONE, + logger.warning( + f"No timezone specified for the output profile: " + f"default UTC has been used for asset {asset_name} " + f"variable {variable}" ) - ) - elif variable in [ - "HeatIn.Q", - "Primary.HeatIn.Q", - "Secondary.HeatIn.Q", - ]: - profile_attributes.profileQuantityAndUnit = ( - esdl.esdl.QuantityAndUnitType( - physicalQuantity=esdl.PhysicalQuantityEnum.FLOW, - unit=esdl.UnitEnum.CUBIC_METRE, - perTimeUnit=esdl.TimeUnitEnum.SECOND, - multiplier=esdl.MultiplierEnum.NONE, + else: + start_date_time = self.io.datetimes[0] + if not self.io.datetimes[-1].tzinfo: + end_date_time = self.io.datetimes[-1].replace( + tzinfo=datetime.timezone.utc ) + else: + end_date_time = self.io.datetimes[-1] + + profile_attributes = esdl.InfluxDBProfile( + database=output_energy_system_id, + measurement=carrier_id, + field=profiles.profile_header[-1], + port=self.influxdb_port, + host=self.influxdb_host, + startDate=start_date_time, + endDate=end_date_time, + id=str(uuid.uuid4()), + filters='"assetId"=' + f"'{str(asset_id)}'", ) - else: - logger.warning( - f"No profile units will be written to the ESDL for: " - f"{asset_name}. + {variable}" - ) + # Assign quantity and units variable + if variable in ["Heat_flow", "Pump_power"]: + profile_attributes.profileQuantityAndUnit = ( + esdl.esdl.QuantityAndUnitType( + physicalQuantity=esdl.PhysicalQuantityEnum.POWER, + unit=esdl.UnitEnum.WATT, + multiplier=esdl.MultiplierEnum.NONE, + ) + ) + elif variable in [ + f"{commodity}In.H", + f"Primary.{commodity}In.H", + f"Secondary.{commodity}In.H", + ]: + profile_attributes.profileQuantityAndUnit = ( + esdl.esdl.QuantityAndUnitType( + physicalQuantity=esdl.PhysicalQuantityEnum.PRESSURE, + unit=esdl.UnitEnum.PASCAL, + multiplier=esdl.MultiplierEnum.NONE, + ) + ) + elif variable in [ + f"{commodity}In.Q", + f"Primary.{commodity}In.Q", + f"Secondary.{commodity}In.Q", + ]: + profile_attributes.profileQuantityAndUnit = ( + esdl.esdl.QuantityAndUnitType( + physicalQuantity=esdl.PhysicalQuantityEnum.FLOW, + unit=esdl.UnitEnum.CUBIC_METRE, + perTimeUnit=esdl.TimeUnitEnum.SECOND, + multiplier=esdl.MultiplierEnum.NONE, + ) + ) + elif variable in ["PostProc.Velocity"]: + profile_attributes.profileQuantityAndUnit = ( + esdl.esdl.QuantityAndUnitType( + physicalQuantity=esdl.PhysicalQuantityEnum.SPEED, + unit=esdl.UnitEnum.METRE, + perTimeUnit=esdl.TimeUnitEnum.SECOND, + multiplier=esdl.MultiplierEnum.NONE, + ) + ) + else: + logger.warning( + f"No profile units will be written to the ESDL for: " + f"{asset_name}. + {variable}" + ) - asset.port[index_outport].profile.append(profile_attributes) + asset.port[index_outport].profile.append(profile_attributes) - # Add variable values in new column - conversion_factor = 0.0 - if variable in [ - "HeatIn.H", - "Primary.HeatIn.H", - "Secondary.HeatIn.H", - ]: - conversion_factor = GRAVITATIONAL_CONSTANT * 988.0 - else: - conversion_factor = 1.0 - data_row.append( - results[f"{asset_name}." + variable][ii] * conversion_factor - ) + # Add variable values in new column + conversion_factor = 0.0 + if variable in [ + f"{commodity}In.H", + f"Primary.{commodity}In.H", + f"Secondary.{commodity}In.H", + ]: + conversion_factor = GRAVITATIONAL_CONSTANT * 988.0 + else: + conversion_factor = 1.0 + if variable not in ["PostProc.Velocity", "PostProc.Pressure"]: + data_row.append( + results[f"{asset_name}." + variable][ii] * conversion_factor + ) + # The variable evaluation below seems unnecessary, but it would be + # used we expand the list of post process type variables + elif variable in ["PostProc.Velocity", "PostProc.Pressure"]: + data_row.append(post_processed[variable][ii]) + + profiles.profile_data_list.append(data_row) + # end time steps + profiles.num_profile_items = len(profiles.profile_data_list) + profiles.start_datetime = profiles.profile_data_list[0][0] + profiles.end_datetime = profiles.profile_data_list[-1][0] + + influxdb_profile_manager = InfluxDBProfileManager( + influxdb_conn_settings, profiles + ) - profiles.profile_data_list.append(data_row) - # end time steps - profiles.num_profile_items = len(profiles.profile_data_list) - profiles.start_datetime = profiles.profile_data_list[0][0] - profiles.end_datetime = profiles.profile_data_list[-1][0] + optim_simulation_tag = { + "simulationRun": simulation_id, + "simulation_type": type(self).__name__, + "assetId": asset_id, + "assetName": asset_name, + "assetClass": asset_class, + "capability": capability, + } + _ = influxdb_profile_manager.save_influxdb( + measurement=carrier_id, + field_names=influxdb_profile_manager.profile_header[1:], + tags=optim_simulation_tag, + ) - influxdb_profile_manager = InfluxDBProfileManager( - influxdb_conn_settings, profiles - ) - optim_simulation_tag = {"output_esdl_id": energy_system.id} - _ = influxdb_profile_manager.save_influxdb( - measurement=asset_name, - field_names=influxdb_profile_manager.profile_header[1:], - tags=optim_simulation_tag, - ) # -- Test tags -- # do not delete - to be used in test case - # prof_loaded_from_influxdb = InfluxDBProfileManager(influxdb_conn_settings) # dicts = [{"tag": "output_esdl_id", "value": energy_system.id}] # prof_loaded_from_influxdb.load_influxdb( # # '"' + "ResidualHeatSource_72d7" + '"' , - # '"' + asset_name + '"' , + # asset_name, # variables_one_hydraulic_system, # # ["HeatIn.Q"], # # ["HeatIn.H"], @@ -1066,6 +1411,7 @@ def _name_to_asset(name): # profiles.end_datetime, # dicts, # ) + # test = 0.0 # ------------------------------------------------------------------------------ # Do not delete the code below: is used in the development of profile viewer in @@ -1152,14 +1498,15 @@ def _name_to_asset(name): # test = 0.0 # ------------------------------------------------------------------------------------------ # Save esdl file - - if self.esdl_parser_class == rtctools_heat_network.esdl.esdl_parser.ESDLFileParser: + # Edwin_marker_esdl_string - line 1224 + if self.esdl_parser_class == mesido.esdl.esdl_parser.ESDLFileParser: extension = "_Simulation.esdl" if optimizer_sim else "_GrowOptimized.esdl" file_path = Path(self.model_folder) / (Path(self.esdl_file_name).stem + extension) self.save_energy_system_to_file(energy_system, file_path=file_path) self.optimized_esdl_string = self.convert_energy_system_to_string( energy_system=energy_system ) + # self.__optimized_energy_system_handler = esh # self.optimized_esdl_string = esh.to_string() # @@ -1174,12 +1521,28 @@ def _name_to_asset(name): # ) # esh.save(str(filename)) - def _write_json_output(self): - # TODO: still add solver stats as json output - results = self.extract_results() + def _write_json_output( + self, + results: Union[AliasDict, Dict], + parameters: Union[AliasDict, Dict], + bounds: Union[AliasDict, Dict], + aliases: OrderedDict, + solver_stats: Dict, + ): + """ + The results, parameters, bounds are saved as json files which can be used for further + processing. Aliases are also saved as this allows us to only save the necessary variables. + :param results: dictionary or Alias dictionary with the results of the optimization problem + :param parameters: dictionary or Alias dictionary with the parameters of the optimization + problem + :param bounds: dictionary or Alias dictionary with the bounds of the optimization problem + :param aliases: Alias dictionary describing all the aliases for the variables used + :param solver_stats: solver statistics provided by the solver + :return: + """ + workdir = self.output_folder - parameters = self.parameters(0) parameters_dict = dict() parameter_path = os.path.join(workdir, "parameters.json") for key, value in parameters.items(): @@ -1188,7 +1551,6 @@ def _write_json_output(self): with open(parameter_path, "w") as file: json.dump(parameters_dict, fp=file) - bounds = self.bounds() bounds_dict = dict() bounds_path = os.path.join(workdir, "bounds.json") for key, value in bounds.items(): @@ -1201,7 +1563,6 @@ def _write_json_output(self): json.dump(bounds_dict, fp=file) results_dict = dict() - for key, values in results.items(): new_value = values.tolist() if len(new_value) == 1: @@ -1214,7 +1575,6 @@ def _write_json_output(self): # save aliases alias_dict = {} - aliases = self.alias_relation._canonical_variables_map for key, values in aliases.items(): new_value = values alias_dict[key] = new_value @@ -1222,3 +1582,9 @@ def _write_json_output(self): aliases_path = os.path.join(workdir, "aliases.json") with open(aliases_path, "w") as file: json.dump(alias_dict, fp=file) + + # save solver_stats + solver_stats_dict = solver_stats + solver_stats_path = os.path.join(workdir, "solver_stats.json") + with open(solver_stats_path, "w") as file: + json.dump(solver_stats_dict, fp=file) diff --git a/src/mesido/workflows/multicommodity_simulator_workflow.py b/src/mesido/workflows/multicommodity_simulator_workflow.py new file mode 100644 index 000000000..a713bd937 --- /dev/null +++ b/src/mesido/workflows/multicommodity_simulator_workflow.py @@ -0,0 +1,862 @@ +import locale +import logging +import time +from pathlib import Path + +import esdl + +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.network_common import NetworkSettings +from mesido.physics_mixin import PhysicsMixin +from mesido.workflows.io.write_output import ScenarioOutput +from mesido.workflows.utils.helpers import main_decorator + +import numpy as np + +from rtctools.optimization.collocated_integrated_optimization_problem import ( + CollocatedIntegratedOptimizationProblem, +) +from rtctools.optimization.goal_programming_mixin import Goal +from rtctools.optimization.linearized_order_goal_programming_mixin import ( + LinearizedOrderGoalProgrammingMixin, +) +from rtctools.optimization.single_pass_goal_programming_mixin import ( + CachingQPSol, + SinglePassGoalProgrammingMixin, +) +from rtctools.optimization.timeseries import Timeseries +from rtctools.util import run_optimization_problem + +DB_HOST = "172.17.0.2" +DB_PORT = 8086 +DB_NAME = "Warmtenetten" +DB_USER = "admin" +DB_PASSWORD = "admin" + +logger = logging.getLogger("WarmingUP-MPC") +logger.setLevel(logging.INFO) + +locale.setlocale(locale.LC_ALL, "") + +WATT_TO_MEGA_WATT = 1.0e6 +WATT_TO_KILO_WATT = 1.0e3 + + +def _extract_values_timeseries(v, type_r=None): + if isinstance(v, Timeseries): + v = v.values + if type_r == "min": + v = min(v) + elif type_r == "max": + v = max(v) + return v + + +class OptimisationOverview: + """ + This class is used to combine the optimisation results, bounds, parameters and aliases + needed for post-processing and visualisation. + """ + + def __init__(self, total_results, bounds, parameters, aliases): + self.results = total_results + self.bounds = bounds + self.parameters = parameters + self.aliases = aliases + + +# ------------------------------------------------------------------------------------------------- +# Step 1: +# Match the target demand specified +class TargetDemandGoal(Goal): + def __init__(self, state, target, priority=1, order=2): + self.state = state + + self.target_min = target + self.target_max = target + self.function_range = (-2.0 * max(target.values), 2.0 * max(target.values)) + self.function_nominal = np.median(target.values) + self.priority = priority + self.order = order + + def function(self, optimization_problem, ensemble_member): + return optimization_problem.state(self.state) + + +# ------------------------------------------------------------------------------------------------- +# Step 2: +# Match the maximum producer profiles +class TargetProducerGoal(Goal): + def __init__(self, state, target, priority=20, order=2): + self.state = state + + self.target_min = target + self.target_max = target + self.function_range = (-2.0 * max(target.values), 2.0 * max(target.values)) + self.function_nominal = np.median(target.values) + self.priority = priority + self.order = order + + def function(self, optimization_problem, ensemble_member): + return optimization_problem.state(self.state) + + +# ------------------------------------------------------------------------------------------------- +# Step 3: +# The merit order of the sources and consumers (something like [3, 1, 2]), determine the priority +# in which the source is available for use and the consumer to consume. +# The priorities are determined based on the marginal costs provided in ESDL. For producer, the +# lower the marginal costs, the more the producer should be used (e.g. cheap to use). For consumers +# the opposite is true, the higher the marginal costs (e.g. more revenue), the more energy should +# be delivered to that consumer. +# Minimize the source use with lowest priority 3 (highest marginal costs), then the source with +# priority 2 etc, while the consumers are maximised starting with the highest marginal costs. +class MinimizeSourcesGoalMerit(Goal): + """ + Apply constraints to enforce esdl specified milp producer merit order usage + """ + + def __init__(self, source_variable, prod_priority, func_range_bound, nominal, order=2): + self.target_max = 0.0 # func_range_bound[0] + self.function_range = func_range_bound + self.source_variable = source_variable + self.function_nominal = nominal + self.priority = prod_priority + self.order = order + + def function(self, optimization_problem, ensemble_member): + return optimization_problem.state(f"{self.source_variable}") + + +class MaximizeDemandGoalMerit(Goal): + """ + Apply constraints to enforce maximisation of consumption, priority is based on the marginal + costs + """ + + def __init__(self, demand_variable, prod_priority, func_range_bound, nominal, order=2): + + self.demand_variable = demand_variable + self.function_nominal = nominal + self.priority = prod_priority + self.order = 1 + + def function(self, optimization_problem, ensemble_member): + return -optimization_problem.state(f"{self.demand_variable}") + + +class MinimizeStorageGoalMerit(Goal): + """ + Apply constraints to enforce minimisation of charging of storage, priority is based on the + marginal costs + """ + + def __init__(self, source_variable, prod_priority, func_range_bound, nominal, order=2): + self.target_max = 0.0 + self.function_range = func_range_bound + self.source_variable = source_variable + self.function_nominal = nominal + self.priority = prod_priority + self.order = order + + def function(self, optimization_problem, ensemble_member): + return optimization_problem.state(f"{self.source_variable}") + + +class MaximizeStorageGoalMerit(Goal): + """ + Apply constraints to enforce maximisation of discharging of storage, priority is based on the + marginal costs + """ + + def __init__(self, demand_variable, prod_priority, func_range_bound, nominal, order=2): + self.target_min = func_range_bound[1] + self.function_range = func_range_bound + self.demand_variable = demand_variable + self.function_nominal = nominal + self.priority = prod_priority + self.order = order + + def function(self, optimization_problem, ensemble_member): + return optimization_problem.state(f"{self.demand_variable}") + + +# ------------------------------------------------------------------------------------------------- +class _GoalsAndOptions: + def path_goals(self): + goals = super().path_goals().copy() + + # Demand and producer matching + map_demand = { + "electricity_demand": { + "target": "target_electricity_demand", + "state": "Electricity_demand", + }, + "gas_demand": {"target": "target_gas_demand", "state": "Gas_demand_mass_flow"}, + } + map_prod = { + "electricity_source": { + "target": "maximum_electricity_source", + "state": "Electricity_source", + }, + "gas_source": {"target": "maximum_gas_source", "state": "Gas_source_mass_flow"}, + } + for type, type_values in [*map_demand.items(), *map_prod.items()]: + for asset in self.energy_system_components.get(type, []): + timeseries_name = f"{asset}.{type_values['target']}" + if timeseries_name in self.io.get_timeseries_names(): + target = self.get_timeseries(timeseries_name) + state = f"{asset}.{type_values['state']}" + if type in map_demand.keys(): + goals.append(TargetDemandGoal(state, target)) + else: + priority = 2 * len(self._esdl_assets) + goals.append(TargetProducerGoal(state, target, priority)) + + return goals + + +# ------------------------------------------------------------------------------------------------- +class MultiCommoditySimulator( + ScenarioOutput, + _GoalsAndOptions, + PhysicsMixin, + LinearizedOrderGoalProgrammingMixin, + SinglePassGoalProgrammingMixin, + ESDLMixin, + CollocatedIntegratedOptimizationProblem, +): + """ + This workflow allows for the simulation of (combined) hydrogen and electricity networks, + containing consumers, producers and conversion assets. + The priority of the consumers, producers and conversion assets is set using the marginal costs + in the ESDL file, allowing for flexible customised operation. Producers with the lowest marginal + costs are maximised in operation before other consumers are used, while consumers with the + highest marginal costs are maximised before other consumers are satisfied. In case both profiles + and marginal costs are provided for producers or consumers, then the marginal costs are ignored + and the profiles will be matched. always are preferred over the + To obtain this workflow the objective functions are setup according to the scheme described + below. + + Goal priorities are: + 1. Match target demand specified + 2. Producers with highest marginal costs are minimised and Consumers with highest marginal + costs are maximised first, working back towards the lower marginal costs. + 3. Producers with a production profile will be matched at end. This goal should be obsolete, as + the bound is set towards the production profile and other producers are first minimised. + + Notes: + - Currently all demand profiles can be used, however the length of the simulation is based on + the length and timestep of these profiles. Too long timehorizons might results in too big + problems for the solver. + - No cyclic constraints are yet applied to storages as this workflow solely functions as a + simulator. + - TODO: When the number of assets become larger, the simulator might be applied in stages with + consecutive parts of the time horizon. + """ + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self._qpsol = None + self._priorities_output = [] + + def pre(self): + self._qpsol = CachingQPSol() + + super().pre() + + @property + def esdl_assets(self): + assets = super().esdl_assets + + for asset in assets.values(): + # Overwrite all assets marked as optional to be used + if asset.attributes["state"].name in ["OPTIONAL"]: + asset.attributes["state"] = esdl.AssetStateEnum.ENABLED + logger.warning( + "The following asset has been specified as OPTIONAL but it has been changed " + f"to be included in the simulation, asset type: {asset.asset_type }, asset " + f"name: {asset.name}" + ) + + return assets + + def __create_asset_list_controls(self, asset_types_to_include, assets_without_control): + """ + This function creates the lists and dictionaries of assets to include in the optimization + based on the marginal costs, e.g. priorities. It excludes the assets who already have + assigned timeseries for demand or production. + Furthermore, it creates a map of the variables that are required for every asset. + :param asset_types_to_include: + :param assets_without_control: + :return: + """ + type_variable_map = { + "electricity_demand": "Electricity_demand", + "electricity_source": "Electricity_source", + "gas_demand": "Gas_demand_mass_flow", + "gas_source": "Gas_source_mass_flow", + "gas_tank_storage": {"charge": "Gas_tank_flow", "discharge": "__Q_discharge"}, + "electricity_storage": { + "charge": "Effective_power_charging", + "discharge": "__effective_power_discharging", + }, + "electrolyzer": "Power_consumed", + } + + assets_to_include = {} + asset_variable_map = {} + available_timeseries = [t.split(".")[0] for t in self.io.get_timeseries_names()] + for group, asset_types in asset_types_to_include.items(): + for asset_type in asset_types: + for asset in self.energy_system_components.get(asset_type, []): + if asset not in available_timeseries: + if group in assets_to_include.keys(): + assets_to_include[group].append(asset) + else: + assets_to_include[group] = [asset] + asset_variable_map[asset] = type_variable_map[asset_type] + + assets_list = [asset for a_type in assets_to_include.values() for asset in a_type] + unused_asset = [ + asset.asset_type + for asset in self.esdl_assets.values() + if asset.asset_type not in assets_without_control + if asset.name not in assets_list + if asset.name not in available_timeseries + ] + assert ( + len(unused_asset) == 0 + ), f"Asset types: {unused_asset} are not included in controls of the simulator" + + asset_info = { + "assets_to_include": assets_to_include, + "assets_to_include_list": assets_list, + "asset_variable_map": asset_variable_map, + } + return asset_info + + def __create_merit_path_goals(self, asset_info, max_value_merit, index_start_of_priority): + """ + This method creates the goals for every asset that is based on the marginal cost and the + relevant variable for that asset. Depending on the type of asset, the goal is a minimisation + or maximisation. + :param asset_info: + :param max_value_merit: + :param index_start_of_priority: + :return: + """ + goals = [] + assets_to_include = asset_info["assets_to_include"] + assets_list = asset_info["assets_to_include_list"] + asset_merit = asset_info["asset_merit"] + asset_variable_map = asset_info["asset_variable_map"] + for asset in assets_list: + index_s = asset_merit["asset_name"].index(f"{asset}") + marginal_priority = ( + index_start_of_priority + max_value_merit - asset_merit["merit_order"][index_s] + ) + assert ( + marginal_priority >= index_start_of_priority + ), "Priorities assigned must be smaller than the total number of producers" + + if asset in [ + *assets_to_include.get("source", []), + ]: + variable_name = f"{asset}.{asset_variable_map[asset]}" + + goals.append( + MinimizeSourcesGoalMerit( + variable_name, + marginal_priority, + self.bounds()[variable_name], + self.variable_nominal(variable_name), + ) + ) + elif asset in assets_to_include.get("conversion", []): + variable_name = f"{asset}.{asset_variable_map[asset]}" + index_s = asset_merit["asset_name"].index(f"{asset}_prod") + marginal_priority_source = ( + index_start_of_priority + max_value_merit - asset_merit["merit_order"][index_s] + ) + goals.append( + MinimizeSourcesGoalMerit( + variable_name, + marginal_priority_source, + self.bounds()[variable_name], + self.variable_nominal(variable_name), + ) + ) + variable_name = f"{asset}.Gas_mass_flow_out" + goals.append( + MaximizeDemandGoalMerit( + variable_name, + marginal_priority, + self.bounds()[variable_name], + self.variable_nominal(variable_name), + ) + ) + elif asset in assets_to_include.get("demand", []): + variable_name = f"{asset}.{asset_variable_map[asset]}" + + goals.append( + MaximizeDemandGoalMerit( + variable_name, + marginal_priority, + self.bounds()[variable_name], + self.variable_nominal(variable_name), + ) + ) + elif asset in assets_to_include.get("storage", []): + # TODO: should use separate variable for charging and discharging + + # charging acts as consumer + # Marginal costs for discharging > marginal cost for charging + variable_name = f"{asset}.{asset_variable_map[asset]['charge']}" + + func_range = self.bounds()[variable_name] + v1 = _extract_values_timeseries(func_range[0], "min") + v2 = _extract_values_timeseries(func_range[1], "max") + func_range = (v1, v2) + + goals.append( + MaximizeStorageGoalMerit( + variable_name, + marginal_priority, + func_range, + self.variable_nominal(variable_name), + ) + ) + + # discharging acts as producer + # Marginal costs for discharging should be larger than marginal cost for charging + # TODO: add check on the marginal costs for charging/discharging + index_s = asset_merit["asset_name"].index(f"{asset}_discharge") + marginal_priority = ( + index_start_of_priority + max_value_merit - asset_merit["merit_order"][index_s] + ) + assert ( + marginal_priority >= index_start_of_priority + ), "Priorities assigned must be smaller than the total number of producers" + + variable_name = f"{asset}{asset_variable_map[asset]['discharge']}" + + func_range = self.bounds()[variable_name] + v1 = _extract_values_timeseries(func_range[0], "min") + v2 = _extract_values_timeseries(func_range[1], "max") + func_range = (v1, v2) + + goals.append( + MinimizeStorageGoalMerit( + variable_name, + marginal_priority, + func_range, + self.variable_nominal(variable_name), + ) + ) + else: + raise Exception( + f"No goal was set for {asset}, while a priority was provided. This asset group " + f"still has to be added to the goals." + ) + return goals + + def __merit_path_goals(self): + """ + This method organizes the goals and assigns their priorities + The first two priorities are reserved for matching of demand. Thereby the priorities of the + other goals to maximize specific producers and minimize demand, start at priority 3. + :return: + """ + + # TODO: improve the asset_types_to_include and esdl_assets_to_include + asset_types_to_include = { + "source": ["electricity_source", "gas_source"], + "demand": ["electricity_demand", "gas_demand"], + "conversion": ["electrolyzer"], + "storage": ["gas_tank_storage", "electricity_storage"], + } + + assets_without_control = ["Pipe", "ElectricityCable", "Joint", "Bus"] + + # TODO also include other assets than producers, e.g. storage, conversion and possible + # demand for the ones without a profile + # TODO exclude producers from merit order if they have a profile, even if a marginal cost + # is set + + # Storage: charge priority should be higher than discharge priority + asset_info = self.__create_asset_list_controls( + asset_types_to_include, assets_without_control + ) + + asset_info["asset_merit"] = self.__merit_controls(asset_info["assets_to_include_list"]) + max_value_merit = max(asset_info["asset_merit"]["merit_order"]) + + # Priority 1 & 2 reserved for target demand goal & additional goal like matching + # producer profile (without merit order) + index_start_of_priority = 3 + + goals = self.__create_merit_path_goals(asset_info, max_value_merit, index_start_of_priority) + + return goals + + def path_goals(self): + goals = super().path_goals().copy() + + goals.extend(self.__merit_path_goals()) + + return goals + + def energy_system_options(self): + options = super().energy_system_options() + + self.gas_network_settings["head_loss_option"] = HeadLossOption.LINEARIZED_N_LINES_EQUALITY + self.gas_network_settings["network_type"] = NetworkSettings.NETWORK_TYPE_HYDROGEN + self.gas_network_settings["minimize_head_losses"] = False + self.gas_network_settings["maximum_velocity"] = 60.0 + options["include_asset_is_switched_on"] = True + options["estimated_velocity"] = 7.5 + + options["gas_storage_discharge_variables"] = True + options["electricity_storage_discharge_variables"] = True + + return options + + def path_constraints(self, ensemble_member): + """ + Constraints to limit producer production in case timeseries for the production exist, + relevant when the first goals is not to match profile. + """ + constraints = super().path_constraints(ensemble_member) + + return constraints + + def constraints(self, ensemble_member): + """ + Add equality constraints to enforce a cyclic energy balance [J] between the end and the + start of the time horizon used as well an inequality constraint to enforce no milp supply + [W] to the netwok in the 1st time step + """ + constraints = super().constraints(ensemble_member) + + # TODO: cyclic constraints + + return constraints + + def __merit_controls(self, assets_list): + attributes = { + "asset_name": [], + "merit_order": [], + } + + assets = self.esdl_assets + for a in assets.values(): + if a.name in assets_list: + attributes["asset_name"].append(a.name) + try: + attributes["merit_order"].append( + a.attributes["costInformation"].marginalCosts.value + ) + if ( + a.asset_type == "Electrolyzer" + ): # electrolyzer would require minimisation of electricity right after + # maximisation gas, therefore a merit_order with a very small adjusted + # value is used (e.g. 1e-6) to ensure these goals are right after each + # other and no other goals are in between. + attributes["asset_name"].append(f"{a.name}_prod") + attributes["merit_order"].append( + a.attributes["costInformation"].marginalCosts.value - 1e-6 + ) + + except AttributeError: + try: + attributes["merit_order"].append( + a.attributes["controlStrategy"].marginalChargeCosts.value + ) + attributes["merit_order"].append( + a.attributes["controlStrategy"].marginalDischargeCosts.value + ) + attributes["asset_name"].append(f"{a.name}_discharge") + except AttributeError: + raise Exception(f"Asset: {a.name} does not have a merit order specified") + + last_merit_order = attributes["merit_order"][-1] + + if attributes["merit_order"][-1] <= 0.0: + raise Exception( + "The specified producer usage merit order must be a " + f"positve integer value, producer name:{a.name}, current " + f"specified merit value: {last_merit_order}" + ) + + # update merit order to be integers and have maximumally one step in priority + set_merit = set(attributes["merit_order"]) + order_prio = list(set_merit) + order_prio.sort() + map_prio = dict(zip(order_prio, list(range(1, len(set_merit) + 1)))) + a = [map_prio[v] for v in attributes["merit_order"]] + attributes["merit_order"] = a + return attributes + + def solver_options(self): + options = super().solver_options() + options["casadi_solver"] = self._qpsol + + options["solver"] = "highs" + highs_options = options["highs"] = {} + highs_options["presolve"] = "on" + + return options + + def priority_started(self, priority): + goals_print = set() + for goal in [*self.path_goals(), *self.goals()]: + if goal.priority == priority: + goals_print.update([str(type(goal))]) + logger.info(f"{goals_print}") + self.__priority = priority + self.__priority_timer = time.time() + + super().priority_started(priority) + + def priority_completed(self, priority): + super().priority_completed(priority) + + self._hot_start = True + + time_taken = time.time() - self.__priority_timer + self._priorities_output.append( + ( + priority, + time_taken, + True, + self.objective_value, + self.solver_stats, + ) + ) + logger.info(f"Goal with priority {priority} has been completed") + if priority == 1 and self.objective_value > 1e-6: + raise RuntimeError( + f"The heating demand is not matched, objective value is {self.objective_value}" + ) + + def __state_vector_scaled(self, variable, ensemble_member): + canonical, sign = self.alias_relation.canonical_signed(variable) + return ( + self.state_vector(canonical, ensemble_member) * self.variable_nominal(canonical) * sign + ) + + # TODO: post will be created later + # def post(self): + # super().post() + # self._write_updated_esdl(self.get_energy_system_copy(), optimizer_sim=True) + + +# ------------------------------------------------------------------------------------------------- +class MultiCommoditySimulatorHIGHS(MultiCommoditySimulator): + + def solver_options(self): + options = super().solver_options() + options["solver"] = "highs" + + return options + + +class MultiCommoditySimulatorNoLosses(MultiCommoditySimulator): + def energy_system_options(self): + options = super().energy_system_options() + + self.gas_network_settings["head_loss_option"] = HeadLossOption.NO_HEADLOSS + self.gas_network_settings["minimize_head_losses"] = False + options["include_electric_cable_power_loss"] = False + + return options + + def solver_options(self): + # For some cases the presolve of the HIGHS solver makes this problem infeasible, therefore + # the presolve is turned off. + options = super().solver_options() + options["solver"] = "highs" + highs_options = options["highs"] = {} + highs_options["presolve"] = "off" + + return options + + +def run_sequatially_staged_simulation( + multi_commodity_simulator_class, simulation_window_size=2, *args, **kwargs +): + """ + This function is to run the MultiCommoditySimulator class in a staged manner where the stages + are sequantial parts of the time horizon. This is done to make the problem smaller and allow + for quicker run of the optimization/simulation. To ensure a physically sound result the + variables that affect the outcome of the next stage are constrained by setting bounds, e.g. the + amount of stored energy in a storage. + + Parameters + ---------- + multi_commodity_simulator_class : The problem class to run + simulation_window_size : The amount of indices to run in a single stage + + Returns + ------- + The results dict where all the time results are concatenated. + """ + + class MultiCommoditySimulatorTimeSequential(multi_commodity_simulator_class): + """ + This Problem class is used to run the MultiCommoditySimulator class in a sequantial manner + to reduce computational time. This class enables this by allowing to run a part of the + timeseries and setting bounds on the (initial-)state variables. + """ + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + self.__start_time_index = kwargs.get("start_index", None) + self.__end_time_index = kwargs.get("end_index", None) + self._full_time_series = None + + self.__storage_initial_state_bounds = kwargs.get("storage_initial_state_bounds", {}) + + def times(self, variable=None) -> np.ndarray: + """ + In this function the part of the time-horizon is enforced. Note that the full + time-horizon is also set to an internal member for enabling setting bounds to the next + sequantial optimization. + """ + if self._full_time_series is None: + self._full_time_series = super().times(variable) + + if self.__start_time_index is not None and self.__end_time_index is not None: + return super().times(variable)[self.__start_time_index : self.__end_time_index] + elif self.__start_time_index is not None: + return super().times(variable)[self.__start_time_index :] + elif self.__end_time_index is not None: + return super().times(variable)[: self.__end_time_index] + else: + return super().times(variable) + + def bounds(self): + """ + Here we set bounds on the initial state to ensure that the sequantial simulation is a + physcially valid. + """ + bounds = super().bounds() + bounds.update(self.__storage_initial_state_bounds) + return bounds + + # Note that the window size should be larger than 1 otherwise this function is has no + # benefit and the writing of the results dict will fail. + assert simulation_window_size >= 2 + + total_results = None + # This is an initial value for end_time, will be corrected after the first stage + end_time = 2 * simulation_window_size + end_time_confirmed = False + storage_initial_state_bounds = {} + + # TODO: make this dict complete for all relevant assets and their associated variables. + constrained_assets = { + "electricity_storage": ["Stored_electricity", "Effective_power_charging"], + "gas_tank_storage": ["Stored_gas_mass", "Gas_tank_flow"], + } + + tic = time.time() + for simulated_window in range(0, end_time, simulation_window_size): + + # Note that the end time is not necessarily a multiple of simulation_window_size + sub_end_time = min(end_time, simulated_window + simulation_window_size) + + # max operation for start_index to avoid the overlap function in the first stage + solution = run_optimization_problem( + MultiCommoditySimulatorTimeSequential, + start_index=max(simulated_window - 1, 0), + end_index=sub_end_time, + storage_initial_state_bounds=storage_initial_state_bounds, + **kwargs, + ) + if not end_time_confirmed: + end_time = len(solution._full_time_series) + end_time_confirmed = True + results = solution.extract_results() + + # TODO: check if we now capture all relevant variables. + if total_results is None: + total_results = results + aliases = solution.alias_relation._canonical_variables_map + bounds = solution.bounds() + parameters = solution.parameters(0) + else: + for key, data in results.items(): + if len(total_results[key]) > 1: + total_results[key] = np.concatenate((total_results[key], data[1:])) + + if sub_end_time < end_time: + for asset_type, variables in constrained_assets.items(): + for asset in solution.energy_system_components.get(asset_type, []): + sub_time_series = solution._full_time_series[ + simulated_window + - 1 + + simulation_window_size : min( + end_time, simulated_window + 2 * simulation_window_size + ) + ] + for variable in variables: + lb_value = _extract_values_timeseries( + solution.bounds()[f"{asset}.{variable}"][0], "min" + ) + ub_value = _extract_values_timeseries( + solution.bounds()[f"{asset}.{variable}"][1], "max" + ) + lb_values = [lb_value] * len(sub_time_series) + ub_values = [ub_value] * len(sub_time_series) + lb_values[0] = ub_values[0] = results[f"{asset}.{variable}"][-1] + lb = Timeseries(sub_time_series, lb_values) + ub = Timeseries(sub_time_series, ub_values) + storage_initial_state_bounds[f"{asset}.{variable}"] = (lb, ub) + + print(time.time() - tic) + + return OptimisationOverview(total_results, bounds, parameters, aliases) + + +# ------------------------------------------------------------------------------------------------- +@main_decorator +def main(runinfo_path, log_level): + logger.info("Run Network Simulator") + + kwargs = { + "write_result_db_profiles": False, + "influxdb_host": "localhost", + "influxdb_port": 8086, + "influxdb_username": None, + "influxdb_password": None, + "influxdb_ssl": False, + "influxdb_verify_ssl": False, + } + + _ = run_optimization_problem( + MultiCommoditySimulatorHIGHS, + esdl_run_info_path=runinfo_path, + log_level=log_level, + **kwargs, + ) + + +if __name__ == "__main__": + # main() + import tests.models.emerge.src.example as example + + base_folder = Path(example.__file__).resolve().parent.parent + solution = run_optimization_problem( + MultiCommoditySimulatorNoLosses, + base_folder=base_folder, + esdl_file_name="emerge_priorities_withoutstorage.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) diff --git a/src/rtctools_heat_network/workflows/simulator_workflow.py b/src/mesido/workflows/simulator_workflow.py similarity index 95% rename from src/rtctools_heat_network/workflows/simulator_workflow.py rename to src/mesido/workflows/simulator_workflow.py index 117d9a76d..684521b93 100644 --- a/src/rtctools_heat_network/workflows/simulator_workflow.py +++ b/src/mesido/workflows/simulator_workflow.py @@ -3,6 +3,15 @@ import esdl +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.head_loss_class import HeadLossOption +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.io.write_output import ScenarioOutput +from mesido.workflows.utils.adapt_profiles import ( + adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day, +) +from mesido.workflows.utils.helpers import main_decorator + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -19,16 +28,6 @@ from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.head_loss_class import HeadLossOption -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin -from rtctools_heat_network.workflows.io.write_output import ScenarioOutput -from rtctools_heat_network.workflows.utils.adapt_profiles import ( - adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day, -) -from rtctools_heat_network.workflows.utils.helpers import main_decorator - - DB_HOST = "172.17.0.2" DB_PORT = 8086 DB_NAME = "Warmtenetten" @@ -313,7 +312,10 @@ def __state_vector_scaled(self, variable, ensemble_member): class NetworkSimulatorHIGHS(NetworkSimulator): def post(self): super().post() - self._write_updated_esdl(self.get_energy_system_copy(), optimizer_sim=True) + self._write_updated_esdl( + self._ESDLMixin__energy_system_handler.energy_system, + optimizer_sim=True, + ) def solver_options(self): options = super().solver_options() @@ -354,7 +356,7 @@ def read(self): """ super().read() - self.__indx_max_peak, _ = adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day( + self.__indx_max_peak, _, _ = adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day( self, self.__day_steps ) logger.info("HeatProblem read") diff --git a/src/mesido/workflows/utils/__init__.py b/src/mesido/workflows/utils/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/mesido/workflows/utils/adapt_profiles.py b/src/mesido/workflows/utils/adapt_profiles.py new file mode 100644 index 000000000..013dc6b6a --- /dev/null +++ b/src/mesido/workflows/utils/adapt_profiles.py @@ -0,0 +1,313 @@ +from __future__ import annotations + +import datetime +import logging +import operator +import sys + +import numpy as np + +from rtctools.data.storage import DataStore + + +logger = logging.getLogger("WarmingUP-MPC") +logger.setLevel(logging.INFO) + + +def set_data_with_averages( + datastore: DataStore, + variable_name: str, + ensemble_member: int, + new_date_times: np.array, + problem: object, +): + try: + data = problem.get_timeseries(variable=variable_name, ensemble_member=ensemble_member) + except KeyError: + datastore.set_timeseries( + variable=variable_name, + datetimes=new_date_times, + values=np.asarray([0.0] * len(new_date_times)), + ensemble_member=ensemble_member, + check_duplicates=True, + ) + return + + new_data = [] + data_timestamps = data.times + new_date_timestamps = [ + (new_dt - problem.io.datetimes[0]).total_seconds() for new_dt in new_date_times + ] + + values_for_mean = [0.0] + for dt, val in zip(data_timestamps, data.values): + if dt in new_date_timestamps: + new_data.append(np.mean(values_for_mean)) + values_for_mean = [val] + else: + values_for_mean.append(val) + + # At this point new_data[0] = 0.0. This value is not utilized. The heat demand value + # new_data[1] at new_date_times[1] is active from new_date_times[0] up to new_date_times[1]. To + # ensure a no 0.0 heat demand values end up in the optimization, new_data[0] is forced to have + # an artificial value below + new_data[0] = new_data[1] + + # last datetime is not in input data, so we need to take the mean of the last bit + new_data.append(np.mean(values_for_mean)) + + datastore.set_timeseries( + variable=variable_name, + datetimes=new_date_times, + values=np.asarray(new_data), + ensemble_member=ensemble_member, + check_duplicates=True, + ) + + +def adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day(problem, problem_day_steps: int): + """ + Adapt yearly porifle with hourly time steps to a common profile (daily averaged profile except + for the day with the peak demand). + + Return the following: + - problem_indx_max_peak: index of the maximum of the peak values + - heat_demand_nominal: max demand value found for a specific heating demand + - cold_demand_nominal: max cold demand value found for a specific cold demand + """ + + # Extract heat and cold demand assets + heat_demands = problem.energy_system_components.get("heat_demand", []) + cold_demands = problem.energy_system_components.get("cold_demand", []) + new_datastore = DataStore(problem) + new_datastore.reference_datetime = problem.io.datetimes[0] + + for ensemble_member in range(problem.ensemble_size): + parameters = problem.parameters(ensemble_member) + + total_heat_demand = None + heat_demand_nominal = dict() + # Assemble all demands together to get the peaks. + for demand in heat_demands: + try: + demand_values = problem.get_timeseries( + f"{demand}.target_heat_demand", ensemble_member + ).values + except KeyError: + continue + if total_heat_demand is None: + total_heat_demand = demand_values + else: + total_heat_demand += demand_values + heat_demand_nominal[f"{demand}.Heat_demand"] = max(demand_values) + heat_demand_nominal[f"{demand}.Heat_flow"] = max(demand_values) + + total_cold_demand = None + cold_demand_nominal = dict() + for demand in cold_demands: + try: + cold_demand_values = problem.get_timeseries( + f"{demand}.target_cold_demand", ensemble_member + ).values + except KeyError: + continue + if total_cold_demand is None: + total_cold_demand = cold_demand_values + else: + total_cold_demand += cold_demand_values + cold_demand_nominal[f"{demand}.Cold_demand"] = max(cold_demand_values) + cold_demand_nominal[f"{demand}.Heat_flow"] = max(cold_demand_values) + + new_date_times = list() + nr_of_days = len(total_heat_demand) // 24 + day_steps = problem_day_steps + + peak_days = [] + if total_heat_demand is not None: + idx_max_hot = int(np.argmax(total_heat_demand)) + max_day_hot = idx_max_hot // 24 + + problem_indx_max_peak = max_day_hot // day_steps + if max_day_hot % day_steps > 0: + problem_indx_max_peak += 1.0 + + peak_days.append(max_day_hot) + else: + max_day_hot = None + + if total_cold_demand is not None: + idx_max_cold = int(np.argmax(total_cold_demand)) + max_day_cold = idx_max_cold // 24 + + problem_indx_max_peak_cold = max_day_cold // day_steps + if max_day_cold % day_steps > 0: + problem_indx_max_peak_cold += 1.0 + + peak_days.append(max_day_cold) + else: + max_day_cold = None + + # TODO: the approach of picking one peak day was introduced for a network with a tree + # layout and all big sources situated at the root of the tree. It is not guaranteed + # that an optimal solution is reached in different network topologies. + + peak_days = sorted(peak_days) + peak_check_days = np.array(peak_days) // day_steps * day_steps + + current_peak_idx = 0 + for day in range(0, nr_of_days, day_steps): + if day in peak_check_days: + peak_day = peak_days[current_peak_idx] + if peak_day > day: + new_date_times.append(problem.io.datetimes[day * 24]) + new_date_times.extend(problem.io.datetimes[peak_day * 24 : peak_day * 24 + 24]) + if (day + day_steps - 1) > peak_day: + new_date_times.append(problem.io.datetimes[peak_day * 24 + 24]) + current_peak_idx += 1 + else: + new_date_times.append(problem.io.datetimes[day * 24]) + + new_date_times.append(problem.io.datetimes[-1] + datetime.timedelta(hours=1)) + + new_date_times = np.asarray(new_date_times) + parameters["times"] = [x.timestamp() for x in new_date_times] + + select_profiles_for_update(problem, new_datastore, new_date_times, ensemble_member) + + problem.io = new_datastore + + logger.info("Profile data has been adapted to a common format") + + return problem_indx_max_peak, heat_demand_nominal, cold_demand_nominal + + +def adapt_hourly_profile_averages_timestep_size(problem, problem_step_size_hours: int): + """ + Adapt yearly porifle with hourly time steps to a common profile with average over a given + stepsize in hours. + + Return the following: + + """ + + new_datastore = DataStore(problem) + new_datastore.reference_datetime = problem.io.datetimes[0] + + org_timeseries = problem.io.datetimes + org_dt = list(map(operator.sub, org_timeseries[1:], org_timeseries[0:-1])) + assert all(dt.seconds == 3600 for dt in org_dt) # checks that the orginal timeseries has + # homogenous horizon with equispaced timesteps of 3600s (1hr). + + for ensemble_member in range(problem.ensemble_size): + parameters = problem.parameters(ensemble_member) + + new_date_times = list() + + for hour in range(0, len(org_timeseries), problem_step_size_hours): + new_date_times.append(problem.io.datetimes[hour]) + + new_date_times.append(problem.io.datetimes[-1] + datetime.timedelta(hours=1)) + + new_date_times = np.asarray(new_date_times) + parameters["times"] = [x.timestamp() for x in new_date_times] + + select_profiles_for_update(problem, new_datastore, new_date_times, ensemble_member) + + problem.io = new_datastore + + logger.info("Profile data has been adapted to a common format") + + +def adapt_profile_to_copy_for_number_of_years(problem, number_of_years: int): + """ + Adapt yearly profile to a multi-year profile. + Copying the profile for the given number of years, where the timeline is updated with the + sequential years. + + """ + + new_datastore = DataStore(problem) + new_datastore.reference_datetime = problem.io.datetimes[0] + + org_timeseries = problem.io.datetimes + + # If a problem has already been modified, the last timestamp should be exactly 1 year after + # the first timestamp. + + skip_last_day = False + if org_timeseries[-1] == org_timeseries[0] + datetime.timedelta(days=365): + skip_last_day = True + elif org_timeseries[0] + datetime.timedelta(days=365) - org_timeseries[ + -1 + ] <= datetime.timedelta(hours=1): + skip_last_day = False + else: + sys.exit("The profile should be a year profile.") + + for ensemble_member in range(problem.ensemble_size): + parameters = problem.parameters(ensemble_member) + + new_date_times = list() + if skip_last_day is False: + new_date_times = org_timeseries.copy() + else: + new_date_times = org_timeseries[:-1].copy() + + for year in range(1, number_of_years): + if year == number_of_years - 1 or skip_last_day is False: + new_date_times.extend( + [i + year * datetime.timedelta(days=365) for i in org_timeseries] + ) + else: + new_date_times.extend( + [i + year * datetime.timedelta(days=365) for i in org_timeseries[:-1]] + ) + + new_date_times = np.asarray(new_date_times) + parameters["times"] = [x.timestamp() for x in new_date_times] + + for var_name in problem.io.get_timeseries_names(): + old_data = problem.io.get_timeseries(var_name)[1] + if skip_last_day: + new_data = np.append(np.tile(old_data[:-1], number_of_years), old_data[-1]) + else: + new_data = np.tile(old_data, number_of_years) + new_datastore.set_timeseries( + variable=var_name, + datetimes=new_date_times, + values=np.asarray(new_data), + ensemble_member=ensemble_member, + check_duplicates=True, + ) + + problem.io = new_datastore + + logger.info("Profile data has been adapted to a common format") + + +def select_profiles_for_update( + problem, new_datastore: DataStore, new_date_times: np.array, ensemble_member: int +): + """ + Selects all the profiles that are relevant for the problem and runs the method to set the new + updated timeseries. + + Args: + problem: optimization problem class + new_datastore: the new datastore object that should be filled + new_date_times: the new date time entries that are required + ensemble_member: + + Returns: + + """ + + timeseries_names = problem.io.get_timeseries_names() + for var_name in timeseries_names: + set_data_with_averages( + datastore=new_datastore, + variable_name=var_name, + ensemble_member=ensemble_member, + new_date_times=new_date_times, + problem=problem, + ) diff --git a/src/mesido/workflows/utils/error_types.py b/src/mesido/workflows/utils/error_types.py new file mode 100644 index 000000000..a12cd44ce --- /dev/null +++ b/src/mesido/workflows/utils/error_types.py @@ -0,0 +1,74 @@ +from enum import Enum + +from mesido.potential_errors import MesidoAssetIssueType, get_potential_errors + +# Convert potentials errors to errors for the following networks/definitions +HEAT_NETWORK_ERRORS = "heat_network" +HEAT_AND_COOL_NETWORK_ERRORS = "heat_and_cool_network" +CUSTOM_ERRORS = "custom_errors" # an example of custom stuff that can be added in the future + + +def mesido_issue_type_gen_message(issue_type: MesidoAssetIssueType) -> str: + """ + Get general message per issue type. + + Returns + ------- + String message + """ + type_and_general_meassage = { + MesidoAssetIssueType.HEAT_PRODUCER_POWER: "Asset insufficient installed capacity: please" + " increase the installed power or reduce the profile constraint peak value of the" + " producer(s) listed.", + MesidoAssetIssueType.HEAT_DEMAND_POWER: "Asset insufficient installed capacity: please" + " increase the installed power or reduce the demand profile peak value of the demand(s)" + " listed.", + MesidoAssetIssueType.COLD_DEMAND_POWER: "Asset insufficient installed capacity: please" + " increase the installed power or reduce the demand profile peak value of the demand(s)" + " listed.", + MesidoAssetIssueType.HEAT_DEMAND_TYPE: "Incorrect asset type: please update.", + MesidoAssetIssueType.ASSET_PROFILE_CAPABILITY: "Profile assigment not allowed.", + MesidoAssetIssueType.HEAT_EXCHANGER_TEMPERATURES: "Temperatures at heat exchanger set " + "incorrectly.", + } + + return type_and_general_meassage[issue_type] + + +def potential_error_to_error(network_check_type: Enum) -> None: + """ + Convert potential errors to errors for the define error types + + """ + + errors_on_types = { + HEAT_NETWORK_ERRORS: [ + MesidoAssetIssueType.HEAT_PRODUCER_POWER, + MesidoAssetIssueType.HEAT_DEMAND_POWER, + MesidoAssetIssueType.COLD_DEMAND_POWER, + MesidoAssetIssueType.HEAT_DEMAND_TYPE, + MesidoAssetIssueType.ASSET_PROFILE_CAPABILITY, + MesidoAssetIssueType.HEAT_EXCHANGER_TEMPERATURES, + ], + HEAT_AND_COOL_NETWORK_ERRORS: [ + MesidoAssetIssueType.HEAT_DEMAND_POWER, + MesidoAssetIssueType.COLD_DEMAND_POWER, + MesidoAssetIssueType.HEAT_DEMAND_TYPE, + MesidoAssetIssueType.ASSET_PROFILE_CAPABILITY, + MesidoAssetIssueType.HEAT_EXCHANGER_TEMPERATURES, + ], + # Example of extra error types / groups that can be added. This one is not used yet. + CUSTOM_ERRORS: [MesidoAssetIssueType.ASSET_PROFILE_CAPABILITY], + } + + # Error checking: + # - installed capacity/power of a heating/cooling demand is sufficient for the specified + # demand profile + # - asset used for a heating demand + # - profile assigment capability + # TODO: Once pyhton 3.11 is used, use the following: Group multiple exceptions (as it is + # possible multiple exceptions at once are true here): + # https://www.geeksforgeeks.org/exception-groups-in-python/ + for etype in errors_on_types[network_check_type]: + if get_potential_errors().have_issues_for(etype): + get_potential_errors().convert_to_exception(etype, mesido_issue_type_gen_message(etype)) diff --git a/src/rtctools_heat_network/workflows/utils/helpers.py b/src/mesido/workflows/utils/helpers.py similarity index 77% rename from src/rtctools_heat_network/workflows/utils/helpers.py rename to src/mesido/workflows/utils/helpers.py index 6cc2ff2bb..6f711b9af 100644 --- a/src/rtctools_heat_network/workflows/utils/helpers.py +++ b/src/mesido/workflows/utils/helpers.py @@ -7,7 +7,9 @@ import esdl -from rtctools_heat_network import __version__ +from mesido import __version__ + +from rtctools.util import run_optimization_problem MULTI_ENUM_NAME_TO_FACTOR = { @@ -132,3 +134,37 @@ def get_cost_value_and_unit(cost_info: esdl.SingleValue): cost_value /= MULTI_ENUM_NAME_TO_FACTOR[per_multiplier] return cost_value, unit, per_unit, per_time_uni + + +def run_optimization_problem_solver( + scenario_problem_class, + solver_class=None, + **kwargs, +): + """ + This method runs the optimisation problem based on the scenario_problem_class. An additional + solver_class can be added to substitute the default solver options of the problem definition + class. + :param scenario_problem_class: Class defining the optimization problem + :param solver_class: Class defining the solver settings. + :param kwargs: + :return: + """ + + new_solver = False + if solver_class: + + if not issubclass(scenario_problem_class, solver_class): + # if solver_class is already a subclass of the problem class, then these settings are + # already used and it should not be added to the inheritance structure. + class ProblemSolverClass(solver_class, scenario_problem_class): + pass + + solution = run_optimization_problem(ProblemSolverClass, **kwargs) + + new_solver = True + + if not new_solver: + solution = run_optimization_problem(scenario_problem_class, **kwargs) + + return solution diff --git a/src/rtctools_heat_network/component_type_mixin.py b/src/rtctools_heat_network/component_type_mixin.py deleted file mode 100644 index b7d2aee80..000000000 --- a/src/rtctools_heat_network/component_type_mixin.py +++ /dev/null @@ -1,335 +0,0 @@ -import logging -from typing import Dict, Set - -from pymoca.backends.casadi.alias_relation import AliasRelation - -from .base_component_type_mixin import BaseComponentTypeMixin -from .heat_network_common import NodeConnectionDirection -from .topology import Topology - -logger = logging.getLogger("rtctools_heat_network") - - -class ModelicaComponentTypeMixin(BaseComponentTypeMixin): - """ - This class is used to make the milp network component information easily accesible in the - heat_mixin. This is achieved by creating a heat_network_components dict where the assets are - sorted by asset_type. Furthermore, the topology object is created in which for specific assets - the connections with directions are saved for later use in the constraints. - """ - - def __init__(self, *args, **kwargs): - super().__init__(**kwargs) - self.__hn_component_types = None - - def pre(self): - """ - In this function the topology object of the milp network is constructed. Meaning that for - nodes, busses and storage assets their relevant information on the positive flow direction - and connections on the ports is gathered and stored in the topology object. - """ - components = self.energy_system_components - nodes = components.get("node", []) - busses = components.get("electricity_node", []) - gas_nodes = components.get("gas_node", []) - buffers = components.get("heat_buffer", []) - atess = components.get("ates", []) - try: - pipes = components["heat_pipe"] - cables = components.get("electricity_cable", []) - gas_pipes = components.get("gas_pipe", []) - except KeyError: - try: - cables = components["electricity_cable"] - gas_pipes = components.get("gas_pipe", []) - pipes = [] - except KeyError: - try: - cables = [] - gas_pipes = components["gas_pipe"] - pipes = [] - except KeyError: - logger.error( - "A valid network should have at least one pipe/cable, " - "assets cannot be connected directly" - ) - - # Figure out which pipes are connected to which nodes, which pipes - # are connected in series, and which pipes are connected to which buffers. - - pipes_set = set(pipes) - cables_set = set(cables) - gas_pipes_set = set(gas_pipes) - parameters = [self.parameters(e) for e in range(self.ensemble_size)] - node_connections = {} - bus_connections = {} - gas_node_connections = {} - - # Figure out if we are dealing with a Heat model, or a QTH model - try: - if len(pipes): - _ = self.variable(f"{pipes[0]}.HeatIn.Heat") - heat_network_model_type = "Heat" - else: - heat_network_model_type = "Heat" - except KeyError: - heat_network_model_type = "QTH" - - for n in [*nodes, *busses, *gas_nodes]: - n_connections = [ens_params[f"{n}.n"] for ens_params in parameters] - - if len(set(n_connections)) > 1: - raise Exception( - "Nodes and busses cannot have differing number of connections per " - "ensemble member" - ) - - n_connections = n_connections[0] - - # Note that we do this based on temperature, because discharge may - # be an alias of yet some other further away connected pipe. - if n in nodes: - node_connections[n] = connected_pipes = {} - elif n in busses: - bus_connections[n] = connected_pipes = {} - elif n in gas_nodes: - gas_node_connections[n] = connected_pipes = {} - - for i in range(n_connections): - if n in nodes: - cur_port = f"{n}.{heat_network_model_type}Conn[{i + 1}]" - prop = "T" if heat_network_model_type == "QTH" else "Heat" - in_suffix = ".QTHIn.T" if heat_network_model_type == "QTH" else ".HeatIn.Heat" - out_suffix = ( - ".QTHOut.T" if heat_network_model_type == "QTH" else ".HeatOut.Heat" - ) - elif n in busses: - cur_port = f"{n}.ElectricityConn[{i + 1}]" - prop = "Power" - in_suffix = ".ElectricityIn.Power" - out_suffix = ".ElectricityOut.Power" - elif n in gas_nodes: - # TODO: Ideally a temporary variable would be created to make the connections - # map that is not passed to the problem - cur_port = f"{n}.GasConn[{i + 1}]" - prop = "Q_shadow" - in_suffix = ".GasIn.Q_shadow" - out_suffix = ".GasOut.Q_shadow" - aliases = [ - x - for x in self.alias_relation.aliases(f"{cur_port}.{prop}") - if not x.startswith(n) and x.endswith(f".{prop}") - ] - - if len(aliases) > 1: - raise Exception(f"More than one connection to {cur_port}") - elif len(aliases) == 0: - raise Exception(f"Found no connection to {cur_port}") - - if aliases[0].endswith(out_suffix): - pipe_w_orientation = ( - aliases[0][: -len(out_suffix)], - NodeConnectionDirection.IN, - ) - else: - assert aliases[0].endswith(in_suffix) - pipe_w_orientation = ( - aliases[0][: -len(in_suffix)], - NodeConnectionDirection.OUT, - ) - - assert ( - pipe_w_orientation[0] in pipes_set - or pipe_w_orientation[0] in cables_set - or pipe_w_orientation[0] in gas_pipes_set - ) - - connected_pipes[i] = pipe_w_orientation - - # Note that a pipe series can include both hot and cold pipes for - # QTH models. It is only about figuring out which pipes are - # related direction-wise. - # For Heat models, only hot pipes are allowed to be part of pipe - # series, as the cold part is zero milp by construction. - if heat_network_model_type == "QTH": - alias_relation = self.alias_relation - elif heat_network_model_type == "Heat": - # There is no proper AliasRelation yet (because there is milp loss in pipes). - # So we build one, as that is the easiest way to figure out which pipes are - # connected to each other in series. We do this by making a temporary/shadow - # discharge (".Q") variable per pipe, as that way we can share the processing - # logic for determining pipe series with that of QTH models. - alias_relation = AliasRelation() - - # Look for aliases only in the hot pipes. All cold pipes are zero by convention anyway. - hot_pipes = self.hot_pipes.copy() - - pipes_map = {f"{pipe}.HeatIn.Heat": pipe for pipe in hot_pipes} - pipes_map.update({f"{pipe}.HeatOut.Heat": pipe for pipe in hot_pipes}) - - for p in hot_pipes: - for port in ["In", "Out"]: - heat_port = f"{p}.Heat{port}.Heat" - connected = self.alias_relation.aliases(heat_port).intersection( - pipes_map.keys() - ) - connected.remove(heat_port) - - if connected: - other_pipe_port = next(iter(connected)) - if other_pipe_port.endswith(f".Heat{port}.Heat"): - sign_prefix = "-" - else: - sign_prefix = "" - other_pipe = pipes_map[other_pipe_port] - if f"{other_pipe}.Q" not in alias_relation.canonical_variables: - alias_relation.add(f"{p}.Q", f"{sign_prefix}{other_pipe}.Q") - - canonical_pipe_qs = {p: alias_relation.canonical_signed(f"{p}.Q") for p in pipes} - # Move sign from canonical to alias - canonical_pipe_qs = {(p, d): c for p, (c, d) in canonical_pipe_qs.items()} - # Reverse the dictionary from `Dict[alias, canonical]` to `Dict[canonical, Set[alias]]` - pipe_sets = {} - for a, c in canonical_pipe_qs.items(): - pipe_sets.setdefault(c, []).append(a) - - pipe_series_with_orientation = list(pipe_sets.values()) - - # Check that all pipes in the series have the same orientation - pipe_series = [] - for ps in pipe_series_with_orientation: - if not len({orientation for _, orientation in ps}) == 1: - raise Exception(f"Pipes in series {ps} do not all have the same orientation") - pipe_series.append([name for name, _ in ps]) - - buffer_connections = {} - - for b in buffers: - buffer_connections[b] = [] - - for k in ["In", "Out"]: - b_conn = f"{b}.{heat_network_model_type}{k}" - prop = "T" if heat_network_model_type == "QTH" else "Heat" - aliases = [ - x - for x in self.alias_relation.aliases(f"{b_conn}.{prop}") - if not x.startswith(b) and x.endswith(f".{prop}") - ] - - if len(aliases) > 1: - raise Exception(f"More than one connection to {b_conn}") - elif len(aliases) == 0: - raise Exception(f"Found no connection to {b_conn}") - - in_suffix = ".QTHIn.T" if heat_network_model_type == "QTH" else ".HeatIn.Heat" - out_suffix = ".QTHOut.T" if heat_network_model_type == "QTH" else ".HeatOut.Heat" - alias = aliases[0] - if alias.endswith(out_suffix): - pipe_w_orientation = ( - alias[: -len(out_suffix)], - NodeConnectionDirection.IN, - ) - else: - assert alias.endswith(in_suffix) - pipe_w_orientation = ( - alias[: -len(in_suffix)], - NodeConnectionDirection.OUT, - ) - - assert pipe_w_orientation[0] in pipes_set - - if k == "In": - assert self.is_hot_pipe(pipe_w_orientation[0]) - else: - assert self.is_cold_pipe(pipe_w_orientation[0]) - - buffer_connections[b].append(pipe_w_orientation) - - buffer_connections[b] = tuple(buffer_connections[b]) - - ates_connections = {} - - for a in atess: - ates_connections[a] = [] - - for k in ["In", "Out"]: - a_conn = f"{a}.{heat_network_model_type}{k}" - prop = "T" if heat_network_model_type == "QTH" else "Heat" - aliases = [ - x - for x in self.alias_relation.aliases(f"{a_conn}.{prop}") - if not x.startswith(a) and x.endswith(f".{prop}") - ] - - if len(aliases) > 1: - raise Exception(f"More than one connection to {a_conn}") - elif len(aliases) == 0: - raise Exception(f"Found no connection to {a_conn}") - - in_suffix = ".QTHIn.T" if heat_network_model_type == "QTH" else ".HeatIn.Heat" - out_suffix = ".QTHOut.T" if heat_network_model_type == "QTH" else ".HeatOut.Heat" - - if aliases[0].endswith(out_suffix): - pipe_w_orientation = ( - aliases[0][: -len(out_suffix)], - NodeConnectionDirection.IN, - ) - else: - assert aliases[0].endswith(in_suffix) - pipe_w_orientation = ( - aliases[0][: -len(in_suffix)], - NodeConnectionDirection.OUT, - ) - - assert pipe_w_orientation[0] in pipes_set - - if k == "Out": - assert self.is_cold_pipe(pipe_w_orientation[0]) - else: - assert self.is_hot_pipe(pipe_w_orientation[0]) - - ates_connections[a].append(pipe_w_orientation) - - ates_connections[a] = tuple(ates_connections[a]) - - self.__topology = Topology( - node_connections, - gas_node_connections, - pipe_series, - buffer_connections, - ates_connections, - bus_connections, - ) - - super().pre() - - @property - def energy_system_components(self) -> Dict[str, Set[str]]: - """ - This method return a dict with the milp network assets ordered per asset type. - """ - if self.__hn_component_types is None: - # Create the dictionary once after that it will be available - string_parameters = self.string_parameters(0) - - # Find the components in model, detection by string - # (name.component_type: type) - component_types = sorted({v for k, v in string_parameters.items()}) - - components = {} - for c in component_types: - components[c] = sorted( - {k.split(".")[0] for k, v in string_parameters.items() if v == c} - ) - - self.__hn_component_types = components - - return self.__hn_component_types - - @property - def energy_system_topology(self) -> Topology: - """ - This method returns the topology object of the milp network. Which contains specific assets - with directions on the ports that are needed in the constraints. - """ - return self.__topology diff --git a/src/rtctools_heat_network/electricity_physics_mixin.py b/src/rtctools_heat_network/electricity_physics_mixin.py deleted file mode 100644 index bb32081c3..000000000 --- a/src/rtctools_heat_network/electricity_physics_mixin.py +++ /dev/null @@ -1,600 +0,0 @@ -import logging -from math import isclose -from typing import Tuple - -import casadi as ca - -import numpy as np - -from rtctools.optimization.collocated_integrated_optimization_problem import ( - CollocatedIntegratedOptimizationProblem, -) -from rtctools.optimization.timeseries import Timeseries - - -from .base_component_type_mixin import BaseComponentTypeMixin - - -logger = logging.getLogger("rtctools_heat_network") - - -class ElectricityPhysicsMixin(BaseComponentTypeMixin, CollocatedIntegratedOptimizationProblem): - """ - This class is used to model the physics of an electricity network with its assets. We model - the different components with variety of linearization strategies. - """ - - def __init__(self, *args, **kwargs): - """ - In this __init__ we prepare the dicts for the variables added by the HeatMixin class - """ - - super().__init__(*args, **kwargs) - - # Variable for when in time an asset switched on due to meeting a requirement - self.__asset_is_switched_on_map = {} - self.__asset_is_switched_on_var = {} - self.__asset_is_switched_on_bounds = {} - - self.__windpark_upper_bounds = {} - - self._electricity_cable_topo_cable_class_map = {} - - def energy_system_options(self): - r""" - Returns a dictionary of milp network specific options. - """ - - options = {} - - options["include_asset_is_switched_on"] = False - options["include_electric_cable_power_loss"] = False - - return options - - def electricity_carriers(self): - """ - This function should be overwritten by the problem and should give a dict with the - carriers as keys and a list of voltage values. - """ - return {} - - def pre(self): - """ - In this pre method we fill the dicts initiated in the __init__. This means that we create - the Casadi variables and determine the bounds, nominals and create maps for easier - retrieving of the variables. - """ - super().pre() - - options = self.energy_system_options() - - self.__update_windpark_upper_bounds() - - if options["include_asset_is_switched_on"]: - for asset in [ - *self.energy_system_components.get("electrolyzer", []), - ]: - var_name = f"{asset}__asset_is_switched_on" - self.__asset_is_switched_on_map[asset] = var_name - self.__asset_is_switched_on_var[var_name] = ca.MX.sym(var_name) - self.__asset_is_switched_on_bounds[var_name] = (0.0, 1.0) - - @property - def extra_variables(self): - """ - In this function we add all the variables defined in the HeatMixin to the optimization - problem. Note that these are only the normal variables not path variables. - """ - variables = super().extra_variables.copy() - - return variables - - @property - def path_variables(self): - """ - In this function we add all the path variables defined in the HeatMixin to the - optimization problem. Note that path_variables are variables that are created for each - time-step. - """ - variables = super().path_variables.copy() - - variables.extend(self.__asset_is_switched_on_var.values()) - - return variables - - def variable_is_discrete(self, variable): - """ - All variables that only can take integer values should be added to this function. - """ - - if variable in self.__asset_is_switched_on_var: - return True - else: - return super().variable_is_discrete(variable) - - def variable_nominal(self, variable): - """ - In this function we add all the nominals for the variables defined/added in the HeatMixin. - """ - - return super().variable_nominal(variable) - - def bounds(self): - """ - In this function we add the bounds to the problem for all the variables defined/added in - the HeatMixin. - """ - bounds = super().bounds() - - bounds.update(self.__asset_is_switched_on_bounds) - bounds.update(self.__windpark_upper_bounds) - - return bounds - - @staticmethod - def __get_abs_max_bounds(*bounds): - """ - This function returns the absolute maximum of the bounds given. Note that bounds can also be - a timeseries. - """ - max_ = 0.0 - - for b in bounds: - if isinstance(b, np.ndarray): - max_ = max(max_, max(abs(b))) - elif isinstance(b, Timeseries): - max_ = max(max_, max(abs(b.values))) - else: - max_ = max(max_, abs(b)) - - return max_ - - def __state_vector_scaled(self, variable, ensemble_member): - """ - This functions returns the casadi symbols scaled with their nominal for the entire time - horizon. - """ - canonical, sign = self.alias_relation.canonical_signed(variable) - return ( - self.state_vector(canonical, ensemble_member) * self.variable_nominal(canonical) * sign - ) - - def __update_windpark_upper_bounds(self): - t = self.times() - for wp in self.energy_system_components.get("wind_park", []): - lb = Timeseries(t, np.zeros(len(self.times()))) - ub = self.get_timeseries(f"{wp}.maximum_electricity_source") - self.__windpark_upper_bounds[f"{wp}.Electricity_source"] = (lb, ub) - - def __wind_park_set_point_constraints(self, ensemble_member): - """ - This function adds constraints for wind parks which generates electrical power. The - produced electrical power is capped with a user specified percentage value of the maximum - value. - """ - constraints = [] - - for wp in self.energy_system_components.get("wind_park", []): - set_point = self.__state_vector_scaled(f"{wp}.Set_point", ensemble_member) - electricity_source = self.__state_vector_scaled( - f"{wp}.Electricity_source", ensemble_member - ) - # TODO: [: len(self.times())] should be removed once the emerge test is properly - # time-sampled. - max = self.bounds()[f"{wp}.Electricity_source"][1].values[: len(self.times())] - nominal = (self.variable_nominal(f"{wp}.Electricity_source") * np.median(max)) ** 0.5 - - constraints.append(((set_point * max - electricity_source) / nominal, 0.0, 0.0)) - - return constraints - - def __electricity_node_mixing_path_constraints(self, ensemble_member): - """ - This function adds constraints for power/energy and current conservation at nodes/busses. - """ - constraints = [] - - for bus, connected_cables in self.energy_system_topology.busses.items(): - power_sum = 0.0 - i_sum = 0.0 - power_nominal = [] - i_nominal = [] - - for i_conn, (_cable, orientation) in connected_cables.items(): - power_con = f"{bus}.ElectricityConn[{i_conn + 1}].Power" - i_port = f"{bus}.ElectricityConn[{i_conn + 1}].I" - power_sum += orientation * self.state(power_con) - i_sum += orientation * self.state(i_port) - power_nominal.append(self.variable_nominal(power_con)) - i_nominal.append(self.variable_nominal(i_port)) - - power_nominal = np.median(power_nominal) - constraints.append((power_sum / power_nominal, 0.0, 0.0)) - - i_nominal = np.median(i_nominal) - constraints.append((i_sum / i_nominal, 0.0, 0.0)) - - return constraints - - def __electricity_cable_mixing_path_constraints(self, ensemble_member): - """ - This function adds constraints relating the electrical power to the current flowing through - the cable. The power through the cable is limited by the maximum voltage and the actual - current variable with an inequality constraint. This is done to allow power losses through - the network. As the current and power are related with an equality constraint at the - demands exactly matching the P = U*I equation, we allow the inequalities for the lines. By - overestimating the power losses and voltage drops, together we ensure that U*I>P. - - - Furthermore, the power loss is estimated by linearizing with the maximum current, meaning - that we are always overestimating the power loss in the cable. - """ - constraints = [] - parameters = self.parameters(ensemble_member) - - for cable in self.energy_system_components.get("electricity_cable", []): - current = self.state(f"{cable}.ElectricityIn.I") - power_in = self.state(f"{cable}.ElectricityIn.Power") - power_out = self.state(f"{cable}.ElectricityOut.Power") - power_loss = self.state(f"{cable}.Power_loss") - # v_loss = self.state(f"{cable}.V_loss") - r = parameters[f"{cable}.r"] - i_max = parameters[f"{cable}.max_current"] - v_nom = parameters[f"{cable}.nominal_voltage"] - v_max = parameters[f"{cable}.max_voltage"] - # v_loss_nom = parameters[f"{cable}.nominal_voltage_loss"] - length = parameters[f"{cable}.length"] - - # Ensure that the current is sufficient to transport the power - constraints.append(((power_in - current * v_max) / (i_max * v_max), -np.inf, 0.0)) - constraints.append(((power_out - current * v_max) / (i_max * v_max), -np.inf, 0.0)) - # Power loss constraint - options = self.energy_system_options() - if options["include_electric_cable_power_loss"]: - if cable in self._electricity_cable_topo_cable_class_map.keys(): - cable_classes = self._electricity_cable_topo_cable_class_map[cable] - max_res = max([cc.resistance for cc in cable_classes]) - max_i_max = max([cc.maximum_current for cc in cable_classes]) - big_m = max_i_max**2 * max_res * length - constraint_nominal = max_i_max * v_nom * max_res * length - for cc_data, cc_name in cable_classes.items(): - if cc_name != "None": - i_max = cc_data.maximum_current - res = cc_data.resistance - exp = current * res * length * i_max - is_selected = self.variable(cc_name) - constraints.append( - ( - (power_loss - exp + big_m * (1 - is_selected)) - / constraint_nominal, - 0.0, - np.inf, - ) - ) - constraints.append( - ( - (power_loss - exp - big_m * (1 - is_selected)) - / (constraint_nominal), - -np.inf, - 0.0, - ) - ) - else: - constraints.append( - ((power_loss - current * r * i_max) / (i_max * v_nom * r), 0.0, 0.0) - ) - else: - constraints.append(((power_loss) / (i_max * v_nom * r), 0.0, 0.0)) - - return constraints - - def __voltage_loss_path_constraints(self, ensemble_member): - """ - Furthermore, the voltage_loss symbol is set, as it depends on the chosen pipe - class, e.g. the related resistance and the current through the cable. - - Parameters - ---------- - ensemble_member : The ensemble of the optimization - - Returns - ------- - list of the added constraints - """ - constraints = [] - parameters = self.parameters(ensemble_member) - - for cable in self.energy_system_components.get("electricity_cable", []): - cable_classes = [] - - current = self.state(f"{cable}.ElectricityIn.I") - v_loss = self.state(f"{cable}.V_loss") - r = parameters[f"{cable}.r"] - # v_loss_nom = parameters[f"{cable}.nominal_voltage_loss"] - v_nom = parameters[f"{cable}.nominal_voltage"] - c_length = parameters[f"{cable}.length"] - - constraint_nominal = self.variable_nominal(v_loss) - - # TODO: still have to check for proper scaling - if cable in self._electricity_cable_topo_cable_class_map.keys(): - cable_classes = self._electricity_cable_topo_cable_class_map[cable] - variables = { - cc.name: self.variable(var_name) for cc, var_name in cable_classes.items() - } - resistances = {cc.name: cc.resistance for cc in cable_classes} - - # to be updated for a better value, but it should also cover the gap between two - # nodes when no cable is placed, so should be able to reach v_max - big_m = v_nom - - for var_size, variable in variables.items(): - if var_size != "None": - expr = resistances[var_size] * c_length * current - constraints.append( - ( - (v_loss - expr + big_m * (1 - variable)) / constraint_nominal, - 0.0, - np.inf, - ) - ) - constraints.append( - ( - (v_loss - expr - big_m * (1 - variable)) / constraint_nominal, - -np.inf, - 0.0, - ) - ) - - else: - constraints.append(((v_loss - r * current) / constraint_nominal, 0.0, 0.0)) - - return constraints - - def __electricity_demand_path_constraints(self, ensemble_member): - """ - This function adds the constraints for the electricity commodity at the demand assets. We - enforce that a minimum voltage is exactly met together with the power that is carried by - the current. By fixing the voltage at the demand we ensure that at the demands - P = U * I is met exactly at this point in the network and the power is conservatively - in the cables at all locations in the network. - """ - constraints = [] - parameters = self.parameters(ensemble_member) - - for elec_demand in [ - *self.energy_system_components.get("electricity_demand", []), - *self.energy_system_components.get("heat_pump_elec", []), - *self.energy_system_components.get("electrolyzer", []), - ]: - min_voltage = parameters[f"{elec_demand}.min_voltage"] - voltage = self.state(f"{elec_demand}.ElectricityIn.V") - # to ensure that voltage entering is equal or larger than the minimum voltage - constraints.append(((voltage - min_voltage) / min_voltage, 0.0, np.inf)) - - power_nom = self.variable_nominal(f"{elec_demand}.ElectricityIn.Power") - curr_nom = self.variable_nominal(f"{elec_demand}.ElectricityIn.I") - power_in = self.state(f"{elec_demand}.ElectricityIn.Power") - current_in = self.state(f"{elec_demand}.ElectricityIn.I") - - constraints.append( - ( - (power_in - min_voltage * current_in) - / (power_nom * curr_nom * min_voltage) ** 0.5, - 0, - 0, - ) - ) - - return constraints - - def __get_electrolyzer_gas_mass_flow_out( - self, coef_a, coef_b, coef_c, electrical_power_input - ) -> float: - """ - This function returns the gas mass flow rate [kg/s] out of an electrolyzer based on the - theoretical efficiency curve: - energy [Ws] / gas mass [kg] = - (coef_a / electrical_power_input) + (b * electrical_power_input) + coef_c - - Parameters - ---------- - coef_a: electrolyzer efficience curve coefficent - coef_b: electrolyzer efficience curve coefficent - coef_c: electrolyzer efficience curve coefficent - electrical_power_input: electrical power consumed [W] - - Returns - ------- - gas mass flow rate produced by the electrolyzer [kg/s] - """ - - if not isclose(electrical_power_input, 0.0): - eff = (coef_a / electrical_power_input) + (coef_b * electrical_power_input) + coef_c - gas_mass_flow_out = (1.0 / eff) * electrical_power_input - else: - gas_mass_flow_out = 0.0 - - return gas_mass_flow_out - - def _get_linear_coef_electrolyzer_mass_vs_epower_fit( - self, coef_a, coef_b, coef_c, n_lines, electrical_power_min, electrical_power_max - ) -> Tuple[np.array, np.array]: - """ - This function returns a set of coefficients to approximate a gas mass flow rate curve with - linear functions in the form of: gass mass flow rate [kg/s] = b + (a * electrical_power) - - Parameters - ---------- - coef_a: electrolyzer efficience curve coefficent - coef_b: electrolyzer efficience curve coefficent - coef_c: electrolyzer efficience curve coefficent - n_lines: numebr of linear lines used to approximate the non-linear curve - electrical_power_min: minimum electrical power consumed [W] - electrical_power_max: maximum electrical power consumed [W] - - Returns - ------- - coefficients for linear curve fit(s) to the theoretical non-linear electrolyzer curve - """ - - electrical_power_points = np.linspace( - electrical_power_min, electrical_power_max, n_lines + 1 - ) - - gas_mass_flow_points = np.array( - [ - self.__get_electrolyzer_gas_mass_flow_out(coef_a, coef_b, coef_c, ep) - for ep in electrical_power_points - ] - ) - - a_vals = np.diff(gas_mass_flow_points) / np.diff(electrical_power_points) - b_vals = gas_mass_flow_points[1:] - a_vals * electrical_power_points[1:] - - return a_vals, b_vals - - def __electrolyzer_path_constaint(self, ensemble_member): - """ - This functions add the constraints for the gas mass flow production based as a functions of - electrical power input. This production is approximated by an electrolyzer efficience curve - (energy/gas mass vs electrical power input, [Ws/kg] vs [W]) which is then linearized. If - the load becomes lower than the minimum load both the gass_mass_flow and the electricity - power should be 0. - """ - constraints = [] - parameters = self.parameters(ensemble_member) - for asset in self.energy_system_components.get("electrolyzer", []): - gas_mass_flow_out = self.state(f"{asset}.Gas_mass_flow_out") - power_consumed = self.state(f"{asset}.Power_consumed") - - # Multiple linear lines - curve_fit_number_of_lines = 3 - linear_coef_a, linear_coef_b = self._get_linear_coef_electrolyzer_mass_vs_epower_fit( - parameters[f"{asset}.a_eff_coefficient"], - parameters[f"{asset}.b_eff_coefficient"], - parameters[f"{asset}.c_eff_coefficient"], - n_lines=curve_fit_number_of_lines, - electrical_power_min=max( - parameters[f"{asset}.minimum_load"], - 0.01 * self.bounds()[f"{asset}.ElectricityIn.Power"][1], - ), - electrical_power_max=self.bounds()[f"{asset}.ElectricityIn.Power"][1], - ) - power_consumed_vect = ca.repmat(power_consumed, len(linear_coef_a)) - gas_mass_flow_out_vect = ca.repmat(gas_mass_flow_out, len(linear_coef_a)) - gass_mass_out_linearized_vect = linear_coef_a * power_consumed_vect + linear_coef_b - var_name = self.__asset_is_switched_on_map[asset] - asset_is_switched_on = self.state(var_name) - - gass_mass_out_max = ( - linear_coef_a[-1] * self.bounds()[f"{asset}.Power_consumed"][1] + linear_coef_b[-1] - ) - big_m = gass_mass_out_max * 2 - nominal = ( - self.variable_nominal(f"{asset}.Gas_mass_flow_out") - * min(linear_coef_a) - * self.variable_nominal(f"{asset}.Power_consumed") - ) ** 0.5 - constraints.extend( - [ - ( - ( - gas_mass_flow_out_vect - - gass_mass_out_linearized_vect - - (1 - asset_is_switched_on) * big_m - ) - / nominal, - -np.inf, - 0.0, - ), - ] - ) - constraints.append( - ((gas_mass_flow_out + asset_is_switched_on * big_m) / big_m, 0.0, np.inf) - ) - constraints.append( - ((gas_mass_flow_out - asset_is_switched_on * big_m) / big_m, -np.inf, 0.0) - ) - - # Add constraints to ensure the electrolyzer is switched off when it reaches a power - # input below the minimum operating value - - big_m = self.bounds()[f"{asset}.ElectricityIn.Power"][1] * 1.5 * 10.0 - constraints.append( - ( - ( - power_consumed - - parameters[f"{asset}.minimum_load"] - + (1.0 - asset_is_switched_on) * big_m - ) - / self.variable_nominal(f"{asset}.Power_consumed"), - 0.0, - np.inf, - ) - ) - constraints.append( - ((power_consumed + asset_is_switched_on * big_m) / big_m, 0.0, np.inf) - ) - constraints.append( - ((power_consumed - asset_is_switched_on * big_m) / big_m, -np.inf, 0.0) - ) - - return constraints - - def path_constraints(self, ensemble_member): - """ - Here we add all the path constraints to the optimization problem. Please note that the - path constraints are the constraints that are applied to each time-step in the problem. - """ - - constraints = super().path_constraints(ensemble_member) - - constraints.extend(self.__electricity_demand_path_constraints(ensemble_member)) - constraints.extend(self.__electricity_node_mixing_path_constraints(ensemble_member)) - constraints.extend(self.__electricity_cable_mixing_path_constraints(ensemble_member)) - constraints.extend(self.__voltage_loss_path_constraints(ensemble_member)) - constraints.extend(self.__electrolyzer_path_constaint(ensemble_member)) - - return constraints - - def constraints(self, ensemble_member): - """ - This function adds the normal constraints to the problem. Unlike the path constraints these - are not applied to every time-step in the problem. Meaning that these constraints either - consider global variables that are independent of time-step or that the relevant time-steps - are indexed within the constraint formulation. - """ - constraints = super().constraints(ensemble_member) - - constraints.extend(self.__wind_park_set_point_constraints(ensemble_member)) - - return constraints - - def goal_programming_options(self): - """ - Here we set the goal programming configuration. We use soft constraints for consecutive - goals. - """ - options = super().goal_programming_options() - options["keep_soft_constraints"] = True - return options - - def solver_options(self): - """ - Here we define the solver options. By default we use the open-source solver cbc and casadi - solver qpsol. - """ - options = super().solver_options() - options["casadi_solver"] = "qpsol" - options["solver"] = "highs" - return options - - def compiler_options(self): - """ - In this function we set the compiler configuration. - """ - options = super().compiler_options() - options["resolve_parameter_values"] = True - return options diff --git a/src/rtctools_heat_network/esdl/esdl_additional_vars_mixin.py b/src/rtctools_heat_network/esdl/esdl_additional_vars_mixin.py deleted file mode 100644 index 11d4fbdae..000000000 --- a/src/rtctools_heat_network/esdl/esdl_additional_vars_mixin.py +++ /dev/null @@ -1,124 +0,0 @@ -import logging - -import esdl - -import numpy as np - -from rtctools.optimization.collocated_integrated_optimization_problem import ( - CollocatedIntegratedOptimizationProblem, -) - -from rtctools_heat_network.network_common import NetworkSettings - -logger = logging.getLogger("rtctools_heat_network") - - -class ESDLAdditionalVarsMixin(CollocatedIntegratedOptimizationProblem): - __temperature_options = {} - - def read(self): - super().read() - - for asset in [ - *self.energy_system_components.get("heat_source", []), - *self.energy_system_components.get("ates", []), - *self.energy_system_components.get("heat_buffer", []), - *self.energy_system_components.get("heat_pump", []), - ]: - esdl_asset = self.esdl_assets[self.esdl_asset_name_to_id_map[asset]] - for constraint in esdl_asset.attributes.get("constraint", []): - if constraint.name == "setpointconstraint": - time_unit = constraint.range.profileQuantityAndUnit.perTimeUnit - if time_unit == esdl.TimeUnitEnum.HOUR: - time_hours = 1 - elif time_unit == esdl.TimeUnitEnum.DAY: - time_hours = 24 - elif time_unit == esdl.TimeUnitEnum.WEEK: - time_hours = 24 * 7 - elif time_unit == esdl.TimeUnitEnum.MOTH: - time_hours = 24 * 7 * 30 - elif time_unit == esdl.TimeUnitEnum.DAY: - time_hours = 365 * 24 - else: - logger.error( - f"{asset} has a setpoint constaint specified with unknown" - f"per time unit" - ) - - asset_setpoints = {asset: (time_hours, constraint.range.maxValue)} - - self._timed_setpoints.update(asset_setpoints) - - def pipe_classes(self, p): - return self._override_pipe_classes.get(p, []) - - def esdl_heat_model_options(self): - """Overwrites the fraction of the minimum tank volume""" - options = super().esdl_heat_model_options() - options["min_fraction_tank_volume"] = 0.0 - return options - - def temperature_carriers(self): - return self.esdl_carriers_typed(type=[str(NetworkSettings.NETWORK_TYPE_HEAT).lower()]) - - def electricity_carriers(self): - return self.esdl_carriers_typed( - type=[str(NetworkSettings.NETWORK_TYPE_ELECTRICITY).lower()] - ) - - def gas_carriers(self): - return self.esdl_carriers_typed( - type=[ - str(NetworkSettings.NETWORK_TYPE_GAS).lower(), - str(NetworkSettings.NETWORK_TYPE_HYDROGEN).lower(), - ] - ) - - def temperature_regimes(self, carrier): - temperature_options = [] - temperature_step = 2.5 - - try: - temperature_options = self.__temperature_options[carrier] - except KeyError: - for asset in [ - *self.energy_system_components.get("heat_source", []), - *self.energy_system_components.get("ates", []), - *self.energy_system_components.get("heat_buffer", []), - *self.energy_system_components.get("heat_pump", []), - *self.energy_system_components.get("heat_exchanger", []), - *self.energy_system_components.get("heat_demand", []), - ]: - esdl_asset = self.esdl_assets[self.esdl_asset_name_to_id_map[asset]] - parameters = self.parameters(0) - for i in range(len(esdl_asset.attributes["constraint"].items)): - constraint = esdl_asset.attributes["constraint"].items[i] - if ( - constraint.name == "supply_temperature" - and carrier == parameters[f"{asset}.T_supply_id"] - ) or ( - constraint.name == "return_temperature" - and carrier == parameters[f"{asset}.T_return_id"] - ): - try: - lb = self.__temperature_options[carrier][0] - ub = self.__temperature_options[carrier][-1] - lb = constraint.range.minValue if constraint.range.minValue > lb else lb - ub = constraint.range.maxValue if constraint.range.maxValue < ub else ub - except KeyError: - lb = constraint.range.minValue - ub = constraint.range.maxValue - n_options = round((ub - lb) / temperature_step) - temperature_options = np.linspace(lb, ub, n_options + 1) - if ( - constraint.range.profileQuantityAndUnit.unit - != esdl.UnitEnum.DEGREES_CELSIUS - ): - RuntimeError( - f"{asset} has a temperature constraint with wrong unit " - f"{constraint.range.profileQuantityAndUnit.unit}, should " - f"always be in degrees celcius." - ) - self.__temperature_options[carrier] = temperature_options - - return temperature_options diff --git a/src/rtctools_heat_network/esdl/esdl_heat_model.py b/src/rtctools_heat_network/esdl/esdl_heat_model.py deleted file mode 100644 index c4fc45777..000000000 --- a/src/rtctools_heat_network/esdl/esdl_heat_model.py +++ /dev/null @@ -1,1439 +0,0 @@ -import logging -import math -from typing import Dict, Tuple, Type, Union - -import CoolProp as cP - -import esdl - -from rtctools_heat_network.pycml.component_library.milp import ( - ATES, - CheckValve, - ControlValve, - ElectricityCable, - ElectricityDemand, - ElectricityNode, - ElectricitySource, - Electrolyzer, - GasDemand, - GasNode, - GasPipe, - GasSource, - GasSubstation, - GasTankStorage, - GeothermalSource, - HeatBuffer, - HeatDemand, - HeatExchanger, - HeatPipe, - HeatPump, - HeatPumpElec, - HeatSource, - Node, - Pump, - WindPark, -) - -from scipy.optimize import fsolve - -from .asset_to_component_base import MODIFIERS, _AssetToComponentBase -from .common import Asset -from .esdl_model_base import _ESDLModelBase -from ..network_common import NetworkSettings - -logger = logging.getLogger("rtctools_heat_network") - - -class _ESDLInputException(Exception): - pass - - -class AssetToHeatComponent(_AssetToComponentBase): - """ - This class is used for the converting logic from the esdl assets with their properties to pycml - objects and set their respective properties. - """ - - def __init__( - self, - *args, - v_nominal=1.0, - v_max=5.0, - rho=988.0, - cp=4200.0, - min_fraction_tank_volume=0.05, - v_max_gas=15.0, - **kwargs, - ): - super().__init__(*args, **kwargs) - - self.v_nominal = v_nominal - self.v_max = v_max - self.rho = rho - self.cp = cp - self.v_max_gas = v_max_gas - self.min_fraction_tank_volume = min_fraction_tank_volume - if "primary_port_name_convention" in kwargs.keys(): - self.primary_port_name_convention = kwargs["primary_port_name_convention"] - if "secondary_port_name_convention" in kwargs.keys(): - self.secondary_port_name_convention = kwargs["secondary_port_name_convention"] - - @property - def _rho_cp_modifiers(self) -> Dict: - """ - For giving the density, rho, in kg/m3 and specic milp, cp, in J/(K*kg) - - Returns - ------- - rho and cp - """ - return dict(rho=self.rho, cp=self.cp) - - def get_density(self, asset_name, carrier): - # TODO: gas carrier temperature still needs to be resolved. - # The default of 20°C is also used in the head_loss_class. Thus, when updating ensure it - # is also updated in the head_loss_class. - temperature = 20.0 - - if NetworkSettings.NETWORK_TYPE_GAS in carrier.name: - density = cP.CoolProp.PropsSI( - "D", - "T", - 273.15 + temperature, - "P", - carrier.pressure * 1.0e5, - NetworkSettings.NETWORK_COMPOSITION_GAS, - ) - elif NetworkSettings.NETWORK_TYPE_HYDROGEN in carrier.name: - density = cP.CoolProp.PropsSI( - "D", - "T", - 273.15 + temperature, - "P", - carrier.pressure * 1.0e5, - str(NetworkSettings.NETWORK_TYPE_HYDROGEN).upper(), - ) - else: - logger.warning( - f"Neither gas or hydrogen was used in the carrier " f"name of pipe {asset_name}" - ) - density = 6.2 # natural gas at about 8 bar - return density * 1.0e3 # to convert from kg/m3 to g/m3 - - def get_asset_attribute_value( - self, - asset: Asset, - attribute_name: str, - default_value: float, - min_value: float, - max_value: float, - ) -> float: - """ - Get the value of the specified attribute for the given asset. - Args: - asset: The asset to retrieve the attribute value for. - attribute_name: The name of the attribute to retrieve. - default_value: The default value to use if the attribute is not present. - min_value: The minimum value for the attribute. - max_value: The maximum value for the attribute. - Returns: - The value of the specified attribute for the given asset. - Raises: - ValueError: If the attribute value is not within the specified range. - """ - if attribute_name == "discountRate": - attribute_value = ( - asset.attributes["costInformation"].discountRate.value - if asset.attributes["costInformation"] - and asset.attributes["costInformation"].discountRate is not None - and asset.attributes["costInformation"].discountRate.value is not None - else default_value - ) - else: - attribute_value = ( - asset.attributes[attribute_name] - if asset.attributes[attribute_name] and asset.attributes[attribute_name] != 0 - else default_value - ) - self.validate_attribute_input( - # NOTE: this validation happens after assigning default values - # discountRate and technicalLife need to be included in input files of tests - # before this input validation can be relocated earlier in this function - asset.name, - attribute_name, - attribute_value, - min_value, - max_value, - ) - return attribute_value - - def validate_attribute_input( - self, - asset_name: str, - attribute_name: str, - input_value: float, - min_value: float, - max_value: float, - ) -> None: - """ - Validates if the input value is within the specified range. - Args: - asset_name (str): The name of the asset. - attribute_name (str): The name of the attribute. - input_value (float): The value to be validated. - min_value (float): The minimum value of the range. - max_value (float): The maximum value of the range. - Raises: - ValueError: If the input value is not within the specified range. - """ - if input_value < min_value or input_value > max_value: - warning_msg = ( - f"Input value {input_value} of attribute {attribute_name} " - f"is not within range ({min_value}, {max_value}) for asset {asset_name}." - ) - logger.warning(warning_msg) - - def convert_heat_buffer(self, asset: Asset) -> Tuple[Type[HeatBuffer], MODIFIERS]: - """ - This function converts the buffer object in esdl to a set of modifiers that can be used in - a pycml object. Most important: - - - Setting the dimensions of the buffer needed for milp loss computation. Currently, assume - cylinder with height equal to radius. - - setting a minimum fill level and minimum asscociated milp - - Setting a maximum stored energy based on the size. - - Setting a cap on the thermal power. - - Setting the state (enabled, disabled, optional) - - Setting the relevant temperatures. - - Setting the relevant cost figures. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - Buffer class with modifiers - """ - assert asset.asset_type == "HeatStorage" - - temperature_modifiers = self._supply_return_temperature_modifiers(asset) - - supply_temperature = temperature_modifiers["T_supply"] - return_temperature = temperature_modifiers["T_return"] - - # Assume that: - # - the capacity is the relative milp that can be stored in the buffer; - # - the tanks are always at least `min_fraction_tank_volume` full; - # - same height as radius to compute dimensions. - if asset.attributes["capacity"] and asset.attributes["volume"]: - logger.warning( - f"{asset.asset_type} '{asset.name}' has both capacity and volume specified. " - f"Volume with value of {asset.attributes['volume']} m3 will be used." - ) - - capacity = 0.0 - if asset.attributes["volume"]: - capacity = ( - asset.attributes["volume"] - * self.rho - * self.cp - * (supply_temperature - return_temperature) - ) - elif asset.attributes["capacity"]: - capacity = asset.attributes["capacity"] - else: - logger.error( - f"{asset.asset_type} '{asset.name}' has both not capacity and volume specified. " - f"Please specify one of the two" - ) - - assert capacity > 0.0 - min_fraction_tank_volume = self.min_fraction_tank_volume - if self.get_state(asset) == 0 or self.get_state(asset) == 2: - min_fraction_tank_volume = 0.0 - # We assume that the height equals the radius of the buffer. - r = ( - capacity - * (1 + min_fraction_tank_volume) - / (self.rho * self.cp * (supply_temperature - return_temperature) * math.pi) - ) ** (1.0 / 3.0) - - min_heat = capacity * min_fraction_tank_volume - max_heat = capacity * (1 + min_fraction_tank_volume) - assert max_heat > 0.0 - # default is set to 10MW - - hfr_charge_max = ( - asset.attributes.get("maxChargeRate") - if asset.attributes.get("maxChargeRate") - else 10.0e6 - ) - hfr_discharge_max = ( - asset.attributes.get("maxDischargeRate") - if asset.attributes.get("maxDischargeRate") - else 10.0e6 - ) - - q_nominal = self._get_connected_q_nominal(asset) - - modifiers = dict( - Q_nominal=q_nominal, - height=r, - radius=r, - heat_transfer_coeff=1.0, - technical_life=self.get_asset_attribute_value( - asset, - "technicalLifetime", - default_value=30.0, - min_value=1.0, - max_value=50.0, - ), - discount_rate=self.get_asset_attribute_value( - asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 - ), - state=self.get_state(asset), - min_fraction_tank_volume=min_fraction_tank_volume, - Stored_heat=dict(min=min_heat, max=max_heat), - Heat_buffer=dict(min=-hfr_discharge_max, max=hfr_charge_max), - Heat_flow=dict(min=-hfr_discharge_max, max=hfr_charge_max, nominal=hfr_charge_max), - HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - init_Heat=min_heat, - **self._supply_return_temperature_modifiers(asset), - **self._rho_cp_modifiers, - **self._get_cost_figure_modifiers(asset), - ) - - return HeatBuffer, modifiers - - def convert_heat_demand(self, asset: Asset) -> Tuple[Type[HeatDemand], MODIFIERS]: - """ - This function converts the demand object in esdl to a set of modifiers that can be used in - a pycml object. Most important: - - - Setting a cap on the thermal power. - - Setting the state (enabled, disabled, optional) - - Setting the relevant temperatures. - - Setting the relevant cost figures. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - Demand class with modifiers - """ - assert asset.asset_type in {"GenericConsumer", "HeatingDemand"} - - max_demand = asset.attributes["power"] if asset.attributes["power"] else math.inf - - q_nominal = self._get_connected_q_nominal(asset) - - modifiers = dict( - Q_nominal=q_nominal, - Heat_demand=dict(max=max_demand, nominal=max_demand / 2.0), - Heat_flow=dict(max=max_demand, nominal=max_demand / 2.0), - HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - state=self.get_state(asset), - **self._supply_return_temperature_modifiers(asset), - **self._rho_cp_modifiers, - **self._get_cost_figure_modifiers(asset), - ) - - return HeatDemand, modifiers - - def convert_node(self, asset: Asset) -> Tuple[Type[Node], MODIFIERS]: - """ - This function converts the node object in esdl to a set of modifiers that can be used in - a pycml object. Most important: - - - Setting the amount of connections - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - Node class with modifiers - """ - assert asset.asset_type == "Joint" - - sum_in = 0 - sum_out = 0 - - node_carrier = None - for x in asset.attributes["port"].items: - if node_carrier is None: - node_carrier = x.carrier.name - else: - if node_carrier != x.carrier.name: - raise _ESDLInputException( - f"{asset.name} has multiple carriers mixing which is not allowed. " - f"Only one carrier (carrier couple) allowed in hydraulicly " - f"coupled system" - ) - if isinstance(x, esdl.esdl.InPort): - sum_in += len(x.connectedTo) - if isinstance(x, esdl.esdl.OutPort): - sum_out += len(x.connectedTo) - - modifiers = dict( - n=sum_in + sum_out, - state=self.get_state(asset), - ) - - if isinstance(asset.in_ports[0].carrier, esdl.esdl.GasCommodity) or isinstance( - asset.out_ports[0].carrier, esdl.esdl.GasCommodity - ): - modifiers = dict( - n=sum_in + sum_out, - ) - return GasNode, modifiers - - return Node, modifiers - - def convert_heat_pipe( - self, asset: Asset - ) -> Tuple[Union[Type[HeatPipe], Type[GasPipe]], MODIFIERS]: - """ - This function converts the pipe object in esdl to a set of modifiers that can be used in - a pycml object. Most important: - - - Setting the dimensions of the pipe needed for milp loss computation. Currently, assume - cylinder with height equal to radius. - - setting if a pipe is disconnecteable for the optimization. - - Setting the isolative properties of the pipe. - - Setting a cap on the thermal power. - - Setting the state (enabled, disabled, optional) - - Setting the relevant temperatures. - - Setting the relevant cost figures. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - Pipe class with modifiers - """ - assert asset.asset_type == "Pipe" - - length = asset.attributes["length"] - if length < 25.0: - length = 25.0 - - ( - diameter, - insulation_thicknesses, - conductivies_insulation, - ) = self._pipe_get_diameter_and_insulation(asset) - - if isinstance(asset.in_ports[0].carrier, esdl.esdl.GasCommodity): - q_nominal = math.pi * diameter**2 / 4.0 * self.v_max_gas / 2.0 - self._set_q_nominal(asset, q_nominal) - q_max = math.pi * diameter**2 / 4.0 * self.v_max_gas - self._set_q_max(asset, q_max) - pressure = asset.in_ports[0].carrier.pressure * 1.0e5 - density = self.get_density(asset.name, asset.in_ports[0].carrier) - bounds_nominals = dict( - Q=dict(min=-q_max, max=q_max, nominal=q_nominal), - mass_flow=dict( - min=-q_max * density, max=q_max * density, nominal=q_nominal * density - ), - ) - modifiers = dict( - length=length, - density=density, - diameter=diameter, - pressure=pressure, - # disconnectable=self._is_disconnectable_pipe(asset), # still to be added - GasIn=bounds_nominals, - GasOut=bounds_nominals, - state=self.get_state(asset), - **self._get_cost_figure_modifiers(asset), - ) - - return GasPipe, modifiers - - temperature_modifiers = self._supply_return_temperature_modifiers(asset) - - temperature = temperature_modifiers["temperature"] - - # Compute the maximum milp flow based on an assumed maximum velocity - area = math.pi * diameter**2 / 4.0 - q_max = area * self.v_max - q_nominal = area * self.v_nominal - - self._set_q_nominal(asset, q_nominal) - - # TODO: This might be an underestimation. We need to add the total - # milp losses in the system to get a proper upper bound. Maybe move - # calculation of Heat bounds to the HeatMixin? - hfr_max = 2.0 * ( - self.rho * self.cp * q_max * temperature - ) # TODO: are there any physical implications of using this bound - - assert hfr_max > 0.0 - - modifiers = dict( - Q_nominal=q_nominal, - length=length, - diameter=diameter, - disconnectable=self._is_disconnectable_pipe(asset), - technical_life=self.get_asset_attribute_value( - asset, - "technicalLifetime", - default_value=30.0, - min_value=1.0, - max_value=50.0, - ), - discount_rate=self.get_asset_attribute_value( - asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 - ), - HeatIn=dict( - Heat=dict(min=-hfr_max, max=hfr_max), - Q=dict(min=-q_max, max=q_max), - Hydraulic_power=dict(nominal=q_nominal * 16.0e5), - ), - HeatOut=dict( - Heat=dict(min=-hfr_max, max=hfr_max), - Q=dict(min=-q_max, max=q_max), - Hydraulic_power=dict(nominal=q_nominal * 16.0e5), - ), - Heat_flow=dict(min=-hfr_max, max=hfr_max, nominal=hfr_max), - insulation_thickness=insulation_thicknesses, - conductivity_insulation=conductivies_insulation, - state=self.get_state(asset), - **self._supply_return_temperature_modifiers(asset), - **self._rho_cp_modifiers, - **self._get_cost_figure_modifiers(asset), - ) - if "T_ground" in asset.attributes.keys(): - modifiers["T_ground"] = asset.attributes["T_ground"] - - return HeatPipe, modifiers - - def convert_pump(self, asset: Asset) -> Tuple[Type[Pump], MODIFIERS]: - """ - This function converts the pump object in esdl to a set of modifiers that can be used in - a pycml object. Most important: - - - Setting the state (enabled, disabled, optional) - - Setting the relevant temperatures. - - Setting the relevant cost figures. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - Pump class with modifiers - """ - assert asset.asset_type == "Pump" - - q_nominal = self._get_connected_q_nominal(asset) - - modifiers = dict( - technical_life=self.get_asset_attribute_value( - asset, - "technicalLifetime", - default_value=30.0, - min_value=1.0, - max_value=50.0, - ), - HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - discount_rate=self.get_asset_attribute_value( - asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 - ), - Q_nominal=self._get_connected_q_nominal(asset), - state=self.get_state(asset), - **self._supply_return_temperature_modifiers(asset), - **self._rho_cp_modifiers, - ) - - return Pump, modifiers - - def convert_heat_exchanger(self, asset: Asset) -> Tuple[Type[HeatExchanger], MODIFIERS]: - """ - This function converts the Heat Exchanger object in esdl to a set of modifiers that can be - used in a pycml object. Most important: - - - Setting the thermal power transfer efficiency. - - Setting a caps on the thermal power on both the primary and secondary side. - - Setting the state (enabled, disabled, optional) - - Setting the relevant temperatures (also checked for making sense physically). - - Setting the relevant cost figures. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - HeatExchanger class with modifiers - """ - assert asset.asset_type in { - "GenericConversion", - "HeatExchange", - } - - params_t = self._supply_return_temperature_modifiers(asset) - params_q = self._get_connected_q_nominal(asset) - params = {} - - if params_t["Primary"]["T_supply"] < params_t["Secondary"]["T_supply"]: - logger.error( - f"{asset.name} has a primary side supply temperature, " - f"{params_t['Primary']['T_supply']}, that is higher than the secondary supply , " - f"{params_t['Secondary']['T_supply']}. This is not possible as the HEX can only " - "transfer milp from primary to secondary." - ) - assert params_t["Primary"]["T_supply"] >= params_t["Secondary"]["T_supply"] - if params_t["Primary"]["T_return"] < params_t["Secondary"]["T_return"]: - logger.error( - f"{asset.name} has a primary side return temperature that is lower than the " - f"secondary return temperature. This is not possible as the HEX can only transfer " - f"milp from primary to secondary." - ) - assert params_t["Primary"]["T_return"] >= params_t["Secondary"]["T_return"] - - if asset.asset_type == "GenericConversion": - max_power = asset.attributes["power"] if asset.attributes["power"] else math.inf - else: - # TODO: Current max_power estimation is not very accurate, a more physics based - # estimation should be implemented, maybe using other ESDL attributs. - max_power = ( - asset.attributes["heatTransferCoefficient"] - * (params_t["Primary"]["T_supply"] - params_t["Secondary"]["T_return"]) - / 2.0 - ) - - max_heat_transport = ( - params_t["Primary"]["T_supply"] - * max_power - / (params_t["Primary"]["T_supply"] - params_t["Primary"]["T_return"]) - ) - - prim_heat = dict( - HeatIn=dict( - Heat=dict(min=-max_heat_transport, max=max_heat_transport, nominal=max_power / 2.0), - Hydraulic_power=dict(nominal=params_q["Primary"]["Q_nominal"] * 16.0e5), - ), - HeatOut=dict( - Heat=dict(min=-max_heat_transport, max=max_heat_transport, nominal=max_power / 2.0), - Hydraulic_power=dict(nominal=params_q["Primary"]["Q_nominal"] * 16.0e5), - ), - Q_nominal=max_power - / ( - 2 - * self.rho - * self.cp - * (params_t["Primary"]["T_supply"] - params_t["Primary"]["T_return"]) - ), - ) - sec_heat = dict( - HeatIn=dict( - Heat=dict(min=-max_heat_transport, max=max_heat_transport, nominal=max_power / 2.0), - Hydraulic_power=dict(nominal=params_q["Secondary"]["Q_nominal"] * 16.0e5), - ), - HeatOut=dict( - Heat=dict(min=-max_heat_transport, max=max_heat_transport, nominal=max_power / 2.0), - Hydraulic_power=dict(nominal=params_q["Secondary"]["Q_nominal"] * 16.0e5), - ), - Q_nominal=max_power - / ( - 2 - * self.cp - * self.rho - * (params_t["Secondary"]["T_supply"] - params_t["Secondary"]["T_return"]) - ), - ) - params["Primary"] = {**params_t["Primary"], **params_q["Primary"], **prim_heat} - params["Secondary"] = { - **params_t["Secondary"], - **params_q["Secondary"], - **sec_heat, - } - - if not asset.attributes["efficiency"]: - efficiency = 1.0 - else: - efficiency = asset.attributes["efficiency"] - - modifiers = dict( - efficiency=efficiency, - technical_life=self.get_asset_attribute_value( - asset, - "technicalLifetime", - default_value=30.0, - min_value=1.0, - max_value=50.0, - ), - discount_rate=self.get_asset_attribute_value( - asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 - ), - nominal=max_power / 2.0, - Primary_heat=dict(min=0.0, max=max_power, nominal=max_power / 2.0), - Secondary_heat=dict(min=0.0, max=max_power, nominal=max_power / 2.0), - Heat_flow=dict(min=0.0, max=max_power, nominal=max_power / 2.0), - state=self.get_state(asset), - **self._get_cost_figure_modifiers(asset), - **params, - ) - return HeatExchanger, modifiers - - def convert_heat_pump(self, asset: Asset) -> Tuple[Type[HeatPump], MODIFIERS]: - """ - This function converts the HeatPump object in esdl to a set of modifiers that can be used in - a pycml object. Most important: - - - Setting the COP of the heatpump - - Setting the cap on the electrical power. - - Setting a caps on the thermal power on both the primary and secondary side. - - Setting the state (enabled, disabled, optional) - - Setting the relevant temperatures. - - Setting the relevant cost figures. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - HeatPump class with modifiers - """ - assert asset.asset_type in { - "HeatPump", - } - if not asset.attributes["power"]: - raise _ESDLInputException(f"{asset.name} has no power specified") - else: - power_electrical = asset.attributes["power"] - - if not asset.attributes["COP"]: - raise _ESDLInputException( - f"{asset.name} has not COP specified, this is required for the model" - ) - else: - cop = asset.attributes["COP"] - - params_t = self._supply_return_temperature_modifiers(asset) - params_q = self._get_connected_q_nominal(asset) - prim_heat = dict( - HeatIn=dict(Hydraulic_power=dict(nominal=params_q["Primary"]["Q_nominal"] * 16.0e5)), - HeatOut=dict(Hydraulic_power=dict(nominal=params_q["Primary"]["Q_nominal"] * 16.0e5)), - ) - sec_heat = dict( - HeatIn=dict(Hydraulic_power=dict(nominal=params_q["Secondary"]["Q_nominal"] * 16.0e5)), - HeatOut=dict(Hydraulic_power=dict(nominal=params_q["Secondary"]["Q_nominal"] * 16.0e5)), - ) - params = {} - params["Primary"] = {**params_t["Primary"], **params_q["Primary"], **prim_heat} - params["Secondary"] = {**params_t["Secondary"], **params_q["Secondary"], **sec_heat} - - max_power = power_electrical * (1.0 + cop) # TODO: dit kan zijn power_electrical*cop - - modifiers = dict( - COP=cop, - efficiency=asset.attributes["efficiency"] if asset.attributes["efficiency"] else 0.5, - technical_life=self.get_asset_attribute_value( - asset, - "technicalLifetime", - default_value=30.0, - min_value=1.0, - max_value=50.0, - ), - discount_rate=self.get_asset_attribute_value( - asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 - ), - Power_elec=dict(min=0.0, max=power_electrical, nominal=power_electrical / 2.0), - Primary_heat=dict(min=0.0, max=max_power, nominal=max_power / 2.0), - Secondary_heat=dict(min=0.0, max=max_power, nominal=max_power / 2.0), - Heat_flow=dict(min=0.0, max=max_power, nominal=max_power / 2.0), - state=self.get_state(asset), - **self._get_cost_figure_modifiers(asset), - **params, - ) - if len(asset.in_ports) == 2: - return HeatPump, modifiers - elif len(asset.in_ports) == 3: - return HeatPumpElec, modifiers - - def convert_heat_source(self, asset: Asset) -> Tuple[Type[HeatSource], MODIFIERS]: - """ - This function converts the Source object in esdl to a set of modifiers that can be used in - a pycml object. Most important: - - - Setting the CO2 emission coefficient in case this is specified as an KPI - - Setting a caps on the thermal power. - - In case of a GeothermalSource object we read the _aggregation count to model the number - of doublets, we then assume that the power specified was also for one doublet and thus - increase the thermal power caps. - - Setting the state (enabled, disabled, optional) - - Setting the relevant temperatures. - - Setting the relevant cost figures. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - Source class with modifiers - """ - assert asset.asset_type in { - "GasHeater", - "GenericProducer", - "HeatProducer", - "GeothermalSource", - "ResidualHeatSource", - } - - max_supply = asset.attributes["power"] - - if not max_supply: - logger.error(f"{asset.asset_type} '{asset.name}' has no max power specified. ") - assert max_supply > 0.0 - - # get price per unit of energy, - # assume cost of 1. if nothing is given (effectively milp loss minimization) - - co2_coefficient = 1.0 - if hasattr(asset.attributes["KPIs"], "kpi"): - co2_coefficient = asset.attributes["KPIs"].kpi.items[0].value - - q_nominal = self._get_connected_q_nominal(asset) - - modifiers = dict( - technical_life=self.get_asset_attribute_value( - asset, - "technicalLifetime", - default_value=30.0, - min_value=1.0, - max_value=50.0, - ), - discount_rate=self.get_asset_attribute_value( - asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 - ), - Q_nominal=q_nominal, - state=self.get_state(asset), - co2_coeff=co2_coefficient, - Heat_source=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), - Heat_flow=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), - HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - **self._supply_return_temperature_modifiers(asset), - **self._rho_cp_modifiers, - **self._get_cost_figure_modifiers(asset), - ) - - if asset.asset_type == "GeothermalSource": - modifiers["nr_of_doublets"] = asset.attributes["aggregationCount"] - modifiers["Heat_source"] = dict( - min=0.0, - max=max_supply * asset.attributes["aggregationCount"], - nominal=max_supply / 2.0, - ) - modifiers["Heat_flow"] = dict( - min=0.0, - max=max_supply * asset.attributes["aggregationCount"], - nominal=max_supply / 2.0, - ) - try: - modifiers["single_doublet_power"] = asset.attributes["single_doublet_power"] - except KeyError: - modifiers["single_doublet_power"] = max_supply - # Note that the ESDL target flow rate is in kg/s, but we want m3/s - try: - modifiers["target_flow_rate"] = asset.attributes["flowRate"] / self.rho - except KeyError: - logger.warning( - f"{asset.asset_type} '{asset.name}' has no desired flow rate specified. " - f"'{asset.name}' will not be actuated in a constant manner" - ) - - return GeothermalSource, modifiers - else: - return HeatSource, modifiers - - def convert_ates(self, asset: Asset) -> Tuple[Type[ATES], MODIFIERS]: - """ - This function converts the ATES object in esdl to a set of modifiers that can be used in - a pycml object. Most important: - - - Setting the milp loss coefficient based upon the efficiency. Here we assume that this - efficiency is realized in 100 days. - - Setting a caps on the thermal power. - - Similar as for the geothermal source we use the aggregation count to model the amount - of doublets. - - Setting caps on the maximum stored energy where we assume that at maximum you can charge - for 180 days at full power. - - Setting the state (enabled, disabled, optional) - - Setting the relevant temperatures. - - Setting the relevant cost figures. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - ATES class with modifiers - """ - assert asset.asset_type in { - "ATES", - } - - hfr_charge_max = asset.attributes.get("maxChargeRate", math.inf) - hfr_discharge_max = asset.attributes.get("maxDischargeRate", math.inf) - - try: - # TODO: this is depriciated it comes out of old integraal times. Should be removed. - single_doublet_power = asset.attributes["single_doublet_power"] - except KeyError: - single_doublet_power = hfr_discharge_max - - # We assume the efficiency is realized over a period of 100 days - efficiency = asset.attributes["dischargeEfficiency"] - if not efficiency: - efficiency = 0.7 - - # TODO: temporary value for standard dT on which capacity is based, Q in m3/s - temperatures = self._supply_return_temperature_modifiers(asset) - dt = temperatures["T_supply"] - temperatures["T_return"] - rho = self.rho - cp = self.cp - q_max_ates = hfr_discharge_max / (cp * rho * dt) - - q_nominal = min( - self._get_connected_q_nominal(asset), q_max_ates * asset.attributes["aggregationCount"] - ) - - modifiers = dict( - technical_life=self.get_asset_attribute_value( - asset, - "technicalLifetime", - default_value=30.0, - min_value=1.0, - max_value=50.0, - ), - discount_rate=self.get_asset_attribute_value( - asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 - ), - Q_nominal=q_nominal, - Q=dict( - min=-q_max_ates * asset.attributes["aggregationCount"], - max=q_max_ates * asset.attributes["aggregationCount"], - nominal=q_nominal, - ), - T_amb=asset.attributes["aquiferMidTemperature"], - Temperature_ates=dict( - min=temperatures["T_return"], # or potentially 0 - max=temperatures["T_supply"], - nominal=temperatures["T_return"], - ), - single_doublet_power=single_doublet_power, - heat_loss_coeff=(1.0 - efficiency ** (1.0 / 100.0)) / (3600.0 * 24.0), - state=self.get_state(asset), - nr_of_doublets=asset.attributes["aggregationCount"], - Heat_ates=dict( - min=-hfr_charge_max * asset.attributes["aggregationCount"], - max=hfr_discharge_max * asset.attributes["aggregationCount"], - nominal=hfr_discharge_max / 2.0, - ), - Stored_heat=dict( - min=0.0, - max=hfr_charge_max * asset.attributes["aggregationCount"] * 180.0 * 24 * 3600.0, - nominal=hfr_charge_max * asset.attributes["aggregationCount"] * 30.0 * 24 * 3600.0, - ), - HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - **self._supply_return_temperature_modifiers(asset), - **self._rho_cp_modifiers, - **self._get_cost_figure_modifiers(asset), - ) - - return ATES, modifiers - - def convert_control_valve(self, asset: Asset) -> Tuple[Type[ControlValve], MODIFIERS]: - """ - This function converts the ControlValve object in esdl to a set of modifiers that can be - used in a pycml object. Most important: - - - Setting the state (enabled, disabled, optional) - - Setting the relevant temperatures. - - Setting the relevant cost figures. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - ControlValve class with modifiers - """ - assert asset.asset_type == "Valve" - - q_nominal = self._get_connected_q_nominal(asset) - - modifiers = dict( - technical_life=self.get_asset_attribute_value( - asset, - "technicalLifetime", - default_value=30.0, - min_value=1.0, - max_value=50.0, - ), - discount_rate=self.get_asset_attribute_value( - asset, "discountRate", default_value=0.0, min_value=0.0, max_value=100.0 - ), - HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - Q_nominal=q_nominal, - state=self.get_state(asset), - **self._supply_return_temperature_modifiers(asset), - **self._rho_cp_modifiers, - ) - - return ControlValve, modifiers - - def convert_check_valve(self, asset: Asset) -> Tuple[Type[CheckValve], MODIFIERS]: - """ - This function converts the CheckValve object in esdl to a set of modifiers that can be - used in a pycml object. Most important: - - - Setting the state (enabled, disabled, optional) - - Setting the relevant temperatures. - - Setting the relevant cost figures. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - CheckValve class with modifiers - """ - assert asset.asset_type == "CheckValve" - - q_nominal = self._get_connected_q_nominal(asset) - - modifiers = dict( - Q_nominal=q_nominal, - state=self.get_state(asset), - HeatIn=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - HeatOut=dict(Hydraulic_power=dict(nominal=q_nominal * 16.0e5)), - **self._supply_return_temperature_modifiers(asset), - **self._rho_cp_modifiers, - ) - - return CheckValve, modifiers - - def convert_electricity_demand(self, asset: Asset) -> Tuple[Type[ElectricityDemand], MODIFIERS]: - """ - This function converts the ElectricityDemand object in esdl to a set of modifiers that can - be used in a pycml object. Most important: - - - Setting the electrical power caps - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - ElectricityDemand class with modifiers - """ - assert asset.asset_type in {"ElectricityDemand"} - - max_demand = asset.attributes.get("power", math.inf) - min_voltage = asset.in_ports[0].carrier.voltage - i_max, i_nom = self._get_connected_i_nominal_and_max(asset) - - id_mapping = asset.global_properties["carriers"][asset.in_ports[0].carrier.id][ - "id_number_mapping" - ] - - modifiers = dict( - min_voltage=min_voltage, - id_mapping_carrier=id_mapping, - elec_power_nominal=max_demand / 2.0, - Electricity_demand=dict(max=max_demand, nominal=max_demand / 2.0), - ElectricityIn=dict( - Power=dict(min=0.0, max=max_demand, nominal=max_demand / 2.0), - I=dict(min=0.0, max=i_max, nominal=i_nom), - V=dict(min=min_voltage, nominal=min_voltage), - ), - **self._get_cost_figure_modifiers(asset), - ) - - return ElectricityDemand, modifiers - - def convert_electricity_source(self, asset: Asset) -> Tuple[Type[ElectricitySource], MODIFIERS]: - """ - This function converts the ElectricitySource object in esdl to a set of modifiers that can - be used in a pycml object. Most important: - - - Setting the electrical power caps - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - ElectricitySource class with modifiers - """ - assert asset.asset_type in {"ElectricityProducer", "WindPark"} - - max_supply = asset.attributes.get( - "power", math.inf - ) # I think it would break with math.inf as input - i_max, i_nom = self._get_connected_i_nominal_and_max(asset) - v_min = asset.out_ports[0].carrier.voltage - - modifiers = dict( - power_nominal=max_supply / 2.0, - Electricity_source=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), - ElectricityOut=dict( - V=dict(min=v_min, nominal=v_min), - I=dict(min=0.0, max=i_max, nominal=i_nom), - Power=dict(min=0.0, max=max_supply, nominal=max_supply / 2.0), - ), - **self._get_cost_figure_modifiers(asset), - ) - - if asset.asset_type == "ElectricityProducer": - return ElectricitySource, modifiers - if asset.asset_type == "WindPark": - return WindPark, modifiers - - def convert_electricity_node(self, asset: Asset) -> Tuple[Type[ElectricityNode], MODIFIERS]: - """ - This function converts the ElectricityNode object in esdl to a set of modifiers that can be - used in a pycml object. Most important: - - - Setting the number of connections - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - ElectricityNode class with modifiers - """ - assert asset.asset_type in {"Bus"} - - sum_in = 0 - sum_out = 0 - - node_carrier = None - for x in asset.attributes["port"].items: - if node_carrier is None: - node_carrier = x.carrier.name - nominal_voltage = x.carrier.voltage - else: - if node_carrier != x.carrier.name: - raise _ESDLInputException( - f"{asset.name} has multiple carriers mixing which is not allowed. " - ) - if isinstance(x, esdl.esdl.InPort): - sum_in += len(x.connectedTo) - if isinstance(x, esdl.esdl.OutPort): - sum_out += len(x.connectedTo) - - modifiers = dict(voltage_nominal=nominal_voltage, n=sum_in + sum_out) - - return ElectricityNode, modifiers - - def convert_electricity_cable(self, asset: Asset) -> Tuple[Type[ElectricityCable], MODIFIERS]: - """ - This function converts the ElectricityCable object in esdl to a set of modifiers that can be - used in a pycml object. Most important: - - - Setting the length of the cable used for power loss computation. - - setting the min and max current. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - ElectricityCable class with modifiers - """ - assert asset.asset_type in {"ElectricityCable"} - - max_power = asset.attributes["capacity"] - min_voltage = asset.in_ports[0].carrier.voltage - max_current = max_power / min_voltage - self._set_electricity_current_nominal_and_max(asset, max_current / 2.0, max_current) - - modifiers = dict( - max_current=max_current, - min_voltage=min_voltage, - nominal_current=max_current / 2.0, - nominal_voltage=min_voltage, - length=asset.attributes["length"], - ElectricityOut=dict( - V=dict(min=min_voltage, nominal=min_voltage), - I=dict(min=-max_current, max=max_current, nominal=max_current / 2.0), - Power=dict(min=-max_power, max=max_power, nominal=max_power / 2.0), - ), - ElectricityIn=dict( - V=dict(min=min_voltage, nominal=min_voltage), - I=dict(min=-max_current, max=max_current, nominal=max_current / 2.0), - Power=dict(min=-max_power, max=max_power, nominal=max_power / 2.0), - ), - **self._get_cost_figure_modifiers(asset), - ) - return ElectricityCable, modifiers - - def convert_gas_demand(self, asset: Asset) -> Tuple[Type[GasDemand], MODIFIERS]: - """ - This function converts the GasDemand object in esdl to a set of modifiers that can be - used in a pycml object. Most important: - - - ... - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - GasDemand class with modifiers - """ - assert asset.asset_type in {"GasDemand"} - - id_mapping = asset.global_properties["carriers"][asset.in_ports[0].carrier.id][ - "id_number_mapping" - ] - # DO not remove due usage in future - # hydrogen_specfic_energy = 20.0 / 1.0e6 - density = self.get_density(asset.name, asset.in_ports[0].carrier) - q_nominal = self._get_connected_q_nominal(asset) - - modifiers = dict( - Q_nominal=q_nominal, - id_mapping_carrier=id_mapping, - # Gas_demand_mass_flow=dict(min=0., max=asset.attributes["power"] - # *hydrogen_specfic_energy), - density=density, - GasIn=dict( - Q=dict( - min=0.0, - max=self._get_connected_q_max(asset), - nominal=self._get_connected_q_nominal(asset), - ), - mass_flow=dict(nominal=density * q_nominal), - ), - **self._get_cost_figure_modifiers(asset), - ) - - return GasDemand, modifiers - - def convert_gas_source(self, asset: Asset) -> Tuple[Type[GasSource], MODIFIERS]: - """ - This function converts the GasDemand object in esdl to a set of modifiers that can be - used in a pycml object. Most important: - - - ... - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - GasDemand class with modifiers - """ - assert asset.asset_type in {"GasProducer"} - - q_nominal = self._get_connected_q_nominal(asset) - density_value = self.get_density(asset.name, asset.out_ports[0].carrier) - - bounds_nominals_mass_flow = dict( - min=0.0, - max=self._get_connected_q_max(asset) * density_value, - nominal=q_nominal * density_value, - ) - - modifiers = dict( - Q_nominal=q_nominal, - density=density_value, - Gas_source_mass_flow=bounds_nominals_mass_flow, - GasOut=dict( - Q=dict(nominal=q_nominal), - mass_flow=bounds_nominals_mass_flow, - ), - **self._get_cost_figure_modifiers(asset), - ) - - return GasSource, modifiers - - def convert_electrolyzer(self, asset: Asset) -> Tuple[Type[Electrolyzer], MODIFIERS]: - """ - This function converts the Electrolyzer object in esdl to a set of modifiers that can be - used in a pycml object. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - Electrolyzer class with modifiers - """ - assert asset.asset_type in {"Electrolyzer"} - - i_max, i_nom = self._get_connected_i_nominal_and_max(asset) - v_min = asset.in_ports[0].carrier.voltage - max_power = asset.attributes.get("power", math.inf) - min_load = float(asset.attributes["minLoad"]) - max_load = float(asset.attributes["maxLoad"]) - eff_min_load = asset.attributes["effMinLoad"] # Wh/g - eff_max_load = asset.attributes["effMaxLoad"] # Wh/g - eff_max = asset.attributes["efficiency"] # Wh/g - - def equations(x): - a, b, c = x - eq1 = a / min_load + b * min_load + c - eff_min_load - eq2 = a / max_load + b * max_load + c - eff_max_load - eq3 = a / (min_load * 2.5) + b * (min_load * 2.5) + c - eff_max - return [eq1, eq2, eq3] - - # Here we approximate the efficiency curve of the electrolyzer with the function: - # 1/eff = a/P_e + b*P_e + c. We find the coefficients with a simple solve function. - # At the moment we abbuse the efficiency attribute of esdl to quantify the maximum - # operational efficiency. - a, b, c = fsolve(equations, (0, 0, 0)) - - q_nominal = self._get_connected_q_nominal(asset) - density = self.get_density(asset.name, asset.out_ports[0].carrier) - - modifiers = dict( - min_voltage=v_min, - a_eff_coefficient=a, - b_eff_coefficient=b, - c_eff_coefficient=c, - minimum_load=min_load, - nominal_power_consumed=max_power / 2.0, - Q_nominal=q_nominal, - density=density, - GasOut=dict( - Q=dict( - min=0.0, - max=self._get_connected_q_max(asset), - nominal=q_nominal, - ), - mass_flow=dict(nominal=q_nominal * density), - ), - ElectricityIn=dict( - Power=dict(min=0.0, max=max_power, nominal=max_power / 2.0), - I=dict(min=0.0, max=i_max, nominal=i_nom), - V=dict(min=v_min, nominal=v_min), - ), - **self._get_cost_figure_modifiers(asset), - ) - - return Electrolyzer, modifiers - - def convert_gas_tank_storage(self, asset: Asset) -> Tuple[Type[GasTankStorage], MODIFIERS]: - """ - This function converts the GasTankStorage object in esdl to a set of modifiers that can be - used in a pycml object. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - GasTankStorage class with modifiers - """ - assert asset.asset_type in {"GasStorage"} - - # DO not remove due usage in future - # hydrogen_specific_energy = 20.0 / 1.0e6 # kg/Wh - q_nominal = self._get_connected_q_nominal(asset) - density = self.get_density(asset.name, asset.in_ports[0].carrier) - - modifiers = dict( - Q_nominal=q_nominal, - density=density, - volume=asset.attributes["workingVolume"], - # Gas_tank_flow=dict(min=-hydrogen_specific_energy*asset.attributes["maxDischargeRate"], - # max=hydrogen_specific_energy*asset.attributes["maxChargeRate"]), - # TODO: Fix -> Gas network is currenlty non-limiting, mass flow is decoupled from the - # volumetric flow - # Gas_tank_flow=dict( - # min=-self._get_connected_q_max(asset), max=self._get_connected_q_max(asset), - # nominal=self._get_connected_q_nominal(asset), - # ) - GasIn=dict(Q=dict(nominal=q_nominal), mass_flow=dict(nominal=q_nominal * density)), - **self._get_cost_figure_modifiers(asset), - ) - - return GasTankStorage, modifiers - - def convert_gas_substation(self, asset: Asset) -> Tuple[Type[GasSubstation], MODIFIERS]: - """ - This function converts the GasTankStorage object in esdl to a set of modifiers that can be - used in a pycml object. - - Parameters - ---------- - asset : The asset object with its properties. - - Returns - ------- - GasTankStorage class with modifiers - """ - assert asset.asset_type in {"GasConversion"} - - q_nom_in, q_nom_out = self._get_connected_q_nominal(asset) - density_in = self.get_density(asset.name, asset.in_ports[0].carrier) - density_out = self.get_density(asset.name, asset.out_ports[0].carrier) - - modifiers = dict( - Q_nominal_in=q_nom_in, - Q_nominal_out=q_nom_out, - density_in=density_in, - density_out=density_out, - GasIn=dict(Q=dict(nominal=q_nom_in), mass_flow=dict(nominal=q_nom_in * density_in)), - GasOut=dict(Q=dict(nominal=q_nom_out), mass_flow=dict(nominal=q_nom_out * density_out)), - **self._get_cost_figure_modifiers(asset), - ) - - return GasSubstation, modifiers - - -class ESDLHeatModel(_ESDLModelBase): - """ - This class is used to convert the esdl Assets to PyCML assets this class only exists to specify - the specific objects used in the conversion step. Note there is no __init__ in the base class. - This probably could be standardized in that case this class would become obsolete. - """ - - def __init__(self, assets: Dict[str, Asset], converter_class=AssetToHeatComponent, **kwargs): - super().__init__(None) - - converter = converter_class( - **{ - **kwargs, - **{ - "primary_port_name_convention": self.primary_port_name_convention, - "secondary_port_name_convention": self.secondary_port_name_convention, - }, - } - ) - - self._esdl_convert(converter, assets, "Heat") diff --git a/src/rtctools_heat_network/esdl/esdl_model_base.py b/src/rtctools_heat_network/esdl/esdl_model_base.py deleted file mode 100644 index 1bd2abacd..000000000 --- a/src/rtctools_heat_network/esdl/esdl_model_base.py +++ /dev/null @@ -1,331 +0,0 @@ -import logging -from typing import Dict - -import esdl -from esdl import InPort - -from rtctools_heat_network.esdl.asset_to_component_base import _AssetToComponentBase -from rtctools_heat_network.pycml import Model as _Model - -from ._exceptions import _RetryLaterException, _SkipAssetException - -logger = logging.getLogger("rtctools_heat_network") - - -RETRY_LOOP_LIMIT = 100 - - -class _ESDLModelBase(_Model): - """ - This is the ESDL base class that is used to convert from the esdl parsed assets to the pycml - model description. In the base class we specify how the network is connected, meaning which - asset is connected to which asset as this is the same for different model types (both - Heat and QTH). Per model type we have a specialization for the converting of the assets as - different models might need different information from the esdl file. - """ - - primary_port_name_convention = "prim" - secondary_port_name_convention = "sec" - - def _esdl_convert(self, converter: _AssetToComponentBase, assets: Dict, prefix: str) -> None: - """ - In this function we convert the esdl parsed assets and instantiate the pycml objects for - those assets. We use the converter to create those pycml objects and the same time we look - at the connections specified in the esdl and create the relevant maps between ports to then - also connect the pycml ports of the assets. - - Parameters - ---------- - converter : class with the different converter functions for all asset types. - assets : a dict with all the parsed esdl assets and their attributes - prefix : prefix for the name of the model type Heat or QTH at the moment - - Returns - ------- - None - """ - # Sometimes we need information of one component in order to convert - # another. For example, the nominal discharge of a pipe is used to set - # the nominal discharge of its connected components. - retry_assets = list(assets.values()) - skip_assets = list() - - for _ in range(RETRY_LOOP_LIMIT): - current_assets = retry_assets - retry_assets = [] - - for asset in current_assets: - try: - pycml_type, modifiers = converter.convert(asset) - except _SkipAssetException: - skip_assets.append(asset) - continue - except _RetryLaterException: - retry_assets.append(asset) - continue - - self.add_variable(pycml_type, asset.name, **modifiers) - - if not retry_assets: - break - else: - raise Exception("Parsing of assets exceeded maximum iteration limit.") - - in_suf = f"{prefix}In" - out_suf = f"{prefix}Out" - node_suf = f"{prefix}Conn" - elec_in_suf = "ElectricityIn" - elec_out_suf = "ElectricityOut" - elec_node_suf = "ElectricityConn" - gas_in_suf = "GasIn" - gas_out_suf = "GasOut" - gas_node_suf = "GasConn" - - skip_asset_ids = {a.id for a in skip_assets} - # pipe_assets = [ - # a - # for a in assets.values() - # if ( - # a.asset_type == "heat_pipe" - # and a.id not in skip_asset_ids - # and isinstance(a.in_ports[0].carrier, esdl.HeatCommodity) - # ) - # ] - node_assets = [ - a - for a in assets.values() - if ( - (a.asset_type == "Joint") - and a.id not in skip_asset_ids - and ( - (isinstance(a.in_ports[0].carrier, esdl.HeatCommodity)) - or isinstance(a.out_ports[0].carrier, esdl.HeatCommodity) - ) - ) - ] - gas_node_assets = [ - a - for a in assets.values() - if ( - (a.asset_type == "Joint") - and a.id not in skip_asset_ids - and ( - (isinstance(a.in_ports[0].carrier, esdl.GasCommodity)) - or isinstance(a.out_ports[0].carrier, esdl.GasCommodity) - ) - ) - ] - bus_assets = [ - a for a in assets.values() if ((a.asset_type == "Bus") and a.id not in skip_asset_ids) - ] - non_node_assets = [ - a - for a in assets.values() - if (a.asset_type != "Joint" and a.asset_type != "Bus") and a.id not in skip_asset_ids - ] - - # First we map all port ids to their respective PyCML ports. We only - # do this for non-nodes, as for nodes we don't quite know what port - # index a connection has to use yet. - port_map = {} - - for asset in non_node_assets: - component = getattr(self, asset.name) - # We assume that every component has 2 ports. Essentially meaning that we are dealing - # with a single commodity for a component. Exceptions, assets that deal with multiple - # have to be specifically specified what port configuration is expected in the model. - if ( - asset.asset_type == "GenericConversion" - or asset.asset_type == "HeatExchange" - or asset.asset_type == "HeatPump" - ): - if prefix != "Heat": - raise Exception( - "Hydraulically decoulpled systems are not yet supported for nonlinear (QTH)" - "optimization" - ) - # check for expected number of ports - if len(asset.in_ports) == 2 and len(asset.out_ports) == 2: - for p in [*asset.in_ports, *asset.out_ports]: - if isinstance(p.carrier, esdl.HeatCommodity): - if isinstance(p, InPort): - if self.secondary_port_name_convention in p.name.lower(): - port_map[p.id] = getattr(component.Secondary, in_suf) - else: - port_map[p.id] = getattr(component.Primary, in_suf) - else: # OutPort - if self.primary_port_name_convention in p.name.lower(): - port_map[p.id] = getattr(component.Primary, out_suf) - else: - port_map[p.id] = getattr(component.Secondary, out_suf) - else: - raise Exception( - f"{asset.name} has does not have 2 Heat in_ports and 2 Heat " - f"out_ports " - ) - elif len(asset.in_ports) == 3 and len(asset.out_ports) == 2: - p_heat = 0 - p_elec = 0 - for p in [*asset.in_ports, *asset.out_ports]: - if isinstance(p.carrier, esdl.HeatCommodity) and p_heat <= 3: - if isinstance(p, InPort): - if self.secondary_port_name_convention in p.name.lower(): - port_map[p.id] = getattr(component.Secondary, in_suf) - else: - port_map[p.id] = getattr(component.Primary, in_suf) - else: # OutPort - if self.primary_port_name_convention in p.name.lower(): - port_map[p.id] = getattr(component.Primary, out_suf) - else: - port_map[p.id] = getattr(component.Secondary, out_suf) - p_heat += 1 - elif isinstance(p.carrier, esdl.ElectricityCommodity) and p_elec == 0: - port_map[p.id] = getattr(component, elec_in_suf) - p_elec += 1 - else: - raise Exception( - f"{asset.name} has total of 5 ports, but no proper split between " - f"milp(4) and electricity (1) ports" - ) - - else: - raise Exception( - f"{asset.name} has does not have 2 or 3 in_ports and 2 " f"out_ports " - ) - elif asset.asset_type == "Electrolyzer": - if len(asset.out_ports) == 1 and len(asset.in_ports) == 1: - if isinstance(asset.out_ports[0].carrier, esdl.GasCommodity): - port_map[asset.out_ports[0].id] = getattr(component, gas_out_suf) - else: - raise Exception(f"{asset.name} must have a gas commodity on the outport") - if isinstance(asset.in_ports[0].carrier, esdl.ElectricityCommodity): - port_map[asset.in_ports[0].id] = getattr(component, elec_in_suf) - else: - raise Exception( - f"{asset.name} must have a electricity commodity on the inport " - ) - else: - raise Exception( - f"{asset.name} must have one inport for electricity and one outport for gas" - ) - elif ( - asset.in_ports is None - and isinstance(asset.out_ports[0].carrier, esdl.ElectricityCommodity) - and len(asset.out_ports) == 1 - ): - port_map[asset.out_ports[0].id] = getattr(component, elec_out_suf) - elif ( - asset.in_ports is None - and isinstance(asset.out_ports[0].carrier, esdl.GasCommodity) - and len(asset.out_ports) == 1 - ): - port_map[asset.out_ports[0].id] = getattr(component, gas_out_suf) - elif ( - len(asset.in_ports) == 1 - and isinstance(asset.in_ports[0].carrier, esdl.ElectricityCommodity) - and asset.out_ports is None - ): - port_map[asset.in_ports[0].id] = getattr(component, elec_in_suf) - elif ( - len(asset.in_ports) == 1 - and isinstance(asset.in_ports[0].carrier, esdl.GasCommodity) - and asset.out_ports is None - ): - port_map[asset.in_ports[0].id] = getattr(component, gas_in_suf) - elif ( - len(asset.in_ports) == 1 - and isinstance(asset.in_ports[0].carrier, esdl.HeatCommodity) - and len(asset.out_ports) == 1 - ): - port_map[asset.in_ports[0].id] = getattr(component, in_suf) - port_map[asset.out_ports[0].id] = getattr(component, out_suf) - elif ( - len(asset.in_ports) == 1 - and isinstance(asset.in_ports[0].carrier, esdl.ElectricityCommodity) - and len(asset.out_ports) == 1 - ): - port_map[asset.in_ports[0].id] = getattr(component, elec_in_suf) - port_map[asset.out_ports[0].id] = getattr(component, elec_out_suf) - elif ( - len(asset.in_ports) == 1 - and isinstance(asset.in_ports[0].carrier, esdl.GasCommodity) - and len(asset.out_ports) == 1 - ): - port_map[asset.in_ports[0].id] = getattr(component, gas_in_suf) - port_map[asset.out_ports[0].id] = getattr(component, gas_out_suf) - else: - raise Exception(f"Unsupported ports for asset type {asset.name}.") - - # Nodes are special in that their in/out ports can have multiple - # connections. This means we have some bookkeeping to do per node. We - # therefore do the nodes first, and do all remaining connections - # after. - connections = set() - - for asset in [*node_assets, *bus_assets, *gas_node_assets]: - component = getattr(self, asset.name) - - i = 1 - if len(asset.in_ports) != 1 or len(asset.out_ports) != 1: - Exception( - f"{asset.name} has !=1 in or out ports, please only use one, " - f"multiple connections to a single joint port are allowed" - ) - for port in (asset.in_ports[0], asset.out_ports[0]): - for connected_to in port.connectedTo.items: - conn = (port.id, connected_to.id) - if conn in connections or tuple(reversed(conn)) in connections: - continue - if isinstance(port.carrier, esdl.HeatCommodity): - self.connect(getattr(component, node_suf)[i], port_map[connected_to.id]) - connections.add(conn) - i += 1 - elif isinstance(port.carrier, esdl.ElectricityCommodity): - self.connect( - getattr(component, elec_node_suf)[i], port_map[connected_to.id] - ) - connections.add(conn) - i += 1 - elif isinstance(port.carrier, esdl.GasCommodity): - self.connect(getattr(component, gas_node_suf)[i], port_map[connected_to.id]) - connections.add(conn) - i += 1 - else: - logger.error( - f"asset {asset.name} has an unsupported carrier type for a node" - ) - - skip_port_ids = set() - for a in skip_assets: - if a.in_ports is not None: - for port in a.in_ports: - skip_port_ids.add(port.id) - if a.out_ports is not None: - for port in a.out_ports: - skip_port_ids.add(port.id) - - # All non-Joints/nodes - for asset in non_node_assets: - ports = [] - if asset.in_ports is not None: - ports.extend(asset.in_ports) - if asset.out_ports is not None: - ports.extend(asset.out_ports) - assert len(ports) > 0 - for port in ports: - connected_ports = [p for p in port.connectedTo.items if p.id not in skip_port_ids] - if len(connected_ports) != 1: - logger.warning( - f"{asset.asset_type} '{asset.name}' has multiple connections" - f" to a single port. " - ) - - assert len(connected_ports) == 1 - - for connected_to in connected_ports: - conn = (port.id, connected_to.id) - if conn in connections or tuple(reversed(conn)) in connections: - continue - - self.connect(port_map[port.id], port_map[connected_to.id]) - connections.add(conn) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/_internal/electricity_component.py b/src/rtctools_heat_network/pycml/component_library/milp/_internal/electricity_component.py deleted file mode 100644 index 48a81ea0b..000000000 --- a/src/rtctools_heat_network/pycml/component_library/milp/_internal/electricity_component.py +++ /dev/null @@ -1,9 +0,0 @@ -from rtctools_heat_network.pycml.component_library.milp._internal.heat_component import BaseAsset - - -class ElectricityComponent(BaseAsset): - """ - Base electricity component nothing to add here yet. - """ - - pass diff --git a/src/rtctools_heat_network/pycml/component_library/milp/_internal/gas_component.py b/src/rtctools_heat_network/pycml/component_library/milp/_internal/gas_component.py deleted file mode 100644 index e137c4cf4..000000000 --- a/src/rtctools_heat_network/pycml/component_library/milp/_internal/gas_component.py +++ /dev/null @@ -1,9 +0,0 @@ -from rtctools_heat_network.pycml.component_library.milp._internal.heat_component import BaseAsset - - -class GasComponent(BaseAsset): - """ - Base gas component nothing to add here yet. - """ - - pass diff --git a/src/rtctools_heat_network/pycml/component_library/milp/electricity/windpark.py b/src/rtctools_heat_network/pycml/component_library/milp/electricity/windpark.py deleted file mode 100644 index 27cd259fb..000000000 --- a/src/rtctools_heat_network/pycml/component_library/milp/electricity/windpark.py +++ /dev/null @@ -1,12 +0,0 @@ -from rtctools_heat_network.pycml import Variable - -from .. import ElectricitySource - - -class WindPark(ElectricitySource): - def __init__(self, name, **modifiers): - super().__init__(name, **modifiers) - - self.component_subtype = "wind_park" - - self.add_variable(Variable, "Set_point", min=0.0, max=1.0) diff --git a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_two_port.py b/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_two_port.py deleted file mode 100644 index 9fc8df892..000000000 --- a/src/rtctools_heat_network/pycml/component_library/milp/heat/heat_two_port.py +++ /dev/null @@ -1,17 +0,0 @@ -from rtctools_heat_network.pycml.component_library.milp._internal import HeatComponent - -from .heat_port import HeatPort - - -class HeatTwoPort(HeatComponent): - """ - The HeatTwoPort component is used as a base for interaction with one hydraulically coupled - system. As milp networks are closed systems we always need two ports to model both the in and - out going flow in the system. - """ - - def __init__(self, name, **modifiers): - super().__init__(name, **modifiers) - - self.add_variable(HeatPort, "HeatIn") - self.add_variable(HeatPort, "HeatOut") diff --git a/src/rtctools_heat_network/pycml/component_library/milp/multicommodity/__init__.py b/src/rtctools_heat_network/pycml/component_library/milp/multicommodity/__init__.py deleted file mode 100644 index f4f241c46..000000000 --- a/src/rtctools_heat_network/pycml/component_library/milp/multicommodity/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -from .electrolyzer import Electrolyzer - -__all__ = [ - "Electrolyzer", -] diff --git a/src/rtctools_heat_network/pycml/component_library/qth/_internal/qth_component.py b/src/rtctools_heat_network/pycml/component_library/qth/_internal/qth_component.py deleted file mode 100644 index 712ec0b1d..000000000 --- a/src/rtctools_heat_network/pycml/component_library/qth/_internal/qth_component.py +++ /dev/null @@ -1,5 +0,0 @@ -from rtctools_heat_network.pycml import Component - - -class QTHComponent(Component): - pass diff --git a/src/rtctools_heat_network/workflows/utils/adapt_profiles.py b/src/rtctools_heat_network/workflows/utils/adapt_profiles.py deleted file mode 100644 index 59fba692f..000000000 --- a/src/rtctools_heat_network/workflows/utils/adapt_profiles.py +++ /dev/null @@ -1,175 +0,0 @@ -from __future__ import annotations - -import datetime -import logging - -import numpy as np - -from rtctools.data.storage import DataStore - - -logger = logging.getLogger("WarmingUP-MPC") -logger.setLevel(logging.INFO) - - -def set_data_with_averages_and_peak_day( - datastore: DataStore, - variable_name: str, - ensemble_member: int, - new_date_times: np.array, - problem: object, -): - try: - data = problem.get_timeseries(variable=variable_name, ensemble_member=ensemble_member) - except KeyError: - datastore.set_timeseries( - variable=variable_name, - datetimes=new_date_times, - values=np.asarray([0.0] * len(new_date_times)), - ensemble_member=ensemble_member, - check_duplicates=True, - ) - return - - new_data = list() - data_timestamps = data.times - data_datetimes = [ - problem.io.datetimes[0] + datetime.timedelta(seconds=s) for s in data_timestamps - ] - assert new_date_times[0] == data_datetimes[0] - data_values = data.values - - values_for_mean = [0.0] - for dt, val in zip(data_datetimes, data_values): - if dt in new_date_times: - new_data.append(np.mean(values_for_mean)) - values_for_mean = [val] - else: - values_for_mean.append(val) - - # last datetime is not in input data, so we need to take the mean of the last bit - new_data.append(np.mean(values_for_mean)) - - datastore.set_timeseries( - variable=variable_name, - datetimes=new_date_times, - values=np.asarray(new_data), - ensemble_member=ensemble_member, - check_duplicates=True, - ) - - -def adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day(problem, problem_day_steps: int): - """ - Adapt yearly porifle with hourly time steps to a common profile (daily averaged profile except - for the day with the peak demand). - - Return the following: - - problem_indx_max_peak: index of the maximum of the peak values - - heat_demand_nominal: max demand value found for a specific heating demand - """ - - demands = problem.energy_system_components.get("heat_demand", []) - new_datastore = DataStore(problem) - new_datastore.reference_datetime = problem.io.datetimes[0] - - for ensemble_member in range(problem.ensemble_size): - parameters = problem.parameters(ensemble_member) - total_demand = None - heat_demand_nominal = dict() - - for demand in demands: - try: - demand_values = problem.get_timeseries( - f"{demand}.target_heat_demand", ensemble_member - ).values - except KeyError: - continue - if total_demand is None: - total_demand = demand_values - else: - total_demand += demand_values - heat_demand_nominal[f"{demand}.Heat_demand"] = max(demand_values) - heat_demand_nominal[f"{demand}.Heat_flow"] = max(demand_values) - - # TODO: the approach of picking one peak day was introduced for a network with a tree - # layout and all big sources situated at the root of the tree. It is not guaranteed - # that an optimal solution is reached in different network topologies. - idx_max = int(np.argmax(total_demand)) - max_day = idx_max // 24 - nr_of_days = len(total_demand) // 24 - new_date_times = list() - day_steps = problem_day_steps - - problem_indx_max_peak = max_day // day_steps - if max_day % day_steps > 0: - problem_indx_max_peak += 1.0 - - for day in range(0, nr_of_days, day_steps): - if day == max_day // day_steps * day_steps: - if max_day > day: - new_date_times.append(problem.io.datetimes[day * 24]) - new_date_times.extend(problem.io.datetimes[max_day * 24 : max_day * 24 + 24]) - if (day + day_steps - 1) > max_day: - new_date_times.append(problem.io.datetimes[max_day * 24 + 24]) - else: - new_date_times.append(problem.io.datetimes[day * 24]) - new_date_times.append(problem.io.datetimes[-1] + datetime.timedelta(hours=1)) - - new_date_times = np.asarray(new_date_times) - parameters["times"] = [x.timestamp() for x in new_date_times] - - for demand in demands: - var_name = f"{demand}.target_heat_demand" - set_data_with_averages_and_peak_day( - datastore=new_datastore, - variable_name=var_name, - ensemble_member=ensemble_member, - new_date_times=new_date_times, - problem=problem, - ) - - # TODO: this has not been tested but is required if a production profile is included - # in the data - for source in problem.energy_system_components.get("heat_source", []): - var_name = f"{source}.maximum_heat_source" - try: - problem.get_timeseries(variable=var_name, ensemble_member=ensemble_member) - except KeyError: - logger.debug( - f"Source {source} has no production profile, thus it also will " - f"not be adapted to a different time scales." - ) - continue - - set_data_with_averages_and_peak_day( - datastore=new_datastore, - variable_name=var_name, - ensemble_member=ensemble_member, - new_date_times=new_date_times, - problem=problem, - ) - - for carrier_properties in problem.esdl_carriers.values(): - carrier_name = carrier_properties["name"] - var_name = f"{carrier_name}.price_profile" - try: - problem.get_timeseries(variable=var_name, ensemble_member=ensemble_member) - except KeyError: - logger.debug( - f"Carrier {carrier_name} has no price profile, thus it also will " - f"not be adapted to different time scales." - ) - set_data_with_averages_and_peak_day( - datastore=new_datastore, - variable_name=var_name, - ensemble_member=ensemble_member, - new_date_times=new_date_times, - problem=problem, - ) - - problem.io = new_datastore - - logger.info("Profile data has been adapted to a common format") - - return problem_indx_max_peak, heat_demand_nominal diff --git a/tests/models/absolute_heat/src/example.py b/tests/models/absolute_heat/src/example.py index a05a9101c..c45ac4fba 100644 --- a/tests/models/absolute_heat/src/example.py +++ b/tests/models/absolute_heat/src/example.py @@ -1,5 +1,10 @@ import casadi as ca +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -13,11 +18,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): """ diff --git a/tests/models/ates_temperature/input/Warmte_test_3.csv b/tests/models/ates_temperature/input/Warmte_test_3.csv index 710b1c657..fb5a4da11 100644 --- a/tests/models/ates_temperature/input/Warmte_test_3.csv +++ b/tests/models/ates_temperature/input/Warmte_test_3.csv @@ -1,4 +1,4 @@ -,DateTime,HeatingDemand_1,HeatingDemand_2,HeatingDemand_3 +DateTime,HeatingDemand_1,HeatingDemand_2,HeatingDemand_3 0,1-1-2019 00:00,885996.6024,226606.7,226606.7 1,1-1-2019 01:00,885788.1031999999,226553.36,226553.36 2,1-1-2019 02:00,929386.5671999999,237704.34,237704.34 diff --git a/tests/models/ates_temperature/src/run_ates_temperature.py b/tests/models/ates_temperature/src/run_ates_temperature.py index 9d91963a7..69024ff52 100644 --- a/tests/models/ates_temperature/src/run_ates_temperature.py +++ b/tests/models/ates_temperature/src/run_ates_temperature.py @@ -1,3 +1,10 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.io.write_output import ScenarioOutput + import numpy as np from rtctools.data.storage import DataStore @@ -13,13 +20,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.head_loss_class import HeadLossOption -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin -from rtctools_heat_network.workflows.io.write_output import ScenarioOutput - ns = {"fews": "http://www.wldelft.nl/fews", "pi": "http://www.wldelft.nl/fews/PI"} WATT_TO_MEGA_WATT = 1.0e6 @@ -331,7 +331,6 @@ def read(self): class HeatProblemMaxFlow(HeatProblem): - def read(self): super().read() diff --git a/tests/models/basic_buffer/src/compare.py b/tests/models/basic_buffer/src/compare.py index d95692a7a..d69e5cd6b 100644 --- a/tests/models/basic_buffer/src/compare.py +++ b/tests/models/basic_buffer/src/compare.py @@ -3,15 +3,15 @@ from abc import ABCMeta from pathlib import Path -from rtctools.optimization.modelica_mixin import ModelicaMixin - -from rtctools_heat_network.pycml.pycml_mixin import PyCMLMixin -from rtctools_heat_network.qth_not_maintained.qth_loop_mixin import ( +from mesido.pycml.pycml_mixin import PyCMLMixin +from mesido.qth_not_maintained.qth_loop_mixin import ( BufferTargetDischargeGoal, QTHLoopMixin, ) -from rtctools_heat_network.qth_not_maintained.qth_mixin import QTHMixin -from rtctools_heat_network.qth_not_maintained.util import run_heat_network_optimization +from mesido.qth_not_maintained.qth_mixin import QTHMixin +from mesido.qth_not_maintained.util import run_heat_network_optimization + +from rtctools.optimization.modelica_mixin import ModelicaMixin # We want to import the example we compare with as a module that is somewhat # uniquely identifiable. We therefore start from the root. diff --git a/tests/models/basic_buffer/src/model_heat.py b/tests/models/basic_buffer/src/model_heat.py index fd5513e6a..f2547393b 100644 --- a/tests/models/basic_buffer/src/model_heat.py +++ b/tests/models/basic_buffer/src/model_heat.py @@ -1,5 +1,5 @@ -from rtctools_heat_network.pycml import ControlInput, Model as _Model, Variable -from rtctools_heat_network.pycml.component_library.milp import ( +from mesido.pycml import ControlInput, Model as _Model, Variable +from mesido.pycml.component_library.milp import ( HeatBuffer, HeatDemand, HeatPipe, diff --git a/tests/models/basic_buffer/src/model_qth.py b/tests/models/basic_buffer/src/model_qth.py index abcbd2736..576b7540f 100644 --- a/tests/models/basic_buffer/src/model_qth.py +++ b/tests/models/basic_buffer/src/model_qth.py @@ -1,5 +1,5 @@ -from rtctools_heat_network.pycml import ControlInput, Model as _Model, SymbolicParameter, Variable -from rtctools_heat_network.pycml.component_library.qth import ( +from mesido.pycml import ControlInput, Model as _Model, SymbolicParameter, Variable +from mesido.pycml.component_library.qth import ( Buffer, Demand, Node, diff --git a/tests/models/basic_source_and_demand/src/heat_comparison.py b/tests/models/basic_source_and_demand/src/heat_comparison.py index ad4bd9834..94959b682 100644 --- a/tests/models/basic_source_and_demand/src/heat_comparison.py +++ b/tests/models/basic_source_and_demand/src/heat_comparison.py @@ -1,3 +1,8 @@ +from mesido.component_type_mixin import ModelicaComponentTypeMixin +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.physics_mixin import PhysicsMixin +from mesido.pycml.pycml_mixin import PyCMLMixin + from rtctools.optimization.collocated_integrated_optimization_problem import ( CollocatedIntegratedOptimizationProblem, ) @@ -6,11 +11,6 @@ from rtctools.optimization.modelica_mixin import ModelicaMixin from rtctools.util import run_optimization_problem -from rtctools_heat_network.component_type_mixin import ModelicaComponentTypeMixin -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.physics_mixin import PhysicsMixin -from rtctools_heat_network.pycml.pycml_mixin import PyCMLMixin - if __name__ == "__main__": from model_heat import Model else: diff --git a/tests/models/basic_source_and_demand/src/model_heat.py b/tests/models/basic_source_and_demand/src/model_heat.py index 61d7c7ce3..016100092 100644 --- a/tests/models/basic_source_and_demand/src/model_heat.py +++ b/tests/models/basic_source_and_demand/src/model_heat.py @@ -1,5 +1,5 @@ -from rtctools_heat_network.pycml import ControlInput, Model as _Model -from rtctools_heat_network.pycml.component_library.milp import ( +from mesido.pycml import ControlInput, Model as _Model +from mesido.pycml.component_library.milp import ( HeatDemand, HeatPipe, HeatSource, diff --git a/tests/models/basic_source_and_demand/src/model_qth.py b/tests/models/basic_source_and_demand/src/model_qth.py index 00d86accb..93fa0a8b6 100644 --- a/tests/models/basic_source_and_demand/src/model_qth.py +++ b/tests/models/basic_source_and_demand/src/model_qth.py @@ -1,5 +1,5 @@ -from rtctools_heat_network.pycml import ControlInput, Model as _Model, SymbolicParameter -from rtctools_heat_network.pycml.component_library.qth import Demand, Pipe, Pump, Source +from mesido.pycml import ControlInput, Model as _Model, SymbolicParameter +from mesido.pycml.component_library.qth import Demand, Pipe, Pump, Source class Model(_Model): diff --git a/tests/models/basic_source_and_demand/src/qth_comparison.py b/tests/models/basic_source_and_demand/src/qth_comparison.py index b96899a4a..30022503c 100644 --- a/tests/models/basic_source_and_demand/src/qth_comparison.py +++ b/tests/models/basic_source_and_demand/src/qth_comparison.py @@ -1,3 +1,11 @@ +from mesido.component_type_mixin import ModelicaComponentTypeMixin +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.pycml.pycml_mixin import PyCMLMixin +from mesido.qth_not_maintained.bounds_to_pipe_flow_directions_mixin import ( + BoundsToPipeFlowDirectionsMixin, +) +from mesido.qth_not_maintained.qth_mixin import QTHMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -10,14 +18,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.component_type_mixin import ModelicaComponentTypeMixin -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.pycml.pycml_mixin import PyCMLMixin -from rtctools_heat_network.qth_not_maintained.bounds_to_pipe_flow_directions_mixin import ( - BoundsToPipeFlowDirectionsMixin, -) -from rtctools_heat_network.qth_not_maintained.qth_mixin import QTHMixin - if __name__ == "__main__": from model_qth import Model else: @@ -97,7 +97,7 @@ class QTHESDL( @property def heat_network_flow_directions(self): pipes = self.energy_system_components["heat_pipe"] - return {p: "__fixed_positive_flow" for p in pipes} + return dict.fromkeys(pipes, "__fixed_positive_flow") def constant_inputs(self, ensemble_member): inputs = super().constant_inputs(ensemble_member) diff --git a/tests/models/basic_source_and_demand/src/qth_minimize_temperatures.py b/tests/models/basic_source_and_demand/src/qth_minimize_temperatures.py index bc84c607f..c7d3c89e0 100644 --- a/tests/models/basic_source_and_demand/src/qth_minimize_temperatures.py +++ b/tests/models/basic_source_and_demand/src/qth_minimize_temperatures.py @@ -1,3 +1,10 @@ +from mesido.component_type_mixin import ModelicaComponentTypeMixin +from mesido.pycml.pycml_mixin import PyCMLMixin +from mesido.qth_not_maintained.bounds_to_pipe_flow_directions_mixin import ( + BoundsToPipeFlowDirectionsMixin, +) +from mesido.qth_not_maintained.qth_mixin import DemandTemperatureOption, QTHMixin + from rtctools.optimization.collocated_integrated_optimization_problem import ( CollocatedIntegratedOptimizationProblem, ) @@ -7,13 +14,6 @@ from rtctools.optimization.single_pass_goal_programming_mixin import SinglePassGoalProgrammingMixin from rtctools.util import run_optimization_problem -from rtctools_heat_network.component_type_mixin import ModelicaComponentTypeMixin -from rtctools_heat_network.pycml.pycml_mixin import PyCMLMixin -from rtctools_heat_network.qth_not_maintained.bounds_to_pipe_flow_directions_mixin import ( - BoundsToPipeFlowDirectionsMixin, -) -from rtctools_heat_network.qth_not_maintained.qth_mixin import DemandTemperatureOption, QTHMixin - if __name__ == "__main__": from model_qth import Model else: diff --git a/tests/models/double_pipe_heat/src/double_pipe_heat.py b/tests/models/double_pipe_heat/src/double_pipe_heat.py index d2be2d28b..41d3dab72 100644 --- a/tests/models/double_pipe_heat/src/double_pipe_heat.py +++ b/tests/models/double_pipe_heat/src/double_pipe_heat.py @@ -1,3 +1,7 @@ +from mesido.component_type_mixin import ModelicaComponentTypeMixin +from mesido.physics_mixin import PhysicsMixin +from mesido.pycml.pycml_mixin import PyCMLMixin + from rtctools.optimization.collocated_integrated_optimization_problem import ( CollocatedIntegratedOptimizationProblem, ) @@ -5,10 +9,6 @@ from rtctools.optimization.goal_programming_mixin import Goal, GoalProgrammingMixin from rtctools.util import run_optimization_problem -from rtctools_heat_network.component_type_mixin import ModelicaComponentTypeMixin -from rtctools_heat_network.physics_mixin import PhysicsMixin -from rtctools_heat_network.pycml.pycml_mixin import PyCMLMixin - if __name__ == "__main__": from model import Model else: diff --git a/tests/models/double_pipe_heat/src/model.py b/tests/models/double_pipe_heat/src/model.py index f217002ee..473a91d71 100644 --- a/tests/models/double_pipe_heat/src/model.py +++ b/tests/models/double_pipe_heat/src/model.py @@ -1,5 +1,5 @@ -from rtctools_heat_network.pycml import ControlInput, Model as _Model -from rtctools_heat_network.pycml.component_library.milp import ( +from mesido.pycml import ControlInput, Model as _Model +from mesido.pycml.component_library.milp import ( HeatDemand, HeatPipe, HeatSource, diff --git a/tests/models/double_pipe_qth/src/cq2_inequality_vs_equality.py b/tests/models/double_pipe_qth/src/cq2_inequality_vs_equality.py index 883f6a957..802a9dcae 100644 --- a/tests/models/double_pipe_qth/src/cq2_inequality_vs_equality.py +++ b/tests/models/double_pipe_qth/src/cq2_inequality_vs_equality.py @@ -1,9 +1,9 @@ from abc import ABCMeta -from rtctools.util import run_optimization_problem +from mesido.qth_not_maintained.qth_loop_mixin import QTHLoopMixin +from mesido.qth_not_maintained.qth_mixin import HeadLossOption, QTHMixin -from rtctools_heat_network.qth_not_maintained.qth_loop_mixin import QTHLoopMixin -from rtctools_heat_network.qth_not_maintained.qth_mixin import HeadLossOption, QTHMixin +from rtctools.util import run_optimization_problem if __name__ == "__main__": from double_pipe_qth import DoublePipeBase diff --git a/tests/models/double_pipe_qth/src/double_pipe_qth.py b/tests/models/double_pipe_qth/src/double_pipe_qth.py index 69316bf14..b76ebd5c6 100644 --- a/tests/models/double_pipe_qth/src/double_pipe_qth.py +++ b/tests/models/double_pipe_qth/src/double_pipe_qth.py @@ -1,3 +1,9 @@ +from mesido.component_type_mixin import ModelicaComponentTypeMixin +from mesido.qth_not_maintained.bounds_to_pipe_flow_directions_mixin import ( + BoundsToPipeFlowDirectionsMixin, +) +from mesido.qth_not_maintained.qth_mixin import QTHMixin + from rtctools.optimization.collocated_integrated_optimization_problem import ( CollocatedIntegratedOptimizationProblem, ) @@ -7,12 +13,6 @@ from rtctools.optimization.modelica_mixin import ModelicaMixin from rtctools.util import run_optimization_problem -from rtctools_heat_network.component_type_mixin import ModelicaComponentTypeMixin -from rtctools_heat_network.qth_not_maintained.bounds_to_pipe_flow_directions_mixin import ( - BoundsToPipeFlowDirectionsMixin, -) -from rtctools_heat_network.qth_not_maintained.qth_mixin import QTHMixin - class TargetDemandGoal(Goal): priority = 1 diff --git a/tests/models/double_pipe_qth/src/single_pipe_no_headloss.py b/tests/models/double_pipe_qth/src/single_pipe_no_headloss.py index 38d0cc3ba..e777c5975 100644 --- a/tests/models/double_pipe_qth/src/single_pipe_no_headloss.py +++ b/tests/models/double_pipe_qth/src/single_pipe_no_headloss.py @@ -1,6 +1,6 @@ -from rtctools.util import run_optimization_problem +from mesido.qth_not_maintained.qth_mixin import HeadLossOption -from rtctools_heat_network.qth_not_maintained.qth_mixin import HeadLossOption +from rtctools.util import run_optimization_problem if __name__ == "__main__": from double_pipe_qth import SinglePipeQTH diff --git a/tests/models/electricity_cable_topology/src/example.py b/tests/models/electricity_cable_topology/src/example.py index 8121ea3ba..0447ec949 100644 --- a/tests/models/electricity_cable_topology/src/example.py +++ b/tests/models/electricity_cable_topology/src/example.py @@ -1,5 +1,11 @@ import casadi as ca +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.pipe_class import CableClass +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -13,12 +19,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.pipe_class import CableClass -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): """ diff --git a/tests/models/emerge/input/timeseries_short.csv b/tests/models/emerge/input/timeseries_short.csv new file mode 100644 index 000000000..9d6629bf8 --- /dev/null +++ b/tests/models/emerge/input/timeseries_short.csv @@ -0,0 +1,24 @@ +DateTime,WindPark_9074,Elec,Hydrogen +2016-01-01Z 00:00:00,.0,2.239e-05,2.4 +2016-01-01Z 01:00:00,.0,2.0589999999999998e-05,2.4 +2016-01-01Z 02:00:00,.0,1.6809999999999997e-05,2.4 +2016-01-01Z 03:00:00,.0,1.741e-05,2.4 +2016-01-01Z 04:00:00,.0,1.702e-05,2.4 +2016-01-01Z 05:00:00,.0,1.5859999999999997e-05,2.4 +2016-01-01Z 06:00:00,1999997849.6,1.816e-05,2.4 +2016-01-01Z 07:00:00,1999999562.2,1.7729999999999998e-05,2.4 +2016-01-01Z 08:00:00,.0,1.977e-05,2.4 +2016-01-01Z 09:00:00,.0,2.3749999999999998e-05,2.4 +2016-01-01Z 10:00:00,1999995228.8,2.603e-05,2.4 +2016-01-01Z 11:00:00,1999995622.6000001,2.706e-05,2.4 +2016-01-01Z 12:00:00,1997697985.6,2.6589999999999998e-05,2.4 +2016-01-01Z 13:00:00,1658513101.4,2.4999999999999998e-05,2.4 +2016-01-01Z 14:00:00,1317659536.0,2.704e-05,2.4 +2016-01-01Z 15:00:00,618343094.1999999,3.446e-05,2.4 +2016-01-01Z 16:00:00,1199762886.2,4.514e-05,2.4 +2016-01-01Z 17:00:00,771068238.2,3.9999999999999996e-05,2.4 +2016-01-01Z 18:00:00,1001978579.5999999,3.530004e-05,2.4 +2016-01-01Z 19:00:00,1132050786.8,3.307e-05,2.4 +2016-01-01Z 20:00:00,1293624672.0,2.952e-05,2.4 +2016-01-01Z 21:00:00,1720023264.3999999,3.01e-05,2.4 +2016-01-01Z 22:00:00,1814015745.6,2.457e-05,2.4 \ No newline at end of file diff --git a/tests/models/emerge/input/timeseries_short_2.csv b/tests/models/emerge/input/timeseries_short_2.csv new file mode 100644 index 000000000..09f28f507 --- /dev/null +++ b/tests/models/emerge/input/timeseries_short_2.csv @@ -0,0 +1,4 @@ +DateTime,WindPark_9074,Elec,Hydrogen +2016-01-01Z 06:00:00,1999997849.6,1.816e-05,2.4 +2016-01-01Z 07:00:00,1999999562.2,1.7729999999999998e-05,2.4 +2016-01-01Z 08:00:00,.0,1.977e-05,2.4 \ No newline at end of file diff --git a/tests/models/emerge/input/timeseries_with_PV.csv b/tests/models/emerge/input/timeseries_with_PV.csv index e2802377a..478fd3bb9 100644 --- a/tests/models/emerge/input/timeseries_with_PV.csv +++ b/tests/models/emerge/input/timeseries_with_PV.csv @@ -1,4 +1,4 @@ -DateTime,WindPark_9074,Elec,Hydrogen,PVInstallation_a3eb +DateTime,PVInstallation_2bcf,Elec,Hydrogen,PVInstallation_2bcf_unused 2016-01-01Z 00:00:00,0,2.24E-05,2.4,0 2016-01-01Z 01:00:00,0,2.06E-05,2.4,0 2016-01-01Z 02:00:00,0,1.68E-05,2.4,0 diff --git a/tests/models/emerge/model/emerge.esdl b/tests/models/emerge/model/emerge.esdl index c3875acf0..bd3302660 100644 --- a/tests/models/emerge/model/emerge.esdl +++ b/tests/models/emerge/model/emerge.esdl @@ -1,14 +1,19 @@ - + - + - + + + + + + @@ -24,15 +29,30 @@ + + + + + + + + + + + + + + + @@ -70,7 +90,7 @@ - + @@ -78,7 +98,7 @@ - + @@ -86,7 +106,7 @@ - + diff --git a/tests/models/emerge/model/emerge_battery_priorities.esdl b/tests/models/emerge/model/emerge_battery_priorities.esdl new file mode 100644 index 000000000..19f76ae25 --- /dev/null +++ b/tests/models/emerge/model/emerge_battery_priorities.esdl @@ -0,0 +1,147 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/emerge/model/emerge_battery_priorities_limited_capacity.esdl b/tests/models/emerge/model/emerge_battery_priorities_limited_capacity.esdl new file mode 100644 index 000000000..99b410ab5 --- /dev/null +++ b/tests/models/emerge/model/emerge_battery_priorities_limited_capacity.esdl @@ -0,0 +1,147 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/emerge/model/emerge_priorities.esdl b/tests/models/emerge/model/emerge_priorities.esdl new file mode 100644 index 000000000..eb4b8641f --- /dev/null +++ b/tests/models/emerge/model/emerge_priorities.esdl @@ -0,0 +1,130 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/emerge/model/emerge_priorities_withoutstorage.esdl b/tests/models/emerge/model/emerge_priorities_withoutstorage.esdl new file mode 100644 index 000000000..028c04d3e --- /dev/null +++ b/tests/models/emerge/model/emerge_priorities_withoutstorage.esdl @@ -0,0 +1,108 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/emerge/model/emerge_priorities_withoutstorage_2prod.esdl b/tests/models/emerge/model/emerge_priorities_withoutstorage_2prod.esdl new file mode 100644 index 000000000..9b1f0a990 --- /dev/null +++ b/tests/models/emerge/model/emerge_priorities_withoutstorage_2prod.esdl @@ -0,0 +1,123 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/emerge/model/emerge_solar.esdl b/tests/models/emerge/model/emerge_solar.esdl new file mode 100644 index 000000000..a48cb4640 --- /dev/null +++ b/tests/models/emerge/model/emerge_solar.esdl @@ -0,0 +1,112 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/emerge/model/emerge_solar_battery.esdl b/tests/models/emerge/model/emerge_solar_battery.esdl new file mode 100644 index 000000000..8a3083189 --- /dev/null +++ b/tests/models/emerge/model/emerge_solar_battery.esdl @@ -0,0 +1,132 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/emerge/model/emerge_with_logical_links.esdl b/tests/models/emerge/model/emerge_with_logical_links.esdl new file mode 100644 index 000000000..cc4d3f45e --- /dev/null +++ b/tests/models/emerge/model/emerge_with_logical_links.esdl @@ -0,0 +1,87 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/emerge/output/aliases.json b/tests/models/emerge/output/aliases.json new file mode 100644 index 000000000..78a5680df --- /dev/null +++ b/tests/models/emerge/output/aliases.json @@ -0,0 +1 @@ +{"Bus_24cf.V": ["ElectricityCable_91e7.ElectricityIn.V", 1], "-Bus_24cf.V": ["ElectricityCable_91e7.ElectricityIn.V", -1], "Bus_24cf.ElectricityConn[1].V": ["ElectricityCable_91e7.ElectricityIn.V", 1], "-Bus_24cf.ElectricityConn[1].V": ["ElectricityCable_91e7.ElectricityIn.V", -1], "Bus_24cf.ElectricityConn[2].V": ["ElectricityCable_91e7.ElectricityIn.V", 1], "-Bus_24cf.ElectricityConn[2].V": ["ElectricityCable_91e7.ElectricityIn.V", -1], "Bus_24cf.ElectricityConn[3].V": ["ElectricityCable_91e7.ElectricityIn.V", 1], "-Bus_24cf.ElectricityConn[3].V": ["ElectricityCable_91e7.ElectricityIn.V", -1], "ElectricityCable_80a3.ElectricityIn.I": ["ElectricityCable_80a3.I", 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400.00000000000034, 400.00000000000034, 400.00000000000034, 400.00000000000034, 400.00000000000034, 400.00000000000034], "ElectricityCable_91e7.V_loss": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 5.586079999998456, 5.586080000000006, 0.0, 0.0, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006, 5.586080000000006], "Pipe_ec1a.GasIn.Q_shadow": [0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003], "Pipe_ec1a.GasIn.H": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "Pipe_ec1a.GasOut.Q": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 16.795378441099263, 16.795378441099263, 0.0, 0.0, 16.795378441099263, 16.795378441099263, 16.795378441099263, 16.795378441099263, 16.795378441099263, 16.795378441099263, 16.795378441099263, 16.795378441099263, 16.795378441099263, 16.795378441099267, 16.795378441099263, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267], "Pipe_ec1a.GasOut.Q_shadow": [0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002], "Pipe_ec1a.GasOut.mass_flow": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 20652.203954552995, 20652.203954552995, 0.0, 0.0, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995], "Pipe_ec1a.dH": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "Pipe_97ee.GasIn.Q_shadow": [0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001], "Pipe_97ee.GasOut.Q": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -3.729323170520275e-15, 4.661653963150344e-15, 0.0, -3.729323170520275e-15, -3.729323170520275e-15, -3.729323170520275e-15, -3.729323170520275e-15, -3.729323170520275e-15, -3.729323170520275e-15, -3.729323170520275e-15, -3.729323170520275e-15, -3.729323170520275e-15, 0.0, -3.729323170520275e-15, 0.0, 0.0, 0.0, 0.0], "Pipe_97ee.GasOut.Q_shadow": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "Pipe_97ee.GasOut.mass_flow": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -4.58571046791989e-12, 5.732138084899862e-12, 0.0, -4.58571046791989e-12, -4.58571046791989e-12, -4.58571046791989e-12, -4.58571046791989e-12, -4.58571046791989e-12, -4.58571046791989e-12, -4.58571046791989e-12, -4.58571046791989e-12, -4.58571046791989e-12, 0.0, -4.58571046791989e-12, 0.0, 0.0, 0.0, 0.0], "Pipe_97ee.GasOut.H": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "Pipe_97ee.dH": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "Pipe_910d.GasIn.Q_shadow": [0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001], "Pipe_910d.GasIn.H": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "Pipe_910d.GasOut.Q": [-0.0, 0.0, -0.0, -0.0, -0.0, -0.0, 16.795378441099263, 16.795378441099267, 0.0, -0.0, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267, 16.795378441099267], "Pipe_910d.GasOut.Q_shadow": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "Pipe_910d.GasOut.mass_flow": [-0.0, 0.0, -0.0, -0.0, -0.0, -0.0, 20652.203954552995, 20652.203954552995, 0.0, -0.0, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995, 20652.203954552995], "Pipe_910d.GasOut.H": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "Pipe_910d.dH": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "WindPark_9074.Set_point": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.000000216160079, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.9999999999999999], "Pipe_910d__gas_flow_direct_var": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "Pipe_97ee__gas_flow_direct_var": [0.0, 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, -0.0, 0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0], "Pipe_ec1a__gas_flow_direct_var": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "Electrolyzer_6327__asset_is_switched_on": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "Pipe_910d__gn_diameter": 1.194, "Pipe_97ee__gn_diameter": 1.194, "Pipe_ec1a__gn_diameter": 1.194, "Pipe_910d__gn_cost": 0.0, "Pipe_97ee__gn_cost": 0.0, "Pipe_ec1a__gn_cost": 0.0, "GasDemand_4146__max_size": 0.0, "GasStorage_9172__max_size": 23715000.0, "Electrolyzer_6327__max_size": 200000000.0, "ElectricityDemand_f833__max_size": 2000000000.0, "WindPark_9074__max_size": 1999999971.8, "ElectricityCable_80a3_aggregation_count": 1.0, "ElectricityCable_91e7_aggregation_count": 1.0, "ElectricityCable_e388_aggregation_count": 1.0, "ElectricityDemand_f833_aggregation_count": 1.0, "Bus_24cf_aggregation_count": 1.0, "WindPark_9074_aggregation_count": 1.0, "Electrolyzer_6327_aggregation_count": 1.0, "GasDemand_4146_aggregation_count": 1.0, "Joint_2503_aggregation_count": 1.0, "Pipe_910d_aggregation_count": 1.0, "Pipe_97ee_aggregation_count": 1.0, "Pipe_ec1a_aggregation_count": 1.0, "GasStorage_9172_aggregation_count": 1.0, "Pipe_910d__gn_max_discharge": 17.0, "Pipe_97ee__gn_max_discharge": 1.0, "Pipe_ec1a__gn_max_discharge": 17.0, "ElectricityCable_80a3__en_max_current": 40000.0, "ElectricityCable_91e7__en_max_current": 401.0, "ElectricityCable_e388__en_max_current": 39600.0, "ElectricityCable_80a3__en_resistance": 0.023801199999999998, "ElectricityCable_91e7__en_resistance": 0.0139652, "ElectricityCable_e388__en_resistance": 0.0782915, "ElectricityCable_80a3__en_cost": 0.0, "ElectricityCable_91e7__en_cost": 0.0, "ElectricityCable_e388__en_cost": 0.0, "ElectricityCable_80a3__fixed_operational_cost": 0.0, "ElectricityCable_91e7__fixed_operational_cost": 0.0, "ElectricityCable_e388__fixed_operational_cost": 0.0, "ElectricityDemand_f833__fixed_operational_cost": 0.0, "WindPark_9074__fixed_operational_cost": 509999992.8090001, "Electrolyzer_6327__fixed_operational_cost": 3000000.0, "GasDemand_4146__fixed_operational_cost": 0.0, "Pipe_910d__fixed_operational_cost": 0.0, "Pipe_97ee__fixed_operational_cost": 0.0, "Pipe_ec1a__fixed_operational_cost": 0.0, "GasStorage_9172__fixed_operational_cost": 0.0, "ElectricityCable_80a3__investment_cost": 0.0, "ElectricityCable_91e7__investment_cost": 0.0, "ElectricityCable_e388__investment_cost": 0.0, "ElectricityDemand_f833__investment_cost": 0.0, "WindPark_9074__investment_cost": 0.0, "Electrolyzer_6327__investment_cost": 0.0, "GasDemand_4146__investment_cost": 0.0, "Pipe_910d__investment_cost": 0.0, "Pipe_97ee__investment_cost": 0.0, "Pipe_ec1a__investment_cost": 0.0, "GasStorage_9172__investment_cost": 0.0, "ElectricityCable_80a3__installation_cost": 0.0, "ElectricityCable_91e7__installation_cost": 0.0, "ElectricityCable_e388__installation_cost": 0.0, "ElectricityDemand_f833__installation_cost": 0.0, "WindPark_9074__installation_cost": 0.0, "Electrolyzer_6327__installation_cost": 0.0, "GasDemand_4146__installation_cost": 0.0, "Pipe_910d__installation_cost": 0.0, "Pipe_97ee__installation_cost": 0.0, "Pipe_ec1a__installation_cost": 0.0, "GasStorage_9172__installation_cost": 0.0, "ElectricityCable_80a3__variable_operational_cost": 0.0, "ElectricityCable_91e7__variable_operational_cost": 0.0, "ElectricityCable_e388__variable_operational_cost": 0.0, "ElectricityDemand_f833__variable_operational_cost": 0.0, "WindPark_9074__variable_operational_cost": 0.0, "Electrolyzer_6327__variable_operational_cost": 0.0, "GasDemand_4146__variable_operational_cost": 0.0, "Pipe_910d__variable_operational_cost": 0.0, "Pipe_97ee__variable_operational_cost": 0.0, "Pipe_ec1a__variable_operational_cost": 0.0, "GasStorage_9172__variable_operational_cost": 0.0, "ElectricityDemand_f833__revenue": 685932.6301589636, "GasDemand_4146__revenue": 842609.9213457622} \ No newline at end of file diff --git a/tests/models/emerge/src/example.py b/tests/models/emerge/src/example.py index 6dca4d252..a91b0fa7e 100644 --- a/tests/models/emerge/src/example.py +++ b/tests/models/emerge/src/example.py @@ -1,5 +1,19 @@ +import time + import casadi as ca +from mesido.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.io.write_output import ScenarioOutput +from mesido.workflows.multicommodity_simulator_workflow import ( + MultiCommoditySimulatorNoLosses, + run_sequatially_staged_simulation, +) + from rtctools.optimization.collocated_integrated_optimization_problem import ( CollocatedIntegratedOptimizationProblem, ) @@ -8,14 +22,6 @@ LinearizedOrderGoalProgrammingMixin, ) from rtctools.optimization.single_pass_goal_programming_mixin import SinglePassGoalProgrammingMixin -from rtctools.util import run_optimization_problem - -from rtctools_heat_network.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.head_loss_class import HeadLossOption -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin class MaxHydrogenProduction(Goal): @@ -56,6 +62,33 @@ def function( return -optimization_problem.state(f"{self.source}.Gas_mass_flow_out") +class MaxElecProduction(Goal): + """ + A maximization goal for the hydrogen production, note that we minimize the negative hydrogen + production to achieve this. + """ + + priority = 1 + + order = 1 + + def __init__(self, source: str): + """ + The constructor of the goal. + + Parameters + ---------- + source : string of the source name that is going to be minimized + """ + self.source = source + + def function( + self, optimization_problem: CollocatedIntegratedOptimizationProblem, ensemble_member: int + ) -> ca.MX: + + return -optimization_problem.state(f"{self.source}.Electricity_source") + + class MaxRevenue(Goal): priority = 1 @@ -102,9 +135,9 @@ class MinCost(Goal): order = 1 def __init__(self, asset_name: str): - self.target_max = 0.0 - self.function_range = (0.0, 1.0e9) - self.function_nominal = 1.0e7 + # self.target_max = 0.0 + # self.function_range = (0.0, 1.0e9) + # self.function_nominal = 1.0e7 self.asset_name = asset_name @@ -120,6 +153,7 @@ def function( class EmergeTest( + ScenarioOutput, ESDLAdditionalVarsMixin, TechnoEconomicMixin, LinearizedOrderGoalProgrammingMixin, @@ -155,26 +189,30 @@ def __init__(self, *args, **kwargs): # for s in self.energy_system_components["electrolyzer"]: # goals.append(MaxHydrogenProduction(s)) # + # # for s in self.energy_system_components["electricity_source"]: + # # goals.append(MaxElecProduction(s)) + # # return goals def goals(self): goals = super().goals().copy() - for asset_name in self.energy_system_components["electricity_demand"]: - goals.append(MaxRevenue(asset_name)) - # goals.append(MinCost(asset_name)) - - for asset_name in self.energy_system_components["gas_demand"]: + for asset_name in [ + *self.energy_system_components.get("electricity_demand", []), + *self.energy_system_components.get("gas_demand", []), + ]: goals.append(MaxRevenue(asset_name)) - # goals.append(MinCost(asset_name)) + goals.append(MinCost(asset_name)) - # for asset_name in [*self.energy_system_components.get("electricity_source", []), - # *self.energy_system_components.get("gas_tank_storage", []), - # #TODO: battery - # *self.energy_system_components.get("electrolyzer", []), - # *self.energy_system_components.get("heat_pump_elec", [])]: - # goals.append(MinCost(asset_name)) + for asset_name in [ + *self.energy_system_components.get("electricity_source", []), + *self.energy_system_components.get("gas_tank_storage", []), + # TODO: battery + *self.energy_system_components.get("electrolyzer", []), + *self.energy_system_components.get("heat_pump_elec", []), + ]: + goals.append(MinCost(asset_name)) return goals @@ -189,6 +227,11 @@ def constraints(self, ensemble_member): gas_flow_t0 = sign * self.state_vector(canonical, ensemble_member)[0] constraints.append((gas_flow_t0, 0.0, 0.0)) + for es in self.energy_system_components.get("electricity_storage", []): + canonical, sign = self.alias_relation.canonical_signed(f"{es}.Stored_electricity") + storage_t0 = sign * self.state_vector(canonical, ensemble_member)[0] + constraints.append((storage_t0, 0.0, 0.0)) + return constraints def solver_options(self): @@ -200,7 +243,7 @@ def solver_options(self): solver options dict """ options = super().solver_options() - options["solver"] = "gurobi" + options["solver"] = "highs" return options def times(self, variable=None): @@ -222,14 +265,87 @@ def energy_system_options(self): options["include_electric_cable_power_loss"] = False return options + def post(self): + # In case the solver fails, we do not get in priority_completed(). We + # append this last priority's statistics here in post(). + # TODO: check if we still need this small part of code below + success, _ = self.solver_success(self.solver_stats, False) + # if not success: + # time_taken = time.time() - self.__priority_timer + # self._priorities_output.append( + # ( + # self.__priority, + # time_taken, + # False, + # self.objective_value, + # self.solver_stats, + # ) + # ) + + super().post() + + # Optimized ESDL + # self._write_updated_esdl(self._ESDLMixin__energy_system_handler.energy_system) + # + # self._save_json = False + # + # if os.path.exists(self.output_folder) and self._save_json: + # self._write_json_output() + # + # results = self.extract_results() + # + # for _type, assets in self.energy_system_components.items(): + # for asset in assets: + # print("----------------------------------") + # print(f"{asset} financials:") + # try: + # print(f"revenue of {asset} in MEUR/day: ", results[f"{asset}__revenue"] / 1e6) + # except KeyError: + # print(f"{asset} does not have a revenue") + # pass + # try: + # print( + # f"fixed operational costs of {asset} in MEUR/yr : ", + # results[f"{asset}__fixed_operational_cost"] / 1e6, + # ) + # print( + # f"variable operational costs of {asset} : ", + # results[f"{asset}__variable_operational_cost"] / 1e6, + # ) # not yet all included in financialmixin + # print(f"max size of {asset} : ", results[f"{asset}__max_size"]) + # except KeyError: + # print(f"{asset} does not have a costs") + # pass + if __name__ == "__main__": - elect = run_optimization_problem( - EmergeTest, - esdl_file_name="emerge.esdl", + + tic = time.time() + # for _ in range(10): + # elect = run_optimization_problem( + # EmergeTest, + # esdl_file_name="emerge_solar_battery.esdl", + # esdl_parser=ESDLFileParser, + # profile_reader=ProfileReaderFromFile, + # input_timeseries_file="timeseries_with_PV.csv", + # ) + + solution = run_sequatially_staged_simulation( + multi_commodity_simulator_class=MultiCommoditySimulatorNoLosses, + simulation_window_size=20, + esdl_file_name="emerge_battery_priorities.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, - input_timeseries_file="timeseries.csv", + input_timeseries_file="timeseries_short.csv", ) - results = elect.extract_results() - a = 1 + + print(time.time() - tic) + # elect = run_optimization_problem( + # EmergeTest, + # esdl_file_name="emerge.esdl", + # esdl_parser=ESDLFileParser, + # profile_reader=ProfileReaderFromFile, + # input_timeseries_file="timeseries.csv", + # ) + # results = elect.extract_results() + # a = 1 diff --git a/tests/models/gas_pipe_topology/model/2a_gas.esdl b/tests/models/gas_pipe_topology/model/2a_gas.esdl index 3589e32b5..c9ac4698c 100644 --- a/tests/models/gas_pipe_topology/model/2a_gas.esdl +++ b/tests/models/gas_pipe_topology/model/2a_gas.esdl @@ -40,7 +40,7 @@ - + diff --git a/tests/models/gas_pipe_topology/src/example.py b/tests/models/gas_pipe_topology/src/example.py index c647bc862..f1d8e2bc3 100644 --- a/tests/models/gas_pipe_topology/src/example.py +++ b/tests/models/gas_pipe_topology/src/example.py @@ -1,5 +1,10 @@ import casadi as ca +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -13,11 +18,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): """ diff --git a/tests/models/heat_exchange/model/test_hex_bypass.esdl b/tests/models/heat_exchange/model/test_hex_bypass.esdl new file mode 100644 index 000000000..ae85e8bf4 --- /dev/null +++ b/tests/models/heat_exchange/model/test_hex_bypass.esdl @@ -0,0 +1,342 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/heat_exchange/model/test_hex_bypass_2.esdl b/tests/models/heat_exchange/model/test_hex_bypass_2.esdl new file mode 100644 index 000000000..66021389b --- /dev/null +++ b/tests/models/heat_exchange/model/test_hex_bypass_2.esdl @@ -0,0 +1,343 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/heat_exchange/src/run_heat_exchanger.py b/tests/models/heat_exchange/src/run_heat_exchanger.py index 3395eb0da..a1847bcac 100644 --- a/tests/models/heat_exchange/src/run_heat_exchanger.py +++ b/tests/models/heat_exchange/src/run_heat_exchanger.py @@ -1,3 +1,10 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.physics_mixin import PhysicsMixin +from mesido.workflows.io.write_output import ScenarioOutput + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -9,12 +16,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.head_loss_class import HeadLossOption -from rtctools_heat_network.physics_mixin import PhysicsMixin - class TargetDemandGoal(Goal): priority = 1 @@ -67,6 +68,7 @@ def function(self, optimization_problem, ensemble_member): class HeatProblem( + ScenarioOutput, _GoalsAndOptions, PhysicsMixin, LinearizedOrderGoalProgrammingMixin, diff --git a/tests/models/heatpump/src/run_heat_pump.py b/tests/models/heatpump/src/run_heat_pump.py index 4fab2dbf6..f32243ce5 100644 --- a/tests/models/heatpump/src/run_heat_pump.py +++ b/tests/models/heatpump/src/run_heat_pump.py @@ -1,3 +1,9 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.physics_mixin import PhysicsMixin +from mesido.workflows.io.write_output import ScenarioOutput + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -9,11 +15,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.physics_mixin import PhysicsMixin - class TargetDemandGoal(Goal): priority = 1 @@ -91,6 +92,7 @@ def function(self, optimization_problem, ensemble_member): class HeatProblem( + ScenarioOutput, _GoalsAndOptions, PhysicsMixin, LinearizedOrderGoalProgrammingMixin, @@ -122,7 +124,7 @@ def solver_options(self): options = super().solver_options() options["solver"] = "highs" highs_options = options["highs"] = {} - highs_options["mip_rel_gap"] = 0.01 + highs_options["mip_rel_gap"] = 0.001 return options def temperature_carriers(self): @@ -136,6 +138,12 @@ def temperature_regimes(self, carrier): return temperatures + def times(self, variable=None) -> np.ndarray: + """ + Shorten the timeseries to speed up the test, when highs is used as a solver. + """ + return super().times(variable)[:10] + if __name__ == "__main__": solution = run_optimization_problem( diff --git a/tests/models/insulation/src/run_insulation.py b/tests/models/insulation/src/run_insulation.py index e20328d36..b668c3b89 100644 --- a/tests/models/insulation/src/run_insulation.py +++ b/tests/models/insulation/src/run_insulation.py @@ -1,5 +1,11 @@ import esdl +from mesido.demand_insulation_class import DemandInsulationClass +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,12 +17,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.demand_insulation_class import DemandInsulationClass -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class MinimizeSourcesHeatGoal(Goal): priority = 2 diff --git a/tests/models/multiple_carriers/src/run_multiple_carriers.py b/tests/models/multiple_carriers/src/run_multiple_carriers.py index 6401c5abc..bf4b4100a 100644 --- a/tests/models/multiple_carriers/src/run_multiple_carriers.py +++ b/tests/models/multiple_carriers/src/run_multiple_carriers.py @@ -1,3 +1,8 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.physics_mixin import PhysicsMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -9,11 +14,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.physics_mixin import PhysicsMixin - class TargetDemandGoal(Goal): priority = 1 diff --git a/tests/models/multiple_gas_carriers/model/compressor.esdl b/tests/models/multiple_gas_carriers/model/compressor.esdl new file mode 100644 index 000000000..10b43e8da --- /dev/null +++ b/tests/models/multiple_gas_carriers/model/compressor.esdl @@ -0,0 +1,42 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/multiple_gas_carriers/src/run_multiple_gas_carriers.py b/tests/models/multiple_gas_carriers/src/run_multiple_gas_carriers.py index 311493a06..d96dfaa98 100644 --- a/tests/models/multiple_gas_carriers/src/run_multiple_gas_carriers.py +++ b/tests/models/multiple_gas_carriers/src/run_multiple_gas_carriers.py @@ -1,3 +1,8 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,11 +16,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 @@ -86,7 +86,7 @@ def times(self, variable=None) -> np.ndarray: if __name__ == "__main__": elect = run_optimization_problem( GasProblem, - esdl_file_name="multiple_carriers.esdl", + esdl_file_name="compressor.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, input_timeseries_file="timeseries.csv", diff --git a/tests/models/pipe_test/src/run_hydraulic_power.py b/tests/models/pipe_test/src/run_hydraulic_power.py index d23df477c..2c22454d9 100644 --- a/tests/models/pipe_test/src/run_hydraulic_power.py +++ b/tests/models/pipe_test/src/run_hydraulic_power.py @@ -1,3 +1,7 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.head_loss_class import HeadLossOption +from mesido.physics_mixin import PhysicsMixin + import numpy as np import pandas as pd @@ -10,10 +14,6 @@ LinearizedOrderGoalProgrammingMixin, ) -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.head_loss_class import HeadLossOption -from rtctools_heat_network.physics_mixin import PhysicsMixin - class TargetDemandGoal(Goal): priority = 1 @@ -70,7 +70,6 @@ class HeatProblem( ESDLMixin, CollocatedIntegratedOptimizationProblem, ): - def __init__(self, *args, **kwargs): global head_loss_setting, n_linearization_lines_setting @@ -78,7 +77,10 @@ def __init__(self, *args, **kwargs): self.heat_network_settings["head_loss_option"] = head_loss_setting if head_loss_setting == HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY: self.heat_network_settings["n_linearization_lines"] = n_linearization_lines_setting - self.heat_network_settings["minimize_head_losses"] = True + if head_loss_setting == HeadLossOption.LINEARIZED_N_LINES_EQUALITY: + self.heat_network_settings["minimize_head_losses"] = False + else: + self.heat_network_settings["minimize_head_losses"] = True def pre(self): super().pre() @@ -105,7 +107,10 @@ def heat_network_options(self): self.heat_network_settings["head_loss_option"] = head_loss_setting if head_loss_setting == HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY: self.heat_network_settings["n_linearization_lines"] = n_linearization_lines_setting - self.heat_network_settings["minimize_head_losses"] = True + if head_loss_setting == HeadLossOption.LINEARIZED_N_LINES_EQUALITY: + self.heat_network_settings["minimize_head_losses"] = False + else: + self.heat_network_settings["minimize_head_losses"] = True return options diff --git a/tests/models/simple_buffer/src/model.py b/tests/models/simple_buffer/src/model.py index 8af810dfa..494091768 100644 --- a/tests/models/simple_buffer/src/model.py +++ b/tests/models/simple_buffer/src/model.py @@ -1,5 +1,5 @@ -from rtctools_heat_network.pycml import ControlInput, Model as _Model -from rtctools_heat_network.pycml.component_library.milp import ( +from mesido.pycml import ControlInput, Model as _Model +from mesido.pycml.component_library.milp import ( HeatBuffer, HeatDemand, HeatPipe, diff --git a/tests/models/simple_buffer/src/simple_buffer.py b/tests/models/simple_buffer/src/simple_buffer.py index 4bec82ce8..4d07f11f6 100644 --- a/tests/models/simple_buffer/src/simple_buffer.py +++ b/tests/models/simple_buffer/src/simple_buffer.py @@ -1,3 +1,7 @@ +from mesido.component_type_mixin import ModelicaComponentTypeMixin +from mesido.pycml.pycml_mixin import PyCMLMixin +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,10 +15,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.component_type_mixin import ModelicaComponentTypeMixin -from rtctools_heat_network.pycml.pycml_mixin import PyCMLMixin -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - if __name__ == "__main__": from model import Model else: diff --git a/tests/models/source_pipe_sink/model/sourcesink_withHP.esdl b/tests/models/source_pipe_sink/model/sourcesink_withHP.esdl new file mode 100644 index 000000000..a91321307 --- /dev/null +++ b/tests/models/source_pipe_sink/model/sourcesink_withHP.esdl @@ -0,0 +1,75 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/source_pipe_sink/model/sourcesink_witheboiler.esdl b/tests/models/source_pipe_sink/model/sourcesink_witheboiler.esdl new file mode 100644 index 000000000..d4f2b4f86 --- /dev/null +++ b/tests/models/source_pipe_sink/model/sourcesink_witheboiler.esdl @@ -0,0 +1,70 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/source_pipe_sink/model/sourcesink_withgasboiler.esdl b/tests/models/source_pipe_sink/model/sourcesink_withgasboiler.esdl new file mode 100644 index 000000000..337bec5e8 --- /dev/null +++ b/tests/models/source_pipe_sink/model/sourcesink_withgasboiler.esdl @@ -0,0 +1,87 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/source_pipe_sink/src/double_pipe_heat.py b/tests/models/source_pipe_sink/src/double_pipe_heat.py index 38329294f..18701f33f 100644 --- a/tests/models/source_pipe_sink/src/double_pipe_heat.py +++ b/tests/models/source_pipe_sink/src/double_pipe_heat.py @@ -1,3 +1,12 @@ +from mesido.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.io.write_output import ScenarioOutput + + from rtctools.optimization.collocated_integrated_optimization_problem import ( CollocatedIntegratedOptimizationProblem, ) @@ -8,13 +17,6 @@ from rtctools.optimization.single_pass_goal_programming_mixin import SinglePassGoalProgrammingMixin from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.head_loss_class import HeadLossOption -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 @@ -40,10 +42,14 @@ def __init__(self): self.function_nominal = 1e6 def function(self, optimization_problem, ensemble_member): - return optimization_problem.state("source.Heat_source") + sum = 0 + for source in optimization_problem.energy_system_components.get("heat_source", []): + sum = optimization_problem.state(f"{source}.Heat_source") + return sum class SourcePipeSink( + ScenarioOutput, TechnoEconomicMixin, LinearizedOrderGoalProgrammingMixin, SinglePassGoalProgrammingMixin, @@ -53,6 +59,11 @@ class SourcePipeSink( def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) + def energy_system_options(self): + options = super().energy_system_options() + self.gas_network_settings["maximum_velocity"] = 20.0 + return options + def path_goals(self): g = super().path_goals().copy() g.append(TargetDemandGoal(self)) @@ -64,7 +75,6 @@ def post(self): class HeatProblemHydraulic(ESDLAdditionalVarsMixin, SourcePipeSink): - def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.heat_network_settings["head_loss_option"] = ( @@ -87,8 +97,8 @@ def solver_options(self): if __name__ == "__main__": sol = run_optimization_problem( - HeatProblemHydraulic, - esdl_file_name="sourcesink.esdl", + SourcePipeSink, + esdl_file_name="sourcesink_witheboiler.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, input_timeseries_file="timeseries_import.csv", diff --git a/tests/models/source_pipe_split_sink/input/timeseries_import.csv b/tests/models/source_pipe_split_sink/input/timeseries_import.csv index bc4127ae1..0791e72b2 100644 --- a/tests/models/source_pipe_split_sink/input/timeseries_import.csv +++ b/tests/models/source_pipe_split_sink/input/timeseries_import.csv @@ -1,46 +1,46 @@ DateTime,demand,elec -2013-05-19 22:00:00,150000.0,10.0 -2013-05-19 23:00:00,150000.0,10.0 -2013-05-20 00:00:00,150000.0,10.0 -2013-05-20 01:00:00,150000.0,10.0 -2013-05-20 02:00:00,150000.0,10.0 -2013-05-20 03:00:00,150000.0,10.0 -2013-05-20 04:00:00,150000.0,10.0 -2013-05-20 05:00:00,150000.0,10.0 -2013-05-20 06:00:00,150000.0,10.0 -2013-05-20 07:00:00,150000.0,10.0 -2013-05-20 08:00:00,150000.0,10.0 -2013-05-20 09:00:00,150000.0,10.0 -2013-05-20 10:00:00,150000.0,10.0 -2013-05-20 11:00:00,150000.0,10.0 -2013-05-20 12:00:00,150000.0,10.0 -2013-05-20 13:00:00,150000.0,10.0 -2013-05-20 14:00:00,100000.0,10.0 -2013-05-20 15:00:00,100000.0,10.0 -2013-05-20 16:00:00,100000.0,10.0 -2013-05-20 17:00:00,100000.0,10.0 -2013-05-20 18:00:00,100000.0,10.0 -2013-05-20 19:00:00,100000.0,10.0 -2013-05-20 20:00:00,100000.0,10.0 -2013-05-20 21:00:00,100000.0,10.0 -2013-05-20 22:00:00,100000.0,10.0 -2013-05-20 23:00:00,100000.0,10.0 -2013-05-21 00:00:00,100000.0,10.0 -2013-05-21 01:00:00,100000.0,10.0 -2013-05-21 02:00:00,100000.0,10.0 -2013-05-21 03:00:00,50000.0,10.0 -2013-05-21 04:00:00,50000.0,10.0 -2013-05-21 05:00:00,50000.0,10.0 -2013-05-21 06:00:00,50000.0,10.0 -2013-05-21 07:00:00,50000.0,10.0 -2013-05-21 08:00:00,50000.0,10.0 -2013-05-21 09:00:00,50000.0,10.0 -2013-05-21 10:00:00,50000.0,10.0 -2013-05-21 11:00:00,50000.0,10.0 -2013-05-21 12:00:00,50000.0,10.0 -2013-05-21 13:00:00,50000.0,10.0 -2013-05-21 14:00:00,50000.0,10.0 -2013-05-21 15:00:00,50000.0,10.0 -2013-05-21 16:00:00,50000.0,10.0 -2013-05-21 17:00:00,50000.0,10.0 -2013-05-21 18:00:00,50000.0,10.0 +2013-05-19 22:00:00,1500000.0,10.0 +2013-05-19 23:00:00,1500000.0,10.0 +2013-05-20 00:00:00,1500000.0,10.0 +2013-05-20 01:00:00,1500000.0,10.0 +2013-05-20 02:00:00,1500000.0,10.0 +2013-05-20 03:00:00,1500000.0,10.0 +2013-05-20 04:00:00,1500000.0,10.0 +2013-05-20 05:00:00,1500000.0,10.0 +2013-05-20 06:00:00,1500000.0,10.0 +2013-05-20 07:00:00,1500000.0,10.0 +2013-05-20 08:00:00,1500000.0,10.0 +2013-05-20 09:00:00,1500000.0,10.0 +2013-05-20 10:00:00,1500000.0,10.0 +2013-05-20 11:00:00,1500000.0,10.0 +2013-05-20 12:00:00,1500000.0,10.0 +2013-05-20 13:00:00,1500000.0,10.0 +2013-05-20 14:00:00,1000000.0,10.0 +2013-05-20 15:00:00,1000000.0,10.0 +2013-05-20 16:00:00,1000000.0,10.0 +2013-05-20 17:00:00,1000000.0,10.0 +2013-05-20 18:00:00,1000000.0,10.0 +2013-05-20 19:00:00,1000000.0,10.0 +2013-05-20 20:00:00,1000000.0,10.0 +2013-05-20 21:00:00,1000000.0,10.0 +2013-05-20 22:00:00,1000000.0,10.0 +2013-05-20 23:00:00,1000000.0,10.0 +2013-05-21 00:00:00,1000000.0,10.0 +2013-05-21 01:00:00,1000000.0,10.0 +2013-05-21 02:00:00,1000000.0,10.0 +2013-05-21 03:00:00,500000.0,10.0 +2013-05-21 04:00:00,500000.0,10.0 +2013-05-21 05:00:00,500000.0,10.0 +2013-05-21 06:00:00,500000.0,10.0 +2013-05-21 07:00:00,500000.0,10.0 +2013-05-21 08:00:00,500000.0,10.0 +2013-05-21 09:00:00,500000.0,10.0 +2013-05-21 10:00:00,500000.0,10.0 +2013-05-21 11:00:00,500000.0,10.0 +2013-05-21 12:00:00,500000.0,10.0 +2013-05-21 13:00:00,500000.0,10.0 +2013-05-21 14:00:00,500000.0,10.0 +2013-05-21 15:00:00,500000.0,10.0 +2013-05-21 16:00:00,500000.0,10.0 +2013-05-21 17:00:00,500000.0,10.0 +2013-05-21 18:00:00,500000.0,10.0 diff --git a/tests/models/source_pipe_split_sink/model/sourcesink_with_node2node_logical_link.esdl b/tests/models/source_pipe_split_sink/model/sourcesink_with_node2node_logical_link.esdl new file mode 100644 index 000000000..81b7dcfa5 --- /dev/null +++ b/tests/models/source_pipe_split_sink/model/sourcesink_with_node2node_logical_link.esdl @@ -0,0 +1,111 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/source_pipe_split_sink/src/double_pipe_heat.py b/tests/models/source_pipe_split_sink/src/double_pipe_heat.py index 8f96c8714..3a331fb16 100644 --- a/tests/models/source_pipe_split_sink/src/double_pipe_heat.py +++ b/tests/models/source_pipe_split_sink/src/double_pipe_heat.py @@ -1,3 +1,6 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.techno_economic_mixin import TechnoEconomicMixin + from rtctools.optimization.collocated_integrated_optimization_problem import ( CollocatedIntegratedOptimizationProblem, ) @@ -8,9 +11,6 @@ from rtctools.optimization.single_pass_goal_programming_mixin import SinglePassGoalProgrammingMixin from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 @@ -20,7 +20,7 @@ class TargetDemandGoal(Goal): def __init__(self, optimization_problem): self.target_min = optimization_problem.get_timeseries("demand.target_heat_demand") self.target_max = optimization_problem.get_timeseries("demand.target_heat_demand") - self.function_range = (0.0, 2e5) + self.function_range = (0.0, 2e6) self.function_nominal = 1e5 def function(self, optimization_problem, ensemble_member): diff --git a/tests/models/test_case_small_network_ates_buffer_optional_assets/src/run_ates.py b/tests/models/test_case_small_network_ates_buffer_optional_assets/src/run_ates.py index c77a71cf6..f5e90a65c 100644 --- a/tests/models/test_case_small_network_ates_buffer_optional_assets/src/run_ates.py +++ b/tests/models/test_case_small_network_ates_buffer_optional_assets/src/run_ates.py @@ -1,3 +1,8 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.data.storage import DataStore @@ -9,11 +14,6 @@ LinearizedOrderGoalProgrammingMixin, ) -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 @@ -153,7 +153,7 @@ def read(self): if __name__ == "__main__": import time - from rtctools_heat_network.workflows import EndScenarioSizingStaged, run_end_scenario_sizing + from mesido.workflows import EndScenarioSizingStaged, run_end_scenario_sizing start_time = time.time() diff --git a/tests/models/test_case_small_network_optional_assets_annualized/src/run_annualized.py b/tests/models/test_case_small_network_optional_assets_annualized/src/run_annualized.py index 74a584ee6..f2c511070 100644 --- a/tests/models/test_case_small_network_optional_assets_annualized/src/run_annualized.py +++ b/tests/models/test_case_small_network_optional_assets_annualized/src/run_annualized.py @@ -2,13 +2,13 @@ import esdl +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.workflows.goals.minimize_tco_goal import MinimizeTCO + from rtctools.optimization.goal_programming_mixin import Goal from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.workflows.goals.minimize_tco_goal import MinimizeTCO - try: from models.test_case_small_network_optional_assets_annualized.src.run_ates import ( HeatProblem, diff --git a/tests/models/test_case_small_network_optional_assets_annualized/src/run_ates.py b/tests/models/test_case_small_network_optional_assets_annualized/src/run_ates.py index 7166f3af9..e06def17e 100644 --- a/tests/models/test_case_small_network_optional_assets_annualized/src/run_ates.py +++ b/tests/models/test_case_small_network_optional_assets_annualized/src/run_ates.py @@ -1,3 +1,8 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.data.storage import DataStore @@ -10,11 +15,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 diff --git a/tests/models/test_case_small_network_with_ates/src/run_ates.py b/tests/models/test_case_small_network_with_ates/src/run_ates.py index db453e388..0235197c7 100644 --- a/tests/models/test_case_small_network_with_ates/src/run_ates.py +++ b/tests/models/test_case_small_network_with_ates/src/run_ates.py @@ -2,6 +2,11 @@ import esdl +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.data.storage import DataStore @@ -19,12 +24,6 @@ from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - - class TargetDemandGoal(Goal): priority = 1 @@ -211,6 +210,7 @@ def energy_system_options(self): """ options = super().energy_system_options() options["include_asset_is_realized"] = True + options["neglect_pipe_heat_losses"] = True return options @@ -254,10 +254,12 @@ def constraints(self, ensemble_member): # Constraints for investment speed, please note that we need to enforce index 0 to be 0. for s in self.energy_system_components.get("heat_source", []): - inv_made = self.state_vector(f"{s}__cumulative_investments_made_in_eur") + inv_made = self.__state_vector_scaled( + f"{s}__cumulative_investments_made_in_eur", ensemble_member + ) nominal = self.variable_nominal(f"{s}__cumulative_investments_made_in_eur") inv_cap = 2.5e5 - constraints.append((inv_made[0], 0.0, 0.0)) + constraints.append((inv_made[0] / nominal, 0.0, 200000.0)) for i in range(1, len(self.times())): constraints.append( (((inv_made[i] - inv_made[i - 1]) * nominal - inv_cap) / nominal, -np.inf, 0.0) @@ -270,6 +272,16 @@ def constraints(self, ensemble_member): return constraints + def __state_vector_scaled(self, variable, ensemble_member): + """ + This functions returns the casadi symbols scaled with their nominal for the entire time + horizon. + """ + canonical, sign = self.alias_relation.canonical_signed(variable) + return ( + self.state_vector(canonical, ensemble_member) * self.variable_nominal(canonical) * sign + ) + def times(self, variable=None): """ For the purposes of this test we take only 25 timesteps to speed up the test. diff --git a/tests/models/test_case_small_network_with_ates_with_buffer/src/run_ates.py b/tests/models/test_case_small_network_with_ates_with_buffer/src/run_ates.py index 6cfef29ed..d1c9d4924 100644 --- a/tests/models/test_case_small_network_with_ates_with_buffer/src/run_ates.py +++ b/tests/models/test_case_small_network_with_ates_with_buffer/src/run_ates.py @@ -1,5 +1,10 @@ import esdl +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.data.storage import DataStore @@ -12,11 +17,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 diff --git a/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles.esdl b/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles.esdl index 8745c9228..e24211ed3 100644 --- a/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles.esdl +++ b/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles.esdl @@ -17,7 +17,7 @@ - + @@ -26,7 +26,7 @@ - + @@ -126,7 +126,7 @@ - + diff --git a/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles_error_check_1.esdl b/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles_error_check_1.esdl new file mode 100644 index 000000000..389762d84 --- /dev/null +++ b/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles_error_check_1.esdl @@ -0,0 +1,172 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles_error_check_2.esdl b/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles_error_check_2.esdl new file mode 100644 index 000000000..220fb191a --- /dev/null +++ b/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles_error_check_2.esdl @@ -0,0 +1,172 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles_error_check_3.esdl b/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles_error_check_3.esdl new file mode 100644 index 000000000..67050c082 --- /dev/null +++ b/tests/models/unit_cases/case_1a/model/1a_with_influx_profiles_error_check_3.esdl @@ -0,0 +1,177 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases/case_1a/src/run_1a.py b/tests/models/unit_cases/case_1a/src/run_1a.py index df05d1f9a..7acad48a9 100644 --- a/tests/models/unit_cases/case_1a/src/run_1a.py +++ b/tests/models/unit_cases/case_1a/src/run_1a.py @@ -1,3 +1,9 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.physics_mixin import PhysicsMixin +from mesido.qth_not_maintained.qth_mixin import QTHMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -10,12 +16,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.physics_mixin import PhysicsMixin -from rtctools_heat_network.qth_not_maintained.qth_mixin import QTHMixin - class TargetDemandGoal(Goal): priority = 1 diff --git a/tests/models/unit_cases/case_1a_t_var/src/run_1a.py b/tests/models/unit_cases/case_1a_t_var/src/run_1a.py index 8211c3b8b..169108f58 100644 --- a/tests/models/unit_cases/case_1a_t_var/src/run_1a.py +++ b/tests/models/unit_cases/case_1a_t_var/src/run_1a.py @@ -1,3 +1,9 @@ +from mesido.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.physics_mixin import PhysicsMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -9,12 +15,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.physics_mixin import PhysicsMixin - class TargetDemandGoal(Goal): priority = 1 diff --git a/tests/models/unit_cases/case_2a/src/equal_temperatures.py b/tests/models/unit_cases/case_2a/src/equal_temperatures.py index 42bc6bd59..75404d13b 100644 --- a/tests/models/unit_cases/case_2a/src/equal_temperatures.py +++ b/tests/models/unit_cases/case_2a/src/equal_temperatures.py @@ -1,3 +1,8 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.heat_mixin import HeatMixin +from mesido.qth_mixin import QTHMixin +from mesido.util import run_heat_network_optimization + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -9,11 +14,6 @@ LinearizedOrderGoalProgrammingMixin, ) -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.heat_mixin import HeatMixin -from rtctools_heat_network.qth_mixin import QTHMixin -from rtctools_heat_network.util import run_heat_network_optimization - class TargetDemandGoal(Goal): priority = 1 diff --git a/tests/models/unit_cases/case_2a/src/run_2a.py b/tests/models/unit_cases/case_2a/src/run_2a.py index 596e6623a..1c2019beb 100644 --- a/tests/models/unit_cases/case_2a/src/run_2a.py +++ b/tests/models/unit_cases/case_2a/src/run_2a.py @@ -1,3 +1,9 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.physics_mixin import PhysicsMixin +from mesido.qth_not_maintained.qth_mixin import QTHMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,12 +17,6 @@ from rtctools.optimization.single_pass_goal_programming_mixin import SinglePassGoalProgrammingMixin from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.physics_mixin import PhysicsMixin -from rtctools_heat_network.qth_not_maintained.qth_mixin import QTHMixin - class TargetDemandGoal(Goal): priority = 1 diff --git a/tests/models/unit_cases/case_3a/model/3a_esdl_source_scaled_profile.esdl b/tests/models/unit_cases/case_3a/model/3a_esdl_source_scaled_profile.esdl new file mode 100644 index 000000000..d234c9b26 --- /dev/null +++ b/tests/models/unit_cases/case_3a/model/3a_esdl_source_scaled_profile.esdl @@ -0,0 +1,305 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases/case_3a/model/3a_esdl_source_unscaled_profile.esdl b/tests/models/unit_cases/case_3a/model/3a_esdl_source_unscaled_profile.esdl new file mode 100644 index 000000000..e307b1d7b --- /dev/null +++ b/tests/models/unit_cases/case_3a/model/3a_esdl_source_unscaled_profile.esdl @@ -0,0 +1,303 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases/case_3a/model/3a_esdl_source_unscaled_profile_sizing.esdl b/tests/models/unit_cases/case_3a/model/3a_esdl_source_unscaled_profile_sizing.esdl new file mode 100644 index 000000000..14d25f4b6 --- /dev/null +++ b/tests/models/unit_cases/case_3a/model/3a_esdl_source_unscaled_profile_sizing.esdl @@ -0,0 +1,303 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases/case_3a/src/run_3a.py b/tests/models/unit_cases/case_3a/src/run_3a.py index 11a6d559f..f18e28ddf 100644 --- a/tests/models/unit_cases/case_3a/src/run_3a.py +++ b/tests/models/unit_cases/case_3a/src/run_3a.py @@ -1,3 +1,11 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.physics_mixin import PhysicsMixin +from mesido.qth_not_maintained.qth_mixin import QTHMixin +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.goals.minimize_tco_goal import MinimizeTCO + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -10,13 +18,6 @@ ) from rtctools.optimization.single_pass_goal_programming_mixin import SinglePassGoalProgrammingMixin -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.physics_mixin import PhysicsMixin -from rtctools_heat_network.qth_not_maintained.qth_mixin import QTHMixin -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 @@ -285,7 +286,7 @@ def constraints(self, ensemble_member): return constraints -class HeatProblemProdProfile( +class HeatProblemESDLProdProfile( _GoalsAndOptions, TechnoEconomicMixin, LinearizedOrderGoalProgrammingMixin, @@ -293,16 +294,6 @@ class HeatProblemProdProfile( ESDLMixin, CollocatedIntegratedOptimizationProblem, ): - def read(self): - super().read() - - for s in self.energy_system_components["heat_source"]: - demand_timeseries = self.get_timeseries("HeatingDemand_a3b8.target_heat_demand") - new_timeseries = np.ones(len(demand_timeseries.values)) * 1 - ind_hlf = int(len(demand_timeseries.values) / 2) - new_timeseries[ind_hlf : ind_hlf + 4] = np.ones(4) * 0.10 - self.set_timeseries(f"{s}.maximum_heat_source", new_timeseries) - def energy_system_options(self): options = super().energy_system_options() options["heat_loss_disconnected_pipe"] = True @@ -324,6 +315,26 @@ def path_goals(self): return goals +class HeatProblemESDLProdProfileTCO(HeatProblemESDLProdProfile): + def goals(self): + goals = super().goals().copy() + goals.append(MinimizeTCO(priority=20, number_of_years=1)) + + return goals + + +class HeatProblemProdProfile(HeatProblemESDLProdProfile): + def read(self): + super().read() + + for s in self.energy_system_components["heat_source"]: + demand_timeseries = self.get_timeseries("HeatingDemand_a3b8.target_heat_demand") + new_timeseries = np.ones(len(demand_timeseries.values)) * 1 + ind_hlf = int(len(demand_timeseries.values) / 2) + new_timeseries[ind_hlf : ind_hlf + 4] = np.ones(4) * 0.10 + self.set_timeseries(f"{s}.maximum_heat_source", new_timeseries) + + class QTHProblem( QTHMixin, HomotopyMixin, @@ -347,7 +358,7 @@ def path_goals(self): def energy_system_options(self): options = super().energy_system_options() - from rtctools_heat_network.head_loss_class import HeadLossOption + from mesido.head_loss_class import HeadLossOption self.heat_network_settings["head_loss_option"] = HeadLossOption.NO_HEADLOSS return options diff --git a/tests/models/unit_cases/case_3a_setpoint/model/3a.esdl b/tests/models/unit_cases/case_3a_setpoint/model/3a.esdl index d896c5451..97c014a23 100644 --- a/tests/models/unit_cases/case_3a_setpoint/model/3a.esdl +++ b/tests/models/unit_cases/case_3a_setpoint/model/3a.esdl @@ -20,7 +20,7 @@ - + diff --git a/tests/models/unit_cases/case_3a_setpoint/src/run_3a.py b/tests/models/unit_cases/case_3a_setpoint/src/run_3a.py index ec1c6f357..4c0146eab 100644 --- a/tests/models/unit_cases/case_3a_setpoint/src/run_3a.py +++ b/tests/models/unit_cases/case_3a_setpoint/src/run_3a.py @@ -1,3 +1,9 @@ +from mesido.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -9,10 +15,6 @@ ) from rtctools.optimization.single_pass_goal_programming_mixin import SinglePassGoalProgrammingMixin -from rtctools_heat_network.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 @@ -24,7 +26,7 @@ def __init__(self, state, target): self.target_min = target self.target_max = target - self.function_range = (0.0, 2.0 * max(target.values)) + self.function_range = (-1.0, 2.0 * max(target.values)) self.function_nominal = np.median(target.values) def function(self, optimization_problem, ensemble_member): @@ -37,8 +39,8 @@ class MinimizeSourcesHeatGoal(Goal): order = 1 def __init__(self, source): - self.target_max = 0.0 - self.function_range = (0.0, 10e6) + # self.target_max = 0.0 + # self.function_range = (0.0, 10e6) self.source = source self.function_nominal = 1e6 @@ -67,17 +69,17 @@ def solver_options(self): # gurobi_options["MIPgap"] = 0.001 return options - def heat_network_options(self): - options = super().heat_network_options() - options["minimum_velocity"] = 0.0001 - # options["heat_loss_disconnected_pipe"] = False - # options["neglect_pipe_heat_losses"] = False + def energy_system_options(self): + options = super().energy_system_options() + # options["minimum_velocity"] = 0.0001 + options["heat_loss_disconnected_pipe"] = False + options["neglect_pipe_heat_losses"] = True return options class HeatProblem( - _GoalsAndOptions, ESDLAdditionalVarsMixin, + _GoalsAndOptions, TechnoEconomicMixin, LinearizedOrderGoalProgrammingMixin, SinglePassGoalProgrammingMixin, @@ -92,20 +94,18 @@ def path_goals(self): return goals - def solver_options(self): - options = super().solver_options() - options["solver"] = "highs" - # highs_options = options["highs"] = {} - # highs_options["mip_rel_gap"] = 0.0025 - # options["gurobi"] = gurobi_options = {} - # gurobi_options["MIPgap"] = 0.0001 - return options - if __name__ == "__main__": from rtctools.util import run_optimization_problem - sol = run_optimization_problem(HeatProblem) + sol = run_optimization_problem( + HeatProblem, + # base_folder=base_folder, + esdl_file_name="3a.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_import.xml", + ) results = sol.extract_results() print(results["GeothermalSource_b702.Heat_source"]) diff --git a/tests/models/unit_cases_electricity/battery/input/timeseries.csv b/tests/models/unit_cases_electricity/battery/input/timeseries.csv new file mode 100644 index 000000000..a4f013033 --- /dev/null +++ b/tests/models/unit_cases_electricity/battery/input/timeseries.csv @@ -0,0 +1,5 @@ +DateTime,ElectricityProducer_b95d,ElectricityDemand_2af6 +01-01-2019 00:00, 900.0, 500.0 +01-01-2019 01:00, 900.0, 500.0 +01-01-2019 02:00, 1000.0, 1000.0 +01-01-2019 03:00, 1200.0, 1500.0 diff --git a/tests/models/unit_cases_electricity/battery/model/source_sink_storage.esdl b/tests/models/unit_cases_electricity/battery/model/source_sink_storage.esdl new file mode 100644 index 000000000..b266be55f --- /dev/null +++ b/tests/models/unit_cases_electricity/battery/model/source_sink_storage.esdl @@ -0,0 +1,53 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases_electricity/battery/src/example.py b/tests/models/unit_cases_electricity/battery/src/example.py new file mode 100644 index 000000000..024faa509 --- /dev/null +++ b/tests/models/unit_cases_electricity/battery/src/example.py @@ -0,0 +1,103 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + +import numpy as np + +from rtctools.optimization.collocated_integrated_optimization_problem import ( + CollocatedIntegratedOptimizationProblem, +) +from rtctools.optimization.goal_programming_mixin import GoalProgrammingMixin +from rtctools.optimization.goal_programming_mixin_base import Goal +from rtctools.optimization.linearized_order_goal_programming_mixin import ( + LinearizedOrderGoalProgrammingMixin, +) +from rtctools.optimization.timeseries import Timeseries +from rtctools.util import run_optimization_problem + + +class TargetDemandGoal(Goal): + priority = 1 + + order = 2 + + def __init__(self, state: str, target: Timeseries): + self.state = state + + self.target_min = target + self.target_max = target + self.function_range = (0.0, 2.0 * max(target.values)) + self.function_nominal = np.median(target.values) + + def function( + self, optimization_problem: CollocatedIntegratedOptimizationProblem, ensemble_member: int + ): + return optimization_problem.state(self.state) + + +class _GoalsAndOptions: + def path_goals(self): + """ + Add goal to meet the specified power demands in the electricity network. + + Returns + ------- + Extended goals list. + """ + goals = super().path_goals().copy() + + for demand in self.energy_system_components["electricity_demand"]: + target = self.get_timeseries(f"{demand}.target_electricity_demand") + state = f"{demand}.Electricity_demand" + + goals.append(TargetDemandGoal(state, target)) + + return goals + + def energy_system_options(self): + options = super().energy_system_options() + options["include_electric_cable_power_loss"] = False + options["electricity_storage_discharge_variables"] = True + + return options + + +class ElectricityProblem( + _GoalsAndOptions, + TechnoEconomicMixin, + LinearizedOrderGoalProgrammingMixin, + GoalProgrammingMixin, + ESDLMixin, + CollocatedIntegratedOptimizationProblem, +): + """ + Problem to check the behaviour of a simple source, cable, demand network and a battery. + """ + + def constraints(self, ensemble_member): + constraints = super().constraints(ensemble_member) + + for bat in self.energy_system_components.get("electricity_storage", []): + stored_elec = self.state_vector(f"{bat}.Stored_electricity") + constraints.append((stored_elec[0], 0.0, 0.0)) + + return constraints + + def solver_options(self): + options = super().solver_options() + options["solver"] = "highs" + return options + + pass + + +if __name__ == "__main__": + elect = run_optimization_problem( + ElectricityProblem, + esdl_file_name="source_sink_storage.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + r = elect.extract_results() diff --git a/tests/models/unit_cases_electricity/bus_networks/input/timeseries_2.csv b/tests/models/unit_cases_electricity/bus_networks/input/timeseries_2.csv new file mode 100644 index 000000000..8be0b94ba --- /dev/null +++ b/tests/models/unit_cases_electricity/bus_networks/input/timeseries_2.csv @@ -0,0 +1,4 @@ +DateTime,ElectricityDemand_e527 +01-01-2019 00:00, 500. +01-01-2019 01:00, 1000. +01-01-2019 02:00, 1500. diff --git a/tests/models/unit_cases_electricity/bus_networks/input/timeseries_2_prod.csv b/tests/models/unit_cases_electricity/bus_networks/input/timeseries_2_prod.csv new file mode 100644 index 000000000..bafe06b17 --- /dev/null +++ b/tests/models/unit_cases_electricity/bus_networks/input/timeseries_2_prod.csv @@ -0,0 +1,4 @@ +DateTime,ElectricityDemand_e527,ElectricityProducer_17a1 +01-01-2019 00:00, 500., 1200. +01-01-2019 01:00, 1000., 400. +01-01-2019 02:00, 1500., 600. diff --git a/tests/models/unit_cases_electricity/bus_networks/input/timeseries_uni.csv b/tests/models/unit_cases_electricity/bus_networks/input/timeseries_uni.csv new file mode 100644 index 000000000..3d249c41c --- /dev/null +++ b/tests/models/unit_cases_electricity/bus_networks/input/timeseries_uni.csv @@ -0,0 +1,4 @@ +DateTime,ElectricityDemand_e527,ElectricityDemand_281a +01-01-2019 00:00, 500., 500. +01-01-2019 01:00, 1000., 500. +01-01-2019 02:00, 500., 1000. diff --git a/tests/models/unit_cases_electricity/bus_networks/model/Electric_bus4.esdl b/tests/models/unit_cases_electricity/bus_networks/model/Electric_bus4.esdl new file mode 100644 index 000000000..a1c72a6f7 --- /dev/null +++ b/tests/models/unit_cases_electricity/bus_networks/model/Electric_bus4.esdl @@ -0,0 +1,78 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases_electricity/bus_networks/model/Electric_bus4_logical_links.esdl b/tests/models/unit_cases_electricity/bus_networks/model/Electric_bus4_logical_links.esdl new file mode 100644 index 000000000..106ca4617 --- /dev/null +++ b/tests/models/unit_cases_electricity/bus_networks/model/Electric_bus4_logical_links.esdl @@ -0,0 +1,33 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases_electricity/bus_networks/model/Electric_bus4_priorities.esdl b/tests/models/unit_cases_electricity/bus_networks/model/Electric_bus4_priorities.esdl new file mode 100644 index 000000000..8b7738a75 --- /dev/null +++ b/tests/models/unit_cases_electricity/bus_networks/model/Electric_bus4_priorities.esdl @@ -0,0 +1,74 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases_electricity/bus_networks/src/example.py b/tests/models/unit_cases_electricity/bus_networks/src/example.py index e84c05cb1..b815765cf 100644 --- a/tests/models/unit_cases_electricity/bus_networks/src/example.py +++ b/tests/models/unit_cases_electricity/bus_networks/src/example.py @@ -1,3 +1,8 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,11 +16,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 @@ -74,7 +74,7 @@ class ElectricityProblem( if __name__ == "__main__": elect = run_optimization_problem( ElectricityProblem, - esdl_file_name="Electric_bus3.esdl", + esdl_file_name="Electric_bus4_logical_links.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, input_timeseries_file="timeseries.csv", diff --git a/tests/models/unit_cases_electricity/electrolyzer/input/timeseries.csv b/tests/models/unit_cases_electricity/electrolyzer/input/timeseries.csv index 3565170c7..3eb40fd20 100644 --- a/tests/models/unit_cases_electricity/electrolyzer/input/timeseries.csv +++ b/tests/models/unit_cases_electricity/electrolyzer/input/timeseries.csv @@ -1,4 +1,5 @@ -DateTime,elec,gas,WindPark_7f14 +DateTime,elec,Hydrogen,WindPark_7f14 01-01-2019 00:00, 1.0, 1000000.0, 100000000.0 01-01-2019 01:00, 1.0, 1000000.0, 100000000.0 01-01-2019 02:00, 1.0, 1000000.0, 100000000.0 + diff --git a/tests/models/unit_cases_electricity/electrolyzer/input/timeseries_electrolyzer_general.csv b/tests/models/unit_cases_electricity/electrolyzer/input/timeseries_electrolyzer_general.csv new file mode 100644 index 000000000..36b4fea0a --- /dev/null +++ b/tests/models/unit_cases_electricity/electrolyzer/input/timeseries_electrolyzer_general.csv @@ -0,0 +1,5 @@ +DateTime,elec,Hydrogen,WindPark_7f14 +01-01-2019 00:00, 10.0, 10000000.0, 100000000.0 +01-01-2019 01:00, 10.0, 11000000.0, 100000000.0 +01-01-2019 02:00, 10.0, 10000000.0, 100000000.0 + diff --git a/tests/models/unit_cases_electricity/electrolyzer/input/timeseries_equality_constraints.csv b/tests/models/unit_cases_electricity/electrolyzer/input/timeseries_equality_constraints.csv new file mode 100644 index 000000000..bf9687fc0 --- /dev/null +++ b/tests/models/unit_cases_electricity/electrolyzer/input/timeseries_equality_constraints.csv @@ -0,0 +1,4 @@ +DateTime,elec,Hydrogen,WindPark_7f14 +01-01-2019 00:00, 10.0, 10000000.0, 100000000.0 +01-01-2019 01:00, 10.0, 10000000.0, 300000000.0 +01-01-2019 02:00, 10.0, 10000000.0, 400000000.0 diff --git a/tests/models/unit_cases_electricity/electrolyzer/input/timeseries_minimum_electrolyzer_power.csv b/tests/models/unit_cases_electricity/electrolyzer/input/timeseries_minimum_electrolyzer_power.csv new file mode 100644 index 000000000..50a007c54 --- /dev/null +++ b/tests/models/unit_cases_electricity/electrolyzer/input/timeseries_minimum_electrolyzer_power.csv @@ -0,0 +1,4 @@ +DateTime,elec,Hydrogen,WindPark_7f14 +01-01-2019 00:00, 1.0, 10000000.0, 100000000.0 +01-01-2019 01:00, 10.0, 10000000.0, 100000000.0 +01-01-2019 02:00, 10.0, 10000000.0, 49000000.0 diff --git a/tests/models/unit_cases_electricity/electrolyzer/model/h2.esdl b/tests/models/unit_cases_electricity/electrolyzer/model/h2.esdl index 562c7bb9c..25a913339 100644 --- a/tests/models/unit_cases_electricity/electrolyzer/model/h2.esdl +++ b/tests/models/unit_cases_electricity/electrolyzer/model/h2.esdl @@ -3,7 +3,7 @@ - + @@ -37,7 +37,7 @@ - + diff --git a/tests/models/unit_cases_electricity/electrolyzer/model/h2_profiles_added_dummy_values.esdl b/tests/models/unit_cases_electricity/electrolyzer/model/h2_profiles_added_dummy_values.esdl index 604f0e275..a9669ea26 100644 --- a/tests/models/unit_cases_electricity/electrolyzer/model/h2_profiles_added_dummy_values.esdl +++ b/tests/models/unit_cases_electricity/electrolyzer/model/h2_profiles_added_dummy_values.esdl @@ -11,7 +11,7 @@ - + diff --git a/tests/models/unit_cases_electricity/electrolyzer/src/example.py b/tests/models/unit_cases_electricity/electrolyzer/src/example.py index d3211c32c..4d88de903 100644 --- a/tests/models/unit_cases_electricity/electrolyzer/src/example.py +++ b/tests/models/unit_cases_electricity/electrolyzer/src/example.py @@ -1,3 +1,10 @@ +from mesido.electricity_physics_mixin import ElectrolyzerOption +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.network_common import NetworkSettings +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -10,11 +17,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class RevenueGoal(Goal): priority = 1 @@ -29,32 +31,13 @@ def __init__(self, state, price_profile, nominal): def function(self, optimization_problem, ensemble_member): canonical, sign = optimization_problem.alias_relation.canonical_signed(self.state) - symbols = ( - sign - * optimization_problem.state_vector(canonical, ensemble_member) - * optimization_problem.variable_nominal(self.state) - ) + + symbols = sign * optimization_problem.state_vector(canonical, ensemble_member) price_profile = optimization_problem.get_timeseries(self.price_profile).values sum = 0.0 for i in range(len(price_profile)): sum += symbols[i] * price_profile[i] - for asset in [ - *optimization_problem.energy_system_components.get("gas_demand", []), - *optimization_problem.energy_system_components.get("gas_source", []), - *optimization_problem.energy_system_components.get("electrolyzer", []), - *optimization_problem.energy_system_components.get("gas_tank_storage", []), - *optimization_problem.energy_system_components.get("wind_park", []), - *optimization_problem.energy_system_components.get("electricity_demand", []), - *optimization_problem.energy_system_components.get("electricity_source", []), - ]: - sum -= optimization_problem.extra_variable( - f"{asset}__variable_operational_cost", ensemble_member - ) - sum -= optimization_problem.extra_variable( - f"{asset}__fixed_operational_cost", ensemble_member - ) - return -sum @@ -124,7 +107,7 @@ def constraints(self, ensemble_member): return constraints -class MILPProblem( +class MILPProblemInequality( _GoalsAndOptions, TechnoEconomicMixin, LinearizedOrderGoalProgrammingMixin, @@ -142,6 +125,8 @@ def path_goals(self): def solver_options(self): options = super().solver_options() options["solver"] = "highs" + highs_options = options["highs"] = {} + highs_options["presolve"] = "off" return options @@ -149,6 +134,7 @@ def energy_system_options(self): options = super().energy_system_options() options["include_asset_is_switched_on"] = True options["include_electric_cable_power_loss"] = False + self.gas_network_settings["network_type"] = NetworkSettings.NETWORK_TYPE_HYDROGEN return options @@ -156,9 +142,27 @@ def energy_system_options(self): # return super().times(variable)[:5] +class MILPProblemConstantEfficiency(MILPProblemInequality): + + def energy_system_options(self): + options = super().energy_system_options() + options["electrolyzer_efficiency"] = ElectrolyzerOption.CONSTANT_EFFICIENCY + + return options + + +class MILPProblemEquality(MILPProblemInequality): + + def energy_system_options(self): + options = super().energy_system_options() + options["electrolyzer_efficiency"] = ElectrolyzerOption.LINEARIZED_THREE_LINES_EQUALITY + + return options + + if __name__ == "__main__": elect = run_optimization_problem( - MILPProblem, + MILPProblemInequality, esdl_file_name="h2.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, diff --git a/tests/models/unit_cases_electricity/heat_pump_elec/input/timeseries_elec.csv b/tests/models/unit_cases_electricity/heat_pump_elec/input/timeseries_elec.csv new file mode 100644 index 000000000..4704c418f --- /dev/null +++ b/tests/models/unit_cases_electricity/heat_pump_elec/input/timeseries_elec.csv @@ -0,0 +1,5 @@ +DateTime,HeatingDemand_3322,HeatingDemand_18aa,Electr +01-01-2019 00:00, 2500000.0, 2500000.0, 0.03 +01-01-2019 01:00, 2500000.0, 2500000.0, 0.03 +01-01-2019 02:00, 2500000.0, 2500000.0, 0.0003 +01-01-2019 03:00, 2500000.0, 2500000.0, 0.03 diff --git a/tests/models/unit_cases_electricity/heat_pump_elec/model/heat_pump_elec_priceprofile.esdl b/tests/models/unit_cases_electricity/heat_pump_elec/model/heat_pump_elec_priceprofile.esdl new file mode 100644 index 000000000..4a7411bb7 --- /dev/null +++ b/tests/models/unit_cases_electricity/heat_pump_elec/model/heat_pump_elec_priceprofile.esdl @@ -0,0 +1,314 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases_electricity/heat_pump_elec/src/run_hp_elec.py b/tests/models/unit_cases_electricity/heat_pump_elec/src/run_hp_elec.py index f76129890..cd8264ae7 100644 --- a/tests/models/unit_cases_electricity/heat_pump_elec/src/run_hp_elec.py +++ b/tests/models/unit_cases_electricity/heat_pump_elec/src/run_hp_elec.py @@ -1,5 +1,15 @@ import esdl +from mesido.esdl.esdl_additional_vars_mixin import ESDLAdditionalVarsMixin +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.physics_mixin import PhysicsMixin +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.goals.minimize_tco_goal import MinimizeTCO + + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,11 +21,6 @@ ) from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.physics_mixin import PhysicsMixin - # TODO: check if this run script is still valid as test case for electric heatpump and update with # functions @@ -260,16 +265,50 @@ def energy_system_options(self): return options +class ElectricityProblemPriceProfile( + _GoalsAndOptions, + ESDLAdditionalVarsMixin, + TechnoEconomicMixin, + LinearizedOrderGoalProgrammingMixin, + GoalProgrammingMixin, + ESDLMixin, + CollocatedIntegratedOptimizationProblem, +): + def read(self): + super().read() + + for d in self.energy_system_components["heat_demand"]: + new_timeseries = self.get_timeseries(f"{d}.target_heat_demand").values * 0.01 + self.set_timeseries(f"{d}.target_heat_demand", new_timeseries) + + def goals(self): + goals = super().goals().copy() + + goals.append(MinimizeTCO(priority=2)) + + return goals + + def energy_system_options(self): + options = super().energy_system_options() + self.heat_network_settings["minimum_velocity"] = 0.0001 + options["heat_loss_disconnected_pipe"] = False + options["neglect_pipe_heat_losses"] = True + self.heat_network_settings["head_loss_option"] = HeadLossOption.NO_HEADLOSS + + return options + + if __name__ == "__main__": sol = run_optimization_problem( - HeatProblem2, - esdl_file_name="heat_pump_elec.esdl", + ElectricityProblemPriceProfile, + esdl_file_name="heat_pump_elec_priceprofile.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, - input_timeseries_file="timeseries_import.xml", + input_timeseries_file="timeseries_elec.csv", ) results = sol.extract_results() print(results["GenericConversion_3d3f.Power_elec"]) + print(results["GenericConversion_3d3f__variable_operational_cost"]) print(results["ResidualHeatSource_aec9.Heat_source"]) # print(results["Pipe3__hn_diameter"]) # print(sol.bounds()["Pipe3__hn_diameter"]) diff --git a/tests/models/unit_cases_electricity/source_sink_cable/model/transformer.esdl b/tests/models/unit_cases_electricity/source_sink_cable/model/transformer.esdl new file mode 100644 index 000000000..19acdc012 --- /dev/null +++ b/tests/models/unit_cases_electricity/source_sink_cable/model/transformer.esdl @@ -0,0 +1,42 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases_electricity/source_sink_cable/src/example.py b/tests/models/unit_cases_electricity/source_sink_cable/src/example.py index 19b5c759f..7883c2136 100644 --- a/tests/models/unit_cases_electricity/source_sink_cable/src/example.py +++ b/tests/models/unit_cases_electricity/source_sink_cable/src/example.py @@ -1,3 +1,9 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.physics_mixin import PhysicsMixin +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,12 +17,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.physics_mixin import PhysicsMixin -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 @@ -133,7 +133,7 @@ def bounds(self): if __name__ == "__main__": elect = run_optimization_problem( ElectricityProblem, - esdl_file_name="case1_elec.esdl", + esdl_file_name="transformer.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, input_timeseries_file="timeseries.csv", diff --git a/tests/models/unit_cases_gas/multi_demand_source_node/model/test.esdl b/tests/models/unit_cases_gas/multi_demand_source_node/model/test.esdl index 192b1e901..c2a534bd1 100644 --- a/tests/models/unit_cases_gas/multi_demand_source_node/model/test.esdl +++ b/tests/models/unit_cases_gas/multi_demand_source_node/model/test.esdl @@ -10,20 +10,20 @@ - + - + - + - + @@ -41,7 +41,7 @@ - + diff --git a/tests/models/unit_cases_gas/multi_demand_source_node/model/test_logical_links.esdl b/tests/models/unit_cases_gas/multi_demand_source_node/model/test_logical_links.esdl new file mode 100644 index 000000000..bb7ba8e20 --- /dev/null +++ b/tests/models/unit_cases_gas/multi_demand_source_node/model/test_logical_links.esdl @@ -0,0 +1,36 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases_gas/multi_demand_source_node/model/test_priorities.esdl b/tests/models/unit_cases_gas/multi_demand_source_node/model/test_priorities.esdl new file mode 100644 index 000000000..fe20d89ab --- /dev/null +++ b/tests/models/unit_cases_gas/multi_demand_source_node/model/test_priorities.esdl @@ -0,0 +1,82 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases_gas/multi_demand_source_node/src/run_test.py b/tests/models/unit_cases_gas/multi_demand_source_node/src/run_test.py index e2dd1a9d0..41562037c 100644 --- a/tests/models/unit_cases_gas/multi_demand_source_node/src/run_test.py +++ b/tests/models/unit_cases_gas/multi_demand_source_node/src/run_test.py @@ -1,3 +1,9 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.physics_mixin import PhysicsMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,11 +17,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 @@ -58,7 +59,7 @@ def path_goals(self): class GasProblem( _GoalsAndOptions, - TechnoEconomicMixin, + PhysicsMixin, LinearizedOrderGoalProgrammingMixin, GoalProgrammingMixin, ESDLMixin, @@ -68,6 +69,11 @@ class GasProblem( This is a problem to check the behaviour of a gas network with a node. """ + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + self.gas_network_settings["head_loss_option"] = HeadLossOption.NO_HEADLOSS + def times(self, variable=None) -> np.ndarray: """ Shorten the horizon here to have a faster test. @@ -86,10 +92,12 @@ def times(self, variable=None) -> np.ndarray: if __name__ == "__main__": elect = run_optimization_problem( GasProblem, - esdl_file_name="test.esdl", + esdl_file_name="test_logical_links.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, input_timeseries_file="timeseries.csv", ) r = elect.extract_results() + print(r["GasProducer_3573.GasOut.Q"]) + print(r["GasDemand_47d0.Gas_demand_mass_flow"]) a = 1 diff --git a/tests/models/unit_cases_gas/source_pipe_split_sink/model/source_sink.esdl b/tests/models/unit_cases_gas/source_pipe_split_sink/model/source_sink.esdl index 2f9a13e5f..2795c0e60 100644 --- a/tests/models/unit_cases_gas/source_pipe_split_sink/model/source_sink.esdl +++ b/tests/models/unit_cases_gas/source_pipe_split_sink/model/source_sink.esdl @@ -10,11 +10,11 @@ - + - + diff --git a/tests/models/unit_cases_gas/source_pipe_split_sink/model/split_with_logical_link.esdl b/tests/models/unit_cases_gas/source_pipe_split_sink/model/split_with_logical_link.esdl new file mode 100644 index 000000000..7908b6e6c --- /dev/null +++ b/tests/models/unit_cases_gas/source_pipe_split_sink/model/split_with_logical_link.esdl @@ -0,0 +1,59 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/unit_cases_gas/source_pipe_split_sink/src/run_source_sink.py b/tests/models/unit_cases_gas/source_pipe_split_sink/src/run_source_sink.py index 1b7912110..9df96989c 100644 --- a/tests/models/unit_cases_gas/source_pipe_split_sink/src/run_source_sink.py +++ b/tests/models/unit_cases_gas/source_pipe_split_sink/src/run_source_sink.py @@ -1,3 +1,8 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,11 +16,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 diff --git a/tests/models/unit_cases_gas/source_sink/input/timeseries.csv b/tests/models/unit_cases_gas/source_sink/input/timeseries.csv index dc34acc97..cb19c43e7 100644 --- a/tests/models/unit_cases_gas/source_sink/input/timeseries.csv +++ b/tests/models/unit_cases_gas/source_sink/input/timeseries.csv @@ -1,4 +1,4 @@ DateTime,GasDemand_a2d8 -01-01-2019 00:00, 0.05 -01-01-2019 01:00, 0.1 -01-01-2019 02:00, 0.15 +01-01-2019 00:00, 0.045 +01-01-2019 01:00, 0.095 +01-01-2019 02:00, 0.14 diff --git a/tests/models/unit_cases_gas/source_sink/model/source_sink.esdl b/tests/models/unit_cases_gas/source_sink/model/source_sink.esdl index ed7f406a5..6d407ac7e 100644 --- a/tests/models/unit_cases_gas/source_sink/model/source_sink.esdl +++ b/tests/models/unit_cases_gas/source_sink/model/source_sink.esdl @@ -2,7 +2,7 @@ - + @@ -10,11 +10,11 @@ - + - + diff --git a/tests/models/unit_cases_gas/source_sink/src/run_source_sink.py b/tests/models/unit_cases_gas/source_sink/src/run_source_sink.py index d1c2517a8..b9ca61ae1 100644 --- a/tests/models/unit_cases_gas/source_sink/src/run_source_sink.py +++ b/tests/models/unit_cases_gas/source_sink/src/run_source_sink.py @@ -1,3 +1,8 @@ +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.techno_economic_mixin import TechnoEconomicMixin + import numpy as np from rtctools.optimization.collocated_integrated_optimization_problem import ( @@ -11,11 +16,6 @@ from rtctools.optimization.timeseries import Timeseries from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_mixin import ESDLMixin -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - class TargetDemandGoal(Goal): priority = 1 diff --git a/tests/models/wko/input/timeseries.csv b/tests/models/wko/input/timeseries.csv new file mode 100644 index 000000000..680e238b1 --- /dev/null +++ b/tests/models/wko/input/timeseries.csv @@ -0,0 +1,9 @@ +DateTime,HeatingDemand_9b90,CoolingDemand_15e8 +01-01-2019 00:00, 50000., 150000. +01-01-2019 01:00, 100000., 150000. +01-01-2019 02:00, 100000., 150000. +01-01-2019 03:00, 100000., 0. +01-01-2019 04:00, 150000., 0. +01-01-2019 05:00, 150000., 0. +01-01-2019 06:00, 150000., 0. + diff --git a/tests/models/wko/input/timeseries_2.csv b/tests/models/wko/input/timeseries_2.csv new file mode 100644 index 000000000..2f7e72ecf --- /dev/null +++ b/tests/models/wko/input/timeseries_2.csv @@ -0,0 +1,11 @@ +DateTime,HeatingDemand_9b90,CoolingDemand_15e8 +01-01-2019 00:00, 10000., 10000. +01-01-2019 01:00, 50000., 150000. +01-01-2019 02:00, 100000., 150000. +01-01-2019 03:00, 100000., 150000. +01-01-2019 04:00, 100000., 0. +01-01-2019 05:00, 150000., 0. +01-01-2019 06:00, 150000., 0. +01-01-2019 07:00, 150000., 0. +01-01-2019 08:00, 0., 150000. + diff --git a/tests/models/wko/input/timeseries_cold_peak_before.csv b/tests/models/wko/input/timeseries_cold_peak_before.csv new file mode 100644 index 000000000..b7401bdd6 --- /dev/null +++ b/tests/models/wko/input/timeseries_cold_peak_before.csv @@ -0,0 +1,73 @@ +DateTime,HeatingDemand_9b90,CoolingDemand_15e8 +01-01-2019 00:00, 53443. , 50107. +01-01-2019 01:00, 52838. , 45983. +01-01-2019 02:00, 52057. , 52349. +01-01-2019 03:00, 45874. , 51427. +01-01-2019 04:00, 49568. , 48338. +01-01-2019 05:00, 47559. , 51436. +01-01-2019 06:00, 54812. , 54657. +01-01-2019 07:00, 47576. , 54822. +01-01-2019 08:00, 53625. , 49199. +01-01-2019 09:00, 52464. , 52204. +01-01-2019 10:00, 52392. , 53479. +01-01-2019 11:00, 53502. , 53136. +01-01-2019 12:00, 50676. , 51021. +01-01-2019 13:00, 47906. , 51038. +01-01-2019 14:00, 50858. , 47504. +01-01-2019 15:00, 53141. , 48440. +01-01-2019 16:00, 45792. , 45363. +01-01-2019 17:00, 52436. , 45404. +01-01-2019 18:00, 48184. , 51854. +01-01-2019 19:00, 54302. , 48753. +01-01-2019 20:00, 54812. , 45921. +01-01-2019 21:00, 52438. , 45172. +01-01-2019 22:00, 53969. , 51356. +01-01-2019 23:00, 51430. , 49830. +02-01-2019 00:00, 50481. , 153460. +02-01-2019 01:00, 54842. , 159155. +02-01-2019 02:00, 48286. , 144197. +02-01-2019 03:00, 50899. , 162283. +02-01-2019 04:00, 51661. , 156897. +02-01-2019 05:00, 48576. , 147894. +02-01-2019 06:00, 54326. , 143438. +02-01-2019 07:00, 52148. , 148501. +02-01-2019 08:00, 50828. , 151202. +02-01-2019 09:00, 51165. , 160992. +02-01-2019 10:00, 50505. , 135468. +02-01-2019 11:00, 47842. , 151263. +02-01-2019 12:00, 45281. , 135936. +02-01-2019 13:00, 52086. , 160194. +02-01-2019 14:00, 48396. , 142512. +02-01-2019 15:00, 53006. , 164212. +02-01-2019 16:00, 49557. , 142815. +02-01-2019 17:00, 49215. , 156393. +02-01-2019 18:00, 51909. , 156898. +02-01-2019 19:00, 45777. , 154097. +02-01-2019 20:00, 45112. , 139101. +02-01-2019 21:00, 45377. , 142508. +02-01-2019 22:00, 50585. , 138014. +02-01-2019 23:00, 52719. , 152271. +03-01-2019 00:00, 105932., 48049. +03-01-2019 01:00, 105250., 52577. +03-01-2019 02:00, 94298. , 52635. +03-01-2019 03:00, 94678. , 45261. +03-01-2019 04:00, 92126. , 50465. +03-01-2019 05:00, 107091., 49095. +03-01-2019 06:00, 90454. , 52078. +03-01-2019 07:00, 101801., 49649. +03-01-2019 08:00, 105812., 49353. +03-01-2019 09:00, 107787., 54142. +03-01-2019 10:00, 105414., 45581. +03-01-2019 11:00, 103343., 46460. +03-01-2019 12:00, 109949., 45319. +03-01-2019 13:00, 99340. , 54311. +03-01-2019 14:00, 95641. , 48355. +03-01-2019 15:00, 96303. , 54496. +03-01-2019 16:00, 100944., 54984. +03-01-2019 17:00, 109763., 49444. +03-01-2019 18:00, 93902. , 54970. +03-01-2019 19:00, 103711., 50130. +03-01-2019 20:00, 107416., 46953. +03-01-2019 21:00, 107923., 46687. +03-01-2019 22:00, 96886. , 47852. +03-01-2019 23:00, 100891., 49318. \ No newline at end of file diff --git a/tests/models/wko/input/timeseries_peak_back_to_back.csv b/tests/models/wko/input/timeseries_peak_back_to_back.csv new file mode 100644 index 000000000..63c614564 --- /dev/null +++ b/tests/models/wko/input/timeseries_peak_back_to_back.csv @@ -0,0 +1,73 @@ +DateTime,HeatingDemand_9b90,CoolingDemand_15e8 +01-01-2019 00:00, 48163. , 50125. +01-01-2019 01:00, 48123. , 45698. +01-01-2019 02:00, 50446. , 51155. +01-01-2019 03:00, 53201. , 54720. +01-01-2019 04:00, 49510. , 51957. +01-01-2019 05:00, 47682. , 53781. +01-01-2019 06:00, 53991. , 50784. +01-01-2019 07:00, 53992. , 49877. +01-01-2019 08:00, 47998. , 51592. +01-01-2019 09:00, 47787. , 49431. +01-01-2019 10:00, 50598. , 51766. +01-01-2019 11:00, 49638. , 50559. +01-01-2019 12:00, 53435. , 47024. +01-01-2019 13:00, 46920. , 51621. +01-01-2019 14:00, 49264. , 46323. +01-01-2019 15:00, 54019. , 51211. +01-01-2019 16:00, 50862. , 46283. +01-01-2019 17:00, 53490. , 46747. +01-01-2019 18:00, 49737. , 48574. +01-01-2019 19:00, 46836. , 48264. +01-01-2019 20:00, 46667. , 46183. +01-01-2019 21:00, 50328. , 54241. +01-01-2019 22:00, 52847. , 52425. +01-01-2019 23:00, 50058. , 48466. +02-01-2019 00:00, 96053. , 52805. +02-01-2019 01:00, 108810., 48834. +02-01-2019 02:00, 94913. , 48822. +02-01-2019 03:00, 106139., 51767. +02-01-2019 04:00, 91062. , 46944. +02-01-2019 05:00, 90406. , 51886. +02-01-2019 06:00, 108616., 51436. +02-01-2019 07:00, 104235., 46217. +02-01-2019 08:00, 108261., 50615. +02-01-2019 09:00, 109924., 45697. +02-01-2019 10:00, 101306., 47033. +02-01-2019 11:00, 106166., 47102. +02-01-2019 12:00, 92342. , 49779. +02-01-2019 13:00, 91949. , 48933. +02-01-2019 14:00, 95640. , 50428. +02-01-2019 15:00, 107007., 47994. +02-01-2019 16:00, 96450. , 50370. +02-01-2019 17:00, 102807., 51620. +02-01-2019 18:00, 106326., 53273. +02-01-2019 19:00, 98016. , 53819. +02-01-2019 20:00, 101713., 48166. +02-01-2019 21:00, 108212., 48868. +02-01-2019 22:00, 95228. , 49287. +02-01-2019 23:00, 105606., 45722. +03-01-2019 00:00, 48924. , 153285. +03-01-2019 01:00, 49292. , 138767. +03-01-2019 02:00, 52958. , 156390. +03-01-2019 03:00, 53518. , 144570. +03-01-2019 04:00, 52088. , 149922. +03-01-2019 05:00, 51023. , 162992. +03-01-2019 06:00, 50081. , 146542. +03-01-2019 07:00, 47060. , 143825. +03-01-2019 08:00, 49705. , 153988. +03-01-2019 09:00, 54909. , 161754. +03-01-2019 10:00, 49875. , 160633. +03-01-2019 11:00, 47890. , 140198. +03-01-2019 12:00, 48081. , 143418. +03-01-2019 13:00, 46185. , 159537. +03-01-2019 14:00, 45522. , 159834. +03-01-2019 15:00, 48496. , 163719. +03-01-2019 16:00, 46757. , 146812. +03-01-2019 17:00, 51280. , 143791. +03-01-2019 18:00, 51671. , 163792. +03-01-2019 19:00, 50333. , 152620. +03-01-2019 20:00, 52582. , 150023. +03-01-2019 21:00, 45266. , 148353. +03-01-2019 22:00, 52358. , 140326. +03-01-2019 23:00, 50046. , 145990. \ No newline at end of file diff --git a/tests/models/wko/input/timeseries_peak_overlap.csv b/tests/models/wko/input/timeseries_peak_overlap.csv new file mode 100644 index 000000000..9a7cb4891 --- /dev/null +++ b/tests/models/wko/input/timeseries_peak_overlap.csv @@ -0,0 +1,146 @@ +DateTime,HeatingDemand_9b90,CoolingDemand_15e8 +01-01-2019 00:00, 50991. , 47239. +01-01-2019 01:00, 52854. , 51847. +01-01-2019 02:00, 54174. , 51806. +01-01-2019 03:00, 54647. , 48892. +01-01-2019 04:00, 50854. , 46900. +01-01-2019 05:00, 48177. , 47169. +01-01-2019 06:00, 52416. , 54583. +01-01-2019 07:00, 45638. , 50171. +01-01-2019 08:00, 47173. , 54423. +01-01-2019 09:00, 50417. , 52437. +01-01-2019 10:00, 48069. , 51288. +01-01-2019 11:00, 52018. , 50804. +01-01-2019 12:00, 50481. , 52572. +01-01-2019 13:00, 47398. , 51165. +01-01-2019 14:00, 46092. , 46955. +01-01-2019 15:00, 47736. , 51857. +01-01-2019 16:00, 48665. , 46034. +01-01-2019 17:00, 47604. , 54948. +01-01-2019 18:00, 52416. , 47725. +01-01-2019 19:00, 53361. , 52538. +01-01-2019 20:00, 45802. , 53722. +01-01-2019 21:00, 52031. , 49848. +01-01-2019 22:00, 45887. , 53855. +01-01-2019 23:00, 52213. , 49858. +02-01-2019 00:00, 103737. , 142059. +02-01-2019 01:00, 93148. , 144229. +02-01-2019 02:00, 105489. , 163870. +02-01-2019 03:00, 105546. , 145441. +02-01-2019 04:00, 102155. , 149894. +02-01-2019 05:00, 92281. , 151198. +02-01-2019 06:00, 97063. , 144699. +02-01-2019 07:00, 108611. , 157305. +02-01-2019 08:00, 108339. , 149188. +02-01-2019 09:00, 105915. , 152256. +02-01-2019 10:00, 103181. , 154173. +02-01-2019 11:00, 99113. , 142099. +02-01-2019 12:00, 107989. , 147518. +02-01-2019 13:00, 98889. , 149804. +02-01-2019 14:00, 97354. , 151552. +02-01-2019 15:00, 104733. , 156566. +02-01-2019 16:00, 93137. , 142764. +02-01-2019 17:00, 91709. , 158885. +02-01-2019 18:00, 101616. , 147229. +02-01-2019 19:00, 95581. , 142932. +02-01-2019 20:00, 94540. , 142302. +02-01-2019 21:00, 106439. , 159477. +02-01-2019 22:00, 93048. , 144135. +02-01-2019 23:00, 104730. , 164029. +03-01-2019 00:00, 49784. , 48657. +03-01-2019 01:00, 51424. , 46441. +03-01-2019 02:00, 52557. , 48876. +03-01-2019 03:00, 49910. , 46944. +03-01-2019 04:00, 51663. , 46212. +03-01-2019 05:00, 47242. , 47255. +03-01-2019 06:00, 47822. , 51569. +03-01-2019 07:00, 47054. , 50903. +03-01-2019 08:00, 45416. , 45633. +03-01-2019 09:00, 45136. , 54069. +03-01-2019 10:00, 54952. , 54883. +03-01-2019 11:00, 46442. , 49053. +03-01-2019 12:00, 50426. , 49120. +03-01-2019 13:00, 46090. , 52167. +03-01-2019 14:00, 46058. , 46794. +03-01-2019 15:00, 45596. , 51173. +03-01-2019 16:00, 52784. , 49191. +03-01-2019 17:00, 50426. , 52196. +03-01-2019 18:00, 45874. , 46466. +03-01-2019 19:00, 49908. , 48105. +03-01-2019 20:00, 50521. , 48673. +03-01-2019 21:00, 48145. , 45985. +03-01-2019 22:00, 45468. , 51786. +03-01-2019 23:00, 53179. , 49870. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/wko/model/LT_wko.esdl b/tests/models/wko/model/LT_wko.esdl new file mode 100644 index 000000000..200fdb7c6 --- /dev/null +++ b/tests/models/wko/model/LT_wko.esdl @@ -0,0 +1,271 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/wko/model/LT_wko_error_check.esdl b/tests/models/wko/model/LT_wko_error_check.esdl new file mode 100644 index 000000000..977801e08 --- /dev/null +++ b/tests/models/wko/model/LT_wko_error_check.esdl @@ -0,0 +1,271 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/wko/model/LT_wko_heating_and_cooling.esdl b/tests/models/wko/model/LT_wko_heating_and_cooling.esdl new file mode 100644 index 000000000..9660a2e8a --- /dev/null +++ b/tests/models/wko/model/LT_wko_heating_and_cooling.esdl @@ -0,0 +1,222 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/wko/model/airco.esdl b/tests/models/wko/model/airco.esdl new file mode 100644 index 000000000..6ef9f433b --- /dev/null +++ b/tests/models/wko/model/airco.esdl @@ -0,0 +1,331 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/wko/model/heatpump_airco_time_parsing.esdl b/tests/models/wko/model/heatpump_airco_time_parsing.esdl new file mode 100644 index 000000000..a03e7874e --- /dev/null +++ b/tests/models/wko/model/heatpump_airco_time_parsing.esdl @@ -0,0 +1,222 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests/models/wko/src/example.py b/tests/models/wko/src/example.py new file mode 100644 index 000000000..4fd9c066d --- /dev/null +++ b/tests/models/wko/src/example.py @@ -0,0 +1,244 @@ +import logging + +import casadi as ca + +from mesido.esdl.esdl_mixin import ESDLMixin +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.workflows.utils.error_types import ( + HEAT_AND_COOL_NETWORK_ERRORS, + potential_error_to_error, +) + +import numpy as np + +from rtctools.optimization.collocated_integrated_optimization_problem import ( + CollocatedIntegratedOptimizationProblem, +) +from rtctools.optimization.goal_programming_mixin_base import Goal +from rtctools.optimization.linearized_order_goal_programming_mixin import ( + LinearizedOrderGoalProgrammingMixin, +) +from rtctools.optimization.single_pass_goal_programming_mixin import SinglePassGoalProgrammingMixin +from rtctools.optimization.timeseries import Timeseries +from rtctools.util import run_optimization_problem + +logger = logging.getLogger("WarmingUP-MPC") +logger.setLevel(logging.INFO) + + +class TargetDemandGoal(Goal): + """ + Goal class for matching a timeseries of values, we use it to match the time series of a demand + profile. We use order 2 to match the profile at every time-step. We set the target in the + constructor and function() method will return the state which should match the target. + """ + + priority = 1 + + order = 2 + + def __init__(self, state: str, target: Timeseries): + """ + The constructor for the class where we pass the name of the state that should be matched to + the target. + + Parameters + ---------- + state : string for the name of the state. + target : Timeseries to match with the state. + """ + self.state = state + + self.target_min = target + self.target_max = target + self.function_range = (-2.0 * max(target.values), 2.0 * max(target.values)) + self.function_nominal = ( + np.median(target.values) if np.median(target.values) else max(abs(target.values)) / 2.0 + ) + + def function( + self, optimization_problem: CollocatedIntegratedOptimizationProblem, ensemble_member: int + ) -> ca.MX: + """ + This function returns the state to which will be tried to match to the target. + + Parameters + ---------- + optimization_problem : The optimization class containing the variables' + ensemble_member : the ensemble member + + Returns + ------- + The optimization problem state, the Heat_demand, which should be matched to the time-series + """ + return optimization_problem.state(self.state) + + +class MinimizeSourcesHeatGoal(Goal): + """ + A minimization goal for source milp production. We use order 1 here as we want to minimize milp + over the full horizon and not per time-step. + """ + + priority = 3 + + order = 1 + + def __init__(self, source: str): + """ + The constructor of the goal. + + Parameters + ---------- + source : string of the source name that is going to be minimized + """ + self.source = source + + def function( + self, optimization_problem: CollocatedIntegratedOptimizationProblem, ensemble_member: int + ) -> ca.MX: + """ + This function returns the state variable to which should to be matched to the target + specified in the __init__. + + Parameters + ---------- + optimization_problem : The optimization class containing the variables'. + ensemble_member : the ensemble member. + + Returns + ------- + The Heat_source state of the optimization problem. + """ + return optimization_problem.state(f"{self.source}.Heat_source") + + +class _GoalsAndOptions: + """ + A goals class that we often use if we specify multiple problem classes. + """ + + def path_goals(self): + """ + In this method we add the goals for matching the demand. + + Returns + ------- + The appended goals list of goals + """ + goals = super().path_goals().copy() + + for demand in self.energy_system_components.get("heat_demand", []): + target = self.get_timeseries(f"{demand}.target_heat_demand") + state = f"{demand}.Heat_demand" + + goals.append(TargetDemandGoal(state, target)) + + for demand in self.energy_system_components.get("cold_demand", []): + target = self.get_timeseries(f"{demand}.target_cold_demand") + state = f"{demand}.Cold_demand" + + goals.append(TargetDemandGoal(state, target)) + + return goals + + +class HeatProblem( + _GoalsAndOptions, + TechnoEconomicMixin, + LinearizedOrderGoalProgrammingMixin, + SinglePassGoalProgrammingMixin, + ESDLMixin, + CollocatedIntegratedOptimizationProblem, +): + """ + This problem class is for the absolute milp tests. Meaning that this problem class + is applied to an esdl where there is no dedicated supply or return line. For this test case + we just match heating demand (_GoalsAndOptions) and minimize the energy production to have a + representative result. + """ + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.heat_network_settings["head_loss_option"] = HeadLossOption.NO_HEADLOSS + self.heat_network_settings["minimum_velocity"] = 0.0 + + def read(self): + """ + Reads the yearly profile with hourly time steps and adapt to a daily averaged profile + except for the day with the peak demand. + """ + super().read() + + potential_error_to_error(HEAT_AND_COOL_NETWORK_ERRORS) + + def path_goals(self): + """ + This function adds the minimization goal for minimizing the milp production. + + Returns + ------- + The appended list of goals + """ + goals = super().path_goals().copy() + + for s in self.energy_system_components["heat_source"]: + goals.append(MinimizeSourcesHeatGoal(s)) + + return goals + + def solver_options(self): + """ + This function does not add anything at the moment but during debugging we use this. + + Returns + ------- + solver options dict + """ + options = super().solver_options() + options["solver"] = "highs" + return options + + def constraints(self, ensemble_member): + constraints = super().constraints(ensemble_member) + + for a in self.energy_system_components.get("ates", []): + stored_heat = self.state_vector(f"{a}.Stored_heat") + constraints.append((stored_heat[0], 0.0, 0.0)) + + return constraints + + def energy_system_options(self): + """ + This function does not add anything at the moment but during debugging we use this. + + Returns + ------- + Options dict for the physics modelling + """ + options = super().energy_system_options() + options["neglect_pipe_heat_losses"] = False + options["heat_loss_disconnected_pipe"] = False + + return options + + +if __name__ == "__main__": + elect = run_optimization_problem( + HeatProblem, + esdl_file_name="airco.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + results = elect.extract_results() + # print(results["CoolingDemand_15e8.Cold_demand"]) + # print(results["HeatingDemand_9b90.Heat_demand"]) + # print(results["HeatPump_b97e.Heat_source"]) + # print(results["ATES_226d.Heat_low_temperature_ates"]) + # for p in elect.energy_system_components.get("heat_pipe", []): + # print(p, results[f"{p}__hn_heat_loss"]) + # print(p, elect.bounds()[f"{p}__hn_heat_loss"]) diff --git a/tests/qth_test_not_maintained/test_qth.py b/tests/qth_test_not_maintained/test_qth.py index 02d515b13..81bdd7412 100644 --- a/tests/qth_test_not_maintained/test_qth.py +++ b/tests/qth_test_not_maintained/test_qth.py @@ -6,10 +6,10 @@ # # from rtctools.util import run_optimization_problem # -# from rtctools_heat_network.util import run_heat_network_optimization +# from mesido.util import run_heat_network_optimization # # -# logger = logging.getLogger("rtctools_heat_network") +# logger = logging.getLogger("mesido") # # # class TestArtificalHeadLoss(TestCase): @@ -64,7 +64,7 @@ # cls.base_folder = Path(double_pipe_qth.__file__).resolve().parent.parent # # def test_single_pipe_no_headloss(self): -# from rtctools_heat_network.qth_mixin import _MinimizeHeadLosses +# from mesido.qth_mixin import _MinimizeHeadLosses # # from models.double_pipe_qth.src.single_pipe_no_headloss import SinglePipeQTHNoHeadLoss # diff --git a/tests/qth_test_not_maintained/test_qth_loop.py b/tests/qth_test_not_maintained/test_qth_loop.py index ac87b8a5b..da7c88572 100644 --- a/tests/qth_test_not_maintained/test_qth_loop.py +++ b/tests/qth_test_not_maintained/test_qth_loop.py @@ -6,11 +6,11 @@ # # from rtctools.util import run_optimization_problem # -# from rtctools_heat_network.qth_loop_mixin import QTHLoopMixin -# from rtctools_heat_network.util import run_heat_network_optimization +# from mesido.qth_loop_mixin import QTHLoopMixin +# from mesido.util import run_heat_network_optimization # # -# logger = logging.getLogger("rtctools_heat_network") +# logger = logging.getLogger("mesido") # # # class TestQTHLoop(TestCase): diff --git a/tests/test_absolute_heat.py b/tests/test_absolute_heat.py index c78268508..a1557b288 100644 --- a/tests/test_absolute_heat.py +++ b/tests/test_absolute_heat.py @@ -1,10 +1,9 @@ from pathlib import Path from unittest import TestCase -from rtctools.util import run_optimization_problem - -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test @@ -19,7 +18,7 @@ def test_absolute_heat(self): Checks: 1. demand is matched 2. energy conservation in the network - 3. milp to discharge + 3. heat to discharge """ import models.absolute_heat.src.example as example @@ -27,7 +26,7 @@ def test_absolute_heat(self): base_folder = Path(example.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="absolute_heat.esdl", diff --git a/tests/test_asset_is_realized.py b/tests/test_asset_is_realized.py index 2846f1e40..a32e5fc52 100644 --- a/tests/test_asset_is_realized.py +++ b/tests/test_asset_is_realized.py @@ -1,12 +1,11 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np class TestAssetIsRealized(TestCase): @@ -16,7 +15,7 @@ def test_asset_is_realized(self): asset is realized variable. We want the asset only to become available once sufficient investments are made. - In this specific test we optimize to match the milp demand. However, the sources are not + In this specific test we optimize to match the heat demand. However, the sources are not available from the start as the cumulative invesments made at timestep 0 is 0. Furthermore, there is a cap on the investments that can be done per timestep. We expect the optimizer to find a solution that releases the sources as soon as possible in order to match demand @@ -36,7 +35,7 @@ def test_asset_is_realized(self): # This is an optimization done over 25 timesteps with a cap on how quickly the cost # for the 2 producers can be realized - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblemPlacingOverTime, base_folder=base_folder, esdl_file_name="test_case_small_network_with_ates.esdl", diff --git a/tests/test_ates.py b/tests/test_ates.py index cc46aa08b..150960447 100644 --- a/tests/test_ates.py +++ b/tests/test_ates.py @@ -1,12 +1,11 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test @@ -15,11 +14,11 @@ class TestAtes(TestCase): def test_ates(self): """ Checks the constraints concerning the milp to discharge and energy conservation - for the ates. The milp loss model used are tested and the typical cyclic constraint that + for the ates. The heat loss model used are tested and the typical cyclic constraint that will be applied in most use cases. Checks: - - the milp loss is computed as expected (loss coef * stored milp [J]) + - the heat loss is computed as expected (loss coef * stored heat [J]) - checks that the efficiency causes less energy discharged than charged - cyclic storage behaviour - standard energy conservation, etc. @@ -33,7 +32,7 @@ def test_ates(self): base_folder = Path(run_ates.__file__).resolve().parent.parent # This is an optimization done over a full year with 365 day timesteps - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="test_case_small_network_with_ates.esdl", diff --git a/tests/test_cable_topology_optimization.py b/tests/test_cable_topology_optimization.py index 1c6e790b0..6363d9421 100644 --- a/tests/test_cable_topology_optimization.py +++ b/tests/test_cable_topology_optimization.py @@ -1,12 +1,11 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np class TestElectricityTopo(TestCase): @@ -25,7 +24,7 @@ def test_electricity_network_topology(self): base_folder = Path(example.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="enettopology.esdl", diff --git a/tests/test_cold_demand.py b/tests/test_cold_demand.py new file mode 100644 index 000000000..1d6476ca9 --- /dev/null +++ b/tests/test_cold_demand.py @@ -0,0 +1,501 @@ +import logging +import unittest.mock +from pathlib import Path +from unittest import TestCase + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.exceptions import MesidoAssetIssueError +from mesido.potential_errors import MesidoAssetIssueType, PotentialErrors +from mesido.util import run_esdl_mesido_optimization +from mesido.workflows.utils.adapt_profiles import ( + adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day, +) +from mesido.workflows.utils.error_types import mesido_issue_type_gen_message + + +import numpy as np + +import pandas as pd + +from utils_test_scaling import create_log_list_scaling + +from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test + + +logger = logging.getLogger("WarmingUP-MPC") +logger.setLevel(logging.INFO) + + +class TestColdDemand(TestCase): + + def test_insufficient_capacity(self): + """ + This test checks that the error checks in the code for sufficient installed cooling + capacity of a cold demand is sufficient (grow_workflow not used) + + Checks: + 1. Correct error is raised + 2. That the error is due to insufficient cold specified capacities + + """ + import models.wko.src.example as example + from models.wko.src.example import HeatProblem + + logger, logs_list = create_log_list_scaling("WarmingUP-MPC") + + base_folder = Path(example.__file__).resolve().parent.parent + + with self.assertRaises(MesidoAssetIssueError) as cm, unittest.mock.patch( + "mesido.potential_errors.POTENTIAL_ERRORS", PotentialErrors() + ): + _ = run_esdl_mesido_optimization( + HeatProblem, + base_folder=base_folder, + esdl_file_name="LT_wko_error_check.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + + # Check that the cold demand had an error + np.testing.assert_equal(cm.exception.error_type, MesidoAssetIssueType.COLD_DEMAND_POWER) + np.testing.assert_equal( + cm.exception.general_issue, + mesido_issue_type_gen_message(MesidoAssetIssueType.COLD_DEMAND_POWER), + ) + np.testing.assert_equal( + cm.exception.message_per_asset_id["15e803b4-1224-4cac-979f-87747a656741"], + "Asset named CoolingDemand_15e8: The installed capacity of 0.05MW should be larger" + " than the maximum of the heat demand profile 0.15MW", + ) + + def test_cold_demand(self): + """ + This test is to check the basic physics for a network which includes cold demand. In this + case we have a network with an air-water hp, a low temperature ates and both hot and cold + demand. In this case the demands are matched and the low temperature ates is utilized. + + Checks: + 1. demand is matched + 2. energy conservation in the network + 3. heat to discharge (note cold line is colder than T_ground) + + """ + import models.wko.src.example as example + from models.wko.src.example import HeatProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + heat_problem = run_esdl_mesido_optimization( + HeatProblem, + base_folder=base_folder, + esdl_file_name="LT_wko.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + results = heat_problem.extract_results() + + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + heat_to_discharge_test(heat_problem, results) + + def test_airco(self): + """ + This test is to check the basic physics for a network which includes an airco. In this + case we have a network with an air-water hp, a low temperature ates and both hot and cold + demand. In this case the demands are matched and the low temperature ates is utilized. + + Checks: + 1. demand is matched + 2. energy conservation in the network + 3. heat to discharge + + """ + import models.wko.src.example as example + from models.wko.src.example import HeatProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + heat_problem = run_esdl_mesido_optimization( + HeatProblem, + base_folder=base_folder, + esdl_file_name="airco.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + results = heat_problem.extract_results() + parameters = heat_problem.parameters(0) + + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + heat_to_discharge_test(heat_problem, results) + + # Check how variable operation cost is calculated + np.testing.assert_allclose( + parameters["HeatPump_b97e.variable_operational_cost_coefficient"] + * sum(results["HeatPump_b97e.Heat_source"][1:]) + / parameters["HeatPump_b97e.cop"], + results["HeatPump_b97e__variable_operational_cost"], + ) + + def test_wko(self): + """ + This test is to check the basic physics for a network which includes cold demand. In this + case we have a network with an air-water hp, a WKO (warm and cold well) and both hot and + cold demand. + + TODO: resolve issue in test case + + The demand profiles and the size of the heat pump has been chosen such that the heat is + required is required to switch on to load the warm well of the WKO. + + Checks for scenario with and without pipe heat losses: + 1. demand is matched + 2. energy conservation in the network + 3. heat to discharge (note cold line is colder than T_ground) + 4. the cyclic heat_stored contraint, which ensures yearly heat balance between the warm and + cold well + 5. pipe heat loss and gain + - pipe heat losses included: expect loss and gain values due to the carrier + temperatures (warm and cold) in the pipes being higher and lower than the ground + temperature + - pipe heat losses excluded: excpect no heat losses or gains + """ + import models.wko.src.example as example + from models.wko.src.example import HeatProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + # ------------------------------------------------------------------------------------------ + # Pipe heat losses inlcuded + class HeatingCoolingProblem(HeatProblem): + + def energy_system_options(self): + options = super().energy_system_options() + options["neglect_pipe_heat_losses"] = False + return options + + def constraints(self, ensemble_member): + constraints = super().constraints(ensemble_member) + + # TODO: confirm if volume or heat balance is required over year. This will + # determine if cyclic contraint below is for stored_heat or stored_volume + # Add stored_heat cyclic constraint, this will also ensure that the total heat + # change in the wko is 0 over the timeline + # Note: + # - WKO in cooling mode: Hot well is being charged with heat and the cold well is + # being discharged + # - WKO in heating mode: Cold well is being charged and the hot well is being + # discharged. + for a in self.energy_system_components.get("low_temperature_ates", []): + stored_heat = self.state_vector(f"{a}.Stored_heat") + constraints.append(((stored_heat[-1] - stored_heat[0]), 0.0, 0.0)) + # This code below might be needed + # Add stored_heat cyclic constraint, this will also ensure that the volume + # into the lower temp & out of the higher temp is the same as the volume + # out of the lower temp & into the higher temp over the timeline. + # Note: + # - Volume increase: Hot well is being charged and the cold well is being + # discharged. -> WKO in cooling mode + # - Volume decrease: Cold well is being charged and the hot well is being + # discharged. -> WKO in heating mode + # for ates_id in self.energy_system_components.get("low_temperature_ates", []): + # stored_volume = self.state_vector(f"{ates_id}.Stored_volume") + # volume_usage = 0.0 + # volume_usage = stored_volume[0] - stored_volume[-1] + # constraints.append((volume_usage, 0.0, 0.0)) + + return constraints + + heat_problem = run_esdl_mesido_optimization( + HeatingCoolingProblem, + base_folder=base_folder, + esdl_file_name="LT_wko_heating_and_cooling.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_2.csv", + ) + results = heat_problem.extract_results() + + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + heat_to_discharge_test(heat_problem, results) + + # Check cyclic constraint + np.testing.assert_allclose( + results["ATES_226d.Stored_heat"][0], results["ATES_226d.Stored_heat"][-1] + ) + # Check heat loss and gain + tol_value = 1.0e-6 + np.testing.assert_array_less( + 0.0, results["Pipe1.HeatIn.Heat"] - results["Pipe1.HeatOut.Heat"] + tol_value + ) + np.testing.assert_array_less( + results["Pipe1_ret.HeatIn.Heat"] - results["Pipe1_ret.HeatOut.Heat"] - tol_value, 0.0 + ) + + # ------------------------------------------------------------------------------------------ + # Pipe heat losses excluded + class HeatingCoolingProblemNoHeatLoss(HeatingCoolingProblem): + def energy_system_options(self): + options = super().energy_system_options() + options["neglect_pipe_heat_losses"] = True + return options + + heat_problem = run_esdl_mesido_optimization( + HeatingCoolingProblemNoHeatLoss, + base_folder=base_folder, + esdl_file_name="LT_wko_heating_and_cooling.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_2.csv", + ) + results = heat_problem.extract_results() + + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + heat_to_discharge_test(heat_problem, results) + + # Check cyclic constraint + np.testing.assert_allclose( + results["ATES_226d.Stored_heat"][0], results["ATES_226d.Stored_heat"][-1] + ) + # Check heat loss and gain + tol_value = 1.0e-6 + np.testing.assert_allclose( + 0.0, results["Pipe1.HeatIn.Heat"] - results["Pipe1.HeatOut.Heat"], atol=1e-6 + ) + np.testing.assert_allclose( + 0.0, results["Pipe1_ret.HeatIn.Heat"] - results["Pipe1_ret.HeatOut.Heat"], atol=1e-6 + ) + # ------------------------------------------------------------------------------------------ + + def test_heat_cold_demand_peak_overlap(self): + """ + This is a demand parsing and time series discretization test. + It checks whether the timeseries are discretized correctly in presence of + a cold and heat demand. This case runs a heat and cold demand case where + both peaks are on the same day. + """ + import models.wko.src.example as example + from models.wko.src.example import HeatProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + class DiscretizationProblem(HeatProblem): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.day_steps = 1 + + def read(self): + super().read() + + ( + self.__indx_max_peak, + self.__heat_demand_nominal, + self.__cold_demand_nominal, + ) = adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day( + self, + self.day_steps, + ) + + heat_problem = run_esdl_mesido_optimization( + DiscretizationProblem, + base_folder=base_folder, + esdl_file_name="heatpump_airco_time_parsing.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_peak_overlap.csv", + ) + results = heat_problem.extract_results() + + cold_demand_timeseries = heat_problem.get_timeseries( + "CoolingDemand_15e8.target_cold_demand" + ) + heat_demand_timeseries = heat_problem.get_timeseries( + "HeatingDemand_9b90.target_heat_demand" + ) + max_cold_idx = np.argmax(cold_demand_timeseries.values) + max_heat_idx = np.argmax(heat_demand_timeseries.values) + + # Check that the resulting discretized series are the correct size. + np.testing.assert_equal(len(cold_demand_timeseries.times), 27) + np.testing.assert_equal(len(heat_demand_timeseries.times), 27) + + # Check that the peak hour is at the correct location after discretization. + np.testing.assert_equal(max_cold_idx, 25) + np.testing.assert_equal(max_heat_idx, 9) + + # Check that the peak day array is the same as the raw input after discretization. + csv_path = base_folder / "input/timeseries_peak_overlap.csv" + raw_demand_data = pd.read_csv(csv_path) + cold_demand_raw_list = np.array(raw_demand_data["CoolingDemand_15e8"]) + heat_demand_raw_list = np.array(raw_demand_data["HeatingDemand_9b90"]) + np.testing.assert_array_equal( + cold_demand_raw_list[24:47], cold_demand_timeseries.values[2:25] + ) + np.testing.assert_array_equal( + heat_demand_raw_list[24:47], heat_demand_timeseries.values[2:25] + ) + + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + heat_to_discharge_test(heat_problem, results) + + def test_heat_cold_demand_peak_back_to_back(self): + """ + This is a demand parsing and time series discretization test. + It checks whether the timeseries are discretized correctly in presence of + a cold and heat demand. This case runs a heat and cold demand case where + both peaks are on consecutive days. + """ + import models.wko.src.example as example + from models.wko.src.example import HeatProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + class DiscretizationProblem(HeatProblem): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.day_steps = 1 + + def read(self): + super().read() + + ( + self.__indx_max_peak, + self.__heat_demand_nominal, + self.__cold_demand_nominal, + ) = adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day( + self, + self.day_steps, + ) + + heat_problem = run_esdl_mesido_optimization( + DiscretizationProblem, + base_folder=base_folder, + esdl_file_name="heatpump_airco_time_parsing.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_peak_back_to_back.csv", + ) + results = heat_problem.extract_results() + + cold_demand_timeseries = heat_problem.get_timeseries( + "CoolingDemand_15e8.target_cold_demand" + ) + heat_demand_timeseries = heat_problem.get_timeseries( + "HeatingDemand_9b90.target_heat_demand" + ) + max_cold_idx = np.argmax(cold_demand_timeseries.values) + max_heat_idx = np.argmax(heat_demand_timeseries.values) + + # Check that the resulting discretized series are the correct size. + np.testing.assert_equal(len(cold_demand_timeseries.times), 50) + np.testing.assert_equal(len(heat_demand_timeseries.times), 50) + + # Check that the peak hour is at the correct location after discretization. + np.testing.assert_equal(max_cold_idx, 44) + np.testing.assert_equal(max_heat_idx, 11) + + # Check that the peak day array is the same as the raw input after discretization. + csv_path = base_folder / "input/timeseries_peak_back_to_back.csv" + raw_demand_data = pd.read_csv(csv_path) + cold_demand_raw_list = np.array(raw_demand_data["CoolingDemand_15e8"]) + heat_demand_raw_list = np.array(raw_demand_data["HeatingDemand_9b90"]) + np.testing.assert_array_equal( + cold_demand_raw_list[48:72], cold_demand_timeseries.values[26:50] + ) + np.testing.assert_array_equal( + heat_demand_raw_list[24:47], heat_demand_timeseries.values[2:25] + ) + + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + heat_to_discharge_test(heat_problem, results) + + def test_heat_cold_peak_before(self): + """ + This is a demand parsing and time series discretization test. + It checks whether the timeseries are discretized correctly in presence of + a cold and heat demand. This case runs a heat and cold demand case where + the cold peak happens before the heat one. + """ + import models.wko.src.example as example + from models.wko.src.example import HeatProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + class DiscretizationProblem(HeatProblem): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.day_steps = 1 + + def read(self): + super().read() + + ( + _, + _, + _, + ) = adapt_hourly_year_profile_to_day_averaged_with_hourly_peak_day( + self, + self.day_steps, + ) + + heat_problem = run_esdl_mesido_optimization( + DiscretizationProblem, + base_folder=base_folder, + esdl_file_name="heatpump_airco_time_parsing.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_cold_peak_before.csv", + ) + results = heat_problem.extract_results() + + cold_demand_timeseries = heat_problem.get_timeseries( + "CoolingDemand_15e8.target_cold_demand" + ) + heat_demand_timeseries = heat_problem.get_timeseries( + "HeatingDemand_9b90.target_heat_demand" + ) + max_cold_idx = np.argmax(cold_demand_timeseries.values) + max_heat_idx = np.argmax(heat_demand_timeseries.values) + + # Check that the resulting discretized series are the correct size. + np.testing.assert_equal(len(cold_demand_timeseries.times), 50) + np.testing.assert_equal(len(heat_demand_timeseries.times), 50) + + # Check that the peak hour is at the correct location after discretization. + np.testing.assert_equal(max_cold_idx, 17) + np.testing.assert_equal(max_heat_idx, 38) + + # Check that the peak day array is the same as the raw input after discretization. + csv_path = base_folder / "input/timeseries_cold_peak_before.csv" + raw_demand_data = pd.read_csv(csv_path) + cold_demand_raw_list = np.array(raw_demand_data["CoolingDemand_15e8"]) + heat_demand_raw_list = np.array(raw_demand_data["HeatingDemand_9b90"]) + np.testing.assert_array_equal( + cold_demand_raw_list[24:48], cold_demand_timeseries.values[2:26] + ) + np.testing.assert_array_equal( + heat_demand_raw_list[48:75], heat_demand_timeseries.values[26:50] + ) + + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + heat_to_discharge_test(heat_problem, results) + + +if __name__ == "__main__": + test_cold_demand = TestColdDemand() + test_cold_demand.test_insufficient_capacity() + test_cold_demand.test_cold_demand() + test_cold_demand.test_wko() + test_cold_demand.test_airco() + test_cold_demand.test_heat_cold_demand_peak_overlap() + test_cold_demand.test_heat_cold_demand_peak_back_to_back() + test_cold_demand.test_heat_cold_peak_before() diff --git a/tests/test_elec_boiler.py b/tests/test_elec_boiler.py new file mode 100644 index 000000000..951c564b3 --- /dev/null +++ b/tests/test_elec_boiler.py @@ -0,0 +1,110 @@ +from pathlib import Path +from unittest import TestCase + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization + +import numpy as np + +from utils_tests import ( + demand_matching_test, + electric_power_conservation_test, + energy_conservation_test, + heat_to_discharge_test, +) + + +class TestElecBoiler(TestCase): + def test_elec_boiler(self): + """ + This tests checks the elec boiler for the standard checks and the energy conservation over + the commodity change. + + Checks: + 1. demand is matched + 2. energy conservation in the network + 3. heat to discharge + 4. energy conservation over the heat and electricity commodity + """ + import models.source_pipe_sink.src.double_pipe_heat as example + from models.source_pipe_sink.src.double_pipe_heat import SourcePipeSink + + base_folder = Path(example.__file__).resolve().parent.parent + + heat_problem = run_esdl_mesido_optimization( + SourcePipeSink, + base_folder=base_folder, + esdl_file_name="sourcesink_witheboiler.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_import.csv", + ) + results = heat_problem.extract_results() + parameters = heat_problem.parameters(0) + + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + heat_to_discharge_test(heat_problem, results) + electric_power_conservation_test(heat_problem, results) + + np.testing.assert_array_less(0.0, results["ElectricBoiler_9aab.Heat_source"]) + np.testing.assert_array_less(0.0, results["ElectricityProducer_4dde.ElectricityOut.Power"]) + np.testing.assert_array_less( + parameters["ElectricBoiler_9aab.efficiency"] + * results["ElectricBoiler_9aab.Power_consumed"], + results["ElectricBoiler_9aab.Heat_source"] + 1.0e-6, + ) + + def test_air_water_hp_elec(self): + """ + This tests checks the air-water hp elec for the standard checks and the energy conservation + over the commodity change. + + Checks: + 1. demand is matched + 2. energy conservation in the network + 3. heat to discharge + 4. energy conservation over the commodity + """ + import models.source_pipe_sink.src.double_pipe_heat as example + from models.source_pipe_sink.src.double_pipe_heat import SourcePipeSink + + base_folder = Path(example.__file__).resolve().parent.parent + + heat_problem = run_esdl_mesido_optimization( + SourcePipeSink, + base_folder=base_folder, + esdl_file_name="sourcesink_withHP.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_import.csv", + ) + results = heat_problem.extract_results() + parameters = heat_problem.parameters(0) + + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + heat_to_discharge_test(heat_problem, results) + electric_power_conservation_test(heat_problem, results) + + np.testing.assert_array_less(0.0, results["HeatPump_d8fd.Heat_source"]) + np.testing.assert_array_less(0.0, results["ElectricityProducer_4dde.ElectricityOut.Power"]) + np.testing.assert_array_less( + parameters["HeatPump_d8fd.cop"] * results["HeatPump_d8fd.Power_consumed"], + results["HeatPump_d8fd.Heat_source"] + 1.0e-6, + ) + + # Check how variable operation cost is calculated + np.testing.assert_allclose( + parameters["HeatPump_d8fd.variable_operational_cost_coefficient"] + * sum(results["HeatPump_d8fd.Heat_source"][1:]) + / parameters["HeatPump_d8fd.cop"], + results["HeatPump_d8fd__variable_operational_cost"], + ) + + +if __name__ == "__main__": + TestElecBoiler = TestElecBoiler() + TestElecBoiler.test_elec_boiler() + TestElecBoiler.test_air_water_hp_elec() diff --git a/tests/test_electric_bus.py b/tests/test_electric_bus.py index 156c972ec..ce8178856 100644 --- a/tests/test_electric_bus.py +++ b/tests/test_electric_bus.py @@ -10,13 +10,13 @@ from pathlib import Path from unittest import TestCase -import numpy as np - +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools.util import run_optimization_problem +import numpy as np -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +from utils_tests import electric_power_conservation_test class TestMILPbus(TestCase): @@ -39,7 +39,7 @@ def test_voltages_and_power_network1(self): base_folder = Path(example.__file__).resolve().parent.parent # Run the problem - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( ElectricityProblem, base_folder=base_folder, esdl_file_name="Electric_bus3.esdl", @@ -48,6 +48,10 @@ def test_voltages_and_power_network1(self): input_timeseries_file="timeseries.csv", ) results = solution.extract_results() + + # electric power conservation system and no dissipation of power and current in bus + electric_power_conservation_test(solution, results) + v1 = results["Bus_f262.ElectricityConn[1].V"] v2 = results["Bus_f262.ElectricityConn[2].V"] v_outgoing_cable = results["ElectricityCable_de9a.ElectricityIn.V"] @@ -55,14 +59,6 @@ def test_voltages_and_power_network1(self): v_demand = results["ElectricityDemand_e527.ElectricityIn.V"] p_demand = results["ElectricityDemand_e527.ElectricityIn.Power"] i_demand = results["ElectricityDemand_e527.ElectricityIn.I"] - p1 = results["Bus_f262.ElectricityConn[1].Power"] - p2 = results["Bus_f262.ElectricityConn[2].Power"] - p3 = results["Bus_f262.ElectricityConn[3].Power"] - p4 = results["Bus_f262.ElectricityConn[4].Power"] - i1 = results["Bus_f262.ElectricityConn[1].I"] - i2 = results["Bus_f262.ElectricityConn[2].I"] - i3 = results["Bus_f262.ElectricityConn[3].I"] - i4 = results["Bus_f262.ElectricityConn[4].I"] # Incoming voltage == outgoing voltage of bus self.assertTrue(all(v1 == v2)) @@ -70,13 +66,67 @@ def test_voltages_and_power_network1(self): self.assertTrue(all(v1 == v_incoming_cable)) # Outgoing voltage of bus == voltage of outgoing cable self.assertTrue(all(v1 == v_outgoing_cable)) - # Power in == power out = no dissipation of power - np.testing.assert_allclose(p1 + p2 - p3 - p4, 0.0, rtol=1.0e-6, atol=1.0e-6) - # Current in == current out = no dissipation of power - np.testing.assert_allclose(i1 + i2 - i3 - i4, 0.0, rtol=1.0e-6, atol=1.0e-6) + # check if minimum voltage is reached np.testing.assert_array_less( solution.parameters(0)["ElectricityDemand_e527.min_voltage"] - 1.0e-3, v_demand ) # Check that current is high enough to carry the power np.testing.assert_array_less(p_demand - 1e-12, v_demand * i_demand) + + def test_unidirectional_cable(self): + """ + Checks the behaviour of electricity networks with a two bus assets connected with a cable + that is only allowed to be unidirectional. + + Electricity from producer 1 can go to demand 1 and demand 2, but electricity from producer 2 + can only go to demand 2 due to unidirectional cable between the two busses + + Checks: + - electric power conservation + - bounds on unidirectional cable set to a minimum power flow of 0.0 + - demand 1 is limited by production of producer 1 + + """ + import models.unit_cases_electricity.bus_networks.src.example as example + from models.unit_cases_electricity.bus_networks.src.example import ElectricityProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + # Run the problem + solution = run_esdl_mesido_optimization( + ElectricityProblem, + base_folder=base_folder, + esdl_file_name="Electric_bus4.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_uni.csv", + ) + results = solution.extract_results() + + # electric power conservation system and no dissipation of power and current in bus + electric_power_conservation_test(solution, results) + + demand_1 = "ElectricityDemand_e527" + demand_2 = "ElectricityDemand_281a" + prod_1 = "ElectricityProducer_a215" + prod_2 = "ElectricityProducer_17a1" + unidirectional_cable = "ElectricityCable_d16c" + + p_demand_1 = results[f"{demand_1}.ElectricityIn.Power"] + p_demand_2 = results[f"{demand_2}.ElectricityIn.Power"] + cable_power_bound = solution.bounds()[f"{unidirectional_cable}.ElectricityIn.Power"][0] + + bound_prod_1 = solution.bounds()[f"{prod_1}.Electricity_source"][1] + bound_prod_2 = solution.bounds()[f"{prod_2}.Electricity_source"][1] + target_demand_1 = solution.get_timeseries(f"{demand_1}.target_electricity_demand").values + target_demand_1[target_demand_1 > bound_prod_1] = bound_prod_1 + target_demand_2 = solution.get_timeseries(f"{demand_2}.target_electricity_demand").values + target_demand_2[target_demand_2 > (bound_prod_1 + bound_prod_2)] = ( + bound_prod_1 + bound_prod_2 + ) + + np.testing.assert_allclose(p_demand_1, target_demand_1) + np.testing.assert_allclose(p_demand_2, target_demand_2) + + np.testing.assert_allclose(0.0, cable_power_bound) diff --git a/tests/test_electric_source_sink.py b/tests/test_electric_source_sink.py index 0053c2339..7b90cff69 100644 --- a/tests/test_electric_source_sink.py +++ b/tests/test_electric_source_sink.py @@ -1,13 +1,14 @@ from pathlib import Path from unittest import TestCase -import numpy as np +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization +import numpy as np -from rtctools.util import run_optimization_problem +from utils_tests import electric_power_conservation_test -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile # TODO: still have to make test where elecitricity direction is switched: # e.g. 2 nodes, with at each node a producer and consumer, first one node medium demand, second @@ -36,7 +37,7 @@ def test_source_sink(self): base_folder = Path(example.__file__).resolve().parent.parent tol = 1e-10 - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( ElectricityProblem, base_folder=base_folder, esdl_file_name="case1_elec.esdl", @@ -47,6 +48,9 @@ def test_source_sink(self): results = solution.extract_results() parameters = solution.parameters(0) + # Test energy conservation + electric_power_conservation_test(solution, results) + max_ = solution.bounds()["ElectricityDemand_2af6__max_size"][0] v_min = solution.parameters(0)["ElectricityCable_238f.min_voltage"] @@ -57,15 +61,7 @@ def test_source_sink(self): biggerthen = all(power_consumed >= np.zeros(len(power_consumed))) self.assertTrue(biggerthen) - # Test energy conservation - power_consumed = results["ElectricityDemand_2af6.ElectricityIn.Power"] - power_delivered = results["ElectricityProducer_b95d.ElectricityOut.Power"] power_loss = results["ElectricityCable_238f.Power_loss"] - total_power_dissipation = power_consumed + power_loss - self.assertIsNone( - np.testing.assert_allclose(total_power_dissipation, power_delivered, rtol=1e-4), - msg="No energy conservation. Total demand is not equal to total delivery.", - ) biggerthen = all(power_loss >= np.zeros(len(power_loss))) self.assertTrue(biggerthen) @@ -123,7 +119,7 @@ def test_source_sink_max_curr(self): base_folder = Path(example.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( ElectricityProblemMaxCurr, base_folder=base_folder, esdl_file_name="case1_elec.esdl", @@ -134,6 +130,9 @@ def test_source_sink_max_curr(self): results = solution.extract_results() parameters = solution.parameters(0) + # Test energy conservation + electric_power_conservation_test(solution, results) + max_power_transport = ( parameters["ElectricityCable_238f.min_voltage"] * parameters["ElectricityCable_238f.max_current"] @@ -158,15 +157,7 @@ def test_source_sink_max_curr(self): biggerthen = all(power_consumed >= np.zeros(len(power_consumed))) self.assertTrue(biggerthen) - # Test energy conservation - power_consumed = results["ElectricityDemand_2af6.ElectricityIn.Power"] - power_delivered = results["ElectricityProducer_b95d.ElectricityOut.Power"] power_loss = results["ElectricityCable_238f.Power_loss"] - total_power_dissipation = power_consumed + power_loss - self.assertIsNone( - np.testing.assert_allclose(total_power_dissipation, power_delivered, rtol=1e-4), - msg="No energy conservation. Total demand is not equal to total delivery.", - ) biggerthen = all(power_loss >= np.zeros(len(power_loss))) self.assertTrue(biggerthen) @@ -200,3 +191,64 @@ def test_source_sink_max_curr(self): results[f"{demand}.ElectricityIn.Power"], atol=1.0e-3, ) + + def test_transformer(self): + """ + This test is to check the transformer component which changes the voltage level. + + Checks: + - demand matching + - check the voltage levels are not equal and are correctly set + - power conservation at the transformer + + """ + + import models.unit_cases_electricity.source_sink_cable.src.example as example + from models.unit_cases_electricity.source_sink_cable.src.example import ( + ElectricityProblem, + ) + + base_folder = Path(example.__file__).resolve().parent.parent + + solution = run_esdl_mesido_optimization( + ElectricityProblem, + base_folder=base_folder, + esdl_file_name="transformer.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + results = solution.extract_results() + parameters = solution.parameters(0) + + # Check power conservation including power conservation in transformer + electric_power_conservation_test(solution, results) + + # Check that the cables have two different voltage levels + assert ( + parameters["ElectricityDemand_2af6.min_voltage"] + != parameters["Transformer_0185.min_voltage"] + ) + + np.testing.assert_allclose( + parameters["Transformer_0185.min_voltage"], + results["ElectricityCable_1fe5.ElectricityOut.V"], + atol=-1.0e-3, + ) + np.testing.assert_allclose( + parameters["ElectricityDemand_2af6.min_voltage"], + results["ElectricityCable_22c9.ElectricityOut.V"], + atol=1.0e-3, + ) + + for demand in solution.energy_system_components_get(["electricity_demand", "transformer"]): + np.testing.assert_allclose( + results[f"{demand}.ElectricityIn.V"], + parameters[f"{demand}.min_voltage"], + atol=1.0e-3, + ) + np.testing.assert_allclose( + results[f"{demand}.ElectricityIn.V"] * results[f"{demand}.ElectricityIn.I"], + results[f"{demand}.ElectricityIn.Power"], + atol=1.0e-3, + ) diff --git a/tests/test_electricity_storage.py b/tests/test_electricity_storage.py new file mode 100644 index 000000000..fa0b592eb --- /dev/null +++ b/tests/test_electricity_storage.py @@ -0,0 +1,110 @@ +from pathlib import Path +from unittest import TestCase + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization + +import numpy as np + +from utils_tests import demand_matching_test, electric_power_conservation_test, feasibility_test + + +class TestMILPElectricSourceSink(TestCase): + def test_source_sink(self): + """ + Tests for an electricity network that consist out of a source, a sink and storage, + connected with electricity cables. + + Checks: + - Check that the efficiency for charging and discharging is used proper to determine the + consumed and stored power + - Check that the battery is used to match demand + - Check that charging and discharging properly connected to the network (direction) + - Check that the is_charging variable is set correctly + + + """ + + import models.unit_cases_electricity.battery.src.example as example + from models.unit_cases_electricity.battery.src.example import ElectricityProblem + + base_folder = Path(example.__file__).resolve().parent.parent + tol = 1e-10 + + solution = run_esdl_mesido_optimization( + ElectricityProblem, + base_folder=base_folder, + esdl_file_name="source_sink_storage.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + results = solution.extract_results() + parameters = solution.parameters(0) + + feasibility_test(solution) + + demand_matching_test(solution, results) + electric_power_conservation_test(solution, results) + + storage_name = solution.energy_system_components.get("electricity_storage")[0] + charge_eff = parameters[f"{storage_name}.charge_efficiency"] + discharge_eff = parameters[f"{storage_name}.discharge_efficiency"] + is_charging = results[f"{storage_name}__is_charging"] + eff_power_change_bat = results[f"{storage_name}.Effective_power_charging"] + eff_power_change_discharge_bat = results[f"{storage_name}__effective_power_discharging"] + power_bat_network = results[f"{storage_name}.ElectricityIn.Power"] + stored_el = results[f"{storage_name}.Stored_electricity"] + + power_cable_bat = results["ElectricityCable_91c1.ElectricityOut.Power"] + np.testing.assert_allclose(power_cable_bat, power_bat_network, atol=tol) + + # if battery is charging (1), ElectricityIn.Power and effective_power charging should be + # positive, else negative + bigger_then = all(is_charging * eff_power_change_bat >= 0) + smaller_then = all((1 - is_charging) * eff_power_change_bat <= 0) + self.assertTrue(bigger_then) + self.assertTrue(smaller_then) + + bigger_then = all(is_charging * power_bat_network >= 0) + smaller_then = all((1 - is_charging) * power_bat_network <= 0) + self.assertTrue(bigger_then) + self.assertTrue(smaller_then) + + # battery should be charging at atleast one timestep to overcome the difference between max + # production and demand + self.assertTrue(sum(is_charging) >= 1) + + # stored electricity starts at 0 + np.testing.assert_allclose( + stored_el[0], + 0.0, + err_msg="The battery should be empty at the start to check if it operates and " + "predicted", + ) + + # stored electricity change should be equal to the effective power change + stored_change = stored_el[1:] - stored_el[:-1] + np.testing.assert_allclose(eff_power_change_bat[1:] * 3600, stored_change, atol=tol) + + # effective power change while charging should be equal to efficiency * powerIn + np.testing.assert_allclose( + eff_power_change_bat * is_charging, + power_bat_network * is_charging * charge_eff, + atol=tol, + ) + # effective power change while discharging should be equal to powerOut/efficiency + np.testing.assert_allclose( + eff_power_change_bat * (1 - is_charging), + power_bat_network * (1 - is_charging) / discharge_eff, + atol=tol, + ) + + # effective power discharge variable should always be the bigger or equal to the negative + # of the charge variable and bigger then zero. The zero should only occur if battery is + # charging. When a goal would be set to minimise discharge it should match the charge power, + # however now this goal is not turned on. + # TODO: when the new goal is included create test, this will end up in the mc_simulator + np.testing.assert_array_less(-eff_power_change_bat, eff_power_change_discharge_bat + tol) + self.assertTrue(all(eff_power_change_discharge_bat >= 0.0)) diff --git a/tests/test_electrolyzer.py b/tests/test_electrolyzer.py index 355696b03..eedc3019c 100644 --- a/tests/test_electrolyzer.py +++ b/tests/test_electrolyzer.py @@ -1,22 +1,21 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem - -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import mesido._darcy_weisbach as darcy_weisbach +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.network_common import NetworkSettings +from mesido.util import run_esdl_mesido_optimization - -# from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test +import numpy as np class TestElectrolyzer(TestCase): - def test_electrolyzer(self): + def test_electrolyzer_inequality(self): """ This test is to check the functioning the example with an offshore wind farm in combination - with an electrolyzer and hydrogen storage. + with an electrolyzer and hydrogen storage. The electrolyzer is modelled as the option + LINEARIZED_THREE_LINES_WEAK_INEQUALITY. Checks: - The objective value with the revenue included @@ -24,32 +23,60 @@ def test_electrolyzer(self): - Check the setpoint for the windfarm - Check the max production profile of the windfarm - Check the electrolyzer inequality constraints formulation - + - The water kinematic viscosity of hydrogen by comparing head loss to a hard-coded value + - The pipe head loss constraint for a hydrogen network """ import models.unit_cases_electricity.electrolyzer.src.example as example - from models.unit_cases_electricity.electrolyzer.src.example import MILPProblem + from models.unit_cases_electricity.electrolyzer.src.example import MILPProblemInequality base_folder = Path(example.__file__).resolve().parent.parent - class MILPProblemSolve(MILPProblem): - def energy_system_options(self): - options = super().energy_system_options() - self.gas_network_settings["pipe_maximum_pressure"] = 100.0 # [bar] - self.gas_network_settings["pipe_minimum_pressure"] = 0.0 + class MILPProblemInequalityWithoutPresolve(MILPProblemInequality): + def solver_options(self): + options = super().solver_options() + options["solver"] = "highs" + highs_options = options["highs"] = {} + highs_options["presolve"] = "off" + return options - solution = run_optimization_problem( - MILPProblem, + solution = run_esdl_mesido_optimization( + MILPProblemInequalityWithoutPresolve, base_folder=base_folder, esdl_file_name="h2.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, - input_timeseries_file="timeseries.csv", + input_timeseries_file="timeseries_electrolyzer_general.csv", ) results = solution.extract_results() - gas_price_profile = "gas.price_profile" + # TODO: potential move this code to the head loss test case (does not contain a hydrogen + # network optimization). For now this was not done, because it would imply adding a + # hydrogen network solve purely for the checks below which seems unnecessary + # Check: + # - Compare the head loss to hard-coded values. Difference expected if an error + # occours in the calculation of the gas kinematic viscosity. + + # - Check head loss contraint + v_inspect = results["Pipe_6ba6.GasOut.Q"] / solution.parameters(0)["Pipe_6ba6.area"] + head_loss_max = darcy_weisbach.head_loss( + solution.gas_network_settings["maximum_velocity"], + solution.parameters(0)["Pipe_6ba6.diameter"], + solution.parameters(0)["Pipe_6ba6.length"], + solution.energy_system_options()["wall_roughness"], + 20.0, + network_type=NetworkSettings.NETWORK_TYPE_HYDROGEN, + pressure=solution.parameters(0)["Pipe_6ba6.pressure"], + ) + for iv in range(len(v_inspect)): + np.testing.assert_allclose( + v_inspect[iv] / solution.gas_network_settings["maximum_velocity"] * head_loss_max, + 2.1760566566624733, + ) + np.testing.assert_allclose(-results["Pipe_6ba6.dH"][iv], 2.1760566566624733) + + gas_price_profile = "Hydrogen.price_profile" state = "GasDemand_0cf3.Gas_demand_mass_flow" nominal = solution.variable_nominal(state) * np.median( solution.get_timeseries(gas_price_profile).values @@ -89,15 +116,14 @@ def energy_system_options(self): # Check that the wind farm setpoint matches with the production np.testing.assert_allclose( - results["WindPark_7f14.ElectricityOut.Power"], ub * results["WindPark_7f14.Set_point"] + results["WindPark_7f14.ElectricityOut.Power"], ub * results["WindPark_7f14__set_point"] ) # Checks on the storage timestep = 3600.0 - rho = solution.parameters(0)["GasStorage_e492.density_max_storage"] np.testing.assert_allclose( np.diff(results["GasStorage_e492.Stored_gas_mass"]), - results["GasStorage_e492.Gas_tank_flow"][1:] * rho * timestep, + results["GasStorage_e492.Gas_tank_flow"][1:] * timestep, rtol=1e-6, atol=1e-8, ) @@ -130,7 +156,10 @@ def energy_system_options(self): coef_b, coef_c, n_lines=3, - electrical_power_min=0.0, + electrical_power_min=max( + solution.parameters(0)["Electrolyzer_fc66.minimum_load"], + 0.01 * solution.bounds()["Electrolyzer_fc66.ElectricityIn.Power"][1], + ), electrical_power_max=solution.bounds()["Electrolyzer_fc66.ElectricityIn.Power"][1], ) # TODO: Add test below once the mass flow is coupled to the volumetric flow rate. Currently @@ -144,8 +173,15 @@ def energy_system_options(self): results["Electrolyzer_fc66.ElectricityIn.Power"] * a[i] + b[i] + 1.0e-3, ) - # print(results["Electrolyzer_fc66.ElectricityIn.Power"]) - # print(results["Electrolyzer_fc66.Gas_mass_flow_out"]) + # Check electrolyzer input power + np.testing.assert_allclose( + results["Electrolyzer_fc66.ElectricityIn.Power"], + [1.00000000e08, 1.00000000e08, 1.00000000e08], + ) + # Check electrolyzer output massflow + np.testing.assert_allclose( + results["Electrolyzer_fc66.Gas_mass_flow_out"], [431.367058, 431.367058, 431.367058] + ) # ----------------------------------------------------------------------------------------- # Do cost checks @@ -187,12 +223,286 @@ def energy_system_options(self): sum(results["Electrolyzer_fc66__investment_cost"]), ) # ----------------------------------------------------------------------------------------- + # TODO: add check on the electricity power conservation + + def test_electrolyzer_minimum_power(self): + """ + This test is to check that the electrolyzer is switched off when input power is below + the minimum power. The electrolyzer is modelled as the option + LINEARIZED_THREE_LINES_WEAK_INEQUALITY. + + Checks: + - Input power to the electrolyzer is 0 when available wind power is 49MW, as the + threshold for the electrolyzer is 50MW + - Output gas is 0 when available wind power is 49MW, as the threshold for the + electrolyzer is 50MW + - Electrolyzer is switched off when available wind power is 49MW, as the threshold for the + electrolyzer is 50MW + - Input power is greater than 0 when available power is greater than 50MW + - Output gas is greater than 0 when available power is greater than 50MW + - Electrolyzer is switched on when available power is greater than 50MW + - Electrolyzer input power equals hardcoded values + - Electrolyzer output massflow equals harcoded values + + """ + import models.unit_cases_electricity.electrolyzer.src.example as example + from models.unit_cases_electricity.electrolyzer.src.example import MILPProblemInequality + + base_folder = Path(example.__file__).resolve().parent.parent + + class MILPProblemInequalityWithoutPresolve(MILPProblemInequality): + def solver_options(self): + options = super().solver_options() + options["solver"] = "highs" + highs_options = options["highs"] = {} + highs_options["presolve"] = "off" + + return options + + solution = run_esdl_mesido_optimization( + MILPProblemInequalityWithoutPresolve, + base_folder=base_folder, + esdl_file_name="h2.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_minimum_electrolyzer_power.csv", + ) + + results = solution.extract_results() + + # Check that the input power is 0 + np.testing.assert_allclose( + results["Electrolyzer_fc66.ElectricityIn.Power"][-1], + 0.0, + atol=5e-5, + ) + # Check that the output gas is 0 + np.testing.assert_allclose( + results["Electrolyzer_fc66.Gas_mass_flow_out"][-1], + 0.0, + ) + # Check that the electrolyzer is switched off + np.testing.assert_allclose( + results["Electrolyzer_fc66__asset_is_switched_on"][-1], + 0, + ) + # Check that the input power is greater than 0 + np.testing.assert_array_less( + np.zeros(2), + results["Electrolyzer_fc66.ElectricityIn.Power"][:-1], + ) + # Check that the output gas is 0 + np.testing.assert_array_less( + np.zeros(2), + results["Electrolyzer_fc66.Gas_mass_flow_out"][:-1], + ) + # Check that the electrolyzer is switched off + np.testing.assert_allclose( + results["Electrolyzer_fc66__asset_is_switched_on"][:-1], + np.ones(2), + ) + # Check electrolyzer input power + # np.testing.assert_allclose( + # results["Electrolyzer_fc66.ElectricityIn.Power"], + # [ 1.00000000e+08, 1.00000000e+08, -3.59365315e-05], + # atol=1e-4, + # ) + # Check electrolyzer output massflow + # np.testing.assert_allclose( + # results["Electrolyzer_fc66.Gas_mass_flow_out"], + # [431.367058, 431.367058, 0. ], + # atol=1e-4, + # ) + + def test_electrolyzer_constant_efficiency(self): + """ + This test is to check the functioning the example with an offshore wind farm in combination + with an electrolyzer and hydrogen storage. The electrolyzer is modelled as the option + CONSTANT_EFFICIENCY. + + Checks: + - Check the constant efficiency formulation of the electrolyzer + - Check hardcoded values for input power and output massflow os the electrolyzer + + """ + import models.unit_cases_electricity.electrolyzer.src.example as example + from models.unit_cases_electricity.electrolyzer.src.example import ( + MILPProblemConstantEfficiency, + ) + + base_folder = Path(example.__file__).resolve().parent.parent + + solution = run_esdl_mesido_optimization( + MILPProblemConstantEfficiency, + base_folder=base_folder, + esdl_file_name="h2.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_electrolyzer_general.csv", + ) + + results = solution.extract_results() + + # Electrolyser + efficiency = solution.parameters(0)["Electrolyzer_fc66.efficiency"] + np.testing.assert_allclose( + results["Electrolyzer_fc66.Gas_mass_flow_out"] * efficiency * 3600, + results["Electrolyzer_fc66.ElectricityIn.Power"], + ) + + # Check input power values. Not really needed since the massflow check is equivalent + # np.testing.assert_allclose( + # results["Electrolyzer_fc66.ElectricityIn.Power"], + # [1.00000000e+08, 1.00000000e+08, 1.00000000e+08], + # atol=1e-4, + # ) + # Check output massflow values + np.testing.assert_allclose( + results["Electrolyzer_fc66.Gas_mass_flow_out"], + [440.91710758, 440.91710758, 440.91710758], + atol=1e-4, + ) + + def test_electrolyzer_equality_constraint(self): + """ + This test is to check the functioning the example with an offshore wind farm in combination + with an electrolyzer and hydrogen storage. The electrolyzer is modelled as the option + LINEARIZED_THREE_LINES_EQUALITY. + + Checks: + - Check that only one line is activated + - Check that the expected lines are activated, depending on the input power + - Check that the output massflow lies on the line segment + - Check hardcoded values + + """ + import models.unit_cases_electricity.electrolyzer.src.example as example + from models.unit_cases_electricity.electrolyzer.src.example import ( + MILPProblemEquality, + ) + + base_folder = Path(example.__file__).resolve().parent.parent + + solution = run_esdl_mesido_optimization( + MILPProblemEquality, + base_folder=base_folder, + esdl_file_name="h2.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_equality_constraints.csv", + ) + + results = solution.extract_results() + + # Check that there is only one activated line per timestep + for timestep in range(len(results["Electrolyzer_fc66__line_0_active"])): + np.testing.assert_allclose( + ( + results["Electrolyzer_fc66__line_0_active"][timestep] + + results["Electrolyzer_fc66__line_1_active"][timestep] + + results["Electrolyzer_fc66__line_2_active"][timestep] + + (1 - results["Electrolyzer_fc66__asset_is_switched_on"][timestep]) + ), + 1.0, + ) + # Check that for the first, second and third timesteps, only the lines + # 0, 1 and 2 are activated (respectively), being the wind power 100, 300 + # and 400 MW. + for idx in range(3): + np.testing.assert_allclose( + ( + results[f"Electrolyzer_fc66__line_{idx}_active"][idx] + + (1 - results["Electrolyzer_fc66__asset_is_switched_on"][idx]) + ), + 1.0, + ) + # Check that the output massflow lies on the line segment + coef_a = solution.parameters(0)["Electrolyzer_fc66.a_eff_coefficient"] + coef_b = solution.parameters(0)["Electrolyzer_fc66.b_eff_coefficient"] + coef_c = solution.parameters(0)["Electrolyzer_fc66.c_eff_coefficient"] + a, b = solution._get_linear_coef_electrolyzer_mass_vs_epower_fit( + coef_a, + coef_b, + coef_c, + n_lines=3, + electrical_power_min=max( + solution.parameters(0)["Electrolyzer_fc66.minimum_load"], + 0.01 * solution.bounds()["Electrolyzer_fc66.ElectricityIn.Power"][1], + ), + electrical_power_max=solution.bounds()["Electrolyzer_fc66.ElectricityIn.Power"][1], + ) + for idx in range(3): + np.testing.assert_allclose( + results["Electrolyzer_fc66.Gas_mass_flow_out"][idx], + results["Electrolyzer_fc66.ElectricityIn.Power"][idx] * a[idx] + b[idx], + ) + # Check hardcoded values + np.testing.assert_allclose( + results["Electrolyzer_fc66.Gas_mass_flow_out"], + [431.367058, 1285.95625642, 1673.61498453], + atol=1e-4, + ) + + def test_electrolyzer_equality_constraint_inactive_line(self): + """ + This test is to check the functioning the example with an offshore wind farm in combination + with an electrolyzer and hydrogen storage. The electrolyzer is modelled as the option + LINEARIZED_THREE_LINES_EQUALITY. + + Checks: + - Check that no line is active when the electrolyzer is switched off + - Check that the input power is 0 when the electrolyzer is switched off + - Check that the output massflow is 0 when the electrolyzer is switched off + + """ + import models.unit_cases_electricity.electrolyzer.src.example as example + from models.unit_cases_electricity.electrolyzer.src.example import ( + MILPProblemEquality, + ) + + base_folder = Path(example.__file__).resolve().parent.parent + + solution = run_esdl_mesido_optimization( + MILPProblemEquality, + base_folder=base_folder, + esdl_file_name="h2.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_minimum_electrolyzer_power.csv", + ) + + results = solution.extract_results() + + # Input power to the electrolyzer is below the minimum one, + # such that no line should be active + np.testing.assert_allclose( + ( + results["Electrolyzer_fc66__line_0_active"][-1] + + results["Electrolyzer_fc66__line_1_active"][-1] + + results["Electrolyzer_fc66__line_2_active"][-1] + + (1 - results["Electrolyzer_fc66__asset_is_switched_on"][-1]) + ), + 1.0, + ) + # Check that the input power is 0 + np.testing.assert_allclose( + results["Electrolyzer_fc66.ElectricityIn.Power"][-1], + 0.0, + atol=1e-4, + ) + # Check that the output gas is 0 + np.testing.assert_allclose( + results["Electrolyzer_fc66.Gas_mass_flow_out"][-1], + 0.0, + atol=1e-4, + ) if __name__ == "__main__": - import time - start_time = time.time() - test = TestElectrolyzer() - sol = test.test_electrolyzer() - print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) + a = TestElectrolyzer() + a.test_electrolyzer_inequality() + a.test_electrolyzer_minimum_power() + a.test_electrolyzer_constant_efficiency() + a.test_electrolyzer_equality_constraint() + a.test_electrolyzer_equality_constraint_inactive_line() diff --git a/tests/test_emerge.py b/tests/test_emerge.py new file mode 100644 index 000000000..5694cd50e --- /dev/null +++ b/tests/test_emerge.py @@ -0,0 +1,39 @@ +from pathlib import Path +from unittest import TestCase + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization + + +class TestEmerge(TestCase): + def test_emerge_workflow(self): + """ + This test checks if the emerge workflow is succesfully optimized + + Checks: + 1. check if solver succeeds + + """ + import models.emerge.src.example as example + from mesido.workflows.emerge import EmergeWorkFlow + + base_folder = Path(example.__file__).resolve().parent.parent + + _ = run_esdl_mesido_optimization( + EmergeWorkFlow, + base_folder=base_folder, + esdl_file_name="emerge.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + + # TODO: checks on values need to be added, not sure if cost values now make sense, scaling + # is not too bad, but if presolve of HIGHS is on, it becomes infeasible. + + +if __name__ == "__main__": + + a = TestEmerge() + a.test_emerge_workflow() diff --git a/tests/test_end_scenario_sizing.py b/tests/test_end_scenario_sizing.py index 6468f08cb..f666ad021 100644 --- a/tests/test_end_scenario_sizing.py +++ b/tests/test_end_scenario_sizing.py @@ -1,26 +1,25 @@ from pathlib import Path from unittest import TestCase +import mesido._darcy_weisbach as darcy_weisbach +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.workflows import ( + EndScenarioSizing, + EndScenarioSizingDiscounted, + EndScenarioSizingStaged, + run_end_scenario_sizing, +) +from mesido.workflows.grow_workflow import EndScenarioSizingHeadLossStaged + import numpy as np from rtctools.util import run_optimization_problem -import rtctools_heat_network._darcy_weisbach as darcy_weisbach -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.workflows import ( - EndScenarioSizingDiscountedHIGHS, - EndScenarioSizingHIGHS, - EndScenarioSizingStagedHIGHS, - run_end_scenario_sizing, -) -from rtctools_heat_network.workflows.grow_workflow import EndScenarioSizingHeadLossStaged - from utils_tests import demand_matching_test class TestEndScenarioSizing(TestCase): - @classmethod def setUpClass(cls) -> None: import models.test_case_small_network_ates_buffer_optional_assets.src.run_ates as run_ates @@ -30,7 +29,7 @@ def setUpClass(cls) -> None: # This is an optimization done over a full year with timesteps of 5 days and hour timesteps # for the peak day cls.solution = run_optimization_problem( - EndScenarioSizingHIGHS, + EndScenarioSizing, base_folder=base_folder, esdl_file_name="test_case_small_network_with_ates_with_buffer_all_optional.esdl", esdl_parser=ESDLFileParser, @@ -46,9 +45,11 @@ def test_end_scenario_sizing(self): day. Checks: + - demand matching + - that the available pipe classes were adapted + - minimum velocity setting - Cyclic behaviour for ATES - That buffer tank is only used on peak day - - demand matching - Check if TCO goal included the desired cost components. @@ -67,6 +68,14 @@ def test_end_scenario_sizing(self): # Check whehter the heat demand is matched demand_matching_test(self.solution, self.results) + # Check that indeed the available pipe classes were adapted based on expected flow + # Pipe connected to a demand + assert self.solution.pipe_classes("Pipe2")[0].name == "DN150" # initially DN->None + assert self.solution.pipe_classes("Pipe2")[-1].name == "DN250" # initially DN450 + # Check the minimum velocity setting==default value. Keep the default value hard-coded to + # prevent future coding bugs + np.testing.assert_equal(1.0e-4, self.solution.heat_network_settings["minimum_velocity"]) + # Check whether cyclic ates constraint is working for a in self.solution.energy_system_components.get("ates", []): stored_heat = self.results[f"{a}.Stored_heat"] @@ -134,7 +143,7 @@ def test_end_scenario_sizing_staged(self): solution_unstaged = self.solution solution_unstaged_2 = run_end_scenario_sizing( - EndScenarioSizingHIGHS, + EndScenarioSizing, staged_pipe_optimization=False, base_folder=base_folder, esdl_file_name="test_case_small_network_with_ates_with_buffer_all_optional.esdl", @@ -144,7 +153,7 @@ def test_end_scenario_sizing_staged(self): ) solution_staged = run_end_scenario_sizing( - EndScenarioSizingStagedHIGHS, + EndScenarioSizingStaged, base_folder=base_folder, esdl_file_name="test_case_small_network_with_ates_with_buffer_all_optional.esdl", esdl_parser=ESDLFileParser, @@ -241,7 +250,7 @@ def test_end_scenario_sizing_discounted(self): base_folder = Path(run_ates.__file__).resolve().parent.parent - class TestEndScenarioSizingDiscountedHIGHS(EndScenarioSizingDiscountedHIGHS): + class TestEndScenarioSizingDiscountedHIGHS(EndScenarioSizingDiscounted): def solver_options(self): options = super().solver_options() options["solver"] = "highs" @@ -315,10 +324,10 @@ def test_end_scenario_sizing_head_loss(self): pipes = solution.energy_system_components.get("heat_pipe") for pipe in pipes: - pipe_diameter = solution.parameters(0)[f"{pipes[0]}.diameter"] + pipe_diameter = solution.parameters(0)[f"{pipe}.diameter"] pipe_wall_roughness = solution.energy_system_options()["wall_roughness"] - temperature = solution.parameters(0)[f"{pipes[0]}.temperature"] - pipe_length = solution.parameters(0)[f"{pipes[0]}.length"] + temperature = solution.parameters(0)[f"{pipe}.temperature"] + pipe_length = solution.parameters(0)[f"{pipe}.length"] if pipe_diameter > 0.0: velocities = results[f"{pipe}.Q"] / solution.parameters(0)[f"{pipe}.area"] else: @@ -342,6 +351,9 @@ def test_end_scenario_sizing_head_loss(self): start_time = time.time() a = TestEndScenarioSizing() - # a.test_end_scenario_sizing() + a.setUpClass() + a.test_end_scenario_sizing() + a.test_end_scenario_sizing_staged() + a.test_end_scenario_sizing_discounted() a.test_end_scenario_sizing_head_loss() print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) diff --git a/tests/test_end_scenario_sizing_annualized.py b/tests/test_end_scenario_sizing_annualized.py index 274f7646e..1da591a64 100644 --- a/tests/test_end_scenario_sizing_annualized.py +++ b/tests/test_end_scenario_sizing_annualized.py @@ -1,19 +1,19 @@ from pathlib import Path from unittest import TestCase +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile + import numpy as np from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile - class TestEndScenarioSizingAnnualized(TestCase): """ Tests for end scenario sizing with annualized costs in a small network with optional assets. - This class tests two models for a milp network: with + This class tests two models for a heat network: with and without annualized costs. It asserts the following: 1. Under some conditions, the objective value of the annualized model is equal to the solution from the non annualized one. @@ -35,7 +35,7 @@ def test_end_scenario_sizing_annualized(self): from models.test_case_small_network_optional_assets_annualized.src import ( run_annualized, ) - from rtctools_heat_network.financial_mixin import calculate_annuity_factor + from mesido.financial_mixin import calculate_annuity_factor base_folder = Path(run_annualized.__file__).resolve().parent.parent diff --git a/tests/test_esdl_parsing.py b/tests/test_esdl_parsing.py index d4c4b8dd0..e3df28f76 100644 --- a/tests/test_esdl_parsing.py +++ b/tests/test_esdl_parsing.py @@ -1,15 +1,16 @@ import unittest from pathlib import Path +from mesido.esdl.esdl_parser import ESDLFileParser, ESDLStringParser +from mesido.esdl.profile_parser import ProfileReaderFromFile + import numpy as np from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser, ESDLStringParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile - class TestESDLParsing(unittest.TestCase): + def test_from_string_and_from_file_are_equal(self): """ This test checks if we load the model for the electrolyzer test case @@ -17,12 +18,12 @@ def test_from_string_and_from_file_are_equal(self): from using either the file or the string as input are the same. """ import models.unit_cases_electricity.electrolyzer.src.example as example - from models.unit_cases_electricity.electrolyzer.src.example import MILPProblem + from models.unit_cases_electricity.electrolyzer.src.example import MILPProblemInequality base_folder = Path(example.__file__).resolve().parent.parent solution_from_file = run_optimization_problem( - MILPProblem, + MILPProblemInequality, base_folder=base_folder, esdl_file_name="h2.esdl", esdl_parser=ESDLFileParser, @@ -34,7 +35,7 @@ def test_from_string_and_from_file_are_equal(self): esdl_string = solution_from_file.esdl_bytes_string solution_from_string = run_optimization_problem( - MILPProblem, + MILPProblemInequality, base_folder=base_folder, esdl_string=esdl_string, esdl_parser=ESDLStringParser, diff --git a/tests/test_esdl_pycml.py b/tests/test_esdl_pycml.py index 909ebb512..45db8362a 100644 --- a/tests/test_esdl_pycml.py +++ b/tests/test_esdl_pycml.py @@ -1,13 +1,13 @@ from pathlib import Path from unittest import TestCase +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile + import numpy as np from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile - class TestESDL(TestCase): def test_basic_source_and_demand_heat(self): @@ -56,3 +56,12 @@ def test_basic_source_and_demand_heat(self): # np.testing.assert_allclose( # case_python._objective_values[0], case_esdl._objective_values, rtol=1e-5, atol=1e-5 # ) + + +if __name__ == "__main__": + import time + + start_time = time.time() + a = TestESDL() + a.test_basic_source_and_demand_heat() + temp = 0 diff --git a/tests/test_gas_boiler.py b/tests/test_gas_boiler.py new file mode 100644 index 000000000..c54b09916 --- /dev/null +++ b/tests/test_gas_boiler.py @@ -0,0 +1,70 @@ +import math +from pathlib import Path +from unittest import TestCase + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization + +import numpy as np + +from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test + + +class TestGasBoiler(TestCase): + def test_gas_boiler(self): + """ + This tests checks the gas boiler for the standard checks and the energy conservation over + the commodity change. + + Checks: + 1. demand is matched + 2. energy conservation in the network + 3. heat to discharge + 4. energy conservation over the commodity + + """ + import models.source_pipe_sink.src.double_pipe_heat as example + from models.source_pipe_sink.src.double_pipe_heat import SourcePipeSink + + base_folder = Path(example.__file__).resolve().parent.parent + + heat_problem = run_esdl_mesido_optimization( + SourcePipeSink, + base_folder=base_folder, + esdl_file_name="sourcesink_withgasboiler.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_import.csv", + ) + results = heat_problem.extract_results() + parameters = heat_problem.parameters(0) + bounds = heat_problem.bounds() + + demand_matching_test(heat_problem, results) + energy_conservation_test(heat_problem, results) + heat_to_discharge_test(heat_problem, results) + + np.testing.assert_array_less(0.0, results["GasHeater_f713.Heat_source"]) + np.testing.assert_array_less(0.0, results["GasProducer_82ec.Gas_source_mass_flow"]) + np.testing.assert_array_less( + parameters["GasHeater_f713.energy_content"] + * results["GasHeater_f713.GasIn.mass_flow"] + / 1000.0, # [J/kg] * [g/s] / 1000.0 = [J/s] + results["GasHeater_f713.Heat_source"] + 1.0e-6, + ) + + # check if the maximum gas velocity set in problem is used to determine bounds on pipes + v_max_gas = heat_problem.gas_network_settings[ + "maximum_velocity" + ] # m/s maximum velocity set in problem. + np.testing.assert_allclose( + bounds["Pipe_a7b5.GasIn.Q"][1], + parameters["Pipe_a7b5.diameter"] ** 2 / 4 * math.pi * v_max_gas, + ) + + +if __name__ == "__main__": + + a = TestGasBoiler() + a.test_gas_boiler() diff --git a/tests/test_gas_multi_demand_source_node.py b/tests/test_gas_multi_demand_source_node.py index bbba051fd..7c9b340f2 100644 --- a/tests/test_gas_multi_demand_source_node.py +++ b/tests/test_gas_multi_demand_source_node.py @@ -1,13 +1,11 @@ from pathlib import Path from unittest import TestCase -import numpy as np - +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools.util import run_optimization_problem - -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np class TestMILPGasMultiDemandSourceNode(TestCase): @@ -35,7 +33,7 @@ def energy_system_options(self): self.gas_network_settings["pipe_minimum_pressure"] = 0.0 return options - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( GasProblem, base_folder=base_folder, esdl_file_name="test.esdl", diff --git a/tests/test_gas_pipe_topology_optimization.py b/tests/test_gas_pipe_topology_optimization.py index 3ba9b14a5..72b7d528b 100644 --- a/tests/test_gas_pipe_topology_optimization.py +++ b/tests/test_gas_pipe_topology_optimization.py @@ -1,13 +1,12 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.head_loss_class import HeadLossOption +import numpy as np class TestGasNetwork(TestCase): @@ -33,10 +32,10 @@ def energy_system_options(self): self.gas_network_settings["head_loss_option"] = ( HeadLossOption.LINEARIZED_ONE_LINE_EQUALITY ) - self.gas_network_settings["minimize_head_losses"] = True + self.gas_network_settings["minimize_head_losses"] = False return options - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( GasNetworkProblem, base_folder=base_folder, esdl_file_name="2a_gas.esdl", @@ -51,8 +50,8 @@ def energy_system_options(self): target = solution.get_timeseries(f"{demand}.target_gas_demand").values np.testing.assert_allclose(target, results[f"{demand}.Gas_demand_mass_flow"]) - removed_pipes = ["Pipe_a718", "Pipe_9a6f", "Pipe_2927"] - remained_pipes = ["Pipe_51e4", "Pipe_6b39", "Pipe_f9b0"] + removed_pipes = ["Pipe_a718", "Pipe_9a6f", "Pipe_2927", "Pipe_8592"] + remained_pipes = ["Pipe_51e4", "Pipe_6b39", "Pipe_f9b0", "Pipe_96bc"] for pipe in removed_pipes: np.testing.assert_allclose(results[f"{pipe}__gn_diameter"], 0.0, atol=1.0e-6) np.testing.assert_allclose(results[f"{pipe}__investment_cost"], 0.0, atol=1.0e-6) diff --git a/tests/test_gas_source_sink.py b/tests/test_gas_source_sink.py index 314ba8465..a4ab006f4 100644 --- a/tests/test_gas_source_sink.py +++ b/tests/test_gas_source_sink.py @@ -1,14 +1,12 @@ from pathlib import Path from unittest import TestCase -import numpy as np - +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.util import run_esdl_mesido_optimization -from rtctools.util import run_optimization_problem - -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.head_loss_class import HeadLossOption +import numpy as np class TestMILPGasSourceSink(TestCase): @@ -40,7 +38,7 @@ def energy_system_options(self): self.heat_network_settings["pipe_minimum_pressure"] = 0.0 return options - soltion = run_optimization_problem( + soltion = run_esdl_mesido_optimization( GasProblem, base_folder=base_folder, esdl_file_name="source_sink.esdl", diff --git a/tests/test_head_loss.py b/tests/test_head_loss.py index 25410ce69..67ba3b39d 100644 --- a/tests/test_head_loss.py +++ b/tests/test_head_loss.py @@ -1,23 +1,22 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +import mesido._darcy_weisbach as darcy_weisbach +from mesido.constants import GRAVITATIONAL_CONSTANT +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.network_common import NetworkSettings +from mesido.util import run_esdl_mesido_optimization -import rtctools_heat_network._darcy_weisbach as darcy_weisbach -from rtctools_heat_network.constants import GRAVITATIONAL_CONSTANT -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.head_loss_class import HeadLossOption -from rtctools_heat_network.network_common import NetworkSettings +import numpy as np from utils_tests import demand_matching_test class TestHeadLoss(TestCase): """ - Test case for a milp network and a gas network consisting out of a source, pipe(s) and a sink + Test case for a heat network and a gas network consisting out of a source, pipe(s) and a sink """ def test_heat_network_head_loss(self): @@ -34,6 +33,7 @@ def test_heat_network_head_loss(self): - That for the dH value approximated by the code is conservative, in other word greater than the theoretical value - That the pump power is conservative + - The water kinematic viscosity of water by comparing head loss to a hard-coded value """ import models.source_pipe_sink.src.double_pipe_heat as example from models.source_pipe_sink.src.double_pipe_heat import SourcePipeSink @@ -46,6 +46,14 @@ def test_heat_network_head_loss(self): ]: # Added for case where head loss is modelled via DW class SourcePipeSinkDW(SourcePipeSink): + # Do not delete: this is used to manualy check writing out of profile data + # def post(self): + # super().post() + # self._write_updated_esdl( + # self._ESDLMixin__energy_system_handler.energy_system, + # optimizer_sim=True, + # ) + def energy_system_options(self): options = super().energy_system_options() @@ -65,18 +73,30 @@ def energy_system_options(self): self.heat_network_settings["head_loss_option"] = ( HeadLossOption.LINEARIZED_N_LINES_EQUALITY ) - self.heat_network_settings["minimize_head_losses"] = True + self.heat_network_settings["minimize_head_losses"] = False self.heat_network_settings["minimum_velocity"] = 1.0e-6 return options - solution = run_optimization_problem( + # Do not delete kwargs: this is used to manualy check writing out of profile data + kwargs = { + "write_result_db_profiles": False, + "influxdb_host": "localhost", + "influxdb_port": 8086, + "influxdb_username": None, + "influxdb_password": None, + "influxdb_ssl": False, + "influxdb_verify_ssl": False, + } + + solution = run_esdl_mesido_optimization( SourcePipeSinkDW, base_folder=base_folder, esdl_file_name="sourcesink.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, input_timeseries_file="timeseries_import.csv", + **kwargs, ) results = solution.extract_results() @@ -150,6 +170,12 @@ def energy_system_options(self): v_inspect, pipe_diameter, pipe_length, pipe_wall_roughness, temperature ) + # Compare the head loss to hard-coded values. Difference expected if an error + # occours in the calculation of the gas kinematic viscosity. + if head_loss_option_setting == HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY: + if itime == 3: # this index was chosen randomly + np.testing.assert_allclose(dh_milp_head_loss_function, 0.001690727020401069) + np.testing.assert_allclose(dh_theory, dh_milp_head_loss_function) np.testing.assert_array_less(dh_milp_head_loss_function, dh_manual_linear) @@ -218,34 +244,66 @@ def test_heat_network_pipe_split_head_loss(self): - That only one linear line is active for the applicable pipes - That the linearized dH value is constraint is satisfied - Pipe 4 for has a zero flow rate, but its dH should be the same as pipe 2 + - Check that the minimum velocity in the longest parallel pipe (Pipe4): + - LINEARIZED_N_LINES_WEAK_INEQUALITY: pipe velo == 0.0 or == default value + - LINEARIZED_N_LINES_EQUALITY: velo > min velocity """ import models.source_pipe_split_sink.src.double_pipe_heat as example from models.source_pipe_split_sink.src.double_pipe_heat import SourcePipeSink base_folder = Path(example.__file__).resolve().parent.parent + # Keep track of the number of runs + counter_linearized_n_lines_weak_ineq_runs = 0 + counter_total_runs = 0 + # Specify the head loss linearizations to be tested for head_loss_option_setting in [ - HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY, + # Do not change the order of the items below. + HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY, # with min velo = 0.0 + HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY, # with min velo = default value HeadLossOption.LINEARIZED_N_LINES_EQUALITY, ]: + counter_total_runs += 1 + + if head_loss_option_setting == HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY: + counter_linearized_n_lines_weak_ineq_runs += 1 + # Added for case where head loss is modelled via DW class SourcePipeSinkDW(SourcePipeSink): def energy_system_options(self): options = super().energy_system_options() - nonlocal head_loss_option_setting + nonlocal head_loss_option_setting, counter_linearized_n_lines_weak_ineq_runs head_loss_option_setting = head_loss_option_setting + counter_linearized_n_lines_weak_ineq_runs = ( + counter_linearized_n_lines_weak_ineq_runs + ) self.heat_network_settings["head_loss_option"] = head_loss_option_setting self.heat_network_settings["n_linearization_lines"] = 2 - self.heat_network_settings["minimum_velocity"] = 0.0 - self.heat_network_settings["minimize_head_losses"] = True + if head_loss_option_setting == HeadLossOption.LINEARIZED_N_LINES_EQUALITY: + self.heat_network_settings["minimize_head_losses"] = False + self.heat_network_settings["minimum_velocity"] = 0.0 + options["neglect_pipe_heat_losses"] = True + elif ( + head_loss_option_setting + == HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY + ): + self.heat_network_settings["minimize_head_losses"] = True + if counter_linearized_n_lines_weak_ineq_runs == 1: + self.heat_network_settings["minimum_velocity"] = 0.0 + options["neglect_pipe_heat_losses"] = True + elif counter_linearized_n_lines_weak_ineq_runs == 2: + ... + # Do not delete. This reminds the dev that different min velo value + # with min velo = default value (>0.0), instead of specifying a value + # here return options - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( SourcePipeSinkDW, base_folder=base_folder, esdl_file_name="sourcesink.esdl", @@ -371,6 +429,44 @@ def energy_system_options(self): results["Pipe2.dH"][ii], results[f"{pipe}.dH"][ii] ) + # Check min pipe velocity + if ( + solution.heat_network_settings["head_loss_option"] + == HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY + and counter_linearized_n_lines_weak_ineq_runs == 1 + ): + np.testing.assert_allclose( + results["Pipe4.HeatIn.Q"] + / (solution.parameters(0)["Pipe4.diameter"] ** 2 / 4.0 * np.pi), + 0.0, + atol=1e-07, + ) + elif ( + solution.heat_network_settings["head_loss_option"] + == HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY + and counter_linearized_n_lines_weak_ineq_runs == 2 + ): + np.testing.assert_allclose( + results["Pipe4.HeatIn.Q"] + / (solution.parameters(0)["Pipe4.diameter"] ** 2 / 4.0 * np.pi), + 0.005, # Keep this value hard-coded to prevent future errors + ) + else: # LINEARIZED_N_LINES_EQUALITY + np.testing.assert_array_less( + solution.heat_network_settings["minimum_velocity"], + results["Pipe4.HeatIn.Q"] + / (solution.parameters(0)["Pipe4.diameter"] ** 2 / 4.0 * np.pi), + ) + # Checking that all the runs were done + if counter_total_runs not in [ + 1, + 2, + 3, + ] or counter_linearized_n_lines_weak_ineq_runs not in [0, 1, 2]: + exit("Something went wrong with the number of runs") + elif counter_total_runs == 3 and counter_linearized_n_lines_weak_ineq_runs != 2: + exit("Something went wrong with the number of runs") + def test_gas_network_head_loss(self): """ Gas network: Test the head loss approximation @@ -380,6 +476,7 @@ def test_gas_network_head_loss(self): - that the approximated head loss matches the manually calculated value - that linearized dH satisfies the specified constraint - that only one linear line segment is active for the head loss linearization + - the kinematic viscosity of natural gas by comparing head loss to a hard-coded value """ import models.unit_cases_gas.source_sink.src.run_source_sink as example @@ -415,14 +512,14 @@ def energy_system_options(self): ): self.gas_network_settings["n_linearization_lines"] = 2 self.gas_network_settings["minimize_head_losses"] = True - if head_loss_option_setting == HeadLossOption.LINEARIZED_N_LINES_EQUALITY: + elif head_loss_option_setting == HeadLossOption.LINEARIZED_N_LINES_EQUALITY: self.gas_network_settings["n_linearization_lines"] = 2 self.gas_network_settings["minimize_head_losses"] = True self.gas_network_settings["minimum_velocity"] = 0.0 return options - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( TestSourceSink, base_folder=base_folder, esdl_file_name="source_sink.esdl", @@ -451,7 +548,7 @@ def energy_system_options(self): # Approximate dH [m] vs Q [m3/s] with a linear line between between v_points # dH_manual_linear = a*Q + b # Then use this linear function to calculate the head loss - delta_dh_theory = darcy_weisbach.head_loss( + head_loss_v_point_1 = darcy_weisbach.head_loss( v_points[1], pipe_diameter, pipe_length, @@ -459,7 +556,8 @@ def energy_system_options(self): temperature, network_type=NetworkSettings.NETWORK_TYPE_GAS, pressure=solution.parameters(0)[f"{pipes[0]}.pressure"], - ) - darcy_weisbach.head_loss( + ) + delta_dh_theory = head_loss_v_point_1 - darcy_weisbach.head_loss( v_points[0], pipe_diameter, pipe_length, @@ -468,6 +566,10 @@ def energy_system_options(self): network_type=NetworkSettings.NETWORK_TYPE_GAS, pressure=solution.parameters(0)[f"{pipes[0]}.pressure"], ) + # Compare the hydraulic power to hard-coded values. Difference expected if an error + # occours in the calculation of the gas kinematic viscosity. + if head_loss_option_setting == HeadLossOption.LINEARIZED_ONE_LINE_EQUALITY: + np.testing.assert_allclose(head_loss_v_point_1, 1339.4824830351974) delta_volumetric_flow = (v_points[1] * np.pi * pipe_diameter**2 / 4.0) - ( v_points[0] * np.pi * pipe_diameter**2 / 4.0 @@ -561,7 +663,7 @@ def energy_system_options(self): if head_loss_option_setting == HeadLossOption.LINEARIZED_N_LINES_EQUALITY: # do not change in value below, see notes above self.gas_network_settings["n_linearization_lines"] = 2 - self.gas_network_settings["minimize_head_losses"] = True + self.gas_network_settings["minimize_head_losses"] = False # if statements below are currently not used, potential use in the future elif head_loss_option_setting == HeadLossOption.LINEARIZED_ONE_LINE_EQUALITY: self.gas_network_settings["minimize_head_losses"] = True @@ -574,7 +676,7 @@ def energy_system_options(self): return options - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( TestSourceSink, base_folder=base_folder, esdl_file_name="source_sink.esdl", @@ -710,7 +812,7 @@ def test_gas_substation(self): base_folder = Path(example.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( GasProblem, base_folder=base_folder, esdl_file_name="multiple_carriers.esdl", @@ -721,7 +823,58 @@ def test_gas_substation(self): results = solution.extract_results() parameters = solution.parameters(0) - assert parameters["Pipe1.pressure"] != parameters["Pipe2.pressure"] + demand_matching_test(solution, results) + + assert parameters["Pipe1.pressure"] >= parameters["Pipe2.pressure"] + + for pipe in solution.energy_system_components.get("gas_pipe", []): + dh = results[f"{pipe}.dH"] + vel = results[f"{pipe}.Q"] / (np.pi * (parameters[f"{pipe}.diameter"] / 2.0) ** 2) + for i in range(len(solution.times())): + analytical_dh = ( + vel[i] + / solution.gas_network_settings["maximum_velocity"] + * darcy_weisbach.head_loss( + solution.gas_network_settings["maximum_velocity"], + parameters[f"{pipe}.diameter"], + parameters[f"{pipe}.length"], + solution.energy_system_options()["wall_roughness"], + 20.0, + network_type=NetworkSettings.NETWORK_TYPE_GAS, + pressure=parameters[f"{pipe}.pressure"], + ) + ) + np.testing.assert_allclose(abs(dh[i]), abs(analytical_dh), atol=1.0e-6) + + def test_compressor(self): + """ + Test to check if the gas compressor increases the pressure and the head loss computation + are correctly performed at the two pressure levels. + + Checks: + - Demand matching ensuring that there is flow + - That the two pipes are at two different pressure levels + _ That the pipes have the expected head loss given their reference pressures + """ + import models.multiple_gas_carriers.src.run_multiple_gas_carriers as example + from models.multiple_gas_carriers.src.run_multiple_gas_carriers import GasProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + solution = run_esdl_mesido_optimization( + GasProblem, + base_folder=base_folder, + esdl_file_name="compressor.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + results = solution.extract_results() + parameters = solution.parameters(0) + + demand_matching_test(solution, results) + + assert parameters["Pipe1.pressure"] <= parameters["Pipe2.pressure"] for pipe in solution.energy_system_components.get("gas_pipe", []): dh = results[f"{pipe}.dH"] diff --git a/tests/test_head_loss_class.py b/tests/test_head_loss_class.py index 3c890a3d6..3f68fb7a0 100644 --- a/tests/test_head_loss_class.py +++ b/tests/test_head_loss_class.py @@ -1,13 +1,13 @@ from pathlib import Path from unittest import TestCase +from mesido.head_loss_class import HeadLossOption +from mesido.network_common import NetworkSettings + import numpy as np from rtctools.util import run_optimization_problem -from rtctools_heat_network.head_loss_class import HeadLossOption -from rtctools_heat_network.network_common import NetworkSettings - class TestHeadLossCalculation(TestCase): def test_scalar_return_type(self): diff --git a/tests/test_heat.py b/tests/test_heat.py index 899ec0011..7f076bb81 100644 --- a/tests/test_heat.py +++ b/tests/test_heat.py @@ -1,13 +1,12 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.head_loss_class import HeadLossOption +import numpy as np from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test @@ -18,7 +17,7 @@ def test_heat_loss(self): This is a test to check whether the network (pipes) are dissipating milp as we expect. Checks: - - Check that the produced milp is strictly higher than the consumed milp + - Check that the produced heat is strictly higher than the consumed heat - Check for energy conservation in the network """ @@ -27,7 +26,7 @@ def test_heat_loss(self): base_folder = Path(double_pipe_heat.__file__).resolve().parent.parent - case = run_optimization_problem( + case = run_esdl_mesido_optimization( SourcePipeSink, base_folder=base_folder, esdl_file_name="sourcesink.esdl", @@ -50,11 +49,11 @@ def test_heat_loss(self): def test_zero_heat_loss(self): """ - Check the optimiziation function when the zero milp loss is used. + Check the optimiziation function when the zero heat loss is used. Checks: - Should check that produced equals consumed. - - Should check the milp loss variable being zero + - Should check the heat loss variable being zero """ import models.source_pipe_sink.src.double_pipe_heat as double_pipe_heat @@ -69,7 +68,7 @@ def energy_system_options(self): base_folder = Path(double_pipe_heat.__file__).resolve().parent.parent - case = run_optimization_problem( + case = run_esdl_mesido_optimization( Model, base_folder=base_folder, esdl_file_name="sourcesink.esdl", @@ -95,7 +94,7 @@ class TestMinMaxPressureOptions(TestCase): from models.source_pipe_sink.src.double_pipe_heat import SourcePipeSink base_folder = Path(double_pipe_heat.__file__).resolve().parent.parent - min_pressure = 4.0 + min_pressure = 5.0 max_pressure = 12.0 esdl_file = "sourcesink.esdl" input_time_series_file = "timeseries_import.csv" @@ -160,7 +159,7 @@ def test_min_max_pressure_options(self): - max pressure """ - case_default = run_optimization_problem( + case_default = run_esdl_mesido_optimization( self.SmallerPipes, base_folder=self.base_folder, esdl_file_name=self.esdl_file, @@ -168,7 +167,7 @@ def test_min_max_pressure_options(self): profile_reader=ProfileReaderFromFile, input_timeseries_file=self.input_time_series_file, ) - case_min_pressure = run_optimization_problem( + case_min_pressure = run_esdl_mesido_optimization( self.MinPressure, base_folder=self.base_folder, esdl_file_name=self.esdl_file, @@ -176,7 +175,7 @@ def test_min_max_pressure_options(self): profile_reader=ProfileReaderFromFile, input_timeseries_file=self.input_time_series_file, ) - case_max_pressure = run_optimization_problem( + case_max_pressure = run_esdl_mesido_optimization( self.MaxPressure, base_folder=self.base_folder, esdl_file_name=self.esdl_file, @@ -184,7 +183,7 @@ def test_min_max_pressure_options(self): profile_reader=ProfileReaderFromFile, input_timeseries_file=self.input_time_series_file, ) - case_min_max_pressure = run_optimization_problem( + case_min_max_pressure = run_esdl_mesido_optimization( self.MinMaxPressure, base_folder=self.base_folder, esdl_file_name=self.esdl_file, @@ -241,7 +240,7 @@ class TestDisconnectablePipe(TestCase): class ModelConnected(SourcePipeSink): # We allow the pipe to be disconnectable. We need to be sure that - # the solution is still feasible (source delivering no milp), so we + # the solution is still feasible (source delivering no heat), so we # lower the lower bound. def parameters(self, ensemble_member): @@ -293,7 +292,7 @@ def test_disconnected_network_pipe(self): - Check that pipe becomes disconnected when flow is forced to zero """ - case_connected = run_optimization_problem( + case_connected = run_esdl_mesido_optimization( self.ModelConnected, base_folder=self.base_folder, esdl_file_name="sourcesink.esdl", @@ -304,7 +303,7 @@ def test_disconnected_network_pipe(self): results_connected = case_connected.extract_results() q_connected = results_connected["Pipe1.Q"] - case_disconnected = run_optimization_problem( + case_disconnected = run_esdl_mesido_optimization( self.ModelDisconnected, base_folder=self.base_folder, esdl_file_name="sourcesink.esdl", @@ -346,7 +345,7 @@ def test_disconnected_pipe_darcy_weisbach(self): """ - case_linear = run_optimization_problem( + case_linear = run_esdl_mesido_optimization( self.ModelDisconnected, base_folder=self.base_folder, esdl_file_name="sourcesink.esdl", @@ -357,7 +356,7 @@ def test_disconnected_pipe_darcy_weisbach(self): results_linear = case_linear.extract_results() q_linear = results_linear["Pipe1.Q"] - case_dw = run_optimization_problem( + case_dw = run_esdl_mesido_optimization( self.ModelDisconnectedDarcyWeisbach, base_folder=self.base_folder, esdl_file_name="sourcesink.esdl", @@ -372,3 +371,9 @@ def test_disconnected_pipe_darcy_weisbach(self): # (loss) in the system, we expect equal results. np.testing.assert_allclose(q_linear, q_dw) np.testing.assert_allclose(results_dw["Pipe1__is_disconnected"][1], 1.0) + + +if __name__ == "__main__": + + a = TestHeat() + a.test_heat_loss() diff --git a/tests/test_heat_loss_u_values.py b/tests/test_heat_loss_u_values.py index 04b1fa4dc..45f4add4d 100644 --- a/tests/test_heat_loss_u_values.py +++ b/tests/test_heat_loss_u_values.py @@ -1,8 +1,8 @@ from unittest import TestCase -import numpy as np +from mesido._heat_loss_u_values_pipe import heat_loss_u_values_pipe -from rtctools_heat_network._heat_loss_u_values_pipe import heat_loss_u_values_pipe +import numpy as np class TestHeatLossUValues(TestCase): diff --git a/tests/test_hydraulic_power.py b/tests/test_hydraulic_power.py index 57ef5b1b3..9239039b0 100644 --- a/tests/test_hydraulic_power.py +++ b/tests/test_hydraulic_power.py @@ -1,19 +1,23 @@ from pathlib import Path from unittest import TestCase +from mesido._darcy_weisbach import head_loss +from mesido.constants import GRAVITATIONAL_CONSTANT +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.network_common import NetworkSettings +from mesido.util import run_esdl_mesido_optimization + import numpy as np import pandas as pd -from rtctools.util import run_optimization_problem - -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.head_loss_class import HeadLossOption +from utils_tests import demand_matching_test class TestHydraulicPower(TestCase): - def test_hydraulic_power(self): + def test_hydraulic_power_heat(self): """ Check the workings for the hydraulic power variable. @@ -100,7 +104,7 @@ def test_hydraulic_power(self): run_hydraulic_power.manual_set_pipe_length = run_hydraulic_power.comp_vars_vals[ "pipe_length" ][val] - run_optimization_problem( + run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="test_simple.esdl", @@ -143,7 +147,7 @@ def test_hydraulic_power(self): run_hydraulic_power.manual_set_pipe_length = run_hydraulic_power.comp_vars_vals[ "pipe_length" ][val] - run_optimization_problem( + run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="test_simple.esdl", @@ -194,7 +198,7 @@ def test_hydraulic_power(self): run_hydraulic_power.manual_set_pipe_length = run_hydraulic_power.comp_vars_vals[ "pipe_length" ][val] - run_optimization_problem( + run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="test_simple.esdl", @@ -237,11 +241,322 @@ def test_hydraulic_power(self): atol=10.0, ) + def test_hydraulic_power_gas(self): + """ + Checks the logic for the hydraulic power of gas pipes. + - checks if value on linearized lines, for multiple lines + - checks if hydraulic power is 0 at end of the pipe + - checks if differences of in/out port is equal to the added hydraulic power of that pipe + - checks absolutae value of the hydraulic power loss over a line + - demand matching + """ + import models.unit_cases_gas.source_sink.src.run_source_sink as run_source_sink + from models.unit_cases_gas.source_sink.src.run_source_sink import ( + GasProblem, + ) + + # Settings + base_folder = Path(run_source_sink.__file__).resolve().parent.parent + + class GasProblemHydraulic(GasProblem): + def read(self): + super().read() + + for d in self.energy_system_components["gas_demand"]: + new_timeseries = self.get_timeseries(f"{d}.target_gas_demand").values * 5e3 + self.set_timeseries(f"{d}.target_gas_demand", new_timeseries) + + def energy_system_options(self): + options = super().energy_system_options() + + self.gas_network_settings["head_loss_option"] = ( + HeadLossOption.LINEARIZED_N_LINES_EQUALITY + ) + self.gas_network_settings["n_linearization_lines"] = 3 + self.gas_network_settings["minimum_velocity"] = 0.0 + self.gas_network_settings["minimize_head_losses"] = False + + return options + + solution = run_esdl_mesido_optimization( + GasProblemHydraulic, + base_folder=base_folder, + esdl_file_name="source_sink.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + + # TODO: add check on values for hydraulic power. + results = solution.extract_results() + parameters = solution.parameters(0) + + demand_matching_test(solution, results) + + pipe = "Pipe_4abc" + pipe_hp_in = results[f"{pipe}.GasIn.Hydraulic_power"] + pipe_hp_out = results[f"{pipe}.GasOut.Hydraulic_power"] + pipe_hp = results[f"{pipe}.Hydraulic_power"] + + pipe_mass = results["Pipe_4abc.GasIn.mass_flow"] + + # due to non linearity, every timestep on new linearized line, a doubled mass flow should + # result in more than doubled hydraulic power + tol_hp = 1.0e-6 + np.testing.assert_array_less( + pipe_hp[0] * (pipe_mass[1] / pipe_mass[0]), pipe_hp[1] + tol_hp + ) + np.testing.assert_array_less( + pipe_hp[1] * (pipe_mass[2] / pipe_mass[1]), pipe_hp[2] + tol_hp + ) + + np.testing.assert_allclose(pipe_hp, pipe_hp_in - pipe_hp_out) + np.testing.assert_allclose(0, pipe_hp_out) + + # TODO: use mass flow to get calculated hydraulic power + + rho = parameters[f"{pipe}.rho"] + d = parameters[f"{pipe}.diameter"] + area = parameters[f"{pipe}.area"] + length = parameters[f"{pipe}.length"] + pressure = parameters[f"{pipe}.pressure"] + wall_roughness = solution.energy_system_options()["wall_roughness"] + v_max = solution.gas_network_settings["maximum_velocity"] + temperature = 20.0 + + v_inspect = results[f"{pipe}.GasOut.Q"] / solution.parameters(0)[f"{pipe}.area"] + + calc_hp_accurate = [ + rho + * GRAVITATIONAL_CONSTANT + * v + * area + * head_loss( + v, + d, + length, + wall_roughness, + temperature, + network_type=NetworkSettings.NETWORK_TYPE_GAS, + pressure=pressure, + ) + for v in v_inspect + ] + np.testing.assert_array_less(calc_hp_accurate, pipe_hp + tol_hp) + + v_points = [ + i * v_max / solution.gas_network_settings["n_linearization_lines"] + for i in range(solution.gas_network_settings["n_linearization_lines"] + 1) + ] + calc_hp_v_points = [ + rho + * GRAVITATIONAL_CONSTANT + * v + * area + * head_loss( + v, + d, + length, + wall_roughness, + temperature, + network_type=NetworkSettings.NETWORK_TYPE_GAS, + pressure=pressure, + ) + for v in v_points + ] + v_points_volumetric = np.asarray(v_points) * np.pi * d**2 / 4.0 + a = np.diff(calc_hp_v_points) / np.diff(v_points_volumetric) + b = calc_hp_v_points[1:] - a * v_points_volumetric[1:] + + np.testing.assert_allclose(pipe_hp[0], a[0] * results[f"{pipe}.GasOut.Q"][0] + b[0]) + np.testing.assert_allclose(pipe_hp[1], a[1] * results[f"{pipe}.GasOut.Q"][1] + b[1]) + np.testing.assert_allclose(pipe_hp[2], a[2] * results[f"{pipe}.GasOut.Q"][2] + b[2]) + + def test_hydraulic_power_gas_multi_demand(self): + """ + Checks the logic for the hydraulic power of gas pipes. + - checks if value on linearized lines, for multiple lines + - checks if hydraulic power is 0 at end of the pipe if connected to a demand + - checks if hydraulic power at start of line connected to a producers is larger than 0 + - checks if differences of in/out port is equal to the added hydraulic power of that pipe + """ + import models.unit_cases_gas.multi_demand_source_node.src.run_test as run_test + from models.unit_cases_gas.multi_demand_source_node.src.run_test import ( + GasProblem, + ) + + # Settings + base_folder = Path(run_test.__file__).resolve().parent.parent + + class GasProblemHydraulic(GasProblem): + + def read(self): + super().read() + + for d in self.energy_system_components["gas_demand"]: + new_timeseries = self.get_timeseries(f"{d}.target_gas_demand").values * 1.39 + self.set_timeseries(f"{d}.target_gas_demand", new_timeseries) + + def energy_system_options(self): + options = super().energy_system_options() + + self.gas_network_settings["head_loss_option"] = ( + HeadLossOption.LINEARIZED_N_LINES_EQUALITY + ) + self.gas_network_settings["n_linearization_lines"] = 3 + self.gas_network_settings["minimum_velocity"] = 0.0 + self.gas_network_settings["minimize_head_losses"] = False + + return options + + solution = run_esdl_mesido_optimization( + GasProblemHydraulic, + base_folder=base_folder, + esdl_file_name="test.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + + # TODO: add check on values for hydraulic power. + results = solution.extract_results() + + pipes = ["Pipe_7c53", "Pipe_f1a4", "Pipe_0e39", "Pipe_c50f"] + for pipe in pipes: + pipe_hp_in = results[f"{pipe}.GasIn.Hydraulic_power"] + pipe_hp_out = results[f"{pipe}.GasOut.Hydraulic_power"] + pipe_hp = results[f"{pipe}.Hydraulic_power"] + + pipe_mass = results[f"{pipe}.GasIn.mass_flow"] + + np.testing.assert_allclose(pipe_hp, pipe_hp_in - pipe_hp_out, atol=1e-8) + if pipe in ["Pipe_7c53", "Pipe_c50f"]: + # connected to demand, thus hydraulic_power should be 0 + np.testing.assert_allclose(0, pipe_hp_out) + + v_max = solution.gas_network_settings["maximum_velocity"] + + v_inspect = results[f"{pipe}.GasOut.Q"] / solution.parameters(0)[f"{pipe}.area"] + v_points = [ + i * v_max / solution.gas_network_settings["n_linearization_lines"] + for i in range(solution.gas_network_settings["n_linearization_lines"] + 1) + ] + + # Check hydraulic power for: + # - On the first linear line (line_index = 0), the line intercepts the y-axis at 0. So a + # simple ratio calc is used + # - On any other linear line (line_index > 0), the line does not intercept the y-axis + # at 0 anymore. But it is known that the gradient of these lines are higher than the + # gradient of the line at line_index=0, due these lines representing a non-linear + # curve. This implies that the hydraulic power on these lines will be higher than the + # hydraulic power that is exrapolated from line_index=0. Also if on line index > 0 then + # the extrapolated value will on a line will be larger. + # Notes: + # - It is ensured that for each pipe more than one line out of the linearized lines is + # used + # - Checks have been added to cater for the scenario where the a pipe has no flow at a + # specific time step + v_inspect_line_ind = [] + v_points = np.array(v_points) + for k in range(len(v_inspect)): + idx = v_points < v_inspect[k] + 1e-6 + v_inspect_line_ind.append(np.where(idx)[0][-1]) + + ind_check = 0 + for k in range(len(v_inspect) - 1): + if ( + v_inspect_line_ind[k] == v_inspect_line_ind[k + 1] + and v_inspect_line_ind[k] == 0 + ): # use simple ratio calc + if pipe_mass[k] > 0: + np.testing.assert_allclose( + pipe_hp[k] * pipe_mass[k + 1] / pipe_mass[k], pipe_hp[k + 1] + ) + elif pipe_mass[k] == 0: + np.testing.assert_array_less(0.0, pipe_hp[k + 1]) + elif pipe_mass[k] < 0: + raise RuntimeWarning("The mass flow cannot be negative for this test case") + elif ( + v_inspect_line_ind[k] == v_inspect_line_ind[k + 1] + and v_inspect_line_ind[k] > 0 + and k > 0 + ): + # use fact that the extrapolated value will be smaller than the value on the + # next line + if pipe_mass[k - 1] > 0: + np.testing.assert_array_less( + pipe_hp[k - 1] * pipe_mass[k + 1] / pipe_mass[k - 1], pipe_hp[k + 1] + ) + np.testing.assert_array_less( + pipe_hp[k - 1] * pipe_mass[k] / pipe_mass[k - 1], pipe_hp[k] + ) + elif pipe_mass[k - 1] == 0: + np.testing.assert_array_less(0.0, pipe_hp[k + 1]) + elif pipe_mass[k] < 0: + raise RuntimeWarning("The mass flow cannot be negative for this test case") + elif ( + v_inspect_line_ind[k] == v_inspect_line_ind[k + 1] + and v_inspect_line_ind[k] > 0 + and k == 0 + ): + # use fact that the extrapolated value will be larger on the same line + if pipe_mass[k] > 0: + np.testing.assert_array_less( + pipe_hp[k] * pipe_mass[k + 1] / pipe_mass[k], pipe_hp[k + 1] + ) + elif pipe_mass[k] == 0: + np.testing.assert_array_less(0.0, pipe_hp[k + 1]) + elif pipe_mass[k] < 0: + raise RuntimeWarning("The mass flow cannot be negative for this test case") + elif v_inspect_line_ind[k] < v_inspect_line_ind[k + 1]: + if pipe_mass[k] > 0: + np.testing.assert_array_less( + (pipe_hp[k]) * pipe_mass[k + 1] / pipe_mass[k], pipe_hp[k + 1] + ) + elif pipe_mass[k] == 0: + np.testing.assert_array_less(0.0, pipe_hp[k + 1]) + elif pipe_mass[k] < 0: + raise RuntimeWarning("The mass flow cannot be negative for this test case") + ind_check += 1 + else: + raise RuntimeWarning( + "For this test to succeed the flow should increase over time" + ) + np.testing.assert_array_less( + 0.5, ind_check, f"{pipe} is not checked between multiple lines" + ) + + # balance of hydraulic power + pipes_demand = ["Pipe_7c53", "Pipe_c50f"] + pipes_source = ["Pipe_0e39", "Pipe_f1a4"] + balance = np.zeros(3) + for p in pipes_demand: + balance += results[f"{p}.GasIn.Hydraulic_power"] + for p in pipes_source: + balance -= results[f"{p}.GasOut.Hydraulic_power"] + np.testing.assert_allclose(balance, 0.0, atol=1e-6) + + for node, connected_pipes in solution.energy_system_topology.gas_nodes.items(): + hydraulic_sum = 0.0 + + for i_conn, (_pipe, orientation) in connected_pipes.items(): + hydraulic_sum += results[f"{node}.GasConn[{i_conn+1}].Q"] * orientation + + np.testing.assert_allclose(hydraulic_sum, 0.0, atol=1.0e-3) + + for d in solution.energy_system_components.get("gas_demand"): + np.testing.assert_allclose(results[f"{d}.GasIn.Hydraulic_power"], 0.0) + for d in solution.energy_system_components.get("gas_source"): + np.testing.assert_array_less(0.0, results[f"{d}.GasOut.Hydraulic_power"]) + if __name__ == "__main__": import time start_time = time.time() a = TestHydraulicPower() - a.test_hydraulic_power() + # a.test_hydraulic_power_heat() + # a.test_hydraulic_power_gas() + a.test_hydraulic_power_gas_multi_demand() + print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) diff --git a/tests/test_insulation.py b/tests/test_insulation.py index 9e0dfcf8b..f1d09da89 100644 --- a/tests/test_insulation.py +++ b/tests/test_insulation.py @@ -1,12 +1,11 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np class TestInsulation(TestCase): @@ -33,10 +32,10 @@ class TestInsulation(TestCase): 4. Test in which not all LT sources are selected as Tmin of demands is not low enough --> maybe 3 and 4 can be combined --> so forinstance only LT source behind HEX is selected due to insulation of that Heating demand, but other HD can not be insulated far enough for LT - source on the primary network.(e.g. goal, minimise milp loss, does not solve the provided + source on the primary network.(e.g. goal, minimise heat loss, does not solve the provided cases) 5. Test where TCO minimised, combination of investment cost of insulation vs lower Temperature - network, thus lower milp loss (and allowing cheaper LT producers). + network, thus lower heat loss (and allowing cheaper LT producers). #TODO: add test cases 2, 2b, 3, 4 and 5 as detailed above #TODO: maybe we can make COP heatpump dependent on the chosen network temperatures """ @@ -45,23 +44,23 @@ class TestInsulation(TestCase): def test_insulation_heatdemand(self): """ Check that the best insulation class is selected when we optimize for minimal - milp production. + heat production. Checks: - That the correct insulation class is selected - Check that the other insulation classes are not selected - - Check that there is sufficient milp. + - Check that there is sufficient heat. - Check that the profile that is matched is as expected Missing: - - Energy conservation and milp to discharge (replace current check of sufficient milp) + - Energy conservation and heat to discharge (replace current check of sufficient heat) """ import models.insulation.src.run_insulation as run_insulation from models.insulation.src.run_insulation import HeatProblem base_folder = Path(run_insulation.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="Insulation.esdl", @@ -98,7 +97,7 @@ def test_insulation_heatdemand(self): other_demand_insulation_class, err_msg="Insulation B or C should not be selected for any demand", ) - # Check that the milp sources (not connected to HP) + HP secondary > demand + # Check that the heat sources (not connected to HP) + HP secondary > demand tot_src = ( results["ResidualHeatSource_6783.Heat_source"] + results["ResidualHeatSource_4539.Heat_source"] @@ -109,7 +108,7 @@ def test_insulation_heatdemand(self): results["HeatingDemand_f15e.Heat_demand"] + results["HeatingDemand_e6b3.Heat_demand"] ) / 1.0e6 np.testing.assert_array_less( - (tot_dmnd - tot_src), 0.0, err_msg="The milp source is not sufficient" + (tot_dmnd - tot_src), 0.0, err_msg="The heat source is not sufficient" ) # Check that the demand load achieved == (base demand load * insulation level scaling # factor. Insulation level "A" should be active, which is index=0 in the insulation_levels @@ -141,7 +140,7 @@ def test_insulation_heatdemand_b(self): from models.insulation.src.run_insulation import HeatProblemB base_folder = Path(run_insulation.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblemB, base_folder=base_folder, esdl_file_name="Insulation.esdl", diff --git a/tests/test_logical_links.py b/tests/test_logical_links.py new file mode 100644 index 000000000..ffd043427 --- /dev/null +++ b/tests/test_logical_links.py @@ -0,0 +1,210 @@ +from pathlib import Path +from unittest import TestCase + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization + +import numpy as np + +from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test + + +class TestLogicalLinks(TestCase): + def test_logical_links_electricity(self): + """ + This test checks if the logic implemented for logically linked energy system, Meaning an + energy system where assets are directly connected to each other without a network + (transport asset(s)) in between. + + Checks: + 1. Check that energy is conserved + + """ + import models.unit_cases_electricity.bus_networks.src.example as example + from models.unit_cases_electricity.bus_networks.src.example import ElectricityProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + problem = run_esdl_mesido_optimization( + ElectricityProblem, + esdl_file_name="Electric_bus4_logical_links.esdl", + base_folder=base_folder, + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + results = problem.extract_results() + + np.testing.assert_allclose( + results["ElectricityDemand_281a.Electricity_demand"] + + results["ElectricityDemand_e527.Electricity_demand"], + results["ElectricityProducer_17a1.Electricity_source"] + + results["ElectricityProducer_a215.Electricity_source"], + ) + + def test_logical_links_gas(self): + """ + This test checks if the logic implemented for logically linked energy system, Meaning an + energy system where assets are directly connected to each other without a network + (transport asset(s)) in between. + + Checks: + 1. Check that energy is conserved + + """ + import models.unit_cases_gas.multi_demand_source_node.src.run_test as example + from models.unit_cases_gas.multi_demand_source_node.src.run_test import GasProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + problem = run_esdl_mesido_optimization( + GasProblem, + esdl_file_name="test_logical_links.esdl", + base_folder=base_folder, + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + results = problem.extract_results() + + np.testing.assert_allclose( + results["GasDemand_47d0.Gas_demand_mass_flow"] + + results["GasDemand_7978.Gas_demand_mass_flow"], + results["GasProducer_a977.Gas_source_mass_flow"] + + results["GasProducer_3573.Gas_source_mass_flow"], + ) + + def test_logical_links_nodes(self): + """ + This test checks if the logic implemented for a partially logically linked energy system. + Meaning an energy system where assets are directly connected to each other without a network + (transport asset(s)) in between. This specific test covers the logical connection between + two nodes. + """ + + import models.unit_cases_gas.source_pipe_split_sink.src.run_source_sink as example + from models.unit_cases_gas.source_pipe_split_sink.src.run_source_sink import GasProblem + + base_folder = Path(example.__file__).resolve().parent.parent + + problem = run_esdl_mesido_optimization( + GasProblem, + esdl_file_name="split_with_logical_link.esdl", + base_folder=base_folder, + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + results = problem.extract_results() + + demand_matching_test(problem, results) + + # We check that no artificial gas in created + np.testing.assert_allclose( + results["GasProducer_0876.GasOut.Q"], results["GasDemand_a2d8.GasIn.Q"] + ) + + # We test conservaiton of flow at the nodes + for node, connected_pipes in problem.energy_system_topology.gas_nodes.items(): + discharge_sum = 0.0 + + for i_conn, (_pipe, orientation) in connected_pipes.items(): + discharge_sum += results[f"{node}.GasConn[{i_conn+1}].Q"] * orientation + np.testing.assert_allclose( + results[f"{node}.GasConn[{i_conn+1}].H"], results[f"{node}.H"], atol=1.0e-6 + ) + np.testing.assert_allclose(discharge_sum, 0.0, atol=1.0e-12) + + def test_logical_links_nodes_heat(self): + """ + This test checks if the logic implemented for a partially logically linked energy system. + Meaning an energy system where assets are directly connected to each other without a network + (transport asset(s)) in between. This specific test covers the logical connection between + two nodes in a heat network. Please note that due to the closed system constraints we need + to set the minimum velocity to zero to avoid backflow in the solution. + """ + + import models.source_pipe_split_sink.src.double_pipe_heat as example + from models.source_pipe_split_sink.src.double_pipe_heat import SourcePipeSink + + base_folder = Path(example.__file__).resolve().parent.parent + + problem = run_esdl_mesido_optimization( + SourcePipeSink, + esdl_file_name="sourcesink_with_node2node_logical_link.esdl", + base_folder=base_folder, + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_import.csv", + ) + results = problem.extract_results() + + demand_matching_test(problem, results) + energy_conservation_test(problem, results) + heat_to_discharge_test(problem, results) + + # We test conservaiton of flow at the nodes + for node, connected_pipes in problem.energy_system_topology.nodes.items(): + discharge_sum = 0.0 + + for i_conn, (_pipe, orientation) in connected_pipes.items(): + discharge_sum += results[f"{node}.HeatConn[{i_conn+1}].Q"] * orientation + np.testing.assert_allclose( + results[f"{node}.HeatConn[{i_conn+1}].H"], results[f"{node}.H"], atol=1.0e-6 + ) + np.testing.assert_allclose(discharge_sum, 0.0, atol=1.0e-12) + + def test_logical_links_network_hybrid(self): + """ + This test checks if the logic implemented for logically linked energy system, Meaning an + energy system where assets are directly connected to each other without a network + (transport asset(s)) in between. This test uses the emerge use-case and the logic is both + checked for the gas and heat commodity. + + Checks: + 1. Check that energy is conserved + + """ + import models.emerge.src.example as example + from models.emerge.src.example import EmergeTest + + base_folder = Path(example.__file__).resolve().parent.parent + + problem = run_esdl_mesido_optimization( + EmergeTest, + base_folder=base_folder, + esdl_file_name="emerge_with_logical_links.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short.csv", + ) + results = problem.extract_results() + + assert all( + results["ElectricityCable_e388.ElectricityIn.V"] + == results["Bus_24cf.ElectricityConn[3].V"] + ) + + assert ( + np.sum( + np.abs( + results["WindPark_9074.ElectricityOut.V"] + - results["Bus_24cf.ElectricityConn[3].V"] + ) + ) + != 0.0 + ) + + +if __name__ == "__main__": + import time + + start_time = time.time() + a = TestLogicalLinks() + a.test_logical_links_electricity() + a.test_logical_links_gas() + a.test_logical_links_nodes() + a.test_logical_links_nodes_heat() + a.test_logical_links_network_hybrid() + print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) diff --git a/tests/test_max_size_and_optional_assets.py b/tests/test_max_size_and_optional_assets.py index f6eb6730b..34b08ee3b 100644 --- a/tests/test_max_size_and_optional_assets.py +++ b/tests/test_max_size_and_optional_assets.py @@ -1,12 +1,11 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test @@ -25,7 +24,7 @@ def test_max_size_and_aggr_count(self): source will be placed due to the minimization of the cost (which cost is this?, I assume operational cost) and installation cost. The placement behaviour is further tested in a second case by adding an optional ates and buffer. However, these 2 additional optional - assets should not be placed by the optmizer because of milp losses. + assets should not be placed by the optmizer because of heat losses. Checks: - Check that source 1 is utilized and also placed @@ -45,7 +44,7 @@ def test_max_size_and_aggr_count(self): base_folder = Path(run_ates.__file__).resolve().parent.parent # This is an optimization done over a few days - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="test_case_small_network_with_ates_with_buffer.esdl", @@ -94,7 +93,7 @@ def test_max_size_and_aggr_count(self): ) # Test that cost only exist for 2 and not for 1. Note the tolerances - # to avoid test failing when milp losses slightly change + # to avoid test failing when heat losses slightly change np.testing.assert_allclose(var_cost_1, 0.0, atol=1e-9) np.testing.assert_allclose( var_cost_2, @@ -123,7 +122,7 @@ def test_max_size_and_aggr_count(self): rtol=1.0e-2, ) - # Since the buffer and ates are not optional they must consume some milp to compensate + # Since the buffer and ates are not optional they must consume some heat to compensate # losses as the buffer has a minimum fraction volume of 5%. # Therefore, we can check the max_size constraint. np.testing.assert_allclose( @@ -143,9 +142,9 @@ def test_max_size_and_aggr_count(self): base_folder = Path(run_ates.__file__).resolve().parent.parent # This is the same problem, but now with the buffer and ates also optional. - # Therefore, we expect that the ates and buffer are no longer placed to avoid their milp + # Therefore, we expect that the ates and buffer are no longer placed to avoid their heat # losses. This allows us to check if their placement constraints are proper. - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="test_case_small_network_with_ates_with_buffer_all_optional.esdl", diff --git a/tests/test_multicommodity.py b/tests/test_multicommodity.py index b733f7579..010537eed 100644 --- a/tests/test_multicommodity.py +++ b/tests/test_multicommodity.py @@ -1,31 +1,29 @@ from pathlib import Path from unittest import TestCase -import numpy as np - - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test class TestMultiCommodityHeatPump(TestCase): """Test to verify that the optimisation problem can handle multicommodity problems, relating - electricity and milp""" + electricity and heat""" def test_heat_pump_elec_min_heat(self): """ Verify that the minimisation of the heat_source used, and thus the optimization should - exploit the heatpump as much as possible, and minimum use of milp source at secondary + exploit the heatpump as much as possible, and minimum use of heat source at secondary side. Checks: - - Standard checks for demand matching, milp to discharge and energy conservation + - Standard checks for demand matching, heat to discharge and energy conservation - Checks for sufficient production - - Checks for milp pump energy conservation and COP modelling + - Checks for heat pump energy conservation and COP modelling - Checks for Power = I * V at the heatpump """ @@ -34,7 +32,7 @@ def test_heat_pump_elec_min_heat(self): base_folder = Path(run_hp_elec.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblem2, base_folder=base_folder, esdl_file_name="heat_pump_elec.esdl", @@ -88,14 +86,14 @@ def test_heat_pump_elec_min_heat_curr_limit(self): """ Verify the minimization of the heat_source used. However, due to limitations in the electricity transport through the cables, the power to the heatpump is limited. This in - turn limits the milp produced by the heatpump which is then not sufficient for the total - heating demand, resulting in milp production by the secondary heatsource (milp produced by + turn limits the heat produced by the heatpump which is then not sufficient for the total + heating demand, resulting in heat production by the secondary heatsource (heat produced by this asset is not 0). Checks: - - Standard checks for demand matching, milp to discharge and energy conservation + - Standard checks for demand matching, heat to discharge and energy conservation - Checks for sufficient production - - Checks for milp pump energy conservation and COP modelling + - Checks for heat pump energy conservation and COP modelling - Checks for Power = I * V at the heatpump """ @@ -104,7 +102,7 @@ def test_heat_pump_elec_min_heat_curr_limit(self): base_folder = Path(run_hp_elec.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="heat_pump_elec.esdl", @@ -160,12 +158,12 @@ def test_heat_pump_elec_min_heat_curr_limit(self): def test_heat_pump_elec_min_elec(self): """ Verify that minimisation of the electricity power used, and thus - exploiting the heatpump only for milp that cannot directly be covered by other sources. + exploiting the heatpump only for heat that cannot directly be covered by other sources. Checks: - - Standard checks for demand matching, milp to discharge and energy conservation + - Standard checks for demand matching, heat to discharge and energy conservation - Checks for sufficient production - - Checks for milp pump energy conservation and COP modelling + - Checks for heat pump energy conservation and COP modelling - Checks for Power = I * V at the heatpump """ @@ -176,7 +174,7 @@ def test_heat_pump_elec_min_elec(self): base_folder = Path(run_hp_elec.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( ElectricityProblem, base_folder=base_folder, esdl_file_name="heat_pump_elec.esdl", @@ -212,3 +210,69 @@ def test_heat_pump_elec_min_elec(self): # check that prim producer is providing more energy to heatpump and primary demand np.testing.assert_array_less(heatdemand_prim - (heatsource_prim - heatpump_heat_prim), 0) + + def test_heat_pump_elec_price_profile(self): + """ + Verify that minimisation of the electricity power used when price of electricity is high. + + Checks: + - Standard checks for demand matching, heat to discharge and energy conservation + - Check that the producer not connected to the heat pump is only used when electricity + prices of HP are high + - Check calculation of variable operational costs which include the electricity prices + + """ + import models.unit_cases_electricity.heat_pump_elec.src.run_hp_elec as run_hp_elec + from models.unit_cases_electricity.heat_pump_elec.src.run_hp_elec import ( + ElectricityProblemPriceProfile, + ) + + base_folder = Path(run_hp_elec.__file__).resolve().parent.parent + + class TestProblem(ElectricityProblemPriceProfile): + def solver_options(self): + options = super().solver_options() + # For some reason the test requires cbc, highs fails for strange reasons + options["solver"] = "cbc" + return options + + solution = run_esdl_mesido_optimization( + TestProblem, + base_folder=base_folder, + esdl_file_name="heat_pump_elec_priceprofile.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_elec.csv", + ) + + results = solution.extract_results() + + demand_matching_test(solution, results) + energy_conservation_test(solution, results) + heat_to_discharge_test(solution, results) + + heatpump_power = results["GenericConversion_3d3f.Power_elec"] + heatpump_heat_sec = results["GenericConversion_3d3f.Secondary_heat"] + heatpump_disabled = results["GenericConversion_3d3f__disabled"] + heatdemand_sec = results["HeatingDemand_18aa.Heat_demand"] + var_opex_hp = results["GenericConversion_3d3f__variable_operational_cost"] + # pipe_sec_out_hp_disconnected = results["Pipe_408e__is_disconnected"] + + # check that heatpump is not used when electricity price is high: + price_profile = solution.get_timeseries("Electr.price_profile").values + price_profile_max = price_profile == max(price_profile) + self.assertTrue(all(price_profile_max >= heatpump_disabled)) + self.assertTrue(all(price_profile_max[1:] * heatpump_power[1:] == 0)) + + # check that heatpump is producing all heat for the heatdemand on the secondary side when + # electricity price is low + ind_hp = np.asarray(1 - price_profile_max).nonzero() + np.testing.assert_allclose(heatpump_heat_sec[ind_hp], heatdemand_sec[ind_hp]) + + # check variable_operational_cost for heat pump including the price_profile of electricity + var_opex_hp_non_el = 1e-6 # var_opex in ESDL for HP + timestep = 1.0 # hr + var_opex_hp_calc = sum( + (price_profile[1:] + var_opex_hp_non_el) * heatpump_power[1:] * timestep + ) + np.testing.assert_allclose(var_opex_hp_calc, var_opex_hp) diff --git a/tests/test_multicommodity_simulator.py b/tests/test_multicommodity_simulator.py new file mode 100644 index 000000000..f9b5437cc --- /dev/null +++ b/tests/test_multicommodity_simulator.py @@ -0,0 +1,699 @@ +from pathlib import Path +from unittest import TestCase + +import mesido._darcy_weisbach as darcy_weisbach +from mesido.electricity_physics_mixin import ElectrolyzerOption +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.network_common import NetworkSettings +from mesido.workflows.multicommodity_simulator_workflow import ( + MultiCommoditySimulator, + MultiCommoditySimulatorNoLosses, + run_sequatially_staged_simulation, +) + +import numpy as np + +from rtctools.util import run_optimization_problem + +from utils_test_scaling import create_problem_with_debug_info, problem_scaling_check + +from utils_tests import ( + demand_matching_test, + electric_power_conservation_test, + energy_conservation_test, + feasibility_test, +) + + +def check_electrolyzer_efficiency(tol, electrolyzer_gas, electrolyzer_power, esdl_electrolyzer): + efficiency = electrolyzer_power / electrolyzer_gas # W/(g/s) = Ws/g + efficiency = efficiency / 3600 # Wh/g + provided_efficiencies = ( + esdl_electrolyzer.attributes["effMaxLoad"], + esdl_electrolyzer.attributes["effMinLoad"], + esdl_electrolyzer.attributes["efficiency"], + ) + np.testing.assert_array_less(min(provided_efficiencies), efficiency[electrolyzer_power > 1]) + np.testing.assert_array_less( + efficiency[electrolyzer_power > 0], max(provided_efficiencies) + tol + ) + + +def checks_all_mc_simulations(solution, results): + # General checks + demand_matching_test(solution, results) + energy_conservation_test(solution, results) + + for prod in solution.energy_system_components.get("electricity_source", []): + prod_profile_name = f"{prod}.maximum_electricity_source" + energy_prod = results[f"{prod}.Electricity_source"] + if prod_profile_name in solution.io.get_timeseries_names(): + target = solution.get_timeseries(prod_profile_name).values[: len(energy_prod)] + np.testing.assert_allclose(target, energy_prod, atol=1.0e-3, rtol=1.0e-6) + # print(prod, energy_prod) + + for demand in solution.energy_system_components.get("electricity_demand", []): + energy_demand = results[f"{demand}.Electricity_demand"] + if f"{demand}.target_electricity_demand" in solution.io.get_timeseries_names(): + target = solution.get_timeseries(f"{demand}.target_electricity_demand").values + np.testing.assert_allclose(target, energy_demand, atol=1.0e-3, rtol=1.0e-6) + # print(demand, target, energy_demand) + # else: + # print(demand, energy_demand) + + for demand in solution.energy_system_components.get("gas_demand", []): + energy_demand = results[f"{demand}.Gas_demand_mass_flow"] + if f"{demand}.target_gas_demand" in solution.io.get_timeseries_names(): + target = solution.get_timeseries(f"{demand}.target_gas_demand").values + np.testing.assert_allclose(target, energy_demand, atol=1.0e-3, rtol=1.0e-6) + # print(demand, target, energy_demand) + # else: + # print(demand, energy_demand) + + +class TestMultiCommoditySimulator(TestCase): + # TODO: update docstring + """ + In this test case several producers and consumers as well as conversion assets are applied, for + the two commodities Hydrogen and electricity. + The priority of the consumers, producers and conversion assets is set using the marginal costs + in the ESDL file, allowing for flexible customised operation. + + Checks: + - General checks namely demand matching, energy conservation and asset milp variable vs + calculated milp (based on flow rate) + - Check that producer 1 (merit oder = 2) is only used for the supply of milp lossed in the + connected and is does not contribute to the heating demands 1, 2 and 3 + - Check that the ATES is not delivering any milp to the network during the 1st time step + """ + + def test_multi_commodity_simulator_priorities_el(self): + import models.unit_cases_electricity.bus_networks.src.example as example + + base_folder = Path(example.__file__).resolve().parent.parent + + multicommoditysimulatorscaling, logger, logs_list = create_problem_with_debug_info( + MultiCommoditySimulator + ) + + solution = run_optimization_problem( + multicommoditysimulatorscaling, + base_folder=base_folder, + esdl_file_name="Electric_bus4_priorities.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_2.csv", + ) + + problem_scaling_check(logs_list, logger) + bounds = solution.bounds() + results = solution.extract_results() + + checks_all_mc_simulations(solution, results) + + prod_1 = results["ElectricityProducer_a215.Electricity_source"] + prod_2 = results["ElectricityProducer_17a1.Electricity_source"] + dem_1 = results["ElectricityDemand_e527.Electricity_demand"] + dem_2 = results["ElectricityDemand_281a.Electricity_demand"] + + # check producer with highest priority (lowest marginal costs is maximizing production) + np.testing.assert_allclose( + prod_1, bounds["ElectricityProducer_a215.Electricity_source"][1], atol=1e-3, rtol=1e-6 + ) + # check producer with second highest priority is only producing to meet profile of demand + prod_2_target = dem_1 - prod_1 + prod_2_target[prod_2_target < 0] = 0 + np.testing.assert_allclose(prod_2, prod_2_target, atol=1e-3, rtol=1e-6) + # check demand with lowest marginal cost is only consuming if electricity left from producer + # with highest priority after the matching of demand profile + demand_2_target = prod_1 - dem_1 + demand_2_target[demand_2_target < 0] = 0 + np.testing.assert_allclose(dem_2, demand_2_target, atol=1e-3, rtol=1e-6) + + def test_multi_commodity_simulator_prod_profile(self): + import models.unit_cases_electricity.bus_networks.src.example as example + + base_folder = Path(example.__file__).resolve().parent.parent + + solution = run_optimization_problem( + MultiCommoditySimulator, + base_folder=base_folder, + esdl_file_name="Electric_bus4_priorities.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_2_prod.csv", + ) + + bounds = solution.bounds() + results = solution.extract_results() + + checks_all_mc_simulations(solution, results) + + prod_1 = results["ElectricityProducer_a215.Electricity_source"] + prod_2 = results["ElectricityProducer_17a1.Electricity_source"] + dem_1 = results["ElectricityDemand_e527.Electricity_demand"] + dem_2 = results["ElectricityDemand_281a.Electricity_demand"] + + # check producer with highest priority (lowest marginal costs is maximizing production) is + # producing at max capacity, except when demand profile + max demand of other demand is + # lower than prod_2 profile and max capacity prod_1 + np.testing.assert_allclose( + prod_1[1:], + bounds["ElectricityProducer_a215.Electricity_source"][1], + atol=1e-3, + rtol=1e-6, + ) + np.testing.assert_allclose( + prod_1[0], + bounds["ElectricityDemand_281a.Electricity_demand"][1] + dem_1[0] - prod_2[0], + atol=1e-3, + rtol=1e-6, + ) + + # check demand with lowest marginal cost is only consuming if electricity left from producer + # with highest priority and producer with profile, after the matching of demand profile + demand_2_target = prod_1 + prod_2 - dem_1 + demand_2_target[demand_2_target < 0] = 0 + np.testing.assert_allclose(dem_2, demand_2_target, atol=1e-3, rtol=1e-6) + + # Check that producer 1 (merit oder = 2) is not used + # and is does not contribute to the heating demands 1, 2 and 3 + # TODO: these tests need to be updated for elec/gas + + import models.unit_cases_gas.multi_demand_source_node.src.run_test as example + + base_folder = Path(example.__file__).resolve().parent.parent + + solution = run_optimization_problem( + MultiCommoditySimulator, + base_folder=base_folder, + esdl_file_name="test_priorities.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries.csv", + ) + + results = solution.extract_results() + bounds = solution.bounds() + + checks_all_mc_simulations(solution, results) + + prod_1 = results["GasProducer_3573.Gas_source_mass_flow"] + prod_2 = results["GasProducer_a977.Gas_source_mass_flow"] + dem_1 = results["GasDemand_47d0.Gas_demand_mass_flow"] + dem_2 = results["GasDemand_7979.Gas_demand_mass_flow"] + prod_1_bound = bounds["GasProducer_3573.Gas_source_mass_flow"][1] + dem_2_bound = bounds["GasDemand_7979.Gas_demand_mass_flow"] + + # check producer with highest marginal cost (prod_2) is only producing to match demand + # profile of dem_1 + the max of dem_2, + # check producer_1 is maxed out + prod_2_target = dem_1 + dem_2 - prod_1 + prod_2_target[prod_2_target < 0] = 0 + np.testing.assert_allclose(prod_2, prod_2_target, atol=1e-3, rtol=1e-6) + np.testing.assert_allclose(prod_1, prod_1_bound) + + # check demand 1 is matching the profile (in check_all_mc_simulations) and that demand 2 + # is maxed out + checks_all_mc_simulations(solution, results) + np.testing.assert_allclose(dem_2, dem_2_bound[1], atol=1e-3, rtol=1e-6) + + def test_multi_commodity_simulator_emerge(self): + import models.emerge.src.example as example + + base_folder = Path(example.__file__).resolve().parent.parent + + solution = run_optimization_problem( + MultiCommoditySimulatorNoLosses, + base_folder=base_folder, + esdl_file_name="emerge_priorities_withoutstorage.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short.csv", + ) + + bounds = solution.bounds() + results = solution.extract_results() + + # all_mc_checks cannot be used because max electricity production of windfarm is larger + # than the max electricity take off at electrolyzer (due to mas gas demand) and the max + # electricity demand. + # checks_all_mc_simulations(solution, results) + tol = 1.0e-6 + + esdl_electrolyzer = solution._esdl_assets[ + solution.esdl_asset_name_to_id_map["Electrolyzer_6327"] + ] + demand_gas = results["GasDemand_4146.Gas_demand_mass_flow"] + demand_el = results["ElectricityDemand_f833.Electricity_demand"] + electrolyzer_power = results["Electrolyzer_6327.Power_consumed"] + electrolyzer_gas = results["Electrolyzer_6327.Gas_mass_flow_out"] + windfarm_power = results["WindPark_9074.Electricity_source"] + windfarm_target = solution.get_timeseries( + "WindPark_9074.maximum_electricity_source" + ).values[: len(windfarm_power)] + # cap on el consumption by electricity_demand (due to cap, 1.3GW) and by electrolyzer + # (due to cap of gas demand) + cap_el_consumption = 2.1e9 + windfarm_target = np.minimum( + np.ones(len(windfarm_target)) * cap_el_consumption, windfarm_target + ) + np.testing.assert_allclose(windfarm_target, windfarm_power, atol=1.0e-3, rtol=tol) + + check_electrolyzer_efficiency(tol, electrolyzer_gas, electrolyzer_power, esdl_electrolyzer) + + # demand gas maximised when sufficient power available to convert electricity to gas + cap_electrolyzer_power = ( + cap_el_consumption - bounds["ElectricityDemand_f833.Electricity_demand"][1] + ) + index_gas_max = windfarm_power >= cap_electrolyzer_power + np.testing.assert_allclose( + demand_gas[index_gas_max], bounds["Electrolyzer_6327.Gas_mass_flow_out"][1] + ) + # due to priority settings, electricity demand only consuming if demand_gas maximised and + # enough windfarm power + demand_el_calc = windfarm_power - electrolyzer_power + demand_el_calc[demand_el_calc < 0] = 0 + np.testing.assert_allclose(demand_el_calc, demand_el, atol=1.0e-3) + + def test_multi_commodity_simulator_emerge_lowprod(self): + import models.emerge.src.example as example + + base_folder = Path(example.__file__).resolve().parent.parent + + class MCSimulatorShortSmallProd(MultiCommoditySimulatorNoLosses): + + def read(self, variable=None): + super().read() + + for asset in self.energy_system_components["wind_park"]: + new_timeseries = ( + self.get_timeseries(f"{asset}.maximum_electricity_source").values * 0.5 + ) + self.set_timeseries(f"{asset}.maximum_electricity_source", new_timeseries) + + def energy_system_options(self): + options = super().energy_system_options() + + options["electrolyzer_efficiency"] = ( + ElectrolyzerOption.LINEARIZED_THREE_LINES_WEAK_INEQUALITY + ) + + return options + + solution = run_optimization_problem( + MCSimulatorShortSmallProd, + base_folder=base_folder, + esdl_file_name="emerge_priorities_withoutstorage_2prod.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short.csv", + ) + + results = solution.extract_results() + bounds = solution.bounds() + + tol = 1.0e-6 + + checks_all_mc_simulations(solution, results) + + esdl_electrolyzer = solution._esdl_assets[ + solution.esdl_asset_name_to_id_map["Electrolyzer_6327"] + ] + demand_gas = results["GasDemand_4146.Gas_demand_mass_flow"] + demand_el = results["ElectricityDemand_f833.Electricity_demand"] + electrolyzer_power = results["Electrolyzer_6327.Power_consumed"] + electrolyzer_gas = results["Electrolyzer_6327.Gas_mass_flow_out"] + windfarm_power = results["WindPark_9074.Electricity_source"] + prod_power = results["ElectricityProducer_4850.Electricity_source"] + prod_power_cap = 3e8 # W + + check_electrolyzer_efficiency(tol, electrolyzer_gas, electrolyzer_power, esdl_electrolyzer) + + # demand gas maximised when sufficient power available to convert electricity to gas + cap_electrolyzer_power = 444880000.0 + index_gas_max = windfarm_power >= cap_electrolyzer_power + np.testing.assert_allclose( + demand_gas[index_gas_max], bounds["Electrolyzer_6327.Gas_mass_flow_out"][1] + ) + # due to priority settings, electricity demand only consuming if demand_gas maximised and + # enough windfarm power + demand_el_calc = windfarm_power - electrolyzer_power + demand_el_calc[demand_el_calc < 0] = 0 + np.testing.assert_allclose(demand_el_calc, demand_el, atol=1e-5 * max(demand_el)) + # electricity_producer only producing upto its own cap if windfarm_power is insufficient to + # fullfill demand_gas + el_prod_calc = np.maximum( + np.minimum(max(electrolyzer_power) - windfarm_power, prod_power_cap), 0.0 + ) + np.testing.assert_allclose(el_prod_calc, prod_power, atol=1e-5 * max(demand_el)) + + def test_multi_commodity_simulator_emerge_storage(self): + """ + Test to run the multicommodity simulator including a gas_storage. + Checks: + - feasibility + - power conservation + - efficiency of electrolyzer + - gas mass balance + - gas storage charges when additional production of hydrogen is possible and discharges + when no production is possible. + """ + + import models.emerge.src.example as example + + base_folder = Path(example.__file__).resolve().parent.parent + + solution = run_optimization_problem( + MultiCommoditySimulatorNoLosses, + base_folder=base_folder, + esdl_file_name="emerge_priorities.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short.csv", + ) + + results = solution.extract_results() + + feasibility_test(solution) + electric_power_conservation_test(solution, results) + + # checks_all_mc_simulations(solution, results) + tol = 1.0e-6 + + esdl_electrolyzer = solution._esdl_assets[ + solution.esdl_asset_name_to_id_map["Electrolyzer_6327"] + ] + demand_gas = results["GasDemand_4146.Gas_demand_mass_flow"] + electrolyzer_power = results["Electrolyzer_6327.Power_consumed"] + electrolyzer_gas = results["Electrolyzer_6327.Gas_mass_flow_out"] + storage_gas_mass_flow = results["GasStorage_9172.Gas_tank_flow"] + + check_electrolyzer_efficiency(tol, electrolyzer_gas, electrolyzer_power, esdl_electrolyzer) + + # gas mass balance including storage + np.testing.assert_allclose( + electrolyzer_gas - storage_gas_mass_flow, demand_gas, rtol=tol, atol=tol + ) + # timestep 7 & 8 electrolyzer should be producing more hydrogen then the demand can take. + # gas_demand is limited by pipe size. + # storage is not charging if gas demand is not maximised at bound + # storage is charging if electrolyzer produces more gas than max of demand. + gas_demand_bound = solution.bounds()["GasDemand_4146.Gas_demand_mass_flow"] + storage_not_charging = demand_gas != gas_demand_bound[1] + np.testing.assert_array_less(storage_gas_mass_flow[storage_not_charging], 0.0 + tol) + storage_charging = electrolyzer_gas >= gas_demand_bound[1] + np.testing.assert_array_less(0.0 - tol, storage_gas_mass_flow[storage_charging]) + + def test_multi_commodity_simulator_emerge_battery(self): + """ + Test to run the multicommodity simulator including a battery and gas storage. + Checks: + - matching of profiles consumer and producers (checks_all_mc_simulations) + - feasibility + - power conservation + - efficiency of electrolyzer + - gas mass balance + - battery charges when over production of electricity and discharges when not enough + electrical power is produced for the electrolyzer. + - gas storage is not charged/discharged due to priority level. + """ + import models.emerge.src.example as example + + base_folder = Path(example.__file__).resolve().parent.parent + + multicommoditysimulatornolossesscaling, logger, logs_list = create_problem_with_debug_info( + MultiCommoditySimulatorNoLosses + ) + + solution = run_optimization_problem( + multicommoditysimulatornolossesscaling, + base_folder=base_folder, + esdl_file_name="emerge_battery_priorities.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short.csv", + ) + problem_scaling_check(logs_list, logger, order_diff=1e7) + results = solution.extract_results() + + feasibility_test(solution) + electric_power_conservation_test(solution, results) + + checks_all_mc_simulations(solution, results) + tol = 1.0e-6 + + esdl_electrolyzer = solution._esdl_assets[ + solution.esdl_asset_name_to_id_map["Electrolyzer_6327"] + ] + demand_gas = results["GasDemand_4146.Gas_demand_mass_flow"] + electrolyzer_power = results["Electrolyzer_6327.Power_consumed"] + electrolyzer_power_bound = solution.bounds()["Electrolyzer_6327.Power_consumed"][1] + electrolyzer_gas = results["Electrolyzer_6327.Gas_mass_flow_out"] + windfarm_power = results["WindPark_9074.Electricity_source"] + storage_gas_mass_flow = results["GasStorage_9172.Gas_tank_flow"] + battery_power = results["Battery_4688.ElectricityIn.Power"] + + check_electrolyzer_efficiency(tol, electrolyzer_gas, electrolyzer_power, esdl_electrolyzer) + + # gas mass balance including storage + np.testing.assert_allclose( + electrolyzer_gas - storage_gas_mass_flow, demand_gas, rtol=tol, atol=tol + ) + + # check battery only discharged if not enough windpower for electrolyzer + discharge_battery = windfarm_power < electrolyzer_power_bound + np.testing.assert_array_less(battery_power[discharge_battery], 0.0 + tol) + charge_battery = windfarm_power > electrolyzer_power_bound + np.testing.assert_array_less(0.0, battery_power[charge_battery]) + + # gas_storage not used due to low priority + np.testing.assert_allclose(storage_gas_mass_flow[1:], 0.0, atol=tol) + + def test_multi_commodity_simulator_emerge_head_losses(self): + """ + Test to run the multicommodity simulator including a battery and gas storage. + Checks: + - feasibility + - power conservation + - efficiency of electrolyzer + - gas mass balance + - battery charges when over production of electricity and discharges when not enough + electrical power is produced for the electrolyzer. + - gas storage is not charged/discharged due to priority level. + """ + import models.emerge.src.example as example + + base_folder = Path(example.__file__).resolve().parent.parent + + solution = run_optimization_problem( + MultiCommoditySimulator, + base_folder=base_folder, + esdl_file_name="emerge_battery_priorities.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short_2.csv", + ) + + results = solution.extract_results() + parameters = solution.parameters(0) + + feasibility_test(solution) + electric_power_conservation_test(solution, results) + + checks_all_mc_simulations(solution, results) + tol = 1.0e-6 + + esdl_electrolyzer = solution._esdl_assets[ + solution.esdl_asset_name_to_id_map["Electrolyzer_6327"] + ] + demand_gas = results["GasDemand_4146.Gas_demand_mass_flow"] + electrolyzer_power = results["Electrolyzer_6327.Power_consumed"] + electrolyzer_power_bound = solution.bounds()["Electrolyzer_6327.Power_consumed"][1] + electrolyzer_gas = results["Electrolyzer_6327.Gas_mass_flow_out"] + windfarm_power = results["WindPark_9074.Electricity_source"] + storage_gas_mass_flow = results["GasStorage_9172.Gas_tank_flow"] + battery_power = results["Battery_4688.ElectricityIn.Power"] + + check_electrolyzer_efficiency(tol, electrolyzer_gas, electrolyzer_power, esdl_electrolyzer) + + # gas mass balance including storage + np.testing.assert_allclose( + electrolyzer_gas - storage_gas_mass_flow, demand_gas, rtol=tol, atol=tol + ) + + # check battery only discharged if not enough windpower for electrolyzer + discharge_battery = windfarm_power < electrolyzer_power_bound + np.testing.assert_array_less(battery_power[discharge_battery], 1.0) + charge_battery = windfarm_power > electrolyzer_power_bound + np.testing.assert_array_less(0.0, battery_power[charge_battery]) + + # gas_storage not used due to low priority + np.testing.assert_allclose(storage_gas_mass_flow[1:], 0.0, atol=tol) + + # linearized dw_headloss calculations + linear_lines = 5 + v_max = solution.gas_network_settings["maximum_velocity"] + velocities = np.linspace(0, v_max, linear_lines + 1) + + for pipe in solution.energy_system_components.get("gas_pipe"): + length = parameters[f"{pipe}.length"] + diameter = parameters[f"{pipe}.diameter"] + vol_flow_rate = results[f"{pipe}.GasIn.Q"] + v_pipe = vol_flow_rate / (3.14 * (diameter / 2) ** 2) + wall_roughness = solution.energy_system_options()["wall_roughness"] + head_loss = results[f"{pipe}.dH"] + head_loss_full_var = results[f"{pipe}.__head_loss"] + # If this test fails there is most likely a scaling issue. + indexes = np.abs(v_pipe) > 1e-11 + indexes[0] = False + np.testing.assert_allclose( + np.abs(np.asarray(head_loss[indexes])), head_loss_full_var[indexes] + ) + for i in range(1, len(v_pipe)): + v = v_pipe[i] + line_num = velocities.searchsorted(abs(v)) + if abs(v) > 1e-8: + dw_headloss_max = darcy_weisbach.head_loss( + velocities[line_num], + diameter, + length, + wall_roughness, + 20, + NetworkSettings.NETWORK_TYPE_HYDROGEN, + 15e5, + ) + dw_headloss_min = darcy_weisbach.head_loss( + velocities[line_num - 1], + diameter, + length, + wall_roughness, + 20, + NetworkSettings.NETWORK_TYPE_HYDROGEN, + 15e5, + ) + a = (dw_headloss_max - dw_headloss_min) / ( + velocities[line_num] - velocities[line_num - 1] + ) + b = dw_headloss_min - a * velocities[line_num - 1] + headloss_calc = a * v + b + np.testing.assert_allclose(abs(head_loss[i]), headloss_calc, 0.1) + + def test_multi_commodity_simulator_sequential_staged(self): + """ + Test to run the multicommodity simulator including a battery and gas storage using + the sequential staged optimization approach. The results between the staged and unstaaged + approach should be equal if the assets in the system do not have an internal state that + makes timesteps interdependent (like Stored_energy for a battery) or when the bounds on + those states do not limit the problem. + + Checks: + - that the staged approach results in same values as the unstaged approach. + - Verify that under limited case bounds are set correctly. + """ + import models.emerge.src.example as example + + base_folder = Path(example.__file__).resolve().parent.parent + + solution_staged_unbounded = run_sequatially_staged_simulation( + multi_commodity_simulator_class=MultiCommoditySimulatorNoLosses, + simulation_window_size=20, + base_folder=base_folder, + esdl_file_name="emerge_battery_priorities.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short.csv", + ) + + results_staged = solution_staged_unbounded.results + + solution_unstaged = run_optimization_problem( + MultiCommoditySimulatorNoLosses, + base_folder=base_folder, + esdl_file_name="emerge_battery_priorities.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short.csv", + ) + + results_unstaged = solution_unstaged.extract_results() + + # Checking that the results are the same. + for key, value in results_unstaged.items(): + value_staged = results_staged[key] + if len(key.split("__")) > 1 and key.split("__")[1] == "gas_flow_direct_var": + # For the scenario when Q is -0 and 0 then gas_flow_direct_var 0 or 1 for the same + # volumetric flow rate of zero. So only check gas_flow_direct_var when Q != zero + zero_staged = results_staged[f"{key.split('__')[0]}.GasIn.Q"] != 0 + zero_unstaged = results_unstaged[f"{key.split('__')[0]}.GasIn.Q"] != 0 + np.testing.assert_allclose(value[zero_staged], value_staged[zero_unstaged]) + else: + np.testing.assert_allclose(value, value_staged) + + solution_staged_bounded = run_sequatially_staged_simulation( + multi_commodity_simulator_class=MultiCommoditySimulatorNoLosses, + simulation_window_size=20, + base_folder=base_folder, + esdl_file_name="emerge_battery_priorities_limited_capacity.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short.csv", + ) + + results_staged_bounded = solution_staged_bounded.results + + solution_unstaged_bounded = run_optimization_problem( + MultiCommoditySimulatorNoLosses, + base_folder=base_folder, + esdl_file_name="emerge_battery_priorities_limited_capacity.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short.csv", + ) + + results_unstaged_bounded = solution_unstaged_bounded.extract_results() + + check_different = np.sum( + np.abs( + results_staged_bounded["Battery_4688.Stored_electricity"] + - results_unstaged_bounded["Battery_4688.Stored_electricity"] + ) + ) + + assert check_different > 0 + + class MultiCommoditySimulatorNoLossesWin(MultiCommoditySimulatorNoLosses): + def times(self, variable=None) -> np.ndarray: + return super().times(variable)[:20] + + solution_unstaged_bounded_win = run_optimization_problem( + MultiCommoditySimulatorNoLossesWin, + base_folder=base_folder, + esdl_file_name="emerge_battery_priorities_limited_capacity.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_short.csv", + ) + + results_unstaged_bounded_win = solution_unstaged_bounded_win.extract_results() + + np.testing.assert_allclose( + results_staged_bounded["Battery_4688.Stored_electricity"][19], + results_unstaged_bounded_win["Battery_4688.Stored_electricity"][-1], + ) + + +if __name__ == "__main__": + import time + + start_time = time.time() + a = TestMultiCommoditySimulator() + # a.test_multi_commodity_simulator_priorities_el() + # a.test_multi_commodity_simulator_prod_profile() + # a.test_multi_commodity_simulator_emerge() + # a.test_multi_commodity_simulator_emerge_lowprod() + # a.test_multi_commodity_simulator_emerge_head_losses() + a.test_multi_commodity_simulator_sequential_staged() + + print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) diff --git a/tests/test_multiple_carriers.py b/tests/test_multiple_carriers.py index f049d9a5f..a3a2ce7fd 100644 --- a/tests/test_multiple_carriers.py +++ b/tests/test_multiple_carriers.py @@ -1,10 +1,9 @@ from pathlib import Path from unittest import TestCase -from rtctools.util import run_optimization_problem - -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test @@ -26,7 +25,7 @@ def test_multiple_carriers(self): base_folder = Path(run_multiple_carriers.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="MultipleCarrierTest.esdl", diff --git a/tests/test_multiple_in_and_out_port_components.py b/tests/test_multiple_in_and_out_port_components.py index 5eb254b48..d284f46ff 100644 --- a/tests/test_multiple_in_and_out_port_components.py +++ b/tests/test_multiple_in_and_out_port_components.py @@ -1,12 +1,11 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test @@ -14,15 +13,15 @@ class TestHEX(TestCase): def test_heat_exchanger(self): """ - Check the modelling of the milp exchanger component which allows two hydraulically - decoupled networks to exchange milp with each other. It is enforced that milp can only flow - from the primary side to the secondary side, and milp exchangers are allowed to be disabled + Check the modelling of the heat exchanger component which allows two hydraulically + decoupled networks to exchange heat with each other. It is enforced that heat can only flow + from the primary side to the secondary side, and heat exchangers are allowed to be disabled for timesteps in which they are not used. This is to allow for the temperature constraints (T_primary > T_secondary) to become deactivated. Checks: - - Standard checks for demand matching, milp to discharge and energy conservation - - That the efficiency is correclty implemented for milp from primary to secondary + - Standard checks for demand matching, heat to discharge and energy conservation + - That the efficiency is correclty implemented for heat from primary to secondary - Check that the is_disabled is set correctly. - Check if the temperatures provided are physically feasible. @@ -33,14 +32,42 @@ def test_heat_exchanger(self): ) base_folder = Path(run_heat_exchanger.__file__).resolve().parent.parent - - solution = run_optimization_problem( - HeatProblem, + # ----------------------------------------------------------------------------------------- + # Do not delete: this is used to manualy check writing out of profile data + + class HeatProblemPost(HeatProblem): + # def post(self): + # super().post() + # self._write_updated_esdl( + # self._ESDLMixin__energy_system_handler.energy_system, + # optimizer_sim=True, + # ) + + def energy_system_options(self): + options = super().energy_system_options() + # self.heat_network_settings["minimize_head_losses"] = True # used for manual tests + return options + + # Do not delete kwargs: this is used to manualy check writing out of profile data + kwargs = { + "write_result_db_profiles": False, + "influxdb_host": "localhost", + "influxdb_port": 8086, + "influxdb_username": None, + "influxdb_password": None, + "influxdb_ssl": False, + "influxdb_verify_ssl": False, + } + # ----------------------------------------------------------------------------------------- + + solution = run_esdl_mesido_optimization( + HeatProblemPost, base_folder=base_folder, esdl_file_name="heat_exchanger.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, input_timeseries_file="timeseries_import.xml", + **kwargs, ) results = solution.extract_results() @@ -65,7 +92,7 @@ def test_heat_exchanger(self): np.testing.assert_allclose(prim_heat[-1], 0.0, atol=1e-5) np.testing.assert_allclose(disabled[-1], 1.0) np.testing.assert_allclose(disabled[:-1], 0.0) - # Check that milp is flowing through the hex + # Check that heat is flowing through the hex np.testing.assert_array_less(-prim_heat[:-1], 0.0) np.testing.assert_array_less( @@ -77,18 +104,217 @@ def test_heat_exchanger(self): parameters["HeatExchange_39ed.Primary.T_return"], ) + def test_heat_exchanger_bypass(self): + """ + Check the modelling of the heat exchanger component which allows two hydraulically + decoupled networks to exchange heat with each other. It is enforced that heat can only flow + from the primary side to the secondary side, and heat exchangers are allowed to be disabled + for timesteps in which they are not used. This is to allow for the temperature constraints + (T_primary > T_secondary) to become deactivated. + An option to allow for bypassing of the heat exchanger has been added, such that when the + heat exchanger is disabled, flow through the heat exchanger is allowed, however no heat + exchange is allowed, in the case the carriers of both the supply and return on one side + of the heat exchanger are the same. + + Checks: + - Standard checks for demand matching and energy conservation. + - Heat to discharge test is not applied as at one heat exchanger (the bypassed one), the + heat going out on the primary side will not coincide exactly with the temperature due to + heatlosses in the network before the heat exchanger. + - Check that the is_disabled is set correctly. + - Check if the temperatures provided are physically feasible. + - Checks that heat exchanger is bypassed, e.g. not exchanging heat, but allowing flow when + both supply and return on one side have the same temperature. + """ + import models.heat_exchange.src.run_heat_exchanger as run_heat_exchanger + from models.heat_exchange.src.run_heat_exchanger import ( + HeatProblem, + ) + + base_folder = Path(run_heat_exchanger.__file__).resolve().parent.parent + + class HeatProblemByPass(HeatProblem): + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + self.heat_network_settings["heat_exchanger_bypass"] = True + + def energy_system_options(self): + options = super().energy_system_options() + options["neglect_pipe_heat_losses"] = False + + return options + + solution = run_esdl_mesido_optimization( + HeatProblemByPass, + base_folder=base_folder, + esdl_file_name="test_hex_bypass.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_import.xml", + ) + + results = solution.extract_results() + + demand_matching_test(solution, results) + energy_conservation_test(solution, results) + + hex_active = "HeatExchange_e410_copy" + hex_bypass = "HeatExchange_e410" + + np.testing.assert_allclose(results[f"{hex_active}__disabled"][:-1], 0) + np.testing.assert_allclose(results[f"{hex_bypass}__disabled"][:-1], 1) + + np.testing.assert_array_less(0.001, results[f"{hex_active}.Primary.Q"][:-1]) + np.testing.assert_array_less(0.001, results[f"{hex_bypass}.Primary.Q"][:-1]) + + np.testing.assert_allclose(results[f"{hex_bypass}.Heat_flow"][:-1], 0, atol=1e-9) + np.testing.assert_array_less(1e5, results[f"{hex_active}.Heat_flow"][:-1]) + + def test_heat_exchanger_bypass_varying_temperature(self): + """ + Check the modelling of the heat exchanger component which allows two hydraulically + decoupled networks to exchange heat with each other. It is enforced that heat can only flow + from the primary side to the secondary side, and heat exchangers are allowed to be disabled + for timesteps in which they are not used. This is to allow for the temperature constraints + (T_primary > T_secondary) to become deactivated. + An option to allow for bypassing of the heat exchanger has been added, such that when the + heat exchanger is disabled, flow through the heat exchanger is allowed, however no heat + exchange is allowed, in the case the carriers of both the supply and return on one side + of the heat exchanger are the same. + + Checks: + - Standard checks for demand matching and energy conservation. + - Heat to discharge test is not applied as at one heat exchanger (the bypassed one), the + heat going out on the primary side will not coincide exactly with the temperature due to + heatlosses in the network before the heat exchanger. + - Check that the is_disabled is set correctly. + - Check if the temperatures provided are physically feasible. + - Checks that heat exchanger is bypassed, e.g. not exchanging heat, but allowing flow when + both supply and return on one side have the same temperature. + - Check that temperatures are selected correctly at the heat exchanger + """ + + import models.heat_exchange.src.run_heat_exchanger as run_heat_exchanger + from models.heat_exchange.src.run_heat_exchanger import ( + HeatProblem, + ) + + base_folder = Path(run_heat_exchanger.__file__).resolve().parent.parent + + class HeatProblemByPassMultiTemp(HeatProblem): + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + self.heat_network_settings["heat_exchanger_bypass"] = True + + def energy_system_options(self): + options = super().energy_system_options() + options["neglect_pipe_heat_losses"] = False + + return options + + def temperature_carriers(self): + return self.esdl_carriers + + def temperature_regimes(self, carrier): + temperatures = [] + if carrier == 829940433102452838: + temperatures = [70.0, 65.0, 60.0] # producer out + + if carrier == 8725433194681736500139: + temperatures = [65.0, 60.0] # first hex out + + return temperatures + + def constraints(self, ensemble_member): + constraints = super().constraints(ensemble_member) + + carriers = self.temperature_carriers() + for carrier in carriers.values(): + carrier_map = carrier["id_number_mapping"] + temperature_regimes = self.temperature_regimes(int(carrier_map)) + if len(temperature_regimes) > 1: + carrier_var_name = str(carrier_map) + "_temperature" + var_carrier = self.extra_variable(carrier_var_name) + for i in range(var_carrier.shape[0] - 1): + constraints.append((var_carrier[i] - var_carrier[i + 1], 0.0, 0.0)) + + for temperature in temperature_regimes: + selected_temp_vec = self.state_vector( + f"{int(carrier_map)}_{temperature}" + ) + for i in range(var_carrier.shape[0] - 1): + constraints.append( + (selected_temp_vec[i] - selected_temp_vec[i + 1], 0.0, 0.0) + ) + + return constraints + + # def solver_options(self): + # options = super().solver_options() + # options["solver"] = "cplex" + # return options + + def times(self, variable=None) -> np.ndarray: + """ + Shorten the timeseries to speed up the test, when highs is used as a solver. + """ + return super().times(variable)[:5] + + solution = run_esdl_mesido_optimization( + HeatProblemByPassMultiTemp, + base_folder=base_folder, + esdl_file_name="test_hex_bypass_2.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_import.xml", + ) + + results = solution.extract_results() + + demand_matching_test(solution, results) + energy_conservation_test(solution, results) + + temp_prod = results["829940433102452838_temperature"] + temp_hex = results["8725433194681736500139_temperature"] + + # check heat exchanger 1 is bypassed + hex_active = "HeatExchange_e410_copy" + hex_bypass = "HeatExchange_e410" + + np.testing.assert_allclose(results[f"{hex_active}__disabled"][:-1], 0) + np.testing.assert_allclose(results[f"{hex_bypass}__disabled"][:-1], 1) + + np.testing.assert_array_less(0.001, results[f"{hex_active}.Primary.Q"][:-1]) + np.testing.assert_array_less(0.001, results[f"{hex_bypass}.Primary.Q"][:-1]) + + np.testing.assert_allclose(results[f"{hex_bypass}.Heat_flow"][:-1], 0, atol=1e-6) + np.testing.assert_array_less(1e5, results[f"{hex_active}.Heat_flow"][:-1]) + + # check lowest temperatures are picked (due to minimum heatloss). + # check temperatures on bypass side are the same. + + np.testing.assert_allclose(temp_prod, 60.0) + np.testing.assert_allclose(temp_hex, 60.0) + np.testing.assert_allclose(temp_hex, temp_prod) + class TestHP(TestCase): def test_heat_pump(self): """ - Check the modelling of the milp pump component which has a constant COP with no energy loss. + Check the modelling of the heat pump component which has a constant COP with no energy loss. In this specific problem we expect the use of the secondary source to be maximised as - electrical milp from the HP is "free". + electrical heat from the HP is "free". Checks: - - Standard checks for demand matching, milp to discharge and energy conservation - - Check that the milp pump is producing according to its COP + - Standard checks for demand matching, heat to discharge and energy conservation + - Check that the heat pump is producing according to its COP - Check that Secondary source use in minimized + - Check that the upper bound value for heat producing capacity is the same as specified in + the esdl """ @@ -99,13 +325,42 @@ def test_heat_pump(self): base_folder = Path(run_heat_pump.__file__).resolve().parent.parent - solution = run_optimization_problem( - HeatProblem, + # ----------------------------------------------------------------------------------------- + # Do not delete: this is used to manualy check writing out of profile data + + class HeatProblemPost(HeatProblem): + # def post(self): + # super().post() + # self._write_updated_esdl( + # self._ESDLMixin__energy_system_handler.energy_system, + # optimizer_sim=True, + # ) + + def energy_system_options(self): + options = super().energy_system_options() + # self.heat_network_settings["minimize_head_losses"] = True # used for manual tests + return options + + # Do not delete kwargs: this is used to manualy check writing out of profile data + kwargs = { + "write_result_db_profiles": False, + "influxdb_host": "localhost", + "influxdb_port": 8086, + "influxdb_username": None, + "influxdb_password": None, + "influxdb_ssl": False, + "influxdb_verify_ssl": False, + } + # ----------------------------------------------------------------------------------------- + + solution = run_esdl_mesido_optimization( + HeatProblemPost, base_folder=base_folder, esdl_file_name="heat_pump.esdl", esdl_parser=ESDLFileParser, profile_reader=ProfileReaderFromFile, input_timeseries_file="timeseries_import.xml", + **kwargs, ) results = solution.extract_results() @@ -131,6 +386,14 @@ def test_heat_pump(self): np.testing.assert_allclose(power_elec * parameters["GenericConversion_3d3f.COP"], sec_heat) np.testing.assert_allclose(power_elec + prim_heat, sec_heat) + # Check that the heat pump upper bound + for key in solution.esdl_assets.keys(): + if solution.esdl_assets[key].asset_type == "HeatPump": + np.testing.assert_equal( + solution.bounds()["GenericConversion_3d3f.Heat_flow"][1], + solution.esdl_assets[key].attributes["power"], + ) + if __name__ == "__main__": import time diff --git a/tests/test_network_simulator.py b/tests/test_network_simulator.py index 0bc21490b..e184dd6cd 100644 --- a/tests/test_network_simulator.py +++ b/tests/test_network_simulator.py @@ -1,28 +1,28 @@ from pathlib import Path from unittest import TestCase +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.workflows import NetworkSimulatorHIGHSTestCase + import numpy as np from rtctools.util import run_optimization_problem -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.workflows import NetworkSimulatorHIGHSTestCase - from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test class TestNetworkSimulator(TestCase): """ - In this test case 2 milp producers and an ATES is used to supply 3 heating demands. A merit + In this test case 2 heat producers and an ATES is used to supply 3 heating demands. A merit order (preference of 1st use) is given to the producers: Producer_1 = 2 and Producer_2 = 1. Checks: - - General checks namely demand matching, energy conservation and asset milp variable vs - calculated milp (based on flow rate) - - Check that producer 1 (merit oder = 2) is only used for the supply of milp lossed in the + - General checks namely demand matching, energy conservation and asset heat variable vs + calculated heat (based on flow rate) + - Check that producer 1 (merit oder = 2) is only used for the supply of heat lossed in the connected and is does not contribute to the heating demands 1, 2 and 3 - - Check that the ATES is not delivering any milp to the network during the 1st time step + - Check that the ATES is not delivering any heat to the network during the 1st time step """ def test_network_simulator(self): @@ -54,7 +54,7 @@ def test_network_simulator(self): 0.0, err_msg="Heat producer 1 should be completely disabled " ", due to producer 2 being sufficient for " - "the total milp demand (incl. milp losses) and it has the 1st priority for usage", + "the total heat demand (incl. heat losses) and it has the 1st priority for usage", rtol=1.0e-3, atol=1.0e-3, ) @@ -62,7 +62,7 @@ def test_network_simulator(self): np.testing.assert_array_less( results["ATES_033c.Heat_ates"][0], 0.0, - err_msg="ATES should not be delivering milp to the network in the 1st time step", + err_msg="ATES should not be delivering heat to the network in the 1st time step", ) diff --git a/tests/test_pipe_diameter_sizing.py b/tests/test_pipe_diameter_sizing.py index 5071f726f..ed791f706 100644 --- a/tests/test_pipe_diameter_sizing.py +++ b/tests/test_pipe_diameter_sizing.py @@ -2,13 +2,12 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido._darcy_weisbach import friction_factor +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network._darcy_weisbach import friction_factor -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test @@ -22,7 +21,7 @@ def test_half_network_gone(self): the left source and the associated left pipes. Checks: - - Standard checks for demand matching, milp to discharge and energy conservation + - Standard checks for demand matching, heat to discharge and energy conservation - That expected pipes are removed - Check that the Q is under the max for the selected pipe class. - Check that head losses are as expected for the selected diameter @@ -49,7 +48,7 @@ def test_half_network_gone(self): del root_folder sys.path.pop(1) - problem = run_optimization_problem( + problem = run_esdl_mesido_optimization( PipeDiameterSizingProblem, base_folder=base_folder, esdl_file_name="2a.esdl", @@ -58,6 +57,9 @@ def test_half_network_gone(self): input_timeseries_file="timeseries_import.xml", ) + feasibility = problem.solver_stats["return_status"] + self.assertTrue((feasibility == "Optimal")) + parameters = problem.parameters(0) diameters = {p: parameters[f"{p}.diameter"] for p in problem.hot_pipes} results = problem.extract_results() @@ -99,7 +101,7 @@ def test_half_network_gone(self): ) for pipe in problem.energy_system_components.get("heat_pipe", []): - if results[f"{pipe}__hn_diameter"] == 0.0: + if results[f"{pipe}__hn_diameter"] <= 1e-15: # TODO: At the moment it is so that a pipe which is not placed (diameter == 0.) can # have head loss since there is an equivalent solution where simultaniously the # is_disconnected variable is also true disabling the head_loss constraints. diff --git a/tests/test_producer_profiles.py b/tests/test_producer_profiles.py index 453305ed5..1901ad2f1 100644 --- a/tests/test_producer_profiles.py +++ b/tests/test_producer_profiles.py @@ -1,34 +1,42 @@ from pathlib import Path from unittest import TestCase -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test class TestProducerMaxProfile(TestCase): """ - A test to verify that the producer can have a given scaled profile, where the producer will - always produce equal or less than said profile. This constraint is checked for a producer, - where the producer's profile was also intentionally reduced for a couple of time-steps - (reducing the profile value at a few time steps). - - Checks: - - Standard checks demand matching, energy conservation and milp to discharge - - check that heat_source <= scaled_profile * size_source. + A test to verify that the heat produced by a heat producer is capped by a profile, where the + producer will always produce equal or less than said profile. This constraint is checked for a + producer, where the producer's profile was also intentionally smaller than required for a + couple of timesteps """ - def test_max_producer_profile(self): + def test_max_producer_scaled_profile(self): + """ + Use a scaled profile, where the profile was intentionally reduced for a couple of + time-steps (reducing the profile value at a few time steps). With the producer size not + being minimized. + + Checks: + - Standard checks demand matching, energy conservation and heat to discharge + - Check that the heat_source <= scaled_profile * size_source + + """ + import models.unit_cases.case_3a.src.run_3a as run_3a from models.unit_cases.case_3a.src.run_3a import HeatProblemProdProfile base_folder = Path(run_3a.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblemProdProfile, base_folder=base_folder, esdl_file_name="3a.esdl", @@ -50,6 +58,130 @@ def test_max_producer_profile(self): ).values heat_producer_profile_full = heat_producer_profile_scaled * size_producer - # check that milp produced is smaller than the profile + # check that heat produced is smaller than the profile biggerthen = all(heat_producer_profile_full + tol >= heat_producer) self.assertTrue(biggerthen) + + def test_max_producer_esdl_unscaled_profile(self): + """ + Use a profile specified in Watts, where the profile was intentionally modified (via the + profile multiplier) such that it is smaller than the requried heating demand at a couple of + timesteps. With the producer size being minimized. + + Checks: + - Standard checks demand matching, energy conservation and heat to discharge + - Check that the heat source <= specified profile [W] + - Check that heat produced is capped at a couple of timesteps + """ + + import models.unit_cases.case_3a.src.run_3a as run_3a + from models.unit_cases.case_3a.src.run_3a import ( + HeatProblemESDLProdProfile, + HeatProblemESDLProdProfileTCO, + ) + + base_folder = Path(run_3a.__file__).resolve().parent.parent + + for problem_class in [HeatProblemESDLProdProfile, HeatProblemESDLProdProfileTCO]: + + if problem_class == HeatProblemESDLProdProfile: + # No sizing of the producer + esdl_file_used = "3a_esdl_source_unscaled_profile.esdl" + elif problem_class == HeatProblemESDLProdProfileTCO: + # Sizing of the producer is included + esdl_file_used = "3a_esdl_source_unscaled_profile_sizing.esdl" + + solution = run_esdl_mesido_optimization( + problem_class, + base_folder=base_folder, + esdl_file_name=esdl_file_used, + esdl_parser=ESDLFileParser, + ) + results = solution.extract_results() + + demand_matching_test(solution, results) + energy_conservation_test(solution, results) + heat_to_discharge_test(solution, results) + tol = 1e-8 + heat_produced = results["HeatProducer_b702.Heat_source"] + + if problem_class == HeatProblemESDLProdProfile: + heat_production_upper_limit = solution.get_timeseries( + "HeatProducer_b702.maximum_heat_source" + ).values + np.testing.assert_equal( + solution.esdl_assets[ + solution.esdl_asset_name_to_id_map["HeatProducer_b702"] + ].attributes["power"], + results["HeatProducer_b702__max_size"], + ) + np.testing.assert_array_less(heat_produced - tol, heat_production_upper_limit) + np.testing.assert_equal( + len(np.where(heat_produced - heat_production_upper_limit == 0)[0]), + 5, + ) + elif problem_class == HeatProblemESDLProdProfileTCO: + heat_production_upper_limit = ( + solution.get_timeseries("HeatProducer_b702.maximum_heat_source").values + / max(solution.get_timeseries("HeatProducer_b702.maximum_heat_source").values) + * results["HeatProducer_b702__max_size"] + ) + np.testing.assert_allclose( + max(heat_production_upper_limit), + results["HeatProducer_b702__max_size"], + atol=1e-9, + ) + np.testing.assert_array_less(heat_produced - tol, heat_production_upper_limit) + np.testing.assert_equal( + len(np.where(heat_produced - heat_production_upper_limit == 0)[0]), + 5, + ) + + def test_max_producer_esdl_scaled_profile(self): + """ + Use a scaled profile, where the profile was intentionally reduced for a couple of + time-steps (reducing the profile value at a few time steps). With the producer size not + being minimized. + + Checks: + - Standard checks demand matching, energy conservation and heat to discharge + - Check that the heat source <= specified profile * producer size + - Check that heat produced is capped at a couple of timesteps + """ + + import models.unit_cases.case_3a.src.run_3a as run_3a + from models.unit_cases.case_3a.src.run_3a import HeatProblemESDLProdProfile + + base_folder = Path(run_3a.__file__).resolve().parent.parent + + solution = run_esdl_mesido_optimization( + HeatProblemESDLProdProfile, + base_folder=base_folder, + esdl_file_name="3a_esdl_source_scaled_profile.esdl", + esdl_parser=ESDLFileParser, + ) + results = solution.extract_results() + + demand_matching_test(solution, results) + energy_conservation_test(solution, results) + heat_to_discharge_test(solution, results) + tol = 1e-8 + heat_produced = results["HeatProducer_b702.Heat_source"] + heat_production_upper_limit = ( + solution.get_timeseries("HeatProducer_b702.maximum_heat_source").values + * results["HeatProducer_b702__max_size"] + ) + + # check that heat produced is smaller than the profile + np.testing.assert_array_less(heat_produced - tol, heat_production_upper_limit) + np.testing.assert_equal( + len(np.where(heat_produced - heat_production_upper_limit == 0)[0]), 4 + ) + + +if __name__ == "__main__": + + a = TestProducerMaxProfile() + a.test_max_producer_scaled_profile() + a.test_max_producer_esdl_unscaled_profile() + a.test_max_producer_esdl_scaled_profile() diff --git a/tests/test_profile_parsing.py b/tests/test_profile_parsing.py index d8ad6d7ba..ce92cc201 100644 --- a/tests/test_profile_parsing.py +++ b/tests/test_profile_parsing.py @@ -1,28 +1,252 @@ +import datetime +import operator import unittest +import unittest.mock from pathlib import Path from typing import Optional import esdl +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import InfluxDBProfileReader, ProfileReaderFromFile +from mesido.exceptions import MesidoAssetIssueError +from mesido.potential_errors import MesidoAssetIssueType, PotentialErrors +from mesido.workflows import EndScenarioSizingStaged +from mesido.workflows.utils.adapt_profiles import ( + adapt_hourly_profile_averages_timestep_size, + adapt_profile_to_copy_for_number_of_years, +) +from mesido.workflows.utils.error_types import mesido_issue_type_gen_message + import numpy as np import pandas as pd -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import InfluxDBProfileReader, ProfileReaderFromFile -from rtctools_heat_network.workflows import EndScenarioSizingStagedHIGHS +from utils_test_scaling import create_log_list_scaling class MockInfluxDBProfileReader(InfluxDBProfileReader): def __init__(self, energy_system: esdl.EnergySystem, file_path: Optional[Path]): super().__init__(energy_system, file_path) - self._loaded_profiles = pd.read_csv(file_path, index_col="DateTime", parse_dates=True) + self._loaded_profiles = pd.read_csv( + file_path, + index_col="DateTime", + date_parser=lambda x: pd.to_datetime(x).tz_convert(datetime.timezone.utc), + ) def _load_profile_timeseries_from_database(self, profile: esdl.InfluxDBProfile) -> pd.Series: return self._loaded_profiles[profile.id] +class TestProfileUpdating(unittest.TestCase): + def test_profile_updating(self): + """ + Tests the updating of the profiles. + The peak day hourly with averaged 5 days is currently tested in test_cold_demand.py. + This test covers the profile updating with varying timescales. Of amongst others the + adapt_hourly_profile_averages_timestep_size method and the + adapt_profile_to_copy_for_number_of_years method in adapt_profiles.py + + Returns: + + """ + import models.unit_cases.case_3a.src.run_3a as run_3a + from models.unit_cases.case_3a.src.run_3a import HeatProblem + + base_folder = Path(run_3a.__file__).resolve().parent.parent + model_folder = base_folder / "model" + input_folder = base_folder / "input" + + problem_step_size = 8 + + class ProfileUpdateHourly(HeatProblem): + def read(self): + """ + Reads a profile with hourly time steps and adapts and adapts to averages over the + specified number of hours. + """ + super().read() + + adapt_hourly_profile_averages_timestep_size(self, problem_step_size) + + problem = ProfileUpdateHourly( + esdl_parser=ESDLFileParser, + base_folder=base_folder, + model_folder=model_folder, + input_folder=input_folder, + esdl_file_name="3a.esdl", + profile_reader=ProfileReaderFromFile, + input_timeseries_file="timeseries_import.xml", + ) + problem.pre() + + timeseries_updated = problem.io.datetimes + dts = list(map(operator.sub, timeseries_updated[1:], timeseries_updated[0:-1])) + assert all(dt.seconds == 3600 * problem_step_size for dt in dts[:-1]) + assert dts[-1].seconds <= 3600 * problem_step_size + + # TODO: also check the values of the averages + + import models.test_case_small_network_ates_buffer_optional_assets.src.run_ates as run_ates + + base_folder = Path(run_ates.__file__).resolve().parent.parent + model_folder = base_folder / "model" + input_folder = base_folder / "input" + problem_years = 3 + + class ProfileUpdateMultiYear(HeatProblem): + def read(self): + """ + Reads the yearly profile with unspecified time steps and copies the profile for + multiple years. + """ + super().read() + + adapt_profile_to_copy_for_number_of_years(self, problem_years) + + problem = ProfileUpdateMultiYear( + esdl_parser=ESDLFileParser, + base_folder=base_folder, + model_folder=model_folder, + input_folder=input_folder, + esdl_file_name="test_case_small_network_with_ates_with_buffer_all_optional.esdl", + profile_reader=ProfileReaderFromFile, + input_timeseries_file="Warmte_test.csv", + ) + problem.pre() + + # TODO: update checks + len_org_time_serie = 8760 # the last timestep is not copied + timeseries_updated = problem.io.datetimes + dts = list( + map( + operator.sub, + timeseries_updated[len_org_time_serie:-1], + timeseries_updated[0:-len_org_time_serie], + ) + ) + assert len(timeseries_updated) == len_org_time_serie * problem_years + assert all(dt.days == 365 for dt in dts) + + +class TestPotentialErrors(unittest.TestCase): + def test_asset_potential_errors(self): + """ + This test checks that the error checks in the code for sufficient installed cool/heatig + capacity of a cold/heat demand is sufficient (grow_workflow) + + Checks: + 1. Correct error is raised + 2. That the error is due to: + - insufficient heat specified capacities for 3 heating demands + - incorrect heating demand type being used for 1 heating demand + - profile cannot be assigned to a specific asset + """ + import models.unit_cases.case_1a.src.run_1a as run_1a + + base_folder = Path(run_1a.__file__).resolve().parent.parent + model_folder = base_folder / "model" + input_folder = base_folder / "input" + + logger, logs_list = create_log_list_scaling("WarmingUP-MPC") + + with self.assertRaises(MesidoAssetIssueError) as cm, unittest.mock.patch( + "mesido.potential_errors.POTENTIAL_ERRORS", PotentialErrors() + ): + problem = EndScenarioSizingStaged( + esdl_parser=ESDLFileParser, + base_folder=base_folder, + model_folder=model_folder, + input_folder=input_folder, + esdl_file_name="1a_with_influx_profiles_error_check_1.esdl", + profile_reader=MockInfluxDBProfileReader, + input_timeseries_file="influx_mock.csv", + ) + problem.pre() + + # Check that the heat demand had an error + np.testing.assert_equal(cm.exception.error_type, MesidoAssetIssueType.HEAT_DEMAND_POWER) + np.testing.assert_equal( + cm.exception.general_issue, + mesido_issue_type_gen_message(MesidoAssetIssueType.HEAT_DEMAND_POWER), + ) + np.testing.assert_equal( + cm.exception.message_per_asset_id["2ab92324-f86e-4976-9a6e-f7454b77ba3c"], + "Asset named HeatingDemand_2ab9: The installed capacity of 6.0MW should be larger than" + " the maximum of the heat demand profile 5175.717MW", + ) + np.testing.assert_equal( + cm.exception.message_per_asset_id["506c41ac-d415-4482-bf10-bf12f17aeac6"], + "Asset named HeatingDemand_506c: The installed capacity of 2.0MW should be larger than" + " the maximum of the heat demand profile 1957.931MW", + ) + np.testing.assert_equal( + cm.exception.message_per_asset_id["6662aebb-f85e-4df3-9f7e-c58993586fba"], + "Asset named HeatingDemand_6662: The installed capacity of 2.0MW should be larger than" + " the maximum of the heat demand profile 1957.931MW", + ) + np.testing.assert_equal(len(cm.exception.message_per_asset_id), 3.0) + + # Check heating demand type error + with self.assertRaises(MesidoAssetIssueError) as cm, unittest.mock.patch( + "mesido.potential_errors.POTENTIAL_ERRORS", PotentialErrors() + ): + problem = EndScenarioSizingStaged( + esdl_parser=ESDLFileParser, + base_folder=base_folder, + model_folder=model_folder, + input_folder=input_folder, + esdl_file_name="1a_with_influx_profiles_error_check_2.esdl", + profile_reader=MockInfluxDBProfileReader, + input_timeseries_file="influx_mock.csv", + ) + problem.pre() + # Check that the heat demand had an error + np.testing.assert_equal(cm.exception.error_type, MesidoAssetIssueType.HEAT_DEMAND_TYPE) + np.testing.assert_equal( + cm.exception.general_issue, + mesido_issue_type_gen_message(MesidoAssetIssueType.HEAT_DEMAND_TYPE), + ) + np.testing.assert_equal( + cm.exception.message_per_asset_id["2ab92324-f86e-4976-9a6e-f7454b77ba3c"], + "Asset named HeatingDemand_2ab9: This asset is currently a GenericConsumer please" + " change it to a HeatingDemand", + ) + np.testing.assert_equal(len(cm.exception.message_per_asset_id), 1.0) + + # Check asset profile capability + with self.assertRaises(MesidoAssetIssueError) as cm, unittest.mock.patch( + "mesido.potential_errors.POTENTIAL_ERRORS", PotentialErrors() + ): + problem = EndScenarioSizingStaged( + esdl_parser=ESDLFileParser, + base_folder=base_folder, + model_folder=model_folder, + input_folder=input_folder, + esdl_file_name="1a_with_influx_profiles_error_check_3.esdl", + profile_reader=MockInfluxDBProfileReader, + input_timeseries_file="influx_mock.csv", + ) + problem.pre() + # Check that the joint has an error + np.testing.assert_equal( + cm.exception.error_type, + MesidoAssetIssueType.ASSET_PROFILE_CAPABILITY, + ) + np.testing.assert_equal( + cm.exception.general_issue, + mesido_issue_type_gen_message(MesidoAssetIssueType.ASSET_PROFILE_CAPABILITY), + ) + np.testing.assert_equal( + cm.exception.message_per_asset_id["95802cf8-61d6-4773-bb99-e275c3bf26cc"], + "Asset named Joint_9580: The assigment of profile field demand3_MW is not possible for" + " this asset type ", + ) + np.testing.assert_equal(len(cm.exception.message_per_asset_id), 1.0) + + class TestProfileLoading(unittest.TestCase): + def test_loading_from_influx(self): """ This test checks if loading an ESDL with influxDB profiles works. Since @@ -32,13 +256,16 @@ def test_loading_from_influx(self): EndScenarioSizing is called thus the checks done are on profile lenghts and some values. This is because this scenario should also do aggragation of the profiles for non-peak days. + + Also check: + - that the timezone setting from the "influx_mock.csv" is correct """ import models.unit_cases.case_1a.src.run_1a as run_1a base_folder = Path(run_1a.__file__).resolve().parent.parent model_folder = base_folder / "model" input_folder = base_folder / "input" - problem = EndScenarioSizingStagedHIGHS( + problem = EndScenarioSizingStaged( esdl_parser=ESDLFileParser, base_folder=base_folder, model_folder=model_folder, @@ -49,28 +276,31 @@ def test_loading_from_influx(self): ) problem.pre() + np.testing.assert_equal(problem.io.reference_datetime.tzinfo, datetime.timezone.utc) + # the three demands in the test ESDL for demand_name in ["HeatingDemand_2ab9", "HeatingDemand_6662", "HeatingDemand_506c"]: profile_values = problem.get_timeseries(f"{demand_name}.target_heat_demand").values - self.assertEqual(profile_values[0], 0.0) + self.assertEqual(profile_values[0], profile_values[1]) self.assertEqual(len(profile_values), 26) heat_price_profile = problem.get_timeseries("Heat.price_profile").values - self.assertEqual(heat_price_profile[0], 0.0) + self.assertEqual(heat_price_profile[0], heat_price_profile[1]) self.assertLess(max(heat_price_profile), 1.0) def test_loading_from_csv(self): """ This test constructs a problem with input profiles read from a CSV file. - The test checks if the profiles read match the profiles from the CVS file. + The test checks if the profiles read match the profiles from the CVS file and that the + default UTC timezone has been set. """ import models.unit_cases_electricity.electrolyzer.src.example as example - from models.unit_cases_electricity.electrolyzer.src.example import MILPProblem + from models.unit_cases_electricity.electrolyzer.src.example import MILPProblemInequality base_folder = Path(example.__file__).resolve().parent.parent model_folder = base_folder / "model" input_folder = base_folder / "input" - problem = MILPProblem( + problem = MILPProblemInequality( esdl_parser=ESDLFileParser, base_folder=base_folder, model_folder=model_folder, @@ -81,6 +311,8 @@ def test_loading_from_csv(self): ) problem.pre() + np.testing.assert_equal(problem.io.reference_datetime.tzinfo, datetime.timezone.utc) + expected_array = np.array([1.0e8] * 3) np.testing.assert_equal( expected_array, @@ -91,12 +323,15 @@ def test_loading_from_csv(self): np.testing.assert_equal(expected_array, problem.get_timeseries("elec.price_profile").values) expected_array = np.array([1.0e6] * 3) - np.testing.assert_equal(expected_array, problem.get_timeseries("gas.price_profile").values) + np.testing.assert_equal( + expected_array, problem.get_timeseries("Hydrogen.price_profile").values + ) def test_loading_from_xml(self): """ This test loads a simple problem using an XML file for input profiles. - The test checks if the load profiles match those specified in the XML file. + The test checks if the load profiles match those specified in the XML file and that the + default UTC timezone has been set. """ import models.basic_source_and_demand.src.heat_comparison as heat_comparison from models.basic_source_and_demand.src.heat_comparison import HeatESDL @@ -115,6 +350,8 @@ def test_loading_from_xml(self): ) problem.pre() + np.testing.assert_equal(problem.io.reference_datetime.tzinfo, datetime.timezone.utc) + expected_array = np.array([1.5e5] * 16 + [1.0e5] * 13 + [0.5e5] * 16) np.testing.assert_equal( expected_array, problem.get_timeseries("demand.target_heat_demand").values @@ -129,12 +366,12 @@ def test_loading_from_csv_with_influx_profiles_given(self): if the loaded profiles match those specified in the csv. """ import models.unit_cases_electricity.electrolyzer.src.example as example - from models.unit_cases_electricity.electrolyzer.src.example import MILPProblem + from models.unit_cases_electricity.electrolyzer.src.example import MILPProblemInequality base_folder = Path(example.__file__).resolve().parent.parent model_folder = base_folder / "model" input_folder = base_folder / "input" - problem = MILPProblem( + problem = MILPProblemInequality( esdl_parser=ESDLFileParser, base_folder=base_folder, model_folder=model_folder, @@ -145,6 +382,8 @@ def test_loading_from_csv_with_influx_profiles_given(self): ) problem.pre() + np.testing.assert_equal(problem.io.reference_datetime.tzinfo, datetime.timezone.utc) + expected_array = np.array([1.0e8] * 3) np.testing.assert_equal( expected_array, @@ -155,8 +394,19 @@ def test_loading_from_csv_with_influx_profiles_given(self): np.testing.assert_equal(expected_array, problem.get_timeseries("elec.price_profile").values) expected_array = np.array([1.0e6] * 3) - np.testing.assert_equal(expected_array, problem.get_timeseries("gas.price_profile").values) + np.testing.assert_equal( + expected_array, problem.get_timeseries("Hydrogen.price_profile").values + ) if __name__ == "__main__": - unittest.main() + # unittest.main() + a = TestProfileLoading() + b = TestPotentialErrors() + c = TestProfileUpdating() + # b.test_asset_potential_errors() + # a.test_loading_from_influx() + # a.test_loading_from_csv() + # a.test_loading_from_xml() + # a.test_loading_from_csv_with_influx_profiles_given() + c.test_profile_updating() diff --git a/tests/test_progress_update.py b/tests/test_progress_update.py new file mode 100644 index 000000000..4cbdc8d67 --- /dev/null +++ b/tests/test_progress_update.py @@ -0,0 +1,207 @@ +from unittest import TestCase +from unittest.mock import MagicMock + +from mesido.workflows.grow_workflow import estimate_and_update_progress_status + + +class TestProgress(TestCase): + + # 1 + def estimate_progress_nhl_ts1_s1_p1(self, task_quantity_perc_completed: float, msg: str): + self.assertEqual( + [task_quantity_perc_completed, msg], + [1.0 / 2.0, "Optimization task 1.0 out of 2.0 has completed"], + ) + + # 2 + def estimate_progress_nhl_ts1_s1_p2(self, task_quantity_perc_completed: float, msg: str): + self.assertEqual( + [task_quantity_perc_completed, msg], + [2.0 / 2.0, "Optimization task 2.0 out of 2.0 has completed"], + ) + return None + + # 3 + def estimate_progress_hl_ts2_s1_phl(self, task_quantity_perc_completed: float, msg: str): + return None + + # 4.1 + def estimate_progress_nhl_ts2_s1_p1(self, task_quantity_perc_completed: float, msg: str): + self.assertEqual( + [task_quantity_perc_completed, msg], + [1.0 / 4.0, "Optimization task 1.0 out of 4.0 has completed"], + ) + return None + + # 4.2 + def estimate_progress_nhl_ts2_s1_p2(self, task_quantity_perc_completed: float, msg: str): + self.assertEqual( + [task_quantity_perc_completed, msg], + [2.0 / 4.0, "Optimization task 2.0 out of 4.0 has completed"], + ) + return None + + # 5.1 + def estimate_progress_nhl_ts2_s2_p1(self, task_quantity_perc_completed: float, msg: str): + self.assertEqual( + [task_quantity_perc_completed, msg], + [3.0 / 4.0, "Optimization task 3.0 out of 4.0 has completed"], + ) + return None + + # 5.2 + def estimate_progress_nhl_ts2_s2_p2(self, task_quantity_perc_completed: float, msg: str): + self.assertEqual( + [task_quantity_perc_completed, msg], + [4.0 / 4.0, "Optimization task 4.0 out of 4.0 has completed"], + ) + return None + + # 6 + def estimate_progress_hl_ts2_s2_phl(self, task_quantity_perc_completed: float, msg: str): + self.assertEqual( + [task_quantity_perc_completed, msg], + [5.0 / 6.0, "Optimization task 5.0 out of 6.0 has completed"], + ) + return None + + # 7 + def estimate_progress_hl_ts2_s2_php(self, task_quantity_perc_completed: float, msg: str): + self.assertEqual( + [task_quantity_perc_completed, msg], + [6.0 / 6.0, "Optimization task 6.0 out of 6.0 has completed"], + ) + return None + + +class TestEstimateAndUpdateProgressStatus(TestCase): + + def test_progess(self): + """ + Test the progress status of the grow workflow for the different scenarios are calculated + correctly. + + Checks: + - #1: Priority = 1, total stages = 1, stage = 1, minimize_head_losses = False -> macth heat + demand + - #2: Priority = 2, total stages = 1, stage = 1, minimize_head_losses = False -> minimize + TCO + + - #3: Priority = 2**31 - 2, total stages = 2, stage = 1, minimize_head_losses = True -> give + error since the function does not cater for this scenario + + - #4.1: Priority = 1, total stages = 2, stage = 1 -> match heating demand + - #4.2: Priority = 1, total stages = 2, stage 1 = -> minimize TCO + - #5.1: Priority = 1, total stages = 2, stage = 2 -> match heating demand + - #5.2: Priority = 2, total stages = 2, stage = 2 -> minimize TCO + + - #6 Priority = 2**31 - 2, total stages = 2, stage = 2, minimize_head_losses = True -> head + loss optimization + - #7 Priority = 2**31 - 1, total stages = 2, stage = 2, minimize_head_losses = True -> + hydraulic power optimization + + + """ + + mock_endscenario_class = MagicMock() + test_progresss = TestProgress() + + # 1 + priority = 1 + mock_endscenario_class._total_stages = 1 + mock_endscenario_class._stage = 1 + mock_endscenario_class.heat_network_settings = {"minimize_head_losses": False} + mock_endscenario_class._workflow_progress_status = ( + test_progresss.estimate_progress_nhl_ts1_s1_p1 + ) + estimate_and_update_progress_status(mock_endscenario_class, priority) + + # 2 + priority = 2 + mock_endscenario_class._total_stages = 1 + mock_endscenario_class._stage = 1 + mock_endscenario_class.heat_network_settings = {"minimize_head_losses": False} + mock_endscenario_class._workflow_progress_status = ( + test_progresss.estimate_progress_nhl_ts1_s1_p2 + ) + estimate_and_update_progress_status(mock_endscenario_class, priority) + + # 3 + priority = 2**31 - 2 + mock_endscenario_class._total_stages = 2 + mock_endscenario_class._stage = 1 + mock_endscenario_class.heat_network_settings = {"minimize_head_losses": True} + mock_endscenario_class._workflow_progress_status = ( + test_progresss.estimate_progress_hl_ts2_s1_phl + ) + with self.assertRaises(SystemExit) as cm: + estimate_and_update_progress_status(mock_endscenario_class, priority) + self.assertEqual( + cm.exception.args[0], + "The function does not cater for stage number:1 & priority:2147483646", + ) + + # 4.1 + priority = 1 + mock_endscenario_class._total_stages = 2 + mock_endscenario_class._stage = 1 + mock_endscenario_class.heat_network_settings = {"minimize_head_losses": False} + mock_endscenario_class._workflow_progress_status = ( + test_progresss.estimate_progress_nhl_ts2_s1_p1 + ) + estimate_and_update_progress_status(mock_endscenario_class, priority) + + # 4.2 + priority = 2 + mock_endscenario_class._total_stages = 2 + mock_endscenario_class._stage = 1 + mock_endscenario_class.heat_network_settings = {"minimize_head_losses": False} + mock_endscenario_class._workflow_progress_status = ( + test_progresss.estimate_progress_nhl_ts2_s1_p2 + ) + estimate_and_update_progress_status(mock_endscenario_class, priority) + + # 5.1 + priority = 1 + mock_endscenario_class._total_stages = 2 + mock_endscenario_class._stage = 2 + mock_endscenario_class.heat_network_settings = {"minimize_head_losses": False} + mock_endscenario_class._workflow_progress_status = ( + test_progresss.estimate_progress_nhl_ts2_s2_p1 + ) + estimate_and_update_progress_status(mock_endscenario_class, priority) + + # 5.2 + priority = 2 + mock_endscenario_class._total_stages = 2 + mock_endscenario_class._stage = 2 + mock_endscenario_class.heat_network_settings = {"minimize_head_losses": False} + mock_endscenario_class._workflow_progress_status = ( + test_progresss.estimate_progress_nhl_ts2_s2_p2 + ) + estimate_and_update_progress_status(mock_endscenario_class, priority) + + # 6 + priority = 2**31 - 2 + mock_endscenario_class._total_stages = 2 + mock_endscenario_class._stage = 2 + mock_endscenario_class.heat_network_settings = {"minimize_head_losses": True} + mock_endscenario_class._workflow_progress_status = ( + test_progresss.estimate_progress_hl_ts2_s2_phl + ) + estimate_and_update_progress_status(mock_endscenario_class, priority) + + # 7 + priority = 2**31 - 1 + mock_endscenario_class._total_stages = 2 + mock_endscenario_class._stage = 2 + mock_endscenario_class.heat_network_settings = {"minimize_head_losses": True} + mock_endscenario_class._workflow_progress_status = ( + test_progresss.estimate_progress_hl_ts2_s2_php + ) + estimate_and_update_progress_status(mock_endscenario_class, priority) + + +if __name__ == "__main__": + a = TestEstimateAndUpdateProgressStatus() + a.test_progess() diff --git a/tests/test_pycml.py b/tests/test_pycml.py index 5264d2123..4207c0b50 100644 --- a/tests/test_pycml.py +++ b/tests/test_pycml.py @@ -1,8 +1,8 @@ from unittest import TestCase -import numpy as np +from mesido.pycml import Model, Variable -from rtctools_heat_network.pycml import Model, Variable +import numpy as np class TestPyCML(TestCase): diff --git a/tests/test_setpoint_constraints.py b/tests/test_setpoint_constraints.py index a5fbb7f9d..fd49167b7 100644 --- a/tests/test_setpoint_constraints.py +++ b/tests/test_setpoint_constraints.py @@ -1,15 +1,14 @@ from pathlib import Path from unittest import TestCase +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization + import numpy as np import pytest -from rtctools.util import run_optimization_problem - -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile - class TestSetpointConstraints(TestCase): @pytest.mark.first @@ -31,7 +30,7 @@ def test_setpoint_constraints(self): base_folder = Path(run_3a.__file__).resolve().parent.parent - _heat_problem_3 = run_optimization_problem( + _heat_problem_3 = run_esdl_mesido_optimization( HeatProblemSetPointConstraints, base_folder=base_folder, esdl_file_name="3a.esdl", @@ -42,7 +41,7 @@ def test_setpoint_constraints(self): ) results_3 = _heat_problem_3.extract_results() - _heat_problem_4 = run_optimization_problem( + _heat_problem_4 = run_esdl_mesido_optimization( HeatProblemSetPointConstraints, base_folder=base_folder, esdl_file_name="3a.esdl", @@ -60,7 +59,7 @@ def test_setpoint_constraints(self): base_folder = Path(run_3a.__file__).resolve().parent.parent - sol_esdl_setpoints = run_optimization_problem( + sol_esdl_setpoints = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="3a.esdl", @@ -99,8 +98,8 @@ def test_setpoint_constraints(self): def test_run_small_ates_timed_setpoints_2_changes(self): """ Run the small network with ATES and check that the setpoint changes as specified. - The milp source for producer_1 changes 8 times (consecutively) when no timed_setpoints are - specified. The 1 year milp demand profiles contains demand values: hourly (peak day), weekly + The heat source for producer_1 changes 8 times (consecutively) when no timed_setpoints are + specified. The 1 year heat demand profiles contains demand values: hourly (peak day), weekly (every 5days/120hours/432000s) and 1 time step of 4days (96hours/345600s, step before the start of the peak day). Now check that the time_setpoints can limit the setpoint changes to 2 changes/year. @@ -114,7 +113,7 @@ def test_run_small_ates_timed_setpoints_2_changes(self): base_folder = Path(run_ates.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblemSetPoints, base_folder=base_folder, esdl_file_name="test_case_small_network_with_ates.esdl", @@ -135,8 +134,8 @@ def test_run_small_ates_timed_setpoints_2_changes(self): def test_run_small_ates_timed_setpoints_0_changes(self): """ Run the small network with ATES and check that the setpoint changes as specified. - The milp source for producer_1 changes 8 times (consecutively) when no timed_setpoints are - specified. The 1 year milp demand profiles contains demand values: hourly (peak day), weekly + The heat source for producer_1 changes 8 times (consecutively) when no timed_setpoints are + specified. The 1 year heat demand profiles contains demand values: hourly (peak day), weekly (every 5days/120hours/432000s) and 1 time step of 4days (96hours/345600s, step before the start of the peak day). Now check that the time_setpoints can limit the setpoint changes to 0 changes/year. @@ -150,7 +149,7 @@ def test_run_small_ates_timed_setpoints_0_changes(self): base_folder = Path(run_ates.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblemSetPoints, base_folder=base_folder, esdl_file_name="test_case_small_network_with_ates.esdl", @@ -163,14 +162,14 @@ def test_run_small_ates_timed_setpoints_0_changes(self): check = abs( results["HeatProducer_1.Heat_source"][2:] - results["HeatProducer_1.Heat_source"][1:-1] ) - np.testing.assert_array_less(check, 1.0e-6) + np.testing.assert_array_less(check, 1.0e-5) @pytest.mark.fourth def test_run_small_ates_timed_setpoints_multiple_constraints(self): """ Run the small network with ATES and check that the setpoint changes as specified. - The milp source for producer_1 changes 8 times (consecutively) when no timed_setpoints are - specified. The 1 year milp demand profiles contains demand values: hourly (peak day), weekly + The heat source for producer_1 changes 8 times (consecutively) when no timed_setpoints are + specified. The 1 year heat demand profiles contains demand values: hourly (peak day), weekly (every 5days/120hours/432000s) and 1 time step of 4days (96hours/345600s, step before the start of the peak day). Now check that the time_setpoints can limit the setpoint changes to 1 changes over multiple window sizes. @@ -186,7 +185,7 @@ def test_run_small_ates_timed_setpoints_multiple_constraints(self): base_folder = Path(run_ates.__file__).resolve().parent.parent for ihrs in range(119, 122): - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblemSetPoints, base_folder=base_folder, esdl_file_name="test_case_small_network_with_ates.esdl", diff --git a/tests/test_temperature_ates_hp.py b/tests/test_temperature_ates_hp.py index cfb3fa899..e6623a4af 100644 --- a/tests/test_temperature_ates_hp.py +++ b/tests/test_temperature_ates_hp.py @@ -1,12 +1,11 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test @@ -42,7 +41,7 @@ def test_ates_temperature(self): basefolder = Path(run_ates_temperature.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblem, base_folder=basefolder, esdl_file_name="HP_ATES with return network.esdl", @@ -96,10 +95,6 @@ def test_ates_temperature(self): ) ) - feasibility = solution.solver_stats["return_status"] - - self.assertTrue((feasibility == "Optimal")) - np.testing.assert_allclose(objective_calc / 1e4, objective) np.testing.assert_array_less(ates_temperature_disc - tol, ates_temperature) @@ -132,7 +127,7 @@ def test_ates_temperature(self): # TODO: potentially update example such that the commented checks will also hold. # np.testing.assert_array_less(heat_pump_sec, geo_source) - charging = np.array([int(val > 0) for val in heat_ates]) + charging = np.array([int(val > tol) for val in heat_ates]) # array less then because ates charging boolean can be either 0 or 1 when there is no flow, # or just flow to compensate the heatloss np.testing.assert_array_less(np.ones(len(hex_disabled)) - tol, hex_disabled + hp_disabled) @@ -160,7 +155,7 @@ def test_ates_max_flow(self): basefolder = Path(run_ates_temperature.__file__).resolve().parent.parent - solution = run_optimization_problem( + solution = run_esdl_mesido_optimization( HeatProblemMaxFlow, base_folder=basefolder, esdl_file_name="HP_ATES with return network.esdl", diff --git a/tests/test_topo_constraints.py b/tests/test_topo_constraints.py index 74a2886f5..03c5c9b9d 100644 --- a/tests/test_topo_constraints.py +++ b/tests/test_topo_constraints.py @@ -3,18 +3,16 @@ from typing import Dict from unittest import TestCase +from mesido._heat_loss_u_values_pipe import pipe_heat_loss +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.pipe_class import PipeClass +from mesido.techno_economic_mixin import TechnoEconomicMixin +from mesido.util import run_esdl_mesido_optimization + import numpy as np import numpy.testing -from rtctools.util import run_optimization_problem - -from rtctools_heat_network._heat_loss_u_values_pipe import pipe_heat_loss -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile -from rtctools_heat_network.pipe_class import PipeClass -from rtctools_heat_network.techno_economic_mixin import TechnoEconomicMixin - - MIP_TOLERANCE = 1e-8 @@ -43,7 +41,7 @@ def setUpClass(cls) -> None: del root_folder sys.path.pop(1) - cls.problem = run_optimization_problem( + cls.problem = run_esdl_mesido_optimization( PipeDiameterSizingProblem, base_folder=base_folder, esdl_file_name="2a.esdl", @@ -175,15 +173,15 @@ class ordering variables are there to help the optimizer in seeing the relation np.testing.assert_almost_equal( heat_loss_ordering_var, 0.0, - err_msg=f"expected the milp loss order var for {p} and {pc=} to be 0.0, " - f"since {chosen_pc=} with higher milp losses", + err_msg=f"expected the heat loss order var for {p} and {pc=} to be 0.0, " + f"since {chosen_pc=} with higher heat losses", ) elif pc_heat_loss > chosen_pc_heat_loss: np.testing.assert_almost_equal( discharge_ordering_var, 1.0, - err_msg=f"Expected the milp loss order var for {p} and {pc=} to be 1.0, " - f"since {chosen_pc=} with lower milp losses", + err_msg=f"Expected the heat loss order var for {p} and {pc=} to be 1.0, " + f"since {chosen_pc=} with lower heat losses", ) for pc_name, total_count in pc_sums.items(): @@ -254,7 +252,7 @@ def get_chosen_pipe_class(self, pipe: str, pipe_class_vars: Dict[str, np.ndarray def get_heat_losses(self, pipe: str, pipe_class: PipeClass): """ - This function computes the expected milp loss for a pipe class. + This function computes the expected heat loss for a pipe class. Parameters ---------- @@ -263,7 +261,7 @@ def get_heat_losses(self, pipe: str, pipe_class: PipeClass): Returns ------- - Pipe milp loss value. + Pipe heat loss value. """ return pipe_heat_loss( self.problem, diff --git a/tests/test_updated_esdl_post_process.py b/tests/test_updated_esdl_post_process.py new file mode 100644 index 000000000..31f3f0ace --- /dev/null +++ b/tests/test_updated_esdl_post_process.py @@ -0,0 +1,325 @@ +import fnmatch +import os +import sys +from pathlib import Path +from unittest import TestCase + +import esdl +from esdl.esdl_handler import EnergySystemHandler + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.workflows import EndScenarioSizingStaged + + +import numpy as np + + +class TestUpdatedESDL(TestCase): + + def test_updated_esdl(self): + """ + Check that the updated ESDL resulting from the optmizer, is correct by using the PoCTutorial + and the Grow_workflow. This is done for the actual esdl file and the esdl string created by + MESIDO. Both these resulting optimized energy systems should be identical and it is only + the MESIDO esdl saving method that differs. + + Checks: + - That the esdl saving method (direct ESDL file and ESDL string) + - That the correct number of KPIs have been added + - Check that the OPEX costs for an asset with a 15 year lifetime == OPEX over optim time + horizon + - That the correct assets have been removed + - That all the assets have a state=ENABLED + - The diameter of all the pipes are as expected + - The aggregation count of the assets, MESIDO problem vs updated ESDL file + - That the KPI values are represented in the correct units + - That assets are connected and that the connections per ports were not changed in the + updated ESDL + - That the size of the source has been made small. Not checking the exact + value - not the purpose of these tests + - The correct number of polygon sub-areas exist + """ + + root_folder = str(Path(__file__).resolve().parent.parent) + sys.path.insert(1, root_folder) + + import examples.PoCTutorial.src.run_grow_tutorial + + base_folder = ( + Path(examples.PoCTutorial.src.run_grow_tutorial.__file__).resolve().parent.parent + ) + model_folder = base_folder / "model" + input_folder = base_folder / "input" + + problem = EndScenarioSizingStaged( + esdl_file_name="PoC Tutorial.esdl", + esdl_parser=ESDLFileParser, + base_folder=base_folder, + model_folder=model_folder, + input_folder=input_folder, + ) + problem.pre() + + # Load in optimized esdl in the form of esdl string created by MESIDO + esh = EnergySystemHandler() + file = os.path.join(base_folder, "model", "PoC Tutorial_GrowOptimized_esdl_string.esdl") + optimized_energy_system_esdl_string: esdl.EnergySystem = esh.load_file(file) + + # Load in optimized esdl in the form of the actual optimized esdl file created by MESIDO + esdl_path = os.path.join(base_folder, "model", "PoC Tutorial_GrowOptimized.esdl") + optimized_energy_system = problem._ESDLMixin__energy_system_handler.load_file(esdl_path) + + optimized_energy_systems = [optimized_energy_system_esdl_string, optimized_energy_system] + + for energy_system in optimized_energy_systems: + # Test KPIs in optimized ESDL + + # High level checks of KPIs + number_of_kpis_top_level_in_esdl = 11 + high_level_kpis_euro = [ + "High level cost breakdown [EUR] (yearly averaged)", + "High level cost breakdown [EUR] (30.0 year period)", + "Overall cost breakdown [EUR] (yearly averaged)", + "Overall cost breakdown [EUR] (30.0 year period)", + "CAPEX breakdown [EUR] (30.0 year period)", + "OPEX breakdown [EUR] (yearly averaged)", + "OPEX breakdown [EUR] (30.0 year period)", + "Area_76a7: Asset cost breakdown [EUR]", + "Area_9d0f: Asset cost breakdown [EUR]", + "Area_a58a: Asset cost breakdown [EUR]", + ] + high_level_kpis_wh = [ + "Energy production [Wh] (yearly averaged)", + ] + all_high_level_kpis = [] + all_high_level_kpis = high_level_kpis_euro + high_level_kpis_wh + + np.testing.assert_allclose( + len(energy_system.instance[0].area.KPIs.kpi), number_of_kpis_top_level_in_esdl + ) + np.testing.assert_allclose( + len(energy_system.instance[0].area.KPIs.kpi), len(all_high_level_kpis) + ) + + # Assign kpi info that has to be used for compairing optim time horizon vs yearly values + # kpi_name_list and kpi_label_list should be the same length and in the same order of + # which the comparison is done + compare_yearly_lifetime_kpis = { + # lists of 2 kpis that have to be compared + "kpi_name_list": [ + [ + "High level cost breakdown [EUR] (yearly averaged)", + "High level cost breakdown [EUR] (30.0 year period)", + ], + [ + "Overall cost breakdown [EUR] (yearly averaged)", + "Overall cost breakdown [EUR] (30.0 year period)", + ], + [ + "Overall cost breakdown [EUR] (yearly averaged)", + "Overall cost breakdown [EUR] (30.0 year period)", + ], + [ + "OPEX breakdown [EUR] (yearly averaged)", + "OPEX breakdown [EUR] (30.0 year period)", + ], + ], + # lists of which kpi label has to be compared for kpi_name_list + "kpi_label_list": [ + ["OPEX"], + ["Variable OPEX"], + ["Fixed OPEX"], + ["ResidualHeatSource"], + ], + "index_high_level_cost_list": [], # leave this empty, this list length is set below + } + for _ in range(len(compare_yearly_lifetime_kpis["kpi_name_list"])): + compare_yearly_lifetime_kpis["index_high_level_cost_list"].append([]) + if len(compare_yearly_lifetime_kpis["kpi_name_list"]) != len( + compare_yearly_lifetime_kpis["kpi_label_list"] + ): + print("List should be the same length") + exit(1) + + for ii in range(len(energy_system.instance[0].area.KPIs.kpi)): + kpi_name = energy_system.instance[0].area.KPIs.kpi[ii].name + np.testing.assert_array_equal( + kpi_name in all_high_level_kpis, + True, + err_msg=f"KPI name {kpi_name} was not expected in the ESDL", + ) + if kpi_name in high_level_kpis_euro: + np.testing.assert_array_equal( + energy_system.instance[0].area.KPIs.kpi[ii].quantityAndUnit.unit.name, + "EURO", + ) + elif kpi_name in high_level_kpis_wh: + np.testing.assert_array_equal( + energy_system.instance[0].area.KPIs.kpi[ii].quantityAndUnit.unit.name, + "WATTHOUR", + ) + else: + exit(f"Unexpected KPI name: {kpi_name}") + + # Check optim time horizon vs yearly cost when the lifetime value is + # 15 years + for il in range(len(compare_yearly_lifetime_kpis["kpi_name_list"])): + + if kpi_name in compare_yearly_lifetime_kpis["kpi_name_list"][il]: + compare_yearly_lifetime_kpis["index_high_level_cost_list"][il].append(ii) + if len(compare_yearly_lifetime_kpis["index_high_level_cost_list"][il]) == 2: + for iitem in range( + len( + energy_system.instance[0] + .area.KPIs.kpi[ii] + .distribution.stringItem.items + ) + ): + if ( + energy_system.instance[0] + .area.KPIs.kpi[ + compare_yearly_lifetime_kpis["index_high_level_cost_list"][ + il + ][0] + ] + .distribution.stringItem.items[iitem] + .label + in compare_yearly_lifetime_kpis["kpi_label_list"][il] + ): + + max_value = max( + energy_system.instance[0] + .area.KPIs.kpi[ + compare_yearly_lifetime_kpis[ + "index_high_level_cost_list" + ][il][0] + ] + .distribution.stringItem.items[iitem] + .value, + energy_system.instance[0] + .area.KPIs.kpi[ + compare_yearly_lifetime_kpis[ + "index_high_level_cost_list" + ][il][1] + ] + .distribution.stringItem.items[iitem] + .value, + ) + min_value = min( + energy_system.instance[0] + .area.KPIs.kpi[ + compare_yearly_lifetime_kpis[ + "index_high_level_cost_list" + ][il][0] + ] + .distribution.stringItem.items[iitem] + .value, + energy_system.instance[0] + .area.KPIs.kpi[ + compare_yearly_lifetime_kpis[ + "index_high_level_cost_list" + ][il][1] + ] + .distribution.stringItem.items[iitem] + .value, + ) + # Lifetime of 15 years and the optim time horizon is 30 years + np.testing.assert_allclose(min_value * 15.0 * 2.0, max_value) + # make ssure that all the items in kpi_name_list was checked + for il in range(len(compare_yearly_lifetime_kpis["kpi_name_list"])): + np.testing.assert_equal( + len(compare_yearly_lifetime_kpis["index_high_level_cost_list"][il]), 2 + ) + + # Check the asset quantity + number_of_assets_in_esdl = 15 + np.testing.assert_allclose( + len(energy_system.instance[0].area.asset), number_of_assets_in_esdl + ) + # Check: + # - that the correct assets were removed + # - asset state + # - pipe diameter sizes + # - asset aggregation count + # - number of ports + # - number of connection to a port + asset_to_be_deleted = ["ResidualHeatSource_76f0", "Pipe_8fa5_ret", "Pipe_8fa5"] + for ii in range(len(energy_system.instance[0].area.asset)): + asset_name = energy_system.instance[0].area.asset[ii].name + # Existance of asset and its state + np.testing.assert_array_equal( + asset_name not in asset_to_be_deleted, + True, + err_msg=f"Asset name {asset_name} was not expected in the ESDL", + ) + np.testing.assert_array_equal( + energy_system.instance[0].area.asset[ii].state.name == "ENABLED", True + ) + + # Check pipe diameter + if len(fnmatch.filter([energy_system.instance[0].area.asset[ii].id], "Pipe*")) == 1: + if asset_name in ["Pipe1", "Pipe1_ret"]: + np.testing.assert_array_equal( + energy_system.instance[0].area.asset[ii].diameter.name, "DN250" + ) # original pipe DN400 being sized + elif asset_name in ["Pipe4", "Pipe4_ret"]: + np.testing.assert_array_equal( + energy_system.instance[0].area.asset[ii].diameter.name, "DN200" + ) # original pipe DN900 being sized + elif asset_name not in ["Pipe5", "Pipe5_ret"]: + np.testing.assert_array_equal( + energy_system.instance[0].area.asset[ii].diameter.name, "DN400" + ) # pipe DN was not sized and should be the same as specified in the ESDL + else: + np.testing.assert_array_equal( + energy_system.instance[0].area.asset[ii].diameter.name, + "DN300", + err_msg=f"Asset name {asset_name} was not expected in the ESDL", + ) # pipe DN was not sized and should be the same as specified in the ESDL + # Check aggregation count + np.testing.assert_array_equal( + energy_system.instance[0].area.asset[ii].aggregationCount, + problem.get_aggregation_count_max(asset_name), + ) + # Check the number of ports of the assets are as expected + np.testing.assert_array_equal( + len(energy_system.instance[0].area.asset[ii].port), + len(problem.esdl_assets[asset_name].in_ports) + + len(problem.esdl_assets[asset_name].out_ports), + ) + # Check the number of connection to a port + energy_system.instance[0].area.asset[ii].port[1].name + for iport in range(len(energy_system.instance[0].area.asset[ii].port)): + if energy_system.instance[0].area.asset[ii].port[iport].name == "In": + np.testing.assert_array_equal( + len( + energy_system.instance[0] + .area.asset[ii] + .port[iport] + .connectedTo.items + ), + len(problem.esdl_assets[asset_name].in_ports), + ) + if asset_name == "ResidualHeatSource_72d7": + asset_id = energy_system.instance[0].area.asset[ii].id + np.testing.assert_array_less( + energy_system.instance[0].area.asset[ii].power, + problem.esdl_assets[asset_id].attributes["power"], + ) + + # High level check on the polygon areas drawn + number_of_areas_in_esdl = 3 + np.testing.assert_allclose( + len(energy_system.instance[0].area.area), number_of_areas_in_esdl + ) + + +if __name__ == "__main__": + import time + + start_time = time.time() + + a = TestUpdatedESDL() + a.test_updated_esdl() + + print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) diff --git a/tests/test_updated_esdl_pre_process.py b/tests/test_updated_esdl_pre_process.py new file mode 100644 index 000000000..23e619029 --- /dev/null +++ b/tests/test_updated_esdl_pre_process.py @@ -0,0 +1,136 @@ +import sys +from pathlib import Path +from unittest import TestCase + +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.workflows import run_end_scenario_sizing + +import numpy as np + +from utils_test_scaling import create_problem_with_debug_info # , problem_scaling_check + +from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test + + +class TestUpdatedESDL(TestCase): + def test_updated_esdl(self): + """ + Check that the updated ESDL resulting from optmizing a network, is correct by using the + PoCTutorial and the Grow_workflow. This is done for the actual esdl file and the esdl + string created by MESIDO. Both these resulting optimized energy systems should be identical + and it is only the MESIDO esdl saving method that differs. + + Additional checks: + - Check that the unique profile identification in profile_parser assigns the correct + profile + - Check that the correct mulitpler value has been used + - Test limiting the pipe classes for a pipe connected to a heat demand + + """ + + root_folder = str(Path(__file__).resolve().parent.parent) + sys.path.insert(1, root_folder) + + import examples.PoCTutorial.src.run_grow_tutorial + from examples.PoCTutorial.src.run_grow_tutorial import EndScenarioSizingStagedHighs + + base_folder = ( + Path(examples.PoCTutorial.src.run_grow_tutorial.__file__).resolve().parent.parent + ) + + optimscaling, logger, logs_list = create_problem_with_debug_info( + EndScenarioSizingStagedHighs + ) + + problem = run_end_scenario_sizing( + optimscaling, + base_folder=base_folder, + esdl_file_name="PoC Tutorial.esdl", + esdl_parser=ESDLFileParser, + ) + + # This code below is used to do manual check. Do not delete + # problem_scaling_check(logs_list, logger) + + # Save optimized esdl string + optimized_esdl_string = problem.optimized_esdl_string + file = open( + Path.joinpath(base_folder, "model", "PoC Tutorial_GrowOptimized_esdl_string.esdl"), "w" + ) + file.write(optimized_esdl_string) + file.close() + + demand_matching_test(problem, problem.extract_results()) + energy_conservation_test(problem, problem.extract_results()) + heat_to_discharge_test(problem, problem.extract_results()) + + # Check the unique profile identification in profile_parser + # Test that the correct demand profile is assigned to a demand as expected. Note that the + # demand profiles are the adapted profiles (peak-hourly, rest-5daily). Therefore the + # expected max and average hard-coded values are compared to the problem values. + np.testing.assert_allclose( + 8857200.0, + max(problem.get_timeseries("HeatingDemand_b0ff.target_heat_demand").values), + # demand4_MW, multiplier 0.75, same demand profile as demand HeatingDemand_08fd, but + # with a different multiplier. So one would expect that this value differs from + # HeatingDemand_08fd + ) + np.testing.assert_allclose( + 724680.0, # demand5_MW, multiplier 0.33 + max(problem.get_timeseries("HeatingDemand_8fbe.target_heat_demand").values), + ) + np.testing.assert_allclose( + 805200.0, # demand4_MW, multiplier 0.5 + max(problem.get_timeseries("HeatingDemand_08fd.target_heat_demand").values), + ) + np.testing.assert_allclose( + 3484288.0247, # demand4_MW, multiplier 5.5 + np.average(problem.get_timeseries("HeatingDemand_b0ff.target_heat_demand").values), + ) + np.testing.assert_allclose( + 285078.111, # demand5_MW, multiplier 0.3 + np.average(problem.get_timeseries("HeatingDemand_8fbe.target_heat_demand").values), + ) + np.testing.assert_allclose( + 316753.457, # demand4_MW, multiplier 0.5 + np.average(problem.get_timeseries("HeatingDemand_08fd.target_heat_demand").values), + ) + + # Check that the correct multiplier value was used + # Compare 2 max values where the same profile was used but with different multiplier values + # HeatingDemand_08fd: multiplier 0.5 + # HeatingDemand_b0ff: multplier 5.5 + np.testing.assert_allclose( + max(problem.get_timeseries("HeatingDemand_08fd.target_heat_demand").values) / 0.5, + max(problem.get_timeseries("HeatingDemand_b0ff.target_heat_demand").values) / 5.5, + ) + np.testing.assert_allclose( + np.average(problem.get_timeseries("HeatingDemand_08fd.target_heat_demand").values) + / 0.5, + np.average(problem.get_timeseries("HeatingDemand_b0ff.target_heat_demand").values) + / 5.5, + ) + + # Test limiting the pipe classes for a pipe connected to a heat demand/producer + # Pipe connected to a demand + # Check that Pipe4 has 2 of pipe classes available, and that DN0 has not been + # included in the list of avialbel pipe classes. Pipe4 started as an optional pipe with + # DN900 as the starting point for the upper limit. + for key in problem._heat_pipe_topo_pipe_class_map["Pipe4"].keys(): + np.testing.assert_equal(key.name in ["DN150", "DN200"], True) + # Pipe connected to a producer + # initially DN900 + np.testing.assert_equal( + [*problem._heat_pipe_topo_pipe_class_map["Pipe1"].keys()][-1].name == "DN400", True + ) + + +if __name__ == "__main__": + import time + + start_time = time.time() + + a = TestUpdatedESDL() + a.test_updated_esdl() + + print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) diff --git a/tests/test_validation_pandapipes.py b/tests/test_validation_pandapipes.py new file mode 100644 index 000000000..a91da05a8 --- /dev/null +++ b/tests/test_validation_pandapipes.py @@ -0,0 +1,327 @@ +import os +import sys +from pathlib import Path +from unittest import TestCase + +from mesido.constants import GRAVITATIONAL_CONSTANT +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.head_loss_class import HeadLossOption +from mesido.util import run_esdl_mesido_optimization + +import numpy as np + +import pandapipes as pp +from pandapipes.timeseries import run_timeseries + +import pandapower.control as control +from pandapower.timeseries import DFData +from pandapower.timeseries import OutputWriter + +import pandas as pd + +from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test + + +class ValidateWithPandaPipes(TestCase): + """ + Test case for a heat network consisting out of a source, pipe(s) and a sink + """ + + def test_heat_network_head_loss(self): + """ + Heat network: compare the piecewise linear inequality constraints of the head loss + approximation to pandapipes + + Checks: + - head losses + - cp value + - check pandapipes values + """ + root_folder = str(Path(__file__).resolve().parent.parent) + sys.path.insert(1, root_folder) + + import examples.pandapipes.src.run_example + from examples.pandapipes.src.run_example import HeatProblemHydraulic + + base_folder = Path(examples.pandapipes.src.run_example.__file__).resolve().parent.parent + + class SourcePipeSinkNetwork(HeatProblemHydraulic): + + def energy_system_options(self): + options = super().energy_system_options() + self.heat_network_settings["head_loss_option"] = ( + HeadLossOption.LINEARIZED_N_LINES_WEAK_INEQUALITY + ) + self.heat_network_settings["n_linearization_lines"] = 10 + + self.heat_network_settings["minimum_velocity"] = 0.0 + + return options + + def times(self, variable=None) -> np.ndarray: + """ + Shorten the timeseries to speed up the test + + Parameters + ---------- + variable : string with name of the variable + + Returns + ------- + The timeseries + """ + return super().times(variable)[:10] + + demand_time_series_file = "timeseries_constant.csv" + + solution = run_esdl_mesido_optimization( + SourcePipeSinkNetwork, + base_folder=base_folder, + esdl_file_name="Test_Tree_S1C1.esdl", + esdl_parser=ESDLFileParser, + profile_reader=ProfileReaderFromFile, + input_timeseries_file=demand_time_series_file, + ) + results = solution.extract_results() + + demand_matching_test(solution, results) + energy_conservation_test(solution, results) + heat_to_discharge_test(solution, results) + + # ------------------------------------------------------------------------------ + # ------------------------------------------------------------------------------ + # Setup and run pandapipes + # ------------------------------------------------------------------------------ + # ------------------------------------------------------------------------------ + from examples.pandapipes.src.pandapipeesdlparser import PandapipeEsdlParserClass + + esdl_file = os.path.join(base_folder, "model", "Test_Tree_S1C1.esdl") + esdlparser = PandapipeEsdlParserClass() + esdlparser.loadESDLFile(esdl_file) + # A producer/consumer cannot directly connect to a pipe, but must be connected to a joint, + # therefore additional joints created for the inlet & outlet of these assets + esdlparser.add_additional_joint() + + # ------------------------------------------------------------------------------ + # ------------------------------------------------------------------------------ + # Setup scenario + total_producers = len(esdlparser.esdl_asset["heat"]["producer"]) + total_consumers = len(esdlparser.esdl_asset["heat"]["consumer"]) + + # Create panda_pipes network + net, net_asset, supply_temperature, return_temperature = esdlparser.createpandapipenet() + + # Setup profile data + raw_profile_demand_load_watt = pd.read_csv( + os.path.join(base_folder, "input", demand_time_series_file) + ) + profile_demand_load_watt = pd.DataFrame(columns=["0"]) + profile_demand_load_watt["0"] = raw_profile_demand_load_watt["demand_1"] + + demand_power = profile_demand_load_watt["0"].to_numpy() / total_consumers + profile_demand_load_watt = pd.DataFrame(results["demand_1.Heat_demand"]) + + # Setup supply mass flow for panda_pipes + average_temperature_kelvin = (supply_temperature + return_temperature) / 2.0 + 273.15 + cp_joule_kgkelvin = pp.get_fluid(net).get_heat_capacity(average_temperature_kelvin) + + # Enforce mass flow rate instead of cacluting it from Q = m_dot... + mesido_demand_flow_kg_s = results["Pipe1.Q"] * 988.0 + demand_flow = mesido_demand_flow_kg_s + supply_flow = demand_flow * total_consumers / total_producers + + # Below control is needed when there is more than 1 producer/heat demand + net.flow_control.control_active[0] = False # 1st supplier + net.flow_control.control_active[0 + total_producers] = False # 1st demand + + # Assign profiles to the following assets: + # - producer mass flow rate, supply temperature + # - heat demand power + # Producer + isupply = 0 + supply_flow_kg_s = pd.DataFrame(supply_flow, columns=[f"{isupply}"]) + ds_supply_pump_flow_kg_s = DFData(supply_flow_kg_s) + control.ConstControl( + net, + element="circ_pump_mass", + variable="mdot_flow_kg_per_s", + element_index=net.circ_pump_mass.index.values[isupply], + data_source=ds_supply_pump_flow_kg_s, + profile_name=net.circ_pump_mass.index.values[isupply].astype(str), + ) + supply_temp_kelvin = pd.DataFrame( + [supply_temperature + 273.15] * len(profile_demand_load_watt), + columns=[f"{isupply}"], + ) + df_supply_pump_temperature_kelvin = DFData(supply_temp_kelvin) + control.ConstControl( + net, + element="circ_pump_mass", + variable="t_flow_k", + element_index=net.circ_pump_mass.index.values[isupply], + data_source=df_supply_pump_temperature_kelvin, + profile_name=net.circ_pump_mass.index.values[isupply].astype(str), + ) + + # Demand settings + idemand = 0 + demand_power_watt = pd.DataFrame(demand_power, columns=[f"{idemand}"]) + ds_demand_power_watt = DFData(demand_power_watt) + control.ConstControl( + net, + element="heat_exchanger", + variable="qext_w", + element_index=net.heat_exchanger.index.values[idemand], + data_source=ds_demand_power_watt, + profile_name=net.heat_exchanger.index.values[idemand].astype(str), + ) + + if profile_demand_load_watt.shape[0] != supply_flow_kg_s.shape[0]: + exit("profiles do not match") + # Completed scenario setup + + # ------------------------------------------------------------------------------ + # ------------------------------------------------------------------------------ + # Run panda_pipes simulation + time_steps = range(profile_demand_load_watt.shape[0]) + log_variables = [ + ("res_pipe", "v_mean_m_per_s"), + ("res_pipe", "p_from_bar"), + ("res_pipe", "p_to_bar"), + ("res_pipe", "mdot_from_kg_per_s"), + ("heat_exchanger", "qext_w"), + ] + ow = OutputWriter( + net, + time_steps, + output_path=None, + log_variables=log_variables, + ) + + try: + run_timeseries(net, time_steps, mode="all", friction_model="colebrook") + except Exception as e: + print(e) + exit("Pandapipes runs was not successful") + + # ------------------------------------------------------------------------------ + # Post processing panda_pipes results and tests + net = esdlparser.correcting_pressure_return(net) + ow.np_results["heat_exchanger.qext_w"] + mdata_points = len(mesido_demand_flow_kg_s) + + density = ( + ow.np_results["res_pipe.mdot_from_kg_per_s"][0:mdata_points] + / ow.np_results["res_pipe.v_mean_m_per_s"][0:mdata_points] + / (np.pi * net.pipe.diameter_m[0] * net.pipe.diameter_m[0] / 4.0) + ) + pandapipes_head_loss_m = ( + ( + ow.np_results["res_pipe.p_to_bar"][0:mdata_points] + - ow.np_results["res_pipe.p_from_bar"][0:mdata_points] + ) + * 100.0e3 + / density[0][0] + / GRAVITATIONAL_CONSTANT + ) + + # Compare head losses + # Hard coded value of 9 used below, since the last data entry has value close to 0, and + # a comparison is not of importance + for ii in range(len(results["Pipe1.dH"][:9])): + np.testing.assert_array_less( + pandapipes_head_loss_m[ii][0], 0.0 + ) # check that values are negative + # check that mesido > pandapipes within % + np.testing.assert_array_less( + results["Pipe1.dH"][ii] / pandapipes_head_loss_m[ii][0], 1.08 + ) + np.testing.assert_array_less( + 1.0, results["Pipe1.dH"][ii] / pandapipes_head_loss_m[ii][0] + ) + # Check cp value + np.testing.assert_allclose(4200.0, cp_joule_kgkelvin) + + # Check panpapipes results + # Expected results (during validation) during validation work + expected_dh = { # + "pandapipes": [ + -1.34309074e01, + -1.06285745e01, + -8.15362473e00, + -6.00606036e00, + -4.18588773e00, + -2.69436747e00, + -1.52897525e00, + -6.91030646e-01, + -1.80687567e-01, + -2.05221922e-05, + ], + } + for ii in range(len(pandapipes_head_loss_m)): + np.testing.assert_allclose(expected_dh["pandapipes"][ii], pandapipes_head_loss_m[ii][0]) + + # ------------------------------------------------------------------------------------------ + # Do not delete the code below. + # ------------------------------------------------------------------------------------------ + + # # Plotting code for manual checking values + # import matplotlib.pyplot as plt + + # # Setup data for easy plotting + # velo_m_s = { + # "pandapipes": [], + # "mesido": results["Pipe1.HeatIn.Q"] / solution.parameters(0)["Pipe1.area"], + # } + # head_loss_m = { + # "pandapipes": [], + # "mesido": -results["Pipe1.dH"], + # } + # for ii in range(len(ow.np_results["res_pipe.v_mean_m_per_s"])): + # velo_m_s["pandapipes"].append(ow.np_results["res_pipe.v_mean_m_per_s"][ii][0]) + # head_loss_m["pandapipes"].append(-pandapipes_head_loss_m[ii][0]) + + # # Plot data + # plt.figure().set_size_inches(10, 6) + # plt.plot(velo_m_s["pandapipes"], head_loss_m["pandapipes"], linewidth=2) + # plt.plot( + # velo_m_s["mesido"], + # head_loss_m["mesido"], + # "k--", + # linewidth=2, + # alpha=0.75, + # marker="x" + # ) + + # plt.legend(["pandapipes", "MESIDO"], prop={'size': 13}) + # plt.xlabel("Flow velocity [m/s]", fontsize=16) + # plt.ylabel("Head loss [m]", fontsize=16) + # plt.grid() + # plt.xticks(np.linspace(0, 2.5, 6), fontsize=16) + # plt.yticks( + # np.linspace(0, 15.0, 7), + # labels=["0.0", "2.5", "5.0", "7.5", "10.0", "12.5", "15.0"], + # fontsize=16, + # ) + # plt.xlim([0., 2.5]) + # plt.tick_params(left=False, right=False, labelleft=False) + # plt.ylim([0., 15.]) + # plt.tick_params(left=True, right=False, labelleft=True) + # n_lines = solution.heat_network_settings["n_linearization_lines"] + # plt.savefig(f"dH MESIDO_{n_lines} vs pandapipes") + # plt.show() + # plt.close() + + # end Plotting code for manual checking values + # ------------------------------------------------------------------------------------------ + + +if __name__ == "__main__": + import time + + start_time = time.time() + a = ValidateWithPandaPipes() + a.test_heat_network_head_loss() + + print("Execution time: " + time.strftime("%M:%S", time.gmtime(time.time() - start_time))) diff --git a/tests/test_varying_temperature.py b/tests/test_varying_temperature.py index ef74c15e8..2db1d2488 100644 --- a/tests/test_varying_temperature.py +++ b/tests/test_varying_temperature.py @@ -1,13 +1,12 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido._heat_loss_u_values_pipe import pipe_heat_loss +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network._heat_loss_u_values_pipe import pipe_heat_loss -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test @@ -17,15 +16,15 @@ def test_1a_temperature_variation(self): """ This test is to check if the varying network temperature works as expected on a simple network. We give it temperature options such that it should select a minimum delta T to be - able to meet the milp demands. It is known which network temperatures should be selected + able to meet the heat demands. It is known which network temperatures should be selected based on the specified input values. Checks: - - Standard checks for demand matching, milp to discharge and energy conservation + - Standard checks for demand matching, heat to discharge and energy conservation - Check expected supply temperature - Check expected return temperature - Check on integer variable for selected temperature. - - Check if the milp losses are correct for the selected temperature + - Check if the heat losses are correct for the selected temperature """ import models.unit_cases.case_1a.src.run_1a as run_1a @@ -33,7 +32,7 @@ def test_1a_temperature_variation(self): base_folder = Path(run_1a.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblemTvar, base_folder=base_folder, esdl_file_name="1a.esdl", @@ -83,13 +82,13 @@ def test_1a_temperature_variation(self): def test_3a_temperature_variation_supply(self): """ Check varying temperature behoviour for network with storage (tank). In this case we - Minimise the produced milp and thus we expect the lowest temperature to be selected. + Minimise the produced heat and thus we expect the lowest temperature to be selected. Checks: - - Standard checks for demand matching, milp to discharge and energy conservation. + - Standard checks for demand matching, heat to discharge and energy conservation. - Check if the expected temperature is selected and if temperature variable is set correctly. - - Check if the milp losses are correct for the selected temperature + - Check if the heat losses are correct for the selected temperature """ import models.unit_cases.case_3a.src.run_3a as run_3a @@ -97,7 +96,7 @@ def test_3a_temperature_variation_supply(self): base_folder = Path(run_3a.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblemTvarsup, base_folder=base_folder, esdl_file_name="3a.esdl", @@ -110,11 +109,11 @@ def test_3a_temperature_variation_supply(self): test.assertTrue(heat_problem.solver_stats["success"], msg="Optimisation did not succeed") # optimization with two choices in supply temp 80 and 120 deg - # lowest temperature should be selected because of lower milp losses and - # milp production minimization goal + # lowest temperature should be selected because of lower heat losses and + # heat production minimization goal results = heat_problem.extract_results() - # Check whehter the milp demand is matched + # Check whehter the heat demand is matched for d in heat_problem.energy_system_components.get("heat_demand", []): target = heat_problem.get_timeseries(f"{d}.target_heat_demand").values[ : len(heat_problem.times()) @@ -158,10 +157,10 @@ def test_3a_temperature_variation_return(self): to maximise the detla T. Checks: - - Standard checks for demand matching, milp to discharge and energy conservation. + - Standard checks for demand matching, heat to discharge and energy conservation. - Check if the expected temperature is selected and if temperature variable is set correctly. - - Check if the milp losses are correct for the selected temperature + - Check if the heat losses are correct for the selected temperature """ import models.unit_cases.case_3a.src.run_3a as run_3a @@ -169,7 +168,7 @@ def test_3a_temperature_variation_return(self): base_folder = Path(run_3a.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblemTvarret, base_folder=base_folder, esdl_file_name="3a.esdl", @@ -218,13 +217,13 @@ def test_3a_temperature_variation_return(self): def test_hex_temperature_variation(self): """ - This test is to check whether the milp exchanger behaves as expected when optimized under + This test is to check whether the heat exchanger behaves as expected when optimized under varying network temperature. This is of special interest as we want to ensure the temperatures stay physically feasible, therefore we create a problem where the lowest available supply T is infeasible. Checks: - - Standard checks for demand matching, milp to discharge and energy conservation. + - Standard checks for demand matching, heat to discharge and energy conservation. - Check that the infeasible temperature is not selected. """ @@ -233,7 +232,7 @@ def test_hex_temperature_variation(self): base_folder = Path(run_heat_exchanger.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblemTvar, base_folder=base_folder, esdl_file_name="heat_exchanger.esdl", @@ -285,12 +284,12 @@ def test_hex_temperature_variation(self): def test_hex_temperature_variation_disablehex(self): """ - This test is to check if the optimizer disables the milp exchanger when only infeasible + This test is to check if the optimizer disables the heat exchanger when only infeasible temperature option are provided to it. Checks: - - Standard checks for demand matching, milp to discharge and energy conservation. - - Infeasible T for milp exchanger is selected. + - Standard checks for demand matching, heat to discharge and energy conservation. + - Infeasible T for heat exchanger is selected. - Heat exchanger is disabled. """ @@ -299,7 +298,7 @@ def test_hex_temperature_variation_disablehex(self): base_folder = Path(run_heat_exchanger.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblemTvarDisableHEX, base_folder=base_folder, esdl_file_name="heat_exchanger.esdl", @@ -312,7 +311,7 @@ def test_hex_temperature_variation_disablehex(self): test.assertTrue(heat_problem.solver_stats["success"], msg="Optimisation did not succeed") # optimization with only one option in temperature which is infeasible for the hex. - # therefore optimization should disable the milp exchanger + # therefore optimization should disable the heat exchanger results = heat_problem.extract_results() # Check that the problem has an infeasible temperature for the hex @@ -327,12 +326,12 @@ def test_hex_temperature_variation_disablehex(self): def test_hex_temperature_variation_secondary(self): """ - Check to see the functioning of the varying network temperature with a milp exchanger where + Check to see the functioning of the varying network temperature with a heat exchanger where all options are feasible and we expect it to take the most advantageous one, which in this case is the lowest one. Checks: - - Standard checks for demand matching, milp to discharge and energy conservation. + - Standard checks for demand matching, heat to discharge and energy conservation. - Check that lowest temperature is selected and set correctly. """ @@ -341,7 +340,7 @@ def test_hex_temperature_variation_secondary(self): base_folder = Path(run_heat_exchanger.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblemTvarSecondary, base_folder=base_folder, esdl_file_name="heat_exchanger.esdl", @@ -354,8 +353,8 @@ def test_hex_temperature_variation_secondary(self): test.assertTrue(heat_problem.solver_stats["success"], msg="Optimisation did not succeed") # optimization with two choices in secondary supply temp 70 and 90 deg - # lowest temperature should be selected because of milp minimization and lower T has - # lower milp loss. + # lowest temperature should be selected because of heat minimization and lower T has + # lower heat loss. results = heat_problem.extract_results() # Check that the lowest temperature (70.0) is the outputted temperature @@ -379,7 +378,7 @@ def test_heat_pump_varying_temperature(self): base_folder = Path(run_heat_pump.__file__).resolve().parent.parent - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblemTvar, base_folder=base_folder, esdl_file_name="heat_pump.esdl", diff --git a/tests/test_warmingup_unit_cases.py b/tests/test_warmingup_unit_cases.py index acffdbc06..ad1ac9876 100644 --- a/tests/test_warmingup_unit_cases.py +++ b/tests/test_warmingup_unit_cases.py @@ -1,12 +1,11 @@ from pathlib import Path from unittest import TestCase -import numpy as np - -from rtctools.util import run_optimization_problem +from mesido.esdl.esdl_parser import ESDLFileParser +from mesido.esdl.profile_parser import ProfileReaderFromFile +from mesido.util import run_esdl_mesido_optimization -from rtctools_heat_network.esdl.esdl_parser import ESDLFileParser -from rtctools_heat_network.esdl.profile_parser import ProfileReaderFromFile +import numpy as np from utils_tests import demand_matching_test, energy_conservation_test, heat_to_discharge_test @@ -21,7 +20,7 @@ def test_1a(self): - Demand matching - Energy conservation - Heat to discharge - - Checks for conservation of flow and milp at the node + - Checks for conservation of flow and heat at the node - Check for equal head at all node connections - Checks that the minimum pressure-drop constraints at the demand are satisfied - Check that Heat_demand & Heat_source are set correctly and are linked to the Heat_flow @@ -34,7 +33,7 @@ def test_1a(self): base_folder = Path(run_1a.__file__).resolve().parent.parent # Just a "problem is not infeasible" - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="1a.esdl", @@ -103,7 +102,7 @@ def test_2a(self): base_folder = Path(run_2a.__file__).resolve().parent.parent # Just a "problem is not infeasible" - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="2a.esdl", @@ -129,8 +128,8 @@ def test_3a(self): direction for the pipe connected to the buffer tank) - Check that the Heat_buffer & Heat_flow variable are set correctly - Check that the history for the buffer is set correctly at t=0 - - Check that the milp loss is positive and as expected - - Check that the Stored milp is the sum of (dis)charge and losses + - Check that the heat loss is positive and as expected + - Check that the Stored heat is the sum of (dis)charge and losses """ import models.unit_cases.case_3a.src.run_3a as run_3a @@ -139,7 +138,7 @@ def test_3a(self): base_folder = Path(run_3a.__file__).resolve().parent.parent # Just a "problem is not infeasible" - heat_problem = run_optimization_problem( + heat_problem = run_esdl_mesido_optimization( HeatProblem, base_folder=base_folder, esdl_file_name="3a.esdl", @@ -171,7 +170,7 @@ def test_3a(self): results[f"{buffer}.HeatIn.Heat"] - results[f"{buffer}.HeatOut.Heat"], results[f"{buffer}.Heat_buffer"], ) - # buffer should have positive milp loss + # buffer should have positive heat loss assert parameters[f"{buffer}.heat_loss_coeff"] > 0.0 np.testing.assert_allclose( results[f"{buffer}.Stored_heat"] * parameters[f"{buffer}.heat_loss_coeff"], @@ -184,6 +183,12 @@ def test_3a(self): results[f"{buffer}.Stored_heat"][-1] - results[f"{buffer}.Stored_heat"][0], np.sum(results[f"{buffer}.Heat_buffer"][1:] * 3600.0) - np.sum(results[f"{buffer}.Heat_loss"][1:] * 3600.0), - atol=1.0e-3, + atol=1.0, ) np.testing.assert_allclose(results[f"{buffer}.Heat_buffer"][0], 0.0, atol=1.0e-6) + + np.testing.assert_allclose( + results[f"{buffer}.dH"][inds], + results[f"{buffer}.HeatOut.H"][inds] - results[f"{buffer}.HeatIn.H"][inds], + atol=1.0e-6, + ) diff --git a/tests/utils_test_scaling.py b/tests/utils_test_scaling.py new file mode 100644 index 000000000..6362d4ce8 --- /dev/null +++ b/tests/utils_test_scaling.py @@ -0,0 +1,112 @@ +import logging +import math +import re + +from rtctools._internal.debug_check_helpers import DebugLevel + + +def create_log_list_scaling(logger_name): + """ + Creation of a list for the logs which will be filled with the logging information of the + problem. + :return: + """ + + class LogRecordsListHandler(logging.Handler): + """ + Handler class to store log entries in a list + """ + + def __init__(self, records_list): + self.records_list = records_list + super().__init__() + + def emit(self, record): + self.records_list.append(record) + + logs_list = [] + + logger = logging.getLogger(logger_name) + logger.setLevel(logging.INFO) + + logger.addHandler(LogRecordsListHandler(logs_list)) + + return logger, logs_list + + +def create_problem_with_debug_info(problem_class): + """ + The problem class that needs to be executed is updated with a debuglevel to + ensure that the information about the scaling is logged. Furthermore, the logging list is + created to allow for backtracking and check scaling information. + :param problem_class: The problem class that should be executed + :return: + The problem class including its debuglevel and the logging list and logger. + """ + # TODO: currently only the default settings can be used to check the scaling. + logger, logs_list = create_log_list_scaling("rtctools") + + class ProblemClassScaling(problem_class): + _debug_check_level = DebugLevel.VERYHIGH + + return ProblemClassScaling, logger, logs_list + + +def check_order(dict_values, maximum_order_diff): + """ + Checks the difference in order between the lower and upperbound of several problem settings; + objective, matrix and right hand side. + :param dict_values: dictionary with the different problem settings and their respective lower + and upperbound + :param maximum_order_diff: the maximum difference that is allowed. + :return: + """ + msg_order = {} + for key, value in dict_values.items(): + if value[0] != 0.0: + order = value[1] / value[0] + else: + order = value[1] + if order > maximum_order_diff: + order_wrong = math.floor(math.log(order, 10)) + msg_order[key] = ( + f"The scaling of this problem is not great, for the {key}, the values are {value} " + f"which is of the order {order_wrong}, {maximum_order_diff} is the maximum allowed " + f"order difference." + ) + assert len(msg_order) == 0, msg_order + + +def problem_scaling_check(logs_list, logger, order_diff=1e6): + """ + Checks the difference in order between the lower and upperbound of several problem settings; + objective, matrix and rhs. + These settings are first to be extracted from the logging information. + :param logs_list: The list containing all the logs. + :param logger: The logger that logs information, warnings and errors depending on the level set. + :param order_diff: The maximum difference between the lower and upperbound. + :return: + """ + linear_coeff_log = [ + log for log in logs_list if "__debug_check_transcribe_linear_coefficients" in log.funcName + ] + range_data = {} + for log in linear_coeff_log: + if ( + "Statistics of constraints: max & min of abs(jac(g, x0))), " "max & min of abs(g(x0))" + ) == log.msg: + data = linear_coeff_log[linear_coeff_log.index(log) + 1] + data_str = re.findall(r"[-+]?\d*\.\d+|\d+", data.msg) + range_data["matrix"] = [float(data_str[1]), float(data_str[0])] + range_data["rhs"] = [float(data_str[3]), float(data_str[2])] + elif ("Statistics of objective: max & min of abs(jac(f,") in log.msg: + data = linear_coeff_log[linear_coeff_log.index(log) + 1] + data_str = re.findall(r"[-+]?\d*\.\d+|\d+", data.msg) + if len(data_str) > 2: + range_data["objective_matrix"] = [float(data_str[1]), float(data_str[0])] + range_data["objective"] = [float(data_str[3]), float(data_str[2])] + else: + range_data["objective"] = [float(data_str[1]), float(data_str[0])] + for k, v in range_data.items(): + logger.info(f"{k,v}") + check_order(range_data, order_diff) diff --git a/tests/utils_tests.py b/tests/utils_tests.py index 0dcf283cc..a77320fcc 100644 --- a/tests/utils_tests.py +++ b/tests/utils_tests.py @@ -3,9 +3,22 @@ import numpy as np +def feasibility_test(solution): + feasibility = solution.solver_stats["return_status"] + + if solution.solver_options()["solver"] == "highs": + assert feasibility.lower() == "optimal" + elif solution.solver_options()["solver"] == "gurobi": + assert feasibility.lower() == "optimal" + else: + RuntimeError( + f"The solver {solution.solver_options()['solver']} is not used in test to check for " + f"optimality, please use highs or gurobi" + ) + + def demand_matching_test(solution, results): """ "Test function to check whether the milp demand of each consumer is matched""" - len_times = 0.0 for d in solution.energy_system_components.get("heat_demand", []): if len(solution.times()) > 0: len_times = len(solution.times()) @@ -13,6 +26,35 @@ def demand_matching_test(solution, results): len_times = len(solution.get_timeseries(f"{d}.target_heat_demand").values) target = solution.get_timeseries(f"{d}.target_heat_demand").values[0:len_times] np.testing.assert_allclose(target, results[f"{d}.Heat_demand"], atol=1.0e-3, rtol=1.0e-6) + for d in solution.energy_system_components.get("cold_demand", []): + if len(solution.times()) > 0: + len_times = len(solution.times()) + else: + len_times = len(solution.get_timeseries(f"{d}.target_cold_demand").values) + target = solution.get_timeseries(f"{d}.target_cold_demand").values[0:len_times] + np.testing.assert_allclose(target, results[f"{d}.Cold_demand"], atol=1.0e-3, rtol=1.0e-6) + for d in solution.energy_system_components.get("gas_demand", []): + timeseries_name = f"{d}.target_gas_demand" + if timeseries_name in solution.io.get_timeseries_names(): + if len(solution.times()) > 0: + len_times = len(solution.times()) + else: + len_times = len(solution.get_timeseries(timeseries_name).values) + target = solution.get_timeseries(timeseries_name).values[0:len_times] + np.testing.assert_allclose( + target, results[f"{d}.Gas_demand_mass_flow"], atol=1.0e-3, rtol=1.0e-6 + ) + for d in solution.energy_system_components.get("electricity_demand", []): + timeseries_name = f"{d}.target_electricity_demand" + if timeseries_name in solution.io.get_timeseries_names(): + if len(solution.times()) > 0: + len_times = len(solution.times()) + else: + len_times = len(solution.get_timeseries(timeseries_name).values) + target = solution.get_timeseries(timeseries_name).values[0:len_times] + np.testing.assert_allclose( + target, results[f"{d}.Electricity_demand"], atol=1.0e-3, rtol=1.0e-6 + ) def _get_component_temperatures(solution, results, component, side=None): @@ -72,7 +114,10 @@ def heat_to_discharge_test(solution, results): """ test = TestCase() tol = 1.0e-2 - for d in solution.energy_system_components.get("heat_demand", []): + for d in [ + *solution.energy_system_components.get("heat_demand", []), + *solution.energy_system_components.get("airco", []), + ]: cp = solution.parameters(0)[f"{d}.cp"] rho = solution.parameters(0)[f"{d}.rho"] # return_id = solution.parameters(0)[f"{d}.T_return_id"] @@ -89,18 +134,25 @@ def heat_to_discharge_test(solution, results): # dt = solution.parameters(0)[f"{d}.dT"] supply_t, return_t, dt = _get_component_temperatures(solution, results, d) np.testing.assert_allclose( - results[f"{d}.Heat_demand"], + results[f"{d}.Heat_flow"], results[f"{d}.HeatIn.Heat"] - results[f"{d}.HeatOut.Heat"], atol=tol, ) np.testing.assert_allclose( results[f"{d}.HeatOut.Heat"], results[f"{d}.Q"] * rho * cp * return_t ) - test.assertTrue( - expr=all(results[f"{d}.HeatIn.Heat"] <= results[f"{d}.Q"] * rho * cp * supply_t + tol) + + for d in solution.energy_system_components.get("cold_demand", []): + cp = solution.parameters(0)[f"{d}.cp"] + rho = solution.parameters(0)[f"{d}.rho"] + supply_t, return_t, dt = _get_component_temperatures(solution, results, d) + np.testing.assert_allclose( + results[f"{d}.Cold_demand"], + results[f"{d}.HeatOut.Heat"] - results[f"{d}.HeatIn.Heat"], + atol=tol, ) - test.assertTrue( - expr=all(results[f"{d}.Heat_demand"] <= results[f"{d}.Q"] * rho * cp * dt + tol) + np.testing.assert_allclose( + results[f"{d}.HeatOut.Heat"], results[f"{d}.Q"] * rho * cp * supply_t ) for d in solution.energy_system_components.get("heat_source", []): @@ -116,15 +168,12 @@ def heat_to_discharge_test(solution, results): # return_t = solution.parameters(0)[f"{d}.T_return"] supply_t, return_t, dt = _get_component_temperatures(solution, results, d) - test.assertTrue( - expr=all(results[f"{d}.Heat_source"] >= results[f"{d}.Q"] * rho * cp * dt - tol) - ) print(d, max(abs(results[f"{d}.HeatOut.Heat"] - results[f"{d}.Q"] * rho * cp * supply_t))) np.testing.assert_allclose( - results[f"{d}.HeatOut.Heat"], results[f"{d}.Q"] * rho * cp * supply_t, atol=tol - ) - test.assertTrue( - expr=all(results[f"{d}.HeatIn.Heat"] <= results[f"{d}.Q"] * rho * cp * return_t + tol) + results[f"{d}.HeatOut.Heat"], + results[f"{d}.Q"] * rho * cp * supply_t, + atol=5.0, + rtol=1.0e-4, ) for d in [ @@ -234,13 +283,19 @@ def heat_to_discharge_test(solution, results): carrier_id = solution.parameters(0)[f"{p}.carrier_id"] indices = results[f"{p}.Q"] > 0 if f"{carrier_id}_temperature" in results.keys(): - temperature = results[f"{carrier_id}_temperature"][indices] + temperature = np.clip( + results[f"{carrier_id}_temperature"][indices], + solution.parameters(0)[f"{p}.T_ground"], + np.inf, + ) else: - temperature = solution.parameters(0)[f"{p}.temperature"] + temperature = max( + solution.parameters(0)[f"{p}.temperature"], solution.parameters(0)[f"{p}.T_ground"] + ) test.assertTrue( expr=all( results[f"{p}.HeatIn.Heat"][indices] - <= results[f"{p}.Q"][indices] * rho * cp * temperature + tol + <= (results[f"{p}.Q"][indices] + 1e-7) * rho * cp * temperature ) ) test.assertTrue( @@ -251,9 +306,15 @@ def heat_to_discharge_test(solution, results): ) indices = results[f"{p}.Q"] < 0 if f"{carrier_id}_temperature" in results.keys(): - temperature = results[f"{carrier_id}_temperature"][indices] + temperature = np.clip( + results[f"{carrier_id}_temperature"][indices], + solution.parameters(0)[f"{p}.T_ground"], + np.inf, + ) else: - temperature = solution.parameters(0)[f"{p}.temperature"] + temperature = max( + solution.parameters(0)[f"{p}.temperature"], solution.parameters(0)[f"{p}.T_ground"] + ) test.assertTrue( expr=all( results[f"{p}.HeatIn.Heat"][indices] @@ -285,6 +346,64 @@ def heat_to_discharge_test(solution, results): ) +def electric_power_conservation_test(solution, results): + """ + Test to check if the electric power is conserved at every timestep. + High level checks: + - Network power conservation + - Power conservation when including power losses in cables. + - Power and current conservation in busses. + - Power conservation in transformers, upto now no losses in transformer. + """ + tol = 1e-2 + energy_sum = np.zeros(len(solution.times())) + + consumers = solution.energy_system_components_get( + [ + "electricity_demand", + "electrolyzer", + "electricity_storage", + "elec_boiler", + "heat_pump_elec", + "air_water_heat_pump_elec", + ] + ) + producers = solution.energy_system_components_get(["electricity_source"]) + cables = solution.energy_system_components_get(["electricity_cable"]) + transformers = solution.energy_system_components.get("transformer", []) + + for asset in consumers: + energy_sum -= results[f"{asset}.ElectricityIn.Power"] + + for asset in producers: + energy_sum += results[f"{asset}.ElectricityOut.Power"] + + for asset in cables: + energy_sum -= results[f"{asset}.Power_loss"] + np.testing.assert_allclose( + results[f"{asset}.Power_loss"], + results[f"{asset}.ElectricityIn.Power"] - results[f"{asset}.ElectricityOut.Power"], + atol=tol, + ) + + for asset, connected_cables in solution.energy_system_topology.busses.items(): + sum_bus_power = np.zeros(len(solution.times())) + sum_bus_current = np.zeros(len(solution.times())) + for i_conn, (_cable, orientation) in connected_cables.items(): + sum_bus_power += orientation * results[f"{asset}.ElectricityConn[{i_conn + 1}].Power"] + sum_bus_current += orientation * results[f"{asset}.ElectricityConn[{i_conn + 1}].I"] + np.testing.assert_allclose(sum_bus_power, 0.0, atol=tol) + np.testing.assert_allclose(sum_bus_current, 0.0, atol=tol) + + for asset in transformers: + np.testing.assert_allclose( + results[f"{asset}.ElectricityIn.Power"], + results[f"{asset}.ElectricityOut.Power"], + ) + + np.testing.assert_allclose(energy_sum, 0.0, atol=tol) + + def energy_conservation_test(solution, results): """Test to check if the energy is conserved at each timestep""" energy_sum = np.zeros(len(solution.times())) @@ -292,6 +411,12 @@ def energy_conservation_test(solution, results): for d in solution.energy_system_components.get("heat_demand", []): energy_sum -= results[f"{d}.Heat_demand"] + for d in solution.energy_system_components.get("airco", []): + energy_sum -= results[f"{d}.Heat_airco"] + + for d in solution.energy_system_components.get("cold_demand", []): + energy_sum += results[f"{d}.Cold_demand"] + for d in solution.energy_system_components.get("heat_buffer", []): energy_sum -= results[f"{d}.Heat_buffer"] @@ -301,6 +426,9 @@ def energy_conservation_test(solution, results): for d in solution.energy_system_components.get("ates", []): energy_sum -= results[f"{d}.Heat_ates"] + for d in solution.energy_system_components.get("low_temperature_ates", []): + energy_sum -= results[f"{d}.Heat_low_temperature_ates"] + for d in solution.energy_system_components.get("heat_exchanger", []): energy_sum -= results[f"{d}.Primary_heat"] - results[f"{d}.Secondary_heat"] @@ -308,14 +436,35 @@ def energy_conservation_test(solution, results): energy_sum += results[f"{d}.Power_elec"] for p in solution.energy_system_components.get("heat_pipe", []): - energy_sum -= abs(results[f"{p}.HeatIn.Heat"] - results[f"{p}.HeatOut.Heat"]) - if f"{p}__is_disconnected" in results.keys(): - p_discon = results[f"{p}__is_disconnected"].copy() + if ( + f"{p}__is_disconnected" in results.keys() + or f"{solution.cold_to_hot_pipe(p)}__is_disconnected" in results.keys() + ): + if p in solution.hot_pipes: + p_discon = results[f"{p}__is_disconnected"].copy() + else: + p_discon = results[f"{solution.cold_to_hot_pipe(p)}__is_disconnected"].copy() + p_discon[p_discon < 0.5] = 0 # fix for discrete value sometimes being 0.003 or so. np.testing.assert_allclose( results[f"{p}__hn_heat_loss"] * (1 - p_discon), - abs(results[f"{p}.HeatIn.Heat"] - results[f"{p}.HeatOut.Heat"]), + results[f"{p}.HeatIn.Heat"] - results[f"{p}.HeatOut.Heat"], atol=1e-3, ) + energy_sum -= results[f"{p}__hn_heat_loss"] * (1 - p_discon) + else: + if len(results[f"{p}__hn_heat_loss"]) == 1: + np.testing.assert_allclose( + results[f"{p}__hn_heat_loss"][0], + results[f"{p}.HeatIn.Heat"] - results[f"{p}.HeatOut.Heat"], + atol=1e-3, + ) + else: + np.testing.assert_allclose( + results[f"{p}__hn_heat_loss"], + results[f"{p}.HeatIn.Heat"] - results[f"{p}.HeatOut.Heat"], + atol=1e-3, + ) + energy_sum -= results[f"{p}__hn_heat_loss"] np.testing.assert_allclose(energy_sum, 0.0, atol=1e-2) diff --git a/tox.ini b/tox.ini index 4b0653246..943ab775a 100644 --- a/tox.ini +++ b/tox.ini @@ -1,27 +1,46 @@ [tox] envlist = - flake8,black,py39 + py39, test_env_main, test_env_pre, test_env_post, flake8, black +# Allowing logging INFO when using pytest +[pytest] +log_cli = 1 +log_cli_level = INFO +# Basic setup for test environments [testenv] deps = pytest pytest-xdist pytest-ordering numpy + pandapipes==0.10.0 + pandapower==2.14.6 + deepdiff==7.0.1 extras = all -commands = pytest -n auto -v tests -s + +# Main tests (typical normal test) +[testenv:test_env_main] +commands = pytest -n auto -v --ignore=tests/test_updated_esdl_pre_process.py --ignore=tests/test_updated_esdl_post_process.py -s + +# Pre-processing / solve systems to create data for post-processing test environment +[testenv:test_env_pre] +commands = pytest -n auto -v tests/test_updated_esdl_pre_process.py -s + +# Post process type of tests +[testenv:test_env_post] +commands = pytest -n auto -v tests/test_updated_esdl_post_process.py -s [testenv:flake8] skip_install = True deps = - flake8 - flake8-bugbear - flake8-comprehensions - flake8-import-order - pep8-naming -commands = flake8 examples src tests setup.py + flake8 == 7.1.1 + flake8-bugbear == 23.7.10 + flake8-comprehensions == 3.15.0 + flake8-import-order == 0.18.2 + pep8-naming == 0.13.3 +commands = flake8 examples src tests setup.py --exclude=pandapipeesdlparser.py [testenv:black] @@ -29,4 +48,4 @@ skip_install = True deps = black >= 24.1.1 commands = - black --line-length 100 --target-version py38 --check --diff examples src tests setup.py + black --line-length 100 --target-version py38 --check --diff examples src tests setup.py --force-exclude=pandapipeesdlparser.py