A curated list of open technology projects to sustain a stable climate, energy supply, biodiversity and natural resources.

openmodelica-microgrid-gym

An OpenAI Gym Environment for Microgrids.
https://github.com/upb-lea/openmodelica-microgrid-gym

Category: Energy Systems
Sub Category: Grid Management and Microgrid

Keywords

control electrical-engineering energy-system-modeling engineering machine-learning microgrid modelica openai-gym openai-gym-environments openmodelica power-electronics power-supply power-systems python reinforcement-learning simulation smart-grids

Keywords from Contributors

latex course-materials lecture lecture-notes online-learning online-videos open-education open-education-resources open-educational-resources prediction

Last synced: about 2 hours ago
JSON representation

Repository metadata

OpenModelica Microgrid Gym (OMG): An OpenAI Gym Environment for Microgrids

README.rst

          ==========================
OpenModelica Microgrid Gym
==========================

| |build| |cov| |nbsp| |nbsp| |python| |pypi| |download| |nbsp| |nbsp| |license|
| |doc| |whitepaper| |joss|

.. |nbsp|   unicode:: U+00A0 .. NO-BREAK SPACE

.. |build| image:: https://github.com/upb-lea/openmodelica-microgrid-gym/actions/workflows/build_and_test.yml/badge.svg
    :target: https://github.com/upb-lea/openmodelica-microgrid-gym/actions/workflows/build_and_test.yml

.. |cov| image:: https://codecov.io/gh/upb-lea/openmodelica-microgrid-gym/branch/master/graph/badge.svg
    :target: https://codecov.io/gh/upb-lea/openmodelica-microgrid-gym

.. |license| image:: https://img.shields.io/github/license/upb-lea/openmodelica-microgrid-gym
    :target: LICENSE

.. |python| image:: https://img.shields.io/pypi/pyversions/openmodelica-microgrid-gym
    :target: https://pypi.python.org/pypi/openmodelica_microgrid_gym

.. |pypi| image:: https://img.shields.io/pypi/v/openmodelica_microgrid_gym
    :target: https://pypi.python.org/pypi/openmodelica_microgrid_gym

.. |download| image:: https://img.shields.io/pypi/dw/openmodelica-microgrid-gym
    :target: https://pypistats.org/packages/openmodelica-microgrid-gym

.. |doc| image:: https://img.shields.io/badge/doc-success-success
    :target: https://upb-lea.github.io/openmodelica-microgrid-gym

.. |whitepaper| image:: https://img.shields.io/badge/arXiv-whitepaper-informational
    :target: https://arxiv.org/pdf/2005.04869.pdf
    
.. |joss| image:: https://joss.theoj.org/papers/10.21105/joss.02435/status.svg
   :target: https://doi.org/10.21105/joss.02435



.. figure:: https://github.com/upb-lea/openmodelica-microgrid-gym/raw/develop/docs/pictures/omg_flow.png

**The OpenModelica Microgrid Gym (OMG) package is a software toolbox for the
simulation and control optimization of microgrids based on energy conversion by power electronic converters.**

The main characteristics of the toolbox are the plug-and-play grid design and simulation in OpenModelica as well as
the ready-to-go approach of intuitive reinfrocement learning (RL) approaches through a Python interface.

The OMG toolbox is built upon the `OpenAI Gym`_ environment definition framework.
Therefore, the toolbox is specifically designed for running reinforcement
learning algorithms to train agents controlling power electronic converters in microgrids. Nevertheless, also arbritary classical control approaches can be combined and tested using the OMG interface.

.. _OpenAI Gym: https://gym.openai.com/

* Free software: GNU General Public License v3
* Documentation: https://upb-lea.github.io/openmodelica-microgrid-gym


Video Tutorial
--------------

Following is a short YouTube video introduction, to get a fist impression how to use OMG.



- https://www.youtube.com/watch?v=rwBNFvCi_dY

Installation
------------


Install Python Environment
^^^^^^^^^^^^^^^^^^^^^^^^^^

This is the short installation guide for Windows and Linux. OpenModelica_ is hardly supported for Mac, they suggest to install in a Linux VM. For this reason, running OMG in a Linux VM is strongly recommended for Mac users!

Since it is not possible to install PyFMI_, a package which is necessary for the communication between the python interface and the environment, via pip, we recommend to install this package in advance in a conda environment.
As of now, only Windows and Linux are supported officially.

- If conda is NOT installed on your PC, install miniconda_ for python 3.8
- Create a new conda environment (e.g. in PyCharm)
- Install PyFMI from the conda-forge channel in the terminal::

    $ conda install -c conda-forge pyfmi


- Install OpenModelica MicrogridGym from PyPI (recommended)::

    $ pip install openmodelica_microgrid_gym

.. _OpenModelica: https://openmodelica.org/download/download-mac
.. _miniconda: https://conda.io/en/latest/miniconda.html
.. _PyFMI: https://github.com/modelon-community/PyFMI

Installation of OpenModelica
^^^^^^^^^^^^^^^^^^^^^^^^^^^^

OMG was create by using OMEdit_ v1.16

In case of installation issues you can resort to their pre-built `virtual machine`_.

.. _OMEdit: https://openmodelica.org/download/download-windows
.. _virtual machine: https://openmodelica.org/download/virtual-machine

Getting started
---------------

The environment is initialized and run like any other OpenAI Gym

.. code-block:: python

    import gym

    if __name__ == '__main__':
        env = gym.make('openmodelica_microgrid_gym:ModelicaEnv-v1',
                   max_episode_steps=None,
                   net='../net/net.yaml',
                   model_path='../omg_grid/grid.network.fmu')

        env.reset()
        for _ in range(1000):
            env.render()
            env.step(env.action_space.sample())  # take a random action
        env.close()




OMG uses the `FMI standard`_ for the exchange of the model between OpenModelica and Python.

.. _FMI standard: https://fmi-standard.org/

An example network consisting out of two inverters, three filters and an inductive load.

.. figure:: https://github.com/upb-lea/openmodelica-microgrid-gym/raw/master/docs/pictures/omedit.jpg

You can either use one of the provided FMUs (Windows and Linux, 64-bit, both included in the grid.network.fmu) or create your own by running::

    openmodelica_microgrid_gym\fmu> omc create_fmu.mos

Windows users might need to open the terminal out of OpenModelica by clicking 'tools' => 'OpenModelica Command Prompt' to make sure that the command 'omc' gets recognized.

Running the ``staticctrl.py`` starts a simulation with a manually tuned cascaded PIPI controller

.. figure:: https://github.com/upb-lea/openmodelica-microgrid-gym/raw/master/docs/pictures/control.jpg
    :scale: 70%
    :align: center

A save Bayesian approach of a reinforcement learning agent is provided under examples/berkamkamp.py.

.. figure:: https://github.com/upb-lea/openmodelica-microgrid-gym/raw/master/docs/pictures/kp_kp_J.png
    :figwidth: 60%
    :align: center

Using pytest
^^^^^^^^^^^^

OMG provides a big range of tests to ensure correct working toolbox after changes are done.
On some windows machines, the tests can only be started from the terminal via 'pytest'.

The standard test OS for the development is Linux. In some cases, we have noticed that the test_modelica.py on windows PCs might throw an error.
Since on Linux everything works fine, it seems to be a numerical issue connected with the FMUs.


Citation & white paper
----------------------

Please find a white paper on the OMG toolbox including an exemplary usage scenario here:

- https://arxiv.org/abs/2005.04869

Please use the following BibTeX entry for citing us::

    @article{OMG-code2020,
        title = {OMG: A Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control},
        author = {Stefan Heid and Daniel Weber and Henrik Bode and Eyke Hüllermeier and Oliver Wallscheid},
        year = {2020},
        doi = {10.21105/joss.02435},
        url = {https://doi.org/10.21105/joss.02435},
        publisher = {The Open Journal},
        volume = {5},
        number = {54},
        pages = {2435},
        journal = {Journal of Open Source Software}
    }

    @article{OMG-whitepaper2020,
        title={Towards a Scalable and Flexible Simulation and
               Testing Environment Toolbox for Intelligent Microgrid Control},
        author={Henrik Bode and Stefan Heid and Daniel Weber and Eyke Hüllermeier and Oliver Wallscheid},
        year={2020},
        eprint={http://arxiv.org/abs/2005.04869},
        archivePrefix={arXiv},
        primaryClass={eess.SY}
    }


Contributing
------------

Please refer to the `contribution guide`_.

.. _`contribution guide`: https://github.com/upb-lea/openmodelica-microgrid-gym/blob/master/CONTRIBUTING.rst


Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage

        

Owner metadata


GitHub Events

Total
Last Year

Committers metadata

Last synced: 5 days ago

Total Commits: 557
Total Committers: 10
Avg Commits per committer: 55.7
Development Distribution Score (DDS): 0.575

Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0

Name Email Commits
Stefan Heid s****d@u****e 237
Daniel Weber w****r@l****e 159
Oliver Wallscheid 5****d 45
Stefan Heid s****d@w****e 36
hbode b****e@l****e 33
h-bode 6****e 27
Webbah D****o@g****e 10
Wilhelm Kirchgässner 1****n 7
Stefan Helmut Heid s****d@m****e 2
David H Hagan d****d@d****m 1

Committer domains:


Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 84
Total pull requests: 55
Average time to close issues: about 1 month
Average time to close pull requests: 2 days
Total issue authors: 9
Total pull request authors: 4
Average comments per issue: 2.8
Average comments per pull request: 0.42
Merged pull request: 53
Bot issues: 0
Bot pull requests: 0

Past year issues: 1
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 1
Past year pull request authors: 0
Past year average comments per issue: 3.0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/upb-lea/openmodelica-microgrid-gym

Top Issue Authors

  • Webbah (26)
  • stheid (23)
  • h-bode (21)
  • wallscheid (8)
  • marvpick (2)
  • JvPost (1)
  • linyunfeng201203 (1)
  • gituser789 (1)
  • elliottower (1)

Top Pull Request Authors

  • stheid (29)
  • h-bode (13)
  • Webbah (12)
  • dhhagan (1)

Top Issue Labels

  • enhancement (22)
  • bug (9)
  • documentation (8)
  • help wanted (7)
  • question (7)
  • wontfix (1)
  • good first issue (1)
  • invalid (1)

Top Pull Request Labels

  • bug (2)
  • enhancement (1)

Package metadata

pypi.org: openmodelica-microgrid-gym

OpenModelica Microgrid Gym

  • Homepage: https://github.com/upb-lea/openmodelica-microgrid-gym
  • Documentation: https://upb-lea.github.io/openmodelica-microgrid-gym/
  • Licenses: GNU General Public License v3
  • Latest release: 0.4.0 (published about 3 years ago)
  • Last Synced: 2025-04-26T12:32:27.171Z (1 day ago)
  • Versions: 6
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 263 Last month
  • Rankings:
    • Stargazers count: 5.693%
    • Forks count: 6.775%
    • Dependent packages count: 7.373%
    • Average: 17.835%
    • Dependent repos count: 22.233%
    • Downloads: 47.099%
  • Maintainers (1)

Dependencies

requirements.txt pypi
  • GPy >=1.9.9
  • PyFMI >=2.5
  • future *
  • gym >=0.15.3
  • matplotlib >=3.1.1
  • more_itertools >=7
  • numexpr >=2.7.1
  • numpy >=1.17.2
  • pandas >=1.0.1
  • pytest *
  • pyyaml *
  • safeopt >=0.16
  • scipy >=1.3.1
  • setuptools *
  • stochastic >=0.6.0
  • tables >=3.6.1
  • tqdm >=4
requirements_dev.txt pypi
  • GPy >=1.9.9 development
  • Sphinx ==3.1 development
  • bump2version ==0.5.11 development
  • pytest >=5.2.2 development
  • pytest-cov * development
  • pytest-runner ==5.1 development
  • safeopt >=0.16 development
  • sphinx-autodoc-typehints >=1.11 development
  • sphinx_rtd_theme * development
  • tables >=3.4.1 development
  • twine ==1.14.0 development
  • watchdog ==0.9.0 development

Score: 13.243607084689692