upb-lea/openmodelica-microgrid-gym
OpenModelica Microgrid Gym (OMG): An OpenAI Gym Environment for Microgrids
This toolbox helps power engineers and researchers simulate and optimize the control of microgrids, particularly those involving power electronic converters. You input your microgrid design in OpenModelica, and it allows you to test and train control algorithms, producing optimized control strategies for your grid. It is designed for those exploring intelligent control of electrical grids.
219 stars. No commits in the last 6 months. Available on PyPI.
Use this if you are a power systems engineer or researcher looking to apply and test reinforcement learning or other advanced control methods on detailed microgrid simulations.
Not ideal if you are solely interested in high-level energy management without detailed power electronics simulation or are not comfortable with programming environments.
Stars
219
Forks
41
Language
Modelica
License
GPL-3.0
Category
Last pushed
Jun 13, 2022
Commits (30d)
0
Dependencies
17
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/upb-lea/openmodelica-microgrid-gym"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
qgallouedec/panda-gym
Set of robotic environments based on PyBullet physics engine and gymnasium.
nicrusso7/rex-gym
OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
amazon-science/auction-gym
AuctionGym is a simulation environment that enables reproducible evaluation of bandit and...
ntasfi/PyGame-Learning-Environment
PyGame Learning Environment (PLE) -- Reinforcement Learning Environment in Python.
vietnh1009/Super-mario-bros-A3C-pytorch
Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros