Gym-ANM

Design Reinforcement Learning environments that model Active Network Management tasks in electricity distribution networks.
https://github.com/robinhenry/gym-anm

Category: Energy Systems
Sub Category: Grid Management and Microgrid

Keywords

active-network-management control electricity-networks gym-environments reinforcement-learning

Last synced: about 12 hours ago
JSON representation

Repository metadata

A framework to design Reinforcement Learning environments that model Active Network Management (ANM) tasks in electricity distribution networks.

• Host: GitHub
• URL: https://github.com/robinhenry/gym-anm
• Owner: robinhenry
• License: mit
• Created: 2019-07-17T23:19:13.000Z (almost 6 years ago)
• Default Branch: main
• Last Pushed: 2024-11-14T09:43:59.000Z (5 months ago)
• Last Synced: 2025-04-25T12:06:53.430Z (3 days ago)
• Topics: active-network-management, control, electricity-networks, gym-environments, reinforcement-learning
• Language: Python
• Homepage: https://gym-anm.readthedocs.io/en/latest/
• Size: 7 MB
• Stars: 155
• Watchers: 4
• Forks: 33
• Open Issues: 0
• Releases: 9
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md
  • Code of conduct: CODE_OF_CONDUCT.md

README.md

pip install gym-anm

git clone https://github.com/robinhenry/gym-anm.git
cd gym-anm
pip install -e .

import gymnasium as gym
import time

def run():
   env = gym.make('gym_anm:ANM6Easy-v0')
   o = env.reset()

   for i in range(100):
       a = env.action_space.sample()
       o, r, done, info = env.step(a)
       env.render()
       time.sleep(0.5)  # otherwise the rendering is too fast for the human eye.

   env.close()

if __name__ == '__main__':
    run()

python -m pytest tests

@article{HENRY2021100092,
    title = {Gym-ANM: Reinforcement learning environments for active network management tasks in electricity distribution systems},
    journal = {Energy and AI},
    volume = {5},
    pages = {100092},
    year = {2021},
    issn = {2666-5468},
    doi = {https://doi.org/10.1016/j.egyai.2021.100092},
    author = {Robin Henry and Damien Ernst},
}

@article{HENRY2021100092,
    title = {Gym-ANM: Open-source software to leverage reinforcement learning for power system management in research and education},
    journal = {Software Impacts},
    volume = {9},
    pages = {100092},
    year = {2021},
    issn = {2665-9638},
    doi = {https://doi.org/10.1016/j.simpa.2021.100092},
    author = {Robin Henry and Damien Ernst}
}

Owner metadata

• Name: Robin Henry
• Login: robinhenry
• Email:
• Kind: user
• Description: Research engineer interested in disruptive technology. Currently Data Scientist @ Habitat Energy.
• Website:
• Location: Oxford, UK
• Twitter:
• Company: Habitat Energy
• Icon url: https://avatars.githubusercontent.com/u/33941047?u=8fbd17ad448b250c5ee1c6f2a4042dd9cdf12778&v=4
• Repositories: 13
• Last ynced at: 2024-06-11T15:44:03.643Z
• Profile URL: https://github.com/robinhenry

GitHub Events

Total

• Release event: 1
• Watch event: 18
• Delete event: 1
• Push event: 21
• Pull request event: 3
• Fork event: 1
• Create event: 4

Last Year

• Release event: 1
• Watch event: 18
• Delete event: 1
• Push event: 21
• Pull request event: 3
• Fork event: 1
• Create event: 4

Committers metadata

Last synced: 6 days ago

Committer domains:

• vega.ulg.ac.be: 1

Issue and Pull Request metadata

Last synced: 1 day ago

Package metadata

• Total packages: 1
• Total downloads:
  • pypi: 463 last-month
• Total dependent packages: 1
• Total dependent repositories: 3
• Total versions: 11
• Total maintainers: 1

Dependencies

Score: 12.290505701505003