energy-py

Reinforcement learning for energy systems

https://github.com/ADGEfficiency/energy-py

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (5.0%) to scientific vocabulary

Keywords

energy reinforcement-learning
Last synced: 11 months ago · JSON representation

Repository

Reinforcement learning for energy systems

Basic Info
  • Host: GitHub
  • Owner: ADGEfficiency
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 269 KB
Statistics
  • Stars: 180
  • Watchers: 8
  • Forks: 34
  • Open Issues: 1
  • Releases: 0
Topics
energy reinforcement-learning
Created over 9 years ago · Last pushed about 1 year ago
Metadata Files
Readme License

README.md

energypy

Tests

A framework for running reinforcement learning experiments on energy environments - starting with electric battery storage.

Features

  • Electric battery storage environment for energy arbitrage
  • Integration with Gymnasium as a custom Gymnasium environment
  • Integration with Stable Baselines 3 for reinforcement learning agents
  • Historical electricity price data for realistic training scenarios
  • Experiment framework for training and evaluation on separate datasets
  • Tensorboard logging for experiment tracking

Setup

shell-session $ make setup

Examples

shell-session $ uv run examples/battery.py

Or run a more extensive experiment with real electricity price data:

shell-session $ uv run examples/battery_arbitrage_experiments.py

Test

shell-session $ make test

Owner

  • Name: Adam Green
  • Login: ADGEfficiency
  • Kind: user

GitHub Events

Total
  • Issues event: 13
  • Watch event: 6
  • Delete event: 5
  • Issue comment event: 12
  • Push event: 85
  • Pull request event: 11
  • Fork event: 1
  • Create event: 4
Last Year
  • Issues event: 13
  • Watch event: 6
  • Delete event: 5
  • Issue comment event: 12
  • Push event: 85
  • Pull request event: 11
  • Fork event: 1
  • Create event: 4

Committers

Last synced: 12 months ago

All Time
  • Total Commits: 18
  • Total Committers: 2
  • Avg Commits per committer: 9.0
  • Development Distribution Score (DDS): 0.167
Past Year
  • Commits: 4
  • Committers: 1
  • Avg Commits per committer: 4.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Adam Green a****n@a****m 15
Adam Green u****u@i****l 3
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 46
  • Total pull requests: 29
  • Average time to close issues: about 1 year
  • Average time to close pull requests: 3 months
  • Total issue authors: 10
  • Total pull request authors: 7
  • Average comments per issue: 1.33
  • Average comments per pull request: 0.52
  • Merged pull requests: 13
  • Bot issues: 0
  • Bot pull requests: 12
Past Year
  • Issues: 5
  • Pull requests: 5
  • Average time to close issues: 18 days
  • Average time to close pull requests: 2 days
  • Issue authors: 2
  • Pull request authors: 1
  • Average comments per issue: 1.2
  • Average comments per pull request: 0.0
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • ADGEfficiency (37)
  • fokx (1)
  • KeirSimmons (1)
  • Sudococommunity (1)
  • LucaNicoliYT88 (1)
  • bollegijscoding (1)
  • satishravindran (1)
  • ghost (1)
  • adityauser (1)
  • IanQS (1)
Pull Request Authors
  • dependabot[bot] (13)
  • ADGEfficiency (12)
  • hassaku (3)
  • tomharvey (3)
  • KeirSimmons (2)
  • nhoening (1)
  • ghost (1)
Top Labels
Issue Labels
Pull Request Labels
dependencies (13)

Dependencies

requirements.txt pypi
  • click *
  • gym ==0.18.0
  • imageio *
  • pandas ==1.2.3
  • pytest *
  • tdqm *
  • tensorflow ==2.5.0
  • tensorflow-estimator ==2.5.0
  • tensorflow-probability ==0.13.0
setup.py pypi
  • Click *
.github/workflows/test.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite