CITATION.cff

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: OPF-Gym
message: >-
  If you use this software, please cite it using the
  metadata from this file. Additionally, please check out the publication
  "Learning the optimal power flow: Environment design matters", where the 
  first version of the library was introduced. 
  (https://www.sciencedirect.com/science/article/pii/S2666546824000764) 
type: software
authors:
  - given-names: Thomas
    family-names: Wolgast
    email: thomas.wolgast@uni-oldenburg.de
    affiliation: Carl von Ossietzky Universität Oldenburg
    orcid: 'https://orcid.org/0000-0002-9042-9964'
repository-code: 'https://github.com/Digitalized-Energy-Systems/opfgym'
abstract: >-
  The OPF-Gym library allows for easy creation of
  reinforcement learning (RL) environments for solving the
  optimal power flow (OPF) problem. OPF-Gym also provides
  five benchmark environments to ensure comparability of
  future RL-OPF research. Various kinds of OPF problems are
  supported, for example, multi-stage OPF, discrete actions,
  stochastic OPF, etc. Further, it is possible to generate
  labeled training data for supervised learning, which again
  improves comparability of research advances. 
keywords:
  - Optimal Power Flow
  - Reinforcement Learning
  - Environment Design
  - Gymnasium
  - Supervised Learning
  - Voltage Control
  - Economic Dispatch
  - Reactive Power Market
  - Load Shedding
  - Power System
  - Benchmark
license: MIT
version: 0.3.2