emarche/RL2Grid

Grid2Op a testbed platform to model sequential decision making in power systems.

The Flatland Framework is a multi-purpose environment to tackle problems around resilient resource allocation under uncertainty. It is designed to be a flexible and method agnostic to solve a wide range of problems in the field of operations research and reinforcement learning.

Reinforcement learning environment for wind farm control. Mirror of https://gitlab.windenergy.dtu.dk/sys/windgym

Official reinforcement learning environment for demand response and load shaping

Simple EnergyPlus environments for control optimization using reinforcement learning

[ICML 2026] Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control

Simple and easily configurable grid world environments for reinforcement learning

Reinforcement learning environments for process control applications.