Grid2Op a testbed platform to model sequential decision making in power systems.
L2RPN Baselines a repository to host baselines for l2rpn competitions.
A gamification of the "powergrid problem" using grid2op that allows you to "operate" a powergrid.
Source code for the papers: RL for Mitigating Cascading Failures: Targeted Exploration via Sensitivity Factors (NeurIPS) / Blackout Mitigation via Physics-guided RL (IEEE TPS). Built with TensorFlow.
This A3C reinforcement learning code is implemented for tensorflow 2.0 and it is focused to demonstrate the implementation of a multi-threading agent (A3C) on [Grid2Op](https://github.com/rte-france/Grid2Op) environment.
Research implementation of Meta-Learning (MAML) in Multi-Agent Reinforcement Learning (MARL) for power grid control using L2RPN. This project explores how meta-learning can improve agent adaptation across varying grid topologies and operational scenarios, aiming for safer and more efficient grid management.
Grid2Op a testbed platform to model sequential decision making in power systems.
Multi-objective PPO for risk-aware power-grid control in Grid2Op
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