Learning to Run a Power Network (L2RPN) is an international Reinforcement Learning Competition organized by RTE, the French Transmission System Operator. The annual competition attracts the attention of top international research teams with the goal to advance the state of the art in AI powered control of large scale power networks.
We are especially proud that this success was once more enabled by our in-house developed RL framework Maze.
Code for reproducing our submission: https://github.com/enlite-ai/maze-l2rpn-2022-submission
Official challenge web page: https://codalab.lisn.upsaclay.fr/competitions/5410
Maze RL Framework: https://github.com/enlite-ai/maze
Our mobile mapping solution Detekt won the IÖB Award in the category 'Innovative Solutions for Infrastructure and Traffic Management'
We are excited to present our work on power grid congestion management at this year’s RL4RealLife Workshop @ NeurIPS