67 citations · 158 across the 15 of their papers we have counts for
15 papers
RL2Grid: Benchmarking Reinforcement Learning in Power Grid Operations
Enrico Marchesini, Benjamin Donnot, Constance Crozier +7
Reinforcement learning (RL) can provide adaptive and scalable controllers essential for power grid decarbonization. However, RL methods struggle with power grids' complex dynamics,…
Superposition theorem for flexible grids
Antoine Marot, Noureddine Henka, Benjamin Donnot +1
Flexible grid topology has become a key enabler of flexibility in modern power grids, particularly for congestion management. Studying the effects of combinatorial topological chan…
Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design
Gaëtan Serré, Eva Boguslawski, Benjamin Donnot +3
Current rapid changes in climate increase the urgency to change energy production and consumption management, to reduce carbon and other green-house gas production. In this context…
Learning to run a power network with trust
Antoine Marot, Benjamin Donnot, Karim Chaouache +4
Artificial agents are promising for real-time power network operations, particularly, to compute remedial actions for congestion management. However, due to high reliability requir…
Learning to run a Power Network Challenge: a Retrospective Analysis
Antoine Marot, Benjamin Donnot, Gabriel Dulac-Arnold +7
Power networks, responsible for transporting electricity across large geographical regions, are complex infrastructures on which modern life critically depend. Variations in demand…
Adversarial Training for a Continuous Robustness Control Problem in Power Systems
Loïc Omnes, Antoine Marot, Benjamin Donnot
We propose a new adversarial training approach for injecting robustness when designing controllers for upcoming cyber-physical power systems. Previous approaches relying deeply on…