67 citations · 191 across the 18 of their papers we have counts for
4 papers · 1 filter
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…
Towards an AI assistant for power grid operators
Antoine Marot, Alexandre Rozier, Matthieu Dussartre +2
Power grids are becoming more complex to operate in the digital age given the current energy transition to cope with climate change. As a result, real-time decision-making is getti…
Exploring grid topology reconfiguration using a simple deep reinforcement learning approach
Medha Subramanian, Jan Viebahn, Simon H. Tindemans +2
System operators are faced with increasingly volatile operating conditions. In order to manage system reliability in a cost-effective manner, control room operators are turning to…
Reinforcement Learning for Electricity Network Operation
Adrian Kelly, Aidan O'Sullivan, Patrick de Mars +1
This paper presents the background material required for the Learning to Run Power Networks Challenge. The challenge is focused on using Reinforcement Learning to train an agent to…