3 papers
cs.MA2025
Centrally Coordinated Multi-Agent Reinforcement Learning for Power Grid Topology Control
Barbera de Mol, Davide Barbieri, Jan Viebahn +1
Power grid operation is becoming more complex due to the increase in generation of renewable energy. The recent series of Learning To Run a Power Network (L2RPN) competitions have…
cs.LG2025
Multi-Objective Reinforcement Learning for Power Grid Topology Control
Thomas Lautenbacher, Ali Rajaei, Davide Barbieri +2
Transmission grid congestion increases as the electrification of various sectors requires transmitting more power. Topology control, through substation reconfiguration, can reduce…
cs.AI2025
Towards Efficient Multi-Objective Optimisation for Real-World Power Grid Topology Control
Yassine El Manyari, Anton R. Fuxjager, Stefan Zahlner +5
Power grid operators face increasing difficulties in the control room as the increase in energy demand and the shift to renewable energy introduce new complexities in managing cong…