141 citations
- Delft University of TechnologyNL6 papers
- Royal Netherlands Meteorological InstituteNL4 papers
- Utrecht UniversityNL4 papers
- Fraunhofer Institute for Energy Economics and Energy System TechnologyDE3 papers
- Shandong UniversityCN2 papers
- University of GroningenNL2 papers
- University of KasselDE2 papers
- Aarhus UniversityDK1 paper
- BOKU UniversityAT1 paper
- Christian-Albrechts-Universität zu KielDE1 paper
- École Nationale Supérieure des Mines de ParisFR1 paper
- Électricité de France (France)FR1 paper
Showing cs.LGShow all
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cs.LG2025★ 3 cited
Learning Topology Actions for Power Grid Control: A Graph-Based Soft-Label Imitation Learning Approach
Mohamed Hassouna, Clara Holzhüter, Malte Lehna +4
The rising proportion of renewable energy in the electricity mix introduces significant operational challenges for power grid operators. Effective power grid management demands ada…
cs.LG2023★ 27 cited
Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents
Malte Lehna, Jan Viebahn, Christoph Scholz +2
The operation of electricity grids has become increasingly complex due to the current upheaval and the increase in renewable energy production. As a consequence, active grid manage…
cs.LG2020★ 5 cited
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…