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cs.LG2025
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.LG2024
Fault Detection for agents on power grid topology optimization: A Comprehensive analysis
Malte Lehna, Mohamed Hassouna, Dmitry Degtyar +2
Optimizing the topology of transmission networks using Deep Reinforcement Learning (DRL) has increasingly come into focus. Various DRL agents have been proposed, which are mostly b…
cs.LG2024
HUGO -- Highlighting Unseen Grid Options: Combining Deep Reinforcement Learning with a Heuristic Target Topology Approach
Malte Lehna, Clara Holzhüter, Sven Tomforde +1
With the growth of Renewable Energy (RE) generation, the operation of power grids has become increasingly complex. One solution could be automated grid operation, where Deep Reinfo…