Our paper Learning Topology Actions for Power Grid Control: A Graph-Based Soft-Label Imitation Learning Approach by Mohamed Hassouna, Clara Holzhüter, Malte Lehna, Matthijs de Jong, Jan Viebahn, Bernhard Sick and Christoph Scholz has been accepted at European Conference on Machine Learning 2025. Abstract: The rising proportion of renewable energy in the electricity mix introduces significant […]
Our paper Graph Neural Networks for Grid Control: Prospects in AI-assisted Transmission Grid Operation by Clara Holzhüter, Pawel Lytaev, Marcel Dipp, Mohamed Hassouna, Kurt Brendlinger, Jan Viebahn, Wiktor Gegelman and Christian Merz has been accepted for ETG Kongress 2025. Abstract:Transmission grid congestion management and outage planning are critical tasks in modern grid operation due to thenon-linear
The workshop Machine Learning for Sustainable Power Systems (ML4SPS) brings together scientists from the fields of machine learning and energy systems at the European Conference of Machine Learning. Researchers and users can share their knowledge and experience in the fields of renewable energy systems, grid management and machine learning and thus benefit from the expertise of the community. Two leading experts [...]