2 citations · 3 across the 4 of their papers we have counts for
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A Systematic Evaluation of Machine Learning Methods for Fault Detection and Line Identification in Electrical Power Grids
Julian Oelhaf, Georg Kordowich, Paula Andrea Pérez-Toro +4
The integration of renewable energy sources into the electrical grid introduces complex challenges in fault detection and coordination of grid recovery mechanisms. Traditional rela…
A Standardized Framework for Machine Learning in Power System Protection
Julian Oelhaf, Georg Kordowich, Paula Andrea Pérez-Toro +4
Studies of machine-learning-based power-system protection increasingly report near-perfect scores, yet the meaning of those scores depends strongly on the evaluation setting. Prote…
Parameter-Efficient Domain Adaptation of Physics-Informed Self-Attention based GNNs for AC Power Flow Prediction
Redwanul Karim, Changhun Kim, Timon Conrad +7
Accurate AC power flow (AC-PF) prediction under domain shift is critical when models trained on medium-voltage (MV) grids are deployed on high-voltage (HV) networks. Existing physi…
Robustness Evaluation of Machine Learning Models for Fault Classification and Localization In Power System Protection
Julian Oelhaf, Mehran Pashaei, Georg Kordowich +4
The growing penetration of renewable and distributed generation is transforming power systems and challenging conventional protection schemes that rely on fixed settings and local…