4 papers
Accurate Data-Based State Estimation from Power Loads Inference in Electric Power Grids
Philippe Jacquod, Laurent Pagnier, Daniel J. Gauthier
Accurate state estimation is a crucial requirement for the reliable operation and control of electric power systems. Here, we construct a data-driven, numerical method to infer mis…
Anomaly Detection with Machine Learning Algorithms in Large-Scale Power Grids
Marc Gillioz, Guillaume Dubuis, Ãtienne Voutaz +1
We apply several machine learning algorithms to the problem of anomaly detection in operational data for large-scale, high-voltage electric power grids. We observe important differ…
Stabilizing Large-Scale Electric Power Grids with Adaptive Inertia
Julian Fritzsch, Philippe Jacquod
The stability of AC power grids relies on ancillary services that mitigate frequency fluctuations. The electromechanical inertia of large synchronous generators is currently the on…
A large synthetic dataset for machine learning applications in power transmission grids
Marc Gillioz, Guillaume Dubuis, Philippe Jacquod
With the ongoing energy transition, power grids are evolving fast. They operate more and more often close to their technical limit, under more and more volatile conditions. Fast, e…