Predicting basin stability of power grids using graph neural networks

Predicting basin stability of power grids using graph neural networks

The prediction of dynamical stability of power grids becomes more important and challenging with increasing shares of renewable energy sources due to their decentralized structure, reduced inertia and volatility. We investigate the feasibility of applying graph neural networks (GNN) to predict dynam...

Full description

Bibliographic Details
Main Authors: Christian Nauck, Michael Lindner, Konstantin Schürholt, Haoming Zhang, Paul Schultz, Jürgen Kurths, Ingrid Isenhardt, Frank Hellmann
Format: Article
Language:English
Published: IOP Publishing 2022-01-01
Series:New Journal of Physics
Subjects:
complex systems
nonlinear dynamics
dynamic stability
basin stability
power grids
machine learning
Online Access:https://doi.org/10.1088/1367-2630/ac54c9

Internet

https://doi.org/10.1088/1367-2630/ac54c9

Similar Items