Explainable Graph Neural Networks for Power Grid Fault Detection

Explainable Graph Neural Networks for Power Grid Fault Detection

This paper proposes the application of explanation methods to enhance the interpretability of graph neural network (GNN) models in fault location for power grids. GNN models have exhibited remarkable precision in utilizing phasor data from various locations around the grid and integrating the system...

Full description

Saved in:
Bibliographic Details
Main Authors: Richard Bosso, Corey Chang, Mahdi Zarif, Yufei Tang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Fault location detection
graph neural network (GNN)
Fidelity
characterization score
model explainability and transparency
power grids
Online Access:https://ieeexplore.ieee.org/document/11088107/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/11088107/

Similar Items