Static information, K-neighbor, and self-attention aggregated scheme: a transient stability prediction model with enhanced interpretability

Abstract

Highlights A fast TSA scheme for pre-failure scanning. A physical mechanism-based attention structure for dynamic graph pooling. A node regression model that responds to key physical mechanisms. Generator label for richer output information. Top performance and post-hoc interpretation.

Keywords

• Transient stability assessment (TSA)
• Data-driven
• Explainable
• Graph neural network (GNN)
• Self-attention