A Power Grid Fault Center Identification Method Based on Feature Vector Centrality

A power grid fault diagnosis method is proposed based on the graph signal modeling according to the fault recording start information and the network node eigenvector centrality algorithm. Firstly, the fault start information network diagram is constructed from the fault record start information of relay protection and fault information master station. Secondly, the graph smoothness analysis method is used to determine whether the grid fails and identify the fault type. Finally, the fault components are identified based on the feature vector centrality algorithm of network nodes and visualized. The simulation verifies the effectiveness of the proposed algorithm. As a part of the intelligent fault analysis of wave recording, this method helps to quickly grasp the fault situation of power grid, and focus on collecting wave recording data for fault analysis and verification, so as to improve the efficiency of wave recording analysis.