Vulnerability Community Detection Based on Concentric Relaxation and Cascading Failure Super-Network Models

Vulnerability community detection is one of the common means to study the higher-order vulnerability of the transmission grid, but the traditional community detection method is often based on topological or weighted topological models, which loses most of the engineering features among nodes. Therefore, this paper establishes two line failure inter-sensitivity models by applying concentric relaxation (CR-FIS) theory and super-network (CFS-FIS) on cascading failure chains. Based on the two models, two types of failure inter-sensitivity modularity are used to identify vulnerability communities. Specially designed indicators are then used to rank the vulnerability communities. By applying the proposed methods to the IEEE39 bus system, the results show that the proposed method can capture around 70% to 100% of vulnerable branches given by other literature within the top 3 communities. The detected communities also exhibit distinct features in terms of contained levels of vulnerability lines.