Analyzing Patterns Transference and Mitigation of Cascading Failures with Interaction Graphs

Abstract

Interaction graphs (IG) can capture the hidden interaction among power system components during cascading failures (CF), which is currently applied to explore vulnerability assessment and resilience enhancement in CF. In this paper, we propose an approach targeted at CF propagation pattern transference with respect to system state evolution and setting related mitigation strategy. The IG is constructed by the CF data generated from a CF model considering balance rules and hidden failure. Then two IG based indexes are employed to investigate CF pattern from two perspective, vulnerability and dispersibility. The simulation results have shown CF propagation pattern transferences in two system state evolutions and verified the critical lines could transfer with system states changing. The results also suggest the existence of Braess paradox in some traditional mitigation strategies considering system state evolution, while the proposed mitigation strategy can avoid the Braess paradox.