Cascading failures forecasting based on running state and structure
Liao Yuan-xi
Abstract
Liao Yuan-xi
Abstract
Power grid cascading failures may cause large scale blackout and lead to serious consequences. The forecasting of the follow-up failures in the initial stage of the failure is very helpful. On the basis of analyzing developing process of the typical cascading failures, branch static energy function model is constructed comprehensively, and an energy index is built to map the change of flow. Meanwhile, combining with the electric betweenness that reflects the network structure vulnerability, considering the cumulative influence of previous failure on the following-up failure, a comprehensive margin index reflecting the change of state and structure after the grid failure is proposed to forecast the following-up cascading failures. The simulation results can search out a set of serious cascading failures, which shows the feasibility and validity of the method.
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Power grid cascading failures may cause large scale blackout and lead to serious consequences. The forecasting of the follow-up failures in the initial stage of the failure is very helpful. On the basis of analyzing developing process of the typical cascading failures, branch static energy function model is constructed comprehensively, and an energy index is built to map the change of flow. Meanwhile, combining with the electric betweenness that reflects the network structure vulnerability, considering the cumulative influence of previous failure on the following-up failure, a comprehensive margin index reflecting the change of state and structure after the grid failure is proposed to forecast the following-up cascading failures. The simulation results can search out a set of serious cascading failures, which shows the feasibility and validity of the method.
Key concepts: Cascading failure, Blackout, Reliability engineering, Margin (machine learning), Betweenness centrality, Vulnerability (computing), Grid, Computer science