Uncertain risk assessment model for catastrophic accidents in power system

Abstract

Catastrophic accidents in power system are characterized by complex and significant uncertainties. The existing risk assessment methods based on probability theory require adequate historical statistic data to ensure the precision of probability model and parameter identification regardless of the rareness of catastrophic accidents. Alternatively, the catastrophic accident can be treated as a fuzzy event, and then a new uncertain risk assessment model to identify the most possible catastrophic accident sequences is presented in this paper. According to physical propagation process and mathematical modeling principle of the catastrophic accident, a risk evaluation system consisting of the credibility measure, global fuzzy severity measure and risk measure is provided based on the credibility theory. The risk assessment model starts from N−1 contingencies, and the most possible catastrophic accident sequences are identified by the risk ranking of all N−k contingencies in each stage. Some numerical cases of the WSCC 9-bus and practical regional power system are simulated to demonstrate the applicability, validity and accuracy of the proposed method.