A Splitting Method for Speedy Composite Network Reliability Evaluation

Abstract

This paper proposes a novel composite power system reliability evaluating approach based on a splitting method. The essential concept of this method is to replicate target realizations of the sampling process to increase the occurrence frequency of the rare events, thereby improving the assessment efficiency of sampling rare failure events. In the traditional Monte Carlo simulation approach, the power system samples are classified into secure and failure states. The secure states are further quantitatively evaluated by a redundant capacity index in the splitting method to enable an adaptive design of gradual failure domains. Gibbs sampling is introduced to generate states conditional on given domains. The results indicate that the proposed method can improve the efficiency of the power system reliability evaluation, especially in the case of high-reliable power systems.