Toward Efficient Cascading Outage Simulation and Probability Analysis in Power Systems

Abstract

This paper addresses how to improve the computational efficiency and estimation reliability in cascading outage analysis. Under mild assumptions, we first formulate a cascading outage as a Markov model with specific state space and transition probability by leveraging the Markov property of cascading outages. Such a model provides a rigorous formulation that allows analytic investigation on cascading outages in the framework of standard mathematical statistics. Then, we derive a sequential importance sampling (SIS)-based strategy for cascading outage simulations and blackout risk analysis with solid theoretical foundation. Numerical experiments manifest that the proposed SIS strategy can significantly enhance the efficiency of simulations and reduce the estimation variance of blackout probability/risk compared with the traditional Monte Carlo simulation strategy.