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This paper addresses how to improve the computational efficiency andestimation reliability in cascading outage analysis. We first formulate acascading outage as a Markov chain with specific state space and transitionprobability by leveraging the Markov property of cascading outages. It providesa rigorous formulation that allows analytic investigation on cascading outagesin the framework of standard mathematical statistics. Then we derive asequential importance sampling (SIS) based simulation strategy for cascadingoutage simulation and blackout risk analysis with theoretical justification.Numerical experiments manifest that the proposed SIS strategy can significantlybring down the number of simulations and reduce the estimation variance ofcascading outage analysis compared with the traditional Monte Carlo simulationstrategy.

Towards High-Efficiency Cascading Outage Simulation and Analysis in Power Systems: A Sequential Importance Sampling Approach