Risk-based composite power system vulnerability evaluation to cascading failures using importance sampling

Large-scale blackouts typically result from cascading failure in power systems operation. Their mitigation in power system planning calls for the development of methods and algorithms that assess the risk of cascading failures due to relay overtripping, short-circuits induced by overgrown vegetation, voltage sags, line and transformer overloading, transient instabilities, voltage collapse, to cite a few. This paper describes such a method based on composite power system reliability evaluation via sequential Monte Carlo simulation. One of the impediments of the study of these phenomena is the prohibitively large computational burden involved by the simulations. To overcome this difficulty, importance sampling technique utilizing the Weibull distribution is applied. It is shown that the method significantly reduce the number of samples that need to be investigated while maintaining the accuracy at a given level. To illustrate the developed approach, a case study is conducted and analyzed on the IEEE reliability test system.