Probabilistic Analytics of Cascading Failures: Modeling, Assessment, and Application

This chapter delves into the probabilistic analytics of cascading failures in power grids. The primary focus is establishing an analytic model that leverages the Markov property, which rigorously fits cascading failure analysis into a probabilistic framework. It enables a sequential importance sampling-based method to simulate cascading failures and analyze the associated blackout risks efficiently. These works lead to a sample-induced semi-analytic approach, which allows researchers to accurately calculate unbiased estimations of blackout risk without the need for time-consuming cascading failure simulations when failure probability functions change. Finally, the suggested probabilistic analytics are applied to mitigate the risks associated with complicated cascading failures, underscoring their potential utility in designing advanced prevention strategies against such catastrophic failures.