Modeling cascading failure propagation in power systems

In this paper, we investigate the dynamic profiles of the cascading failure propagations in power systems. We use a circuit-based power flow model and combine it with a stochastic model to describe the uncertain failure time instants. The sequence of failures is determined by power stresses of individual elements which are governed by deterministic circuit equations, while the time durations between failures are described by stochastic processes. The use of stochastic processes here addresses the uncertainties in individual components' physical failure mechanisms which may depend on manufacturing quality and environmental factors. In this model, the element failure rate is related to the extent of overloading. A network-based stochastic model is developed to study the failure propagation dynamics of the entire power network. Simulation results show that our model generates dynamic profiles of cascading failures that contains all salient features displayed in historical blackout data. The proposed model thus offers predictive information about occurrences of large-scale blackouts.