Risk assessment for cascading failures in regional integrated energy system considering the pipeline dynamics

With the close coupling of multiple energies (i.e., electricity, gas, cold, and heat) in a regional integrated energy system (RIES), failures in an energy subsystem can easily propagate to other energy subsystems via multi-energy coupling devices and result in cascading failures. Considering the dynamics of pipeline energy transmission and pipeline leakage failures, a novel dynamic model of analyzing the cooling/heating or gas pipeline leakage failure is proposed. Then a risk assessment model for cascading failures in a RIES is established, including the calcu-lation of the probability and severity of cascading failure chain (CFC). A model for determining the failure probability of multi-energy coupling devices based on the device operation state is established, and a method for calculating the probability of CFC based on Bayes theorem is proposed. Considering the uncertainty and time correlation of renewable power, an ambiguity set based on the Jensen-Shannon divergence and the moment information of actual historical data is proposed, and then a distributionally robust optimization model for calculating the severity of CFC is established and solved by the column-and-constraint generation algorithm. Test results on a RIES demonstrate the high computational accuracy and efficiency of the proposed method.

Automated summary

In this study, a dynamic model for analyzing the failure propagation in a regional integrated energy system (RIES) is proposed. A risk assessment model for cascading failures is established, and a method for calculating the probability of cascading failure chain (CFC) based on Bayes theorem is proposed. Furthermore, a distributionally robust optimization model is developed to calculate the severity of CFC considering the uncertainty and time correlation of renewable power.