Risk assessment for cascading failures in regional integrated energy system considering the pipeline dynamics. (1st May 2023)

• Record Type: Journal Article
• Authors: Liang, Weikun; Lin, Shunjiang; Liu, Mingbo; Sheng, Xuan; Pan, Yue; Liu, Yun
• Is Part Of: Energy. Volume 270(2023)
• Publication Date: 2023-05-01
• Subjects: RIES -- Pipeline leakage dynamics -- Cascading failures -- Risk assessment -- Bayes theorem -- Distributionally robust optimization; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2023.126898
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: 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 calculation 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. Highlights: A novel pipeline leakage failure model considering the pipeline leakage dynamics is proposed. A risk assessment model for cascading failures in RIES considering the pipeline dynamics is proposed. A method for calculating the probability of cascading failures in RIES based on Bayes theorem is proposed. A novel ambiguity set combining JS divergence and uncertain moment is proposed to establish DRO model. Test results show the computational accuracy and efficiency of the proposed method.