Power System Reliability Evaluation Based on Sequential Monte Carlo Simulation Considering Multiple Failure Modes of Components

作     者：Wei Huang Bo Hu Changzheng Shao Wei Li Xiaozhe Wang Kaigui Xie C.Y.Chung 

作者机构：State Key Laboratory of Power Transmission Equipment TechnologySchool of Electrical EngineeringChongqing UniversityChongqingChina China Southern Power GridGuangzhouChina Department of Electrical and Computer EngineeringMcGill UniversityMontrealCanada Department of Electrical and Electronic EngineeringHong Kong Polytechnic UniversityHong KongChina 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报(英文))

年 卷 期：2025年第13卷第1期

页      面：202-214页

核心收录：

学科分类：080802[工学-电力系统及其自动化] 0808[工学-电气工程] 08[工学] 

基　　金：supported by the National Natural Science Foundation of China(No.52022016) the Fundamental Research Funds for the Central Universities(No.2023CDJYXTD-004) the Graduate Research and Innovation Foundation of Chongqing(No.CYB22014) 

主　　题：Power system reliability evaluation aging failure sequential Monte Carlo simulation 

摘      要：The component aging has become a significant concern worldwide,and the frequent failures pose a serious threat to the reliability of modern power *** light of this issue,this paper presents a power system reliability evaluation method based on sequential Monte Carlo simulation(SMCS)to quantify system reliability considering multiple failure modes of ***,a three-state component reliability model is established to explicitly describe the state transition process of the component subject to both aging failure and random failure *** this model,the impact of each failure mode is decoupled and characterized as the combination of two state duration variables,which are separately modeled using specific probability ***,SMCS is used to integrate the three-state component reliability model for state transition sequence generation and system reliability ***,various reliability metrics,including the probability of load curtailment(PLC),expected frequency of load curtailment(EFLC),and expected energy not supplied(EENS),can be *** ensure the applicability of the proposed method,Hash table grouping and the maximum feasible load level judgment techniques are jointly adopted to enhance its computational *** studies are conducted on different aging scenarios to illustrate and validate the effectiveness and practicality of the proposed method.