基于状态空间分割非重复抽样的电力系统可靠性评估方法  

Power System Reliability Evaluation Method Based on State Space Segmentation and Non-Repetitive Sampling

作　　者：高泰路 曲丽萍 张杰 刘斌 崔文超 GAO Tailu;QU Liping;ZHANG Jie;LIU Bin;CUI Wenchao(College of Electrical and Information Engineering,Beihua University,Jilin 132021,China)

机构地区：[1]北华大学电气与信息工程学院,吉林吉林132021

出　　处：《北华大学学报（自然科学版）》2022年第3期388-395,共8页Journal of Beihua University（Natural Science）

基　　金：国家重点新产品计划项目(2010GRB10003);吉林省科技发展计划项目(20190102015JH);吉林省教育厅科学技术研究项目(JJKH20200043KJ).

摘　　要：为提高非序贯蒙特卡洛模拟法的抽样效率,将状态空间分割思想与状态筛选法相结合,提出基于状态空间分割非重复抽样的电力系统可靠性评估方法.通过重要状态子空间确定方法划分系统状态空间,采用解析法高效求解重要状态子空间可靠性指标,采用拉丁超立方抽样法对剩余状态子空间进行采样,采样过程中进行两次状态筛选,避免对相同状态的重复抽取.应用该方法对IEEE-RTS系统与修改后的IEEE-RTS系统进行可靠性评估.结果表明,所提出的方法既能确保计算精度,又可以加快收敛速度,降低抽样方差.In order to improve the sampling efficiency of non-sequential Monte Carlo simulation method,a reliability evaluation method of power system based on state space segmentation and non-repetitive sampling is proposed by combining state space segmentation with state screening method.The system state space is divided by the determination method of the important state subspace.The reliability index of the important state subspace is solved efficiently by the analytic method.Latin hypercube sampling method is used to sample the remaining state subspace.Two state screenings are carried out in the sampling process to avoid the repeated extraction of the same state.This method is used to evaluate the reliability of IEEE-RTS system and modified IEEE-RTS system.The results show that the proposed algorithm can not only ensure the calculation accuracy,but also accelerate the convergence speed and reduce the sampling variance.

关 键 词：电力系统可靠性评估 重要抽样 拉丁超立方抽样 状态空间分割 状态筛选 

分 类 号：TM71[电气工程—电力系统及自动化]