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电网可靠性概率分布的参数不确定性辨识
引用本文:芦晶晶,赵渊,郭胤,张煦. 电网可靠性概率分布的参数不确定性辨识[J]. 重庆大学学报(自然科学版), 2014, 37(3): 29-34
作者姓名:芦晶晶  赵渊  郭胤  张煦
作者单位:中国电力科学研究院,北京100192;输配电装备及系统安全与新技术国家重点实验室重庆大学,重庆 400044;输配电装备及系统安全与新技术国家重点实验室重庆大学,重庆 400044;输配电装备及系统安全与新技术国家重点实验室重庆大学,重庆 400044
基金项目:国家自然科学基金资助项目(50977094,50607021);输配电装备及系统安全与新技术国家重点实验室自主研究项目(2007DA10512711208);中央高校基本科研业务费科研专项(CDJZR11150012);重庆市自然科学基金(CSTC,2011BB6047)
摘    要:元件可靠性参数受元件类型、运行时间、气候条件等诸多因素影响而具有不确定性,电网可靠性指标本质上也是一种随机变量。笔者从电网可靠性指标的概率分布计算以及其变动规律受参数不确定性影响的角度开展辨识研究,为探索参数不确定性对电网可靠性评估影响提供工程实用参考。在双循环蒙特卡洛模拟法的基础上提出了点估计法,为进一步提高计算效率,提出了改进序贯蒙特卡洛模拟法,并详细讨论了它们的原理及优缺点。评估结果表明:3种方法计算结果比较接近,但改进蒙特卡洛模拟法的计算效率最高,点估计法次之。通过对IEEE-RTS 79系统的评估分析,验证了改进序贯蒙特卡洛模拟法的实用性和有效性。

关 键 词:可靠性;概率分布;参数不确定性
收稿时间:2013-10-11

Parameter uncertainty analysis for probability distribution of bulk power systerm reliability
LU Jingjing,ZHAO Yuan,GUO Yin and ZHANG Xu. Parameter uncertainty analysis for probability distribution of bulk power systerm reliability[J]. Journal of Chongqing University(Natural Science Edition), 2014, 37(3): 29-34
Authors:LU Jingjing  ZHAO Yuan  GUO Yin  ZHANG Xu
Affiliation:China Electric Power Research Institute, Beijing 100192, China;State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 400044, China;State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 400044, China;State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 400044, China
Abstract:Component reliability parameters are of uncertainty and are affected by the component type, operation time, and weather conditions. So do the reliability indices of bulk power systems. The calculation of its probability distributions and its alteration law affected by parameters uncertainty are researched to provide practical engineering reference with exploring the impact of the parameter uncertainty on reliability assessment. The point estimate method is firstly proposed based on the two-loop Monte-Carlo simulation, and then the improved Monte-Carlo simulation is presented to enhance the calculation efficiency further. Moreover, their theories, merits and faults are explained in detail. It can be seen from the evaluation results for the RBTS power systems that the accuracy of the three methods are similar but the improved Monte-Carlo simulation has the highest efficiency, followed by the point estimate method. The IEEE-RTS 79 power system is evaluated by using the improved Monte-Carlo simulation, and the results verify its validity.
Keywords:reliability   probability distribution   parameter uncertainty
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