基于初值修正的电力元件可靠性参数校正  

Calibration method for electrical components reliability parameters based on initial values modification strategy

作　　者：彭吕斌 胡博[1] 谢开贵[1] 林铖嵘 卢慧 李维展 曹侃 周鲲鹏 PENG Lvbin;HU Bo;XIE Kaigui;LIN Chengrong;LU Hui;LI Weizhan;CAO Kan;ZHOU Kunpeng(State Key Laboratory of Power Transmission Equipment&System Security and New Technology(Chongqing University),Chongqing 400044,China;Electric Power Research Institute,State Grid Hubei Electric Power Co.,Ltd.,Wuhan 430077,China)

机构地区：[1]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 [2]国网湖北省电力有限公司电力科学研究院,湖北武汉430077

出　　处：《电工电能新技术》2023年第3期32-45,共14页Advanced Technology of Electrical Engineering and Energy

基　　金：国家电网有限公司总部管理科技项目(5100-202099273A-0-0-00)。

摘　　要：由于元件停运记录的疏漏,少部分元件可靠性参数统计值可能存在错误。错误的可靠性参数会导致误差较大的评估结果,进而影响电网的规划和运行决策,因此,有必要辨识并校正错误可靠性参数。在该背景下,本文利用电力系统可靠性评估逆问题理论,提出基于初值估计策略的元件可靠性参数辨识和校正方法。首先,提出可靠性参数辨识与校正效果的评价指标。其次,采用具有全局寻优能力的改进粒子群优化算法,估计敏感可靠性参数。然后,采用基于参数初值动态修正的滚动估计算法,估计全体参数,并根据各参数估值与其统计值的偏差,辨识错误参数。最后,利用区间算法校正错误参数。算例表明:当系统中参数错误的元件占比不超过9%时,所提模型及算法可辨识出全部错误参数,且其校正结果的误差在1%以内。Due to the omission of component outage records, the statistical values of reliability parameters of a small number of electrical components may be wrong. The errors of component reliability parameters are almost inevitable, which thereby leads to wrong reliability evaluation results and then affects the planning decision of power systems. To solve this problem, this paper proposes the model of IPRE for wrong CRPs calibration, and corresponding identification and calibration algorithms based on the initial value estimation strategy. First, the evaluation indexes of reliability parameter identification effect are proposed. Next, an improved particle swarm optimization algorithm with global optimization capability is used to estimate the sensitive reliability parameters. Then, a rolling estimation algorithm based on the dynamic correction for the initial values of CRPs is adopted to estimate all CRPs, and wrong CRPs are identified according to the deviations between the estimated values and the statistical values. Finally, the error parameters are corrected by the modified interval algorithm. Case studies show that our proposed algorithm can correct all the error parameters within 1% accuracy when the proportion of the false indexes is less than 9%.

关 键 词：电力系统 可靠性评估 逆问题 区间算法 粒子群优化算法 

分 类 号：TM732[电气工程—电力系统及自动化]