基于改进鸡群算法的静止无功补偿器模型参数辨识方法  

Research on Parameter Identification of Static Var Compensator Model Based on Improved Chicken Swarm Optimization Algorithm

作　　者：聂永辉 张春雷 高磊 赵妍[4] 王明超 NIE Yonghui;ZHANG Chunlei;GAO Lei;ZHAO Yan;WANG Mingchao(Academic Administration Office,Northeast Electric Power University,Jilin 132012,Jilin Province,China;College of Electrical Engineering,Northeast Electric Power University,Jilin 132012,Jilin Province,China;China Electric Power Research Institute,Haidian District,Beijing 100192,China;School of Power Transmission and Distribution Technology,Northeast Electric Power University, Jilin 132012,Jilin Province,China)

机构地区：[1]东北电力大学教务处,吉林省吉林市132012 [2]东北电力大学电气工程学院,吉林省吉林市132012 [3]中国电力科学研究院有限公司,北京市海淀区100192 [4]东北电力大学输变电技术学院,吉林省吉林市132012

出　　处：《电网技术》2019年第2期731-738,共8页Power System Technology

基　　金：国家自然科学基金资助项目(51577023);吉林省教育厅"十三五"科学技术研究项目(JJKH20180445KJ)~~

摘　　要：为获取准确的静止无功补偿器模型参数以满足电力系统日益精细化的仿真要求,提出一种基于改进鸡群算法的静止无功补偿器模型参数辨识方法。首先建立考虑各环节特性的静止无功补偿器数学模型;然后对鸡群算法进行改进,并应用于静止无功补偿器模型参数辨识;最后,针对多参数同时辨识引起的辨识结果不准确问题,提出一种基于参数敏感度的静止无功补偿器模型参数逐步辨识方法,为准确辨识静止无功补偿器模型参数提供了新的辨识策略。算例结果证明了所提方法的有效性和准确性。In order to obtain accurate parameters of static var compensator(SVC) model to meet increasingly sophisticated simulation requirements of power system, a method of SVC model parameter identification based on chicken swarm optimization algorithm(CSO) is proposed in this paper. Firstly, an SVC mathematic model considering the characteristics of each link is established. Secondly, the CSO is improved and applied to identify the SVC model parameters. Finally, according to the problem of inaccurate identification result caused by simultaneous identification of multiple parameters, a stepwise identification method of SVC model parameters based on parameter sensitivity is proposed, providing a new identification strategy for accurate identification of SVC model parameters. Simulation results show that the proposed method is effective and accurate in parameter identification of the SVC model.

关 键 词：静止无功补偿器 数学模型 改进鸡群算法(ICSO) 敏感度分析 参数辨识 

分 类 号：TM721[电气工程—电力系统及自动化]