摘要
为了实现配电网拓扑和线路参数精确辨识,考虑拓扑结构的变化,提出一种基于智能电表量测数据的配电网拓扑与线路参数联合在线辨识方法。首先,利用不同拓扑结构下的历史量测数据,分别建立基于支持向量机(SVM)的多分类模型和基于线性回归的拓扑与线路参数辨识初始模型。然后,以SVM多分类模型实现在线量测数据与拓扑结构间的映射,得到拓扑与线路参数初值,并结合拓扑与线路参数辨识修正模型,获得精确的辨识结果。此外,为了提高数值稳定性,采用正交三角分解求解辨识过程中的线性方程。最后,通过算例仿真验证了该方法的有效性。
In order to achieve accurate identification of distribution network topology and line parameters,a joint online identification method for topology and line parameters of distribution network based on smart meter measurement data is proposed considering the change of topology.Firstly,a support vector machine(SVM)based multi-classification model and a linear regression based initial model for topology and line parameter identification are established using historical measurement data of different topologies.Then,the SVM multi-classification model is used to realize the mapping between online measurement data and topology structure to obtain the initial values of topology and line parameters,and the topology and line parameter identification correction model is combined to obtain accurate identification results.In addition,to improve the numerical stability,orthogonal matrix and right triangular matrix decomposition is used to solve the linear equations in the identification process.Finally,the effectiveness of the method is verified by arithmetic simulation.
作者
杨冬锋
付强
刘晓军
刘迎迎
姜超
YANG Dongfeng;FU Qiang;LIU Xiaojun;LIU Yingying;JIANG Chao(Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology,Ministry of Education(Northeast Electric Power University),Jilin 132012,China;State Grid Weifang Hanting Power Supply Company,Weifang 261100,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2022年第2期101-108,共8页
Automation of Electric Power Systems
基金
国家重点研发计划资助项目(2019YFB1505405)。
关键词
配电网
拓扑辨识
线路参数辨识
支持向量机
正交三角(QR)分解
distribution network
topology identification
line parameter identification
support vector machine
orthogonal matrix and right triangular matrix decomposition
