Joint Online Identification Method for Dynamic Topology and Line Parameters of Distribution Network

被引：0
|
作者：
Yang D. [1 ]
Fu Q. [1 ]
Liu X. [1 ]
Liu Y. [2 ]
Jiang C. [1 ]
机构：
[1] Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education (Northeast Electric Power University), Jilin
[2] State Grid Weifang Hanting Power Supply Company, Weifang
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2022年 / 46卷 / 02期
关键词：
Distribution network; Line parameter identification; Orthogonal matrix and right triangular matrix decomposition; Support vector machine; Topology identification;
D O I：
10.7500/AEPS20210524011
中图分类号：
学科分类号：
摘要：
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. © 2022 Automation of Electric Power Systems Press.
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页码：101 / 108
页数：7
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