Eigen Characteristic of Sample Covariance Matrix Based Multi-Disturbance Positioning Method of Power System

被引:0
|
作者
Li H. [1 ]
Han S. [1 ]
Zhou Z. [2 ]
机构
[1] Department of Electrical Engineering, Guizhou University, Guiyang
[2] Guizhou Power Grid Dispatching and Control Centers, Guiyang
关键词
Disturbance positioning; Eigen characteristic; Multi-disturbance; Phase-transition phenomenon; Sample covariance matrix; Spiked model;
D O I
10.19595/j.cnki.1000-6753.tces.200013
中图分类号
学科分类号
摘要
A random matrix theory based multiple disturbance positioning method employing maximum eigenvalue of sample covariance matrix (Max-ESCM) and its corresponding Minimum Eigenvector (Min-ESCM) is proposed for improving the efficiency of disturbance positioning and the adaptability in multi-disturbance condition. A group of data source matrices should be firstly constructed considering random load fluctuation and noise interference for simulating the working conditions in the real world. Then the standard matrices can be obtained using a moving window matrix. The sample covariance matrices would be formed as a consequence. Furthermore, the Max-ESCM may be acquired. Meanwhile, the Spiked model based dynamic threshold for Max-ESCM might be used for detecting the abnormal disturbance in power system. Consequently, the abnormal elements involving the Min-ESCM will be found according to the phase-transition phenomenon if the dynamic threshold for Max-ESCM is violated, which might be helpful for identifying the disturbed buses with anomalous variation. The case studies have been carried on an IEEE 118-bus system utilizing DIgSILENT and Matlab® software, involving three kinds of working conditions such as simultaneous disturbance events, successive disturbance events and simultaneous fault events. The results show that the proposed methodology is valid and efficient. © 2021, Electrical Technology Press Co. Ltd. All right reserved.
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页码:646 / 655
页数:9
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