Fault Location Detection of Transmission Lines in Noise Environments Based on Random Matrix Theory

查看全文 作　　者：Jun [1]An;Zihan [1]Deng;Haipeng [1]Chen;Gang [1]Mu

机构地区：[1]Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology,Ministry of Education(Northeast Electric Power University),Jilin 132012.Jilin Province,China

出　　处：《CSEE Journal of Power and Energy Systems》索引2022年第8卷第4期,共9页

基　　金：This work was supported in part by the National Natural Science Foundation of China(Key Project Number:51437003)。 摘　　要：Fault detection and location are critically significant applications of a supervisory control system in a smart grid.The methods,based on random matrix theory(RMT),have been practiced using measurements to detect short circuit faults occurring on transmission lines.However,the diagnostic accuracy is infuenced by the noise signal in the measurements.The relationship between mean eigenvalue of a random matrix and noise is detected in this paper,and the defects of the Mean Spectral Radius(MSR),as an indicator to detect faults,are theoretically determined,along with a novel indicator of the shifting degree of maximum eigenvalue and its threshold.By comparing the indicator and the threshold,the occurrence of a fault can be assessed.Finally,an augmented matrix is constructed to locate the fault area.The proposed method can effectively achieve fault detection via the RMT without any influence of noise,and also does not depend on system models.The experiment results are based on the IEEE 39-bus system.Also,actual provincial grid data is applied to validate the effectiveness of the proposed method. 关键词：Fault detection maximum eigenvalue noise random matrix theory smart grid

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Fault Location Detection of Transmission Lines in Noise Environments Based on Random Matrix Theory

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