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

作     者:Jun An Zihan Deng Haipeng Chen Gang Mu Jun An;Zihan Deng;Haipeng Chen;Gang Mu

作者机构:Key Laboratory of Modern Power System Simulation and Control&Renewable Energy TechnologyMinistry of Education(Northeast Electric Power University)Jilin 132012.Jilin ProvinceChina 

出 版 物:《CSEE Journal of Power and Energy Systems》 (中国电机工程学会电力与能源系统学报(英文))

年 卷 期:2022年第8卷第4期

页      面:1233-1241页

核心收录:

学科分类:080802[工学-电力系统及其自动化] 0808[工学-电气工程] 08[工学] 

基  金:This work was supported in part by the National Natural Science Foundation of China(Key Project Number:51437003) 

主  题:Fault detection maximum eigenvalue noise random matrix theory smart grid 

摘      要:Fault detection and location are critically significant applications of a supervisory control system in a smart *** methods,based on random matrix theory(RMT),have been practiced using measurements to detect short circuit faults occurring on transmission ***,the diagnostic accuracy is infuenced by the noise signal in 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 *** comparing the indicator and the threshold,the occurrence of a fault can be ***,an augmented matrix is constructed to locate the fault *** proposed method can effectively achieve fault detection via the RMT without any influence of noise,and also does not depend on system *** experiment results are based on the IEEE 39-bus ***,actual provincial grid data is applied to validate the effectiveness of the proposed method.

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