Power Quality Dectection and Classification in Active Distribution Networks Based on Improved Empiricial Wavelet Transform and Disperson Entropy  

作　　者：Yanchun Xu Shirong Fan Shasha Xie Mi Lu 

机构地区：[1]College of Electrical Engineering and New Energy,China Three Gorges University,Yichang 443002,China [2]State Grid Changchun Power Supply Company,Changchun 13000,China [3]Department of Electrical and Computer Engineering,Texas A&M University,Texas 77843,USA

出　　处：《CSEE Journal of Power and Energy Systems》2022年第6期1646-1658,共13页中国电机工程学会电力与能源系统学报（英文）

基　　金：supported in part by National Natural Science Foundation of China Under Grant No.51507091;in part by the Research Fund for Excellent Dissertation of the China Three Gorges University Under Grant No.2020SSPY064.

摘　　要：In this paper,a model including wind power generation,photovoltaic power generation and electric vehicle for high permeability active distribution network(ADN)is established.The power quality(PQ)disturbance signals in the high permeability are extracted,and the characteristics of disturbance signals are analyzed in the situation of grid connection,interruption and islanding.The multi-scale fluctuation dispersion entropy(MFDE)initialized by the improved empirical wavelet transform(IEWT)is utilized to detect and classify the disturbance signals in the high permeability ADN.First,the eigenvectors of the disturbance signals are obtained by using the multi-scale fluctuation dispersion entropy initiated by the IEWT,and then the reduced eigenvectors are put into the support vector machine to classify the PQ disturbances caused by the access of the different distributed generators accessed.The classification results are compared with that in the traditional methods and other similar ways;the effectiveness of the IEWT-MFDE system is verified.

关 键 词：Active distribution network feature extraction power quality 

分 类 号：TM91[电气工程—电力电子与电力传动] TM761.12