High Impedance Fault Detection Method Based on Variational Mode Decomposition and Teager–Kaiser Energy Operators for Distribution Network

Xiaowei Wang(Xi'an Jiaotong University), Jie Gao, Xiangxiang Wei(Technische Universität Berlin), Guobing Song(Xi'an Jiaotong University), Lei Wu(Xi'an Jiaotong University), Jingwei Liu, Zhihui Zeng(Henan Polytechnic University), Mostafa Kheshti(Shandong University)
IEEE Transactions on Smart Grid
January 29, 2019
Cited by 146

Abstract

The focus of the paper is the difficulty of high impedance fault (HIF) detection in distribution network, and its ease to be confused with capacitor switching (CS) and load switching (LS). Based on the intermittent reignition and extinction characteristics of HIF current, this paper proposes a novel HIF detection method, which combines variational mode decomposition (VMD) and Teager-Kaiser energy operators (TKEOs). The HIF detection method is as follows: First, perform the VMD on transient zero sequence currents to obtain the intrinsic mode functions (IMFs) and select the IMFs with the largest kurtosis value as the characteristic IMFs. Second, calculate the characteristic IMFs to obtain TKEOs and divide into subintervals of TKEOs waveform to calculate the time entropy values. Finally, construct HIF detection criterion as follows: when time entropy value is 0, it is judged as CS or LS. When the entropy value is not 0, it is judged as HIF. A large number of simulations and field data tests show that the method is accurate and stable, and under the interference of 1 dB strong noise, it can accurately judge. Compared with other methods, the method has higher feature extraction accuracy, less calculation time, and better judgment accuracy.


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