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

被引:129
作者
Wang, Xiaowei [1 ,2 ]
Gao, Jie [3 ]
Wei, Xiangxiang [4 ]
Song, Guobing [1 ]
Wu, Lei [1 ]
Liu, Jingwei [5 ]
Zeng, Zhihui [2 ]
Kheshti, Mostafa [6 ]
机构
[1] Xi An Jiao Tong Univ, Sch Elect Engn, Xian 710049, Peoples R China
[2] Henan Polytech Univ, Sch Elect Engn & Automat, Jiaozuo 454000, Henan, Peoples R China
[3] Zhejiang Elect Power Co State Grid, Wenzhou Power Supply Co, Wenzhou 325000, Peoples R China
[4] Tech Univ Berlin, Fac Elect Engn & Comp Sci, D-10623 Berlin, Germany
[5] Zhuhai Xuji Elect Co, Dept Res & Dev, Zhuhai 519000, Peoples R China
[6] Shandong Univ, Key Lab Power Syst Intelligent Dispatch & Control, Jinan 250061, Peoples R China
基金
中国国家自然科学基金;
关键词
High impedance fault; variational mode decomposition; intrinsic mode function; Teager-Kaiser energy operators; time entropy; PROTECTION; SCHEME; LINE; WAVE;
D O I
10.1109/TSG.2019.2895634
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:6041 / 6054
页数:14
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