Detection of high-impedance fault in distribution network based on time-frequency entropy of wavelet transform

被引:4
作者
Zhang, Shu [1 ]
Xiao, Xianyong [1 ]
He, Zhengyou [2 ]
机构
[1] Sichuan Univ, Coll Elect Engn, Chengdu 610065, Peoples R China
[2] Southwest Jiaotong Univ, Coll Elect Engn, Chengdu 610031, Peoples R China
关键词
high-impedance fault; wavelet transform; wavelet time-frequency entropy; time sequence; distribution network; VARIANCE; LOCATION;
D O I
10.1002/tee.23126
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
Due to the characteristics of small, nonlinear, random, and unstable current, the high impedance faults (HIF) are not always effectively cleared by conventional over current relays. A new simple and effective algorithm of HIF detection in distribution network based on the wavelet time-frequency entropy is presented in this article. On the basis of analysis, the time-frequency distribution characteristics in the concerned frequency band of HIFs by wavelet transform. The feature sequence developed by the wavelet time-frequency entropy at the time sequence is employed to detect HIF at substation. This criterion is calculated from the sum of wavelet time-frequency entropy at the time sequence every half cycle. If the value of the criterion is more than the threshold during four cycles, the HIF event can be identified. The developed detection method has been tested with real-world recorded signals from different HIF medium and PSCAD/EMTDC-generated signals. The result shows that the proposed method is robust to transients generated during normal events such as capacitor bank switching, load switching, and harmonic load. It has good performance for antinoise ability by noise reduction coefficient improved appropriately. And the proposed method has better reliability than the traditional third-harmonic-based method. (c) 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
引用
收藏
页码:844 / 853
页数:10
相关论文
共 50 条
  • [41] An improved high-impedance fault identification scheme for distribution networks based on kernel extreme learning machine
    Sheng, Wanxing
    Liu, Keyan
    Jia, Dongli
    Wang, Yao
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2024, 155
  • [42] Fault Detection of Distribution Network Considering High Impedance Faults
    Liu S.
    Liu H.
    Bi T.
    Yu X.
    Jiang Y.
    Dianwang Jishu/Power System Technology, 2023, 47 (08): : 3438 - 3447
  • [43] High Impedance Fault Detection in EHV Series Compensated Lines Using The Wavelet Transform
    Eldin, El Sayed Tag
    Ibrahim, Doaa Khalil
    Aboul-Zahab, Essam M.
    Saleh, Saber Mohamed
    2009 IEEE/PES POWER SYSTEMS CONFERENCE AND EXPOSITION, VOLS 1-3, 2009, : 1550 - +
  • [44] High Impedance Fault Detection Technique based on Discrete Wavelet Transform and Support Vector Machine In Power Distribution Networks
    Moloi, K.
    Jordaan, J. A.
    Hamam, Y.
    2017 IEEE AFRICON, 2017, : 9 - 14
  • [45] Time-Frequency Representation of Signals by Wavelet Transform
    Pukhova, Valentina
    Gorelova, Elizaveta
    Burnasheva, Sakhaya
    Ferrini, Gabriele
    PROCEEDINGS OF THE 2017 IEEE RUSSIA SECTION YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING CONFERENCE (2017 ELCONRUS), 2017, : 715 - 718
  • [46] A Novel High-Impedance Fault Detection Technique in Smart Active Distribution Systems
    Dubey, Kartika
    Jena, Premalata
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2024, 71 (05) : 4861 - 4872
  • [47] Active High-Impedance Fault Detection Method for Resonant Grounding Distribution Networks
    Yao, Zhiwei
    Liu, Yang
    Chen, Jian
    Ji, Jinpeng
    Zhang, Mengdi
    Gong, Yanyong
    IEEE ACCESS, 2024, 12 : 10932 - 10945
  • [48] Detection of shallow underground fissures by time-frequency analysis of Rayleigh waves based on wavelet transform
    Guang-zhou Shao
    Ting Du
    Applied Geophysics, 2020, 17 : 233 - 242
  • [49] Detection of shallow underground fissures by time-frequency analysis of Rayleigh waves based on wavelet transform
    Shao, Guang-zhou
    Du, Ting
    APPLIED GEOPHYSICS, 2020, 17 (02) : 233 - 242
  • [50] High Impedance Fault Detection based on Stockwell Transform
    Lima, Erica Mangueira
    de Almeida Coelho, Rodrigo
    Dantas Brito, Nubia Silva
    de Souza, Benemar Alencar
    PROCEEDINGS OF THE 2018 IEEE PES TRANSMISSION & DISTRIBUTION CONFERENCE AND EXHIBITION - LATIN AMERICA (T&D-LA), 2018,