High Impedance Fault Identification Method of Distribution Networks

被引:0
|
作者
Huang, Yong [1 ]
Chen, Minyou [1 ]
Zhai, Jinqian [1 ]
Yan, Hong [2 ]
机构
[1] Chongqing Univ, State Key Lab Power Transmiss Equipment & Syst Se, Chongqing 400044, Peoples R China
[2] AnHui Elect Power Corp, NingGuo Elect Power Supply Co LTD, Xuan Cheng 242300, Peoples R China
来源
ELECTRICAL POWER & ENERGY SYSTEMS, PTS 1 AND 2 | 2012年 / 516-517卷
基金
中国国家自然科学基金;
关键词
high-impedance fault; Discrete Wavelet Transform; Distribution networks; fault mode; Transients signal;
D O I
10.4028/www.scientific.net/AMR.516-517.1785
中图分类号
O414.1 [热力学];
学科分类号
摘要
High impedance fault has always been difficult for distribution network fault identification due to its unobvious fault signature and difficult detection. This paper decomposed the transient signal in multi-scale by utilizing the good localization performance of the wavelet in both time domain and frequency domain, reconstructed the wavelet coefficients under each scale, took the wavelet reconstruction coefficient which was under the scale 3, calculated the size spectrum of each feeder line in timing floating window and identified the circuits in which the faults lined according to the value of the size spectrum. The high impedance fault simulation system was built based upon the study of the various transient signals in power systems, and the high impedance fault simulation analysis of the distribution feeder was undertaken through PSCAD simulation platform using high impedance fault model. Simulation analysis showed that the method could effectively extract the feature of high impedance fault on high impedance fault identification.
引用
收藏
页码:1785 / +
页数:2
相关论文
共 50 条
  • [1] Detection of High Impedance Fault in Distribution Networks
    Kavaskar, Sekar
    Mohanty, Nalin Kant
    AIN SHAMS ENGINEERING JOURNAL, 2019, 10 (01) : 5 - 13
  • [2] Explainable incremental learning for high-impedance fault detection in distribution networks
    Bai, Hao
    Gao, Jian-Hong
    Liu, Tong
    Guo, Zi-Yi
    Guo, Mou-Fa
    COMPUTERS & ELECTRICAL ENGINEERING, 2025, 122
  • [3] High impedance fault detection method for distribution networks under non-linear conditions
    Lima, Erica Mangueira
    Coelho, Rodrigo de Almeida
    Brito, Nubia Silva Dantas
    de Souza, Benemar Alencar
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2021, 131
  • [4] Support Vector Machine Based Method for High Impedance Fault Diagnosis in Power Distribution Networks
    Moloi, K.
    Jordaan, J. A.
    Hamam, Y.
    INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2018, PT I, 2018, 11314 : 9 - 16
  • [5] High-impedance fault modeling and classification in power distribution networks
    Sousa Carvalho, Jose Genilson
    Almeida, Aryfrance Rocha
    Ferreira, Danton Diego
    dos Santos Jr, Bartolomeu Ferreira
    Pereira Vasconcelos, Luis Henrique
    Sobreira, Danilo de Oliveira
    ELECTRIC POWER SYSTEMS RESEARCH, 2022, 204
  • [6] Comparative Analysis of High Impedance Fault Detection Techniques on Distribution Networks
    Hamatwi, Ester
    Imoru, Odunayo
    Kanime, Matheus M. M.
    Kanelombe, Hitila S. A.
    IEEE ACCESS, 2023, 11 : 25817 - 25834
  • [7] An incremental high impedance fault detection method under non-stationary environments in distribution networks
    Guo, Mou-Fa
    Yao, Meitao
    Gao, Jian-Hong
    Liu, Wen-Li
    Lin, Shuyue
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2024, 156
  • [8] 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
  • [9] High-impedance fault detection method based on sparse data divergence discrimination in distribution networks
    Cui, Laixi
    Liu, Yang
    Wang, Lei
    Chen, Jian
    Zhang, Xue
    ELECTRIC POWER SYSTEMS RESEARCH, 2023, 223
  • [10] AN IMPROVED METHOD FOR HIGH IMPEDANCE FAULT DETECTION IN MEDIUM VOLTAGE NETWORKS
    Ravlic, Sonja
    Marusic, Ante
    Havelka, Juraj
    TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2017, 24 (02): : 391 - 396