Faulty feeder detection based on image recognition of current waveform superposition in distribution networks

被引:11
|
作者
Yuan, Jiawei [1 ]
Jiao, Zaibin [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Elect Engn, Xianning West Rd 28, Xian 710000, Peoples R China
关键词
Attention strategy; Correlation comparison; Waveform superposition; Faulty feeder detection; Topology adaptability; LOCATION; TRANSFORM; DIAGNOSIS; ENTROPY; SYSTEMS;
D O I
10.1016/j.asoc.2022.109663
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Faulty feeder detection is essential for maintaining the security and stability of energy supply in distribution networks. However, it is rather difficult to identify a specific faulty feeder owing to small fault currents and complex fault transients. To improve the detection accuracy, this study proposes a faulty-feeder detection method based on image recognition of superimposed zero-sequence currents. A convolutional neural network (CNN) is utilized to recognize the superimposed currents in the same plot, rather than a raw single current, which can realize correlation comparisons between the currents. In addition, the zero-sequence currents of different feeders are superimposed according to a specific sequence, and the CNN can adapt to the changing topologies of distribution networks while conducting correlation comparisons. Because zero-sequence currents decay rapidly over time, an attention learning block is embedded into the CNN to enhance the discriminative capability. A total of 14,718 sets of experimental data obtained from simulations and practical distribution networks were collected to verify the effectiveness of the proposed method. Comparisons with other traditional methods and learning-based methods adopted in previous studies justify the superiority of the proposed method in terms of detection accuracy and detection efficiency. Therefore, the proposed method can be implemented in real distribution networks for faulty feeder detection.(c) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] High-impedance faulty feeder detection for cross-country faults in distribution networks based on zero-sequence active power regulation
    Lan, Yuting
    Yu, Kun
    Zeng, Xiangjun
    Cai, Rong
    Deng, Qingbo
    Wu, Chenyu
    He, Shigeng
    Xu, Shijie
    Jia, Youcheng
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2024, 162
  • [32] Discrete Frechet Distance Algorithm-Based Faulty Feeder Selection Method for Flexible Grounding System in Distribution Networks
    Zhang, Chi
    Liu, Kangli
    Zhang, Sen
    Liu, Biyang
    Zhao, Jianfeng
    2021 IEEE TEXAS POWER AND ENERGY CONFERENCE (TPEC), 2021, : 166 - 171
  • [33] GAN-based semi-supervised learning method for identification of the faulty feeder in resonant grounding distribution networks
    Yu, Xiuyong
    Gu, Juping
    Zhang, Xinsong
    Mao, Jingfeng
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2023, 144
  • [34] An Arc Grounding Fault Detection Method in Distribution Networks Using Chaotic DC Waveform Recognition
    Yang, Shiwu
    Chen, Qing
    Li, Hongbin
    Jiao, Yang
    Tian, Ruoyan
    He, Yuxiang
    Zhang, Chuanji
    Liu, Chang
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2025, 74
  • [35] Faulty feeder detection by adjusting the compensation degree of arc-suppression coil for distribution network
    Huang, Chun
    Tang, Tao
    Jiang, Yajun
    Hua, Leng
    Hong, Chen
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2018, 12 (04) : 807 - 814
  • [36] Nonlinearity Characteristic of High Impedance Fault at Resonant Distribution Networks: Theoretical Basis to Identify the Faulty Feeder
    Wei, Mingjie
    Zhang, Hengxu
    Shi, Fang
    Chen, Weijiang
    Terzija, Vladimir
    IEEE TRANSACTIONS ON POWER DELIVERY, 2022, 37 (02) : 923 - 936
  • [37] A faulty feeder selection method for SLG faults based on active injection approach in non-effectively grounded DC distribution networks
    Xu, Ruidong
    Song, Guobing
    Chang, Zhongxue
    Yang, Jiayi
    ELECTRIC POWER SYSTEMS RESEARCH, 2024, 234
  • [38] A Novel Approach Based on CEEMDAN to Select the Faulty Feeder in Neutral Resonant Grounded Distribution Systems
    Jin, Tao
    Zhuo, Feng
    Mohamed, Mohamed A.
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2020, 69 (07) : 4712 - 4721
  • [39] An Intrinsic Faulty Feeder Selection Approach for Resonant Grounded Power Distribution Networks in Bushfire Prone Areas Using Zero-Sequence Current Ratio
    Pirmani, Susheel Kumar
    Mahmud, Md Apel
    IEEE SYSTEMS JOURNAL, 2023, 17 (04): : 6460 - 6471
  • [40] Zero Sequence Current Detection Method of High Impedance Faults Using Distortion Waveform in Distribution Networks
    Manmoh, Jiraphat
    Srirattanawichaikul, Watcharin
    2023 IEEE PES 15TH ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE, APPEEC, 2023,