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<p>In light of the significant likelihood of single-phase ground faults, it’s vital to quickly and accurately identify faulty feeders to improve power supply reliability. This paper proposes a feeder detection technique based on the Wasserstein distance (WD) coefficient as a solution to the problem of feeder identification in the event of a single-phase ground fault (SPGF) in a neutral non-effectively grounded system. The technique employs the Empirical Wavelet Transform (EWT) for preliminary processing of zero sequence current (ZSC) and subsequently calculates the WD coefficient between different feeders to identify the faulty feeder. To evaluate the efficacy of the proposed method, a 10kV distribution network model was constructed in MATLAB for simulating four ground fault types and six fault scenarios. The results demonstrate that the proposed algorithm exhibits high accuracy and robust performance.</p>

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Distribution Network Faulty Feeder Detection Method Based on Empirical Wavelet Transform and Wasserstein Distance Coefficient

  • 期刊论文

  • 发表日期：

    2025年5月7日

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  • Miaomiao Zhou,
  • Mengshi Li,
  • Haiting Shan

摘要

In light of the significant likelihood of single-phase ground faults, it’s vital to quickly and accurately identify faulty feeders to improve power supply reliability. This paper proposes a feeder detection technique based on the Wasserstein distance (WD) coefficient as a solution to the problem of feeder identification in the event of a single-phase ground fault (SPGF) in a neutral non-effectively grounded system. The technique employs the Empirical Wavelet Transform (EWT) for preliminary processing of zero sequence current (ZSC) and subsequently calculates the WD coefficient between different feeders to identify the faulty feeder. To evaluate the efficacy of the proposed method, a 10kV distribution network model was constructed in MATLAB for simulating four ground fault types and six fault scenarios. The results demonstrate that the proposed algorithm exhibits high accuracy and robust performance.