Single-ended fault location method for multi-terminal overhead-cable hybrid transmission line using alternating search algorithm

With rapid urbanization and power grid expansion, multi-terminal overhead-cable hybrid transmission lines have been increasingly utilized. However, the significant differences between overhead lines and cables, combined with the complexity of multi-terminal structures, lead to complicated refraction and reflection of travelling waves (TWs). Therefore, conventional single-ended TW-based fault location methods, which rely on accurate identification of reflected waves and a high sampling frequency in the MHz range, are not suitable. To address this issue, the paper proposes an enhanced TW-based fault location method based on waveform similarity. First, this method incorporates a frequency-dependent multi-terminal hybrid transmission line analytical model to reproduce fault transient voltage waveforms. On this basis, dynamic time warping and normalized mean square error collaborative similarity metrics are established to evaluate calculated and actual fault transient waveform characteristics, and the sensitivity analysis of the similarity metrics shows that there is a coupling relationship among the fault variables. Then, a variable-step, dual-metric alternating search algorithm is proposed to accurately identify fault variables (e.g., fault inception angle, fault resistance, and fault distance). Finally, simulation results using PSCAD/EMTDC demonstrate that the proposed method can accurately locate the fault at a sampling frequency of 200 kHz, is less affected by fault resistance, and does not require data synchronization.

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Publication Details

Journal
Electric Power Systems Research
Published
2026-09-17
DOI
https://doi.org/10.1016/j.epsr.2026.114196
Primary Topic
Power Systems Fault Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Single-ended fault location method for multi-terminal overhead-cable hybrid transmission line using alternating search algorithm

Haifeng Li, Yuansheng Liang, Xinquan Chen, Luo Zhengcheng et al.
Electric Power Systems Research
Power Systems Fault Detection
article

Single-ended fault location method for multi-terminal overhead-cable hybrid transmission line using alternating search algorithm

Haifeng Li, Yuansheng Liang, Xinquan Chen, Luo Zhengcheng, Gang Wang
article en

Abstract

With rapid urbanization and power grid expansion, multi-terminal overhead-cable hybrid transmission lines have been increasingly utilized. However, the significant differences between overhead lines and cables, combined with the complexity of multi-terminal structures, lead to complicated refraction and reflection of travelling waves (TWs). Therefore, conventional single-ended TW-based fault location methods, which rely on accurate identification of reflected waves and a high sampling frequency in the MHz range, are not suitable. To address this issue, the paper proposes an enhanced TW-based fault location method based on waveform similarity. First, this method incorporates a frequency-dependent multi-terminal hybrid transmission line analytical model to reproduce fault transient voltage waveforms. On this basis, dynamic time warping and normalized mean square error collaborative similarity metrics are established to evaluate calculated and actual fault transient waveform characteristics, and the sensitivity analysis of the similarity metrics shows that there is a coupling relationship among the fault variables. Then, a variable-step, dual-metric alternating search algorithm is proposed to accurately identify fault variables (e.g., fault inception angle, fault resistance, and fault distance). Finally, simulation results using PSCAD/EMTDC demonstrate that the proposed method can accurately locate the fault at a sampling frequency of 200 kHz, is less affected by fault resistance, and does not require data synchronization.

Electric Power Systems ResearchVol. 265
Hong Kong Polytechnic University (HK), South China University of Technology (CN)
Major Projects of Guangdong Education Department for Foundation Research and Applied Research
Sustainable cities and communities
Openalex Percentile: Top 15%
Power Systems Fault Detection
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