Research on Single-Phase Grounding Fault Line Selection Method Based on MPA-VMD and Multiscale Dispersion Entropy

Single phase grounding faults occur frequently in distribution networks. The challenge of fault line selection arises due to the weak and indistinct characteristics of the fault signals. To solve this problem, a single-phase grounding fault line selection method based on the Marine Predators Algorithm (MPA) optimized Variational Mode Decomposition (VMD) and multi-scale dispersion entropy is proposed in this paper. Firstly, the zero-sequence current signals from each line are collected by simulating the fault point. Secondly, the Marine Predators Algorithm is utilized to optimize and obtain the best parameters for decomposing the zero-sequence current signals using VMD. Subsequently, the multi-scale dispersion entropy values of the decomposed zero-sequence current components for each line are calculated to construct feature vectors. Finally, the faulty line is identified by analyzing the modulus values of these feature vectors. Experimental results demonstrate that the proposed method can accurately select the faulty line under various complex operating conditions, exhibiting high accuracy and robustness.

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Publication Details

Published
2025-08-08
DOI
https://doi.org/10.1109/iaeac65194.2025.11166002
Primary Topic
Power Systems Fault Detection
Type
article
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article

Research on Single-Phase Grounding Fault Line Selection Method Based on MPA-VMD and Multiscale Dispersion Entropy

Bo Dang, Xiaomeng Wu, Zhongxue Yang
Power Systems Fault Detection
article

Research on Single-Phase Grounding Fault Line Selection Method Based on MPA-VMD and Multiscale Dispersion Entropy

Bo Dang, Xiaomeng Wu, Zhongxue Yang
article en

Abstract

Single phase grounding faults occur frequently in distribution networks. The challenge of fault line selection arises due to the weak and indistinct characteristics of the fault signals. To solve this problem, a single-phase grounding fault line selection method based on the Marine Predators Algorithm (MPA) optimized Variational Mode Decomposition (VMD) and multi-scale dispersion entropy is proposed in this paper. Firstly, the zero-sequence current signals from each line are collected by simulating the fault point. Secondly, the Marine Predators Algorithm is utilized to optimize and obtain the best parameters for decomposing the zero-sequence current signals using VMD. Subsequently, the multi-scale dispersion entropy values of the decomposed zero-sequence current components for each line are calculated to construct feature vectors. Finally, the faulty line is identified by analyzing the modulus values of these feature vectors. Experimental results demonstrate that the proposed method can accurately select the faulty line under various complex operating conditions, exhibiting high accuracy and robustness.

Xi'an Shiyou University (CN)
Openalex Percentile: Top 68%
Power Systems Fault Detection
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