Research on a Novel Fault Identification and Rapid Location Method for Low-Voltage Distribution Lines

Zongyan Xue; Ning Shao

doi:10.54097/hdxzsf79

Research on a Novel Fault Identification and Rapid Location Method for Low-Voltage Distribution Lines

Zongyan Xue, Ning Shao

International Journal of Energy, (2026), Vol.10, No.3, pp.13-17

Published: October 30, 2026

DOI: 10.54097/hdxzsf79

PDF: Download Full Text PDF

Abstract

Fault diagnosis on low-voltage distribution lines is often limited by inaccurate classification, delayed localization, and sensitivity to interference. This study develops a fault-identification and rapid-location method that combines multisource feature analysis with Internet of Things (IoT) sensing. Short-circuit, grounding, and open-circuit faults are first characterized using line measurements. A wavelet-transform and random-forest model then classifies the fault type, while an improved weighted-centroid algorithm uses data from deployed IoT sensor nodes to estimate its position. The method was evaluated in simulations and on an operating line. Across these tests, fault-identification accuracy exceeded 95%, location error remained within 5m, and response time was below 2s. These results satisfy the stated engineering requirements for fault handling on low-voltage distribution lines.

Keywords: Low-Voltage Distribution Lines, Fault Identification, Rapid Location, Machine Learning, Internet of Things, Weighted Centroid Algorithm

APA Citation: Zongyan Xue, Ning Shao (2026). Research on a Novel Fault Identification and Rapid Location Method for Low-Voltage Distribution Lines. International Journal of Energy, 10(3), 13-17. https://doi.org/10.54097/hdxzsf79

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