Article: A self-healing method for faults in low and medium voltage substations during large-scale power outages Journal: International Journal of Energy Technology and Policy (IJETP) 2026 Vol.21 No.2 pp.136 - 155 Abstract: To address the coordination gap between distributed generation anti-islanding protection and feeder automation, this study proposes a self-healing method for low/medium-voltage faults during large-scale outages. A multi-domain (time, frequency, wavelet) detection approach was developed using zero-sequence current analysis and a single-phase grounding fault model. Feature selection via random forest and fault zone identification with LightGBM enhance fault response efficiency. A distributed self-healing strategy based on smart terminal collaboration achieves autonomous fault isolation via associated feeder partitioning. Combining switch transfer and DG islanding restores power to non-fault zones. A topological adjacency matrix and load-based repair priority model optimise fault location, network reconfiguration, and repair scheduling. Experimental results demonstrate 50ms fault detection (0.5%-1% false positives) and 95%-99% load recovery, improving grid resilience. Inderscience Publishers - linking academia, business and industry through research

Title: A self-healing method for faults in low and medium voltage substations during large-scale power outages

Authors: Rongsheng Zhou; Jiaxin Lv; Guanquan Dai; Zhaoyu Wu; Shaozhong Xiang

Addresses: Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guang'zhou, 510630, China ' Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guang'zhou, 510630, China ' Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guang'zhou, 510630, China ' Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guang'zhou, 510630, China ' Dongfang Electronics Corporation, Yantai, 264000, China

Abstract: To address the coordination gap between distributed generation anti-islanding protection and feeder automation, this study proposes a self-healing method for low/medium-voltage faults during large-scale outages. A multi-domain (time, frequency, wavelet) detection approach was developed using zero-sequence current analysis and a single-phase grounding fault model. Feature selection via random forest and fault zone identification with LightGBM enhance fault response efficiency. A distributed self-healing strategy based on smart terminal collaboration achieves autonomous fault isolation via associated feeder partitioning. Combining switch transfer and DG islanding restores power to non-fault zones. A topological adjacency matrix and load-based repair priority model optimise fault location, network reconfiguration, and repair scheduling. Experimental results demonstrate 50ms fault detection (0.5%-1% false positives) and 95%-99% load recovery, improving grid resilience.

Keywords: large-scale power outage; low to medium pressure platform area; fault self-healing; zero sequence current characteristics.

DOI: 10.1504/IJETP.2026.153601

International Journal of Energy Technology and Policy, 2026 Vol.21 No.2, pp.136 - 155

Received: 05 Sep 2025
Accepted: 15 Dec 2025
Published online: 18 May 2026 *

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Title: A self-healing method for faults in low and medium voltage substations during large-scale power outages

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