Quasi-single phase permanent fault identification method and reclosing strategy based on multi-level confidence rules

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Authors: Hongchun Shu, Baisong Liu, Weijie Lou, Yutao Tang, Haoming Liu, Yiming Han, Yue Dai, Ying Cao
Cited by: 2
References: 26

Abstract

As global temperatures rise, the frequency of lightning increases, making lightning one of the principal threats to power-system security. Field incidents indicate that, within the automatic reclosing time window, multiple-stroke lightning can exhibit behavior resembling a permanent fault, which leads misoperation and reclosure failure and, in many cases, severe outages. Analysis in this paper indicates that, within this window, transient impulses on the microsecond scale from successive strokes superimpose on the secondary arc current, driving dynamic arc re-ignition and in extreme cases, sustained arcing on the transmission line. This mechanism distorts the steady-state electrical quantities used by conventional criteria and accounts for the observed misoperations and failures to operate. To address this problem, this paper proposes an identification method for quasi-single phase permanent fault (Q-SPF) based on multi-level confidence rules. The scheme adopts a cascaded logic that comprises arc sustainment identification, fault occurrence identification, and lightning fault identification, together with corresponding confidence assessments, to accurately distinguish Q-SPF events induced by multiple strokes. Robustness is verified on an RTDS model under variations in sensor deployment, lightning striking location, conventional short-circuit faults, positive-polarity lightning, and double-circuit same-tower configurations.© 2017 Elsevier Inc. All rights reserved.

Fields of Study & Subjects

Electrical Fault Detection and Protection Power Systems Fault Detection Lightning and Electromagnetic Phenomena

Publication details

Journal / source
International Journal of Electrical Power & Energy Systems
Publisher
Elsevier BV
Volume
175
Pages
111569–111569
Publication date
18 January 2026
Language
EN