IEEE Access (Jan 2022)

SF<sub>6</sub> Decomposed Component Analysis for Partial Discharge Diagnosis in GIS: A Review

  • Ammar Salah Mahdi,
  • Zulkurnain Abdul-Malek,
  • Rai Naveed Arshad

DOI
https://doi.org/10.1109/ACCESS.2022.3156926
Journal volume & issue
Vol. 10
pp. 27270 – 27288

Abstract

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This paper compiles, summarizes, and deliberates over one hundred important works on the different approaches and advances in the surveillance and diagnosis of the internal status of SF6 gas-insulated equipment (GIE), particularly partial discharge (PD) diagnosis in gas-insulated switchgear (GIS), and the proposed diagnosis techniques used. This review focused on four research aspects on PD diagnosis related to the SF6 decomposition mechanism under PD activity, the developments in PD detection techniques, PD sources identification, and PD severity evaluation. Besides, the effect of various factors such as gas pressure, applied voltage, and impurities on the deterioration of the insulation gas and its influence on the diagnosis process has been reviewed. Currently, some reviews on PD diagnosis in SF6-insulated switchgear have been presented and analysed; however, to date, most of them tend to focus on various PD detection techniques in GIS, while others are not extensive and comprehensive reviews. Unlike the available review publications, this paper highlighted various aspects of PD diagnosis in GIS and created a base for further development. The research trend in this field is expected to be directed toward a comprehensive assessment. This review provided a position of the current PD diagnosis in GIS studies and developments that can be a guideline for researchers for further research on the topic’s actual impact in the field.

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