Research on Online Monitoring of Partial Discharge of Insulation Defects in Air Switchgear Based on Characteristic Gases

Air switchgear is an important power equipment in the transmission, transformation, and distribution process of the power system. Insulation defects can lead to partial discharge, which is one of the primary causes of air switchgear failure. Current monitoring methods primarily rely on detecting ultra-high frequency or ultrasonic signals generated by partial discharge to identify insulation defects. However, these methods are prone to external signal interference, resulting in substantial detection errors. Based on gas discharge theory and engineering practice, this paper uses three typical defects to represent the main insulation defects of air switchgear, namely metal protrusion defects, insulation layer air gap defects, and metal particle defects. After that, the validity of the numerical model to describe the partial discharge process of air switchgear insulation defects is verified by the volt-ampere characteristic curve. The discharge process of three typical defect models was investigated by using the numerical model, and the variation curves of the volume fractions of CO, NO2, and O3 gases at different voltage levels and different discharge durations were obtained. After analysis, the volume fractions of the three characteristic gases are unique under different defect models and partial discharge quantities. Finally, this paper designed a partial discharge inversion method based on characteristic gases, and fitted time-domain regression equations and partial discharge inversion regression equations based on the changes in volume fractions of the three characteristic gases measured. The research results of this paper provide a theoretical basis for online detection of partial discharge in high-voltage air switchgear through characteristic gases. The method proposed in this paper can also be applied to other gas-insulated equipment, such as GIS, metal-enclosed switchgear, and vacuum circuit breakers.

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Publication Details

Journal
Applied Sciences
Published
2025-02-26
DOI
https://doi.org/10.3390/app15052538
Citations
1
Primary Topic
High voltage insulation and dielectric phenomena
Type
article
Field-Weighted Citation Impact
0.52

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article

Research on Online Monitoring of Partial Discharge of Insulation Defects in Air Switchgear Based on Characteristic Gases

一也 西田, Shuai Wang, Haotian Niu, Guixin Zhu
1 citations
Applied Sciences
High voltage insulation and dielectric phenomena
0.52
article

Research on Online Monitoring of Partial Discharge of Insulation Defects in Air Switchgear Based on Characteristic Gases

一也 西田, Shuai Wang, Haotian Niu, Guixin Zhu
article en
1 citations

Abstract

Air switchgear is an important power equipment in the transmission, transformation, and distribution process of the power system. Insulation defects can lead to partial discharge, which is one of the primary causes of air switchgear failure. Current monitoring methods primarily rely on detecting ultra-high frequency or ultrasonic signals generated by partial discharge to identify insulation defects. However, these methods are prone to external signal interference, resulting in substantial detection errors. Based on gas discharge theory and engineering practice, this paper uses three typical defects to represent the main insulation defects of air switchgear, namely metal protrusion defects, insulation layer air gap defects, and metal particle defects. After that, the validity of the numerical model to describe the partial discharge process of air switchgear insulation defects is verified by the volt-ampere characteristic curve. The discharge process of three typical defect models was investigated by using the numerical model, and the variation curves of the volume fractions of CO, NO2, and O3 gases at different voltage levels and different discharge durations were obtained. After analysis, the volume fractions of the three characteristic gases are unique under different defect models and partial discharge quantities. Finally, this paper designed a partial discharge inversion method based on characteristic gases, and fitted time-domain regression equations and partial discharge inversion regression equations based on the changes in volume fractions of the three characteristic gases measured. The research results of this paper provide a theoretical basis for online detection of partial discharge in high-voltage air switchgear through characteristic gases. The method proposed in this paper can also be applied to other gas-insulated equipment, such as GIS, metal-enclosed switchgear, and vacuum circuit breakers.

Applied SciencesVol. 15(5)
Xi'an Polytechnic University (CN)
China Postdoctoral Science Foundation
Openalex Percentile: Top 41%
High voltage insulation and dielectric phenomena
0.52
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