Coupled Multi-Physics Study on SF6 Decomposition Gas Diffusion and Sensor Placement Optimization in GIS Busbars

Traditional fault diagnosis methods for gas-insulated switchgear (GIS) equipment primarily rely on offline detection and periodic maintenance, which suffer from limitations such as poor real-time performance and localization difficulties, thereby compromising the safe and stable operation of ultra-high-voltage power grids. To enhance the accurate identification and localization capabilities of defects within GIS equipment, this study first establishes a multi-physics coupled simulation model integrating temperature field, flow field, and concentration field to analyze gas diffusion characteristics under varying conditions of fault source locations, decomposition product types, and initial concentrations. Subsequently, a GIS busbar gas chamber experimental platform is constructed to validate the simulation model. Finally, a response time matrix, a peak concentration matrix, and a fault coverage index are developed, and a weighted comprehensive evaluation method is employed to optimize sensor placement schemes. The findings reveal that fault source location significantly influences concentration response speed and spatial distribution patterns; SO2, HF, H2S, and SOF2 exhibit distinct diffusion characteristics due to their differing physical properties; and initial concentration primarily affects the non-uniformity during the early diffusion stage. The simulation results demonstrate good agreement with experimental data, with a maximum root-mean-square error of 3.936 × 10−4. Monitoring point M4 achieves the highest comprehensive score, making it the preferred location for single-sensor deployment. These results provide a theoretical foundation and technical guidance for GIS online monitoring and fault diagnosis.

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Publication Details

Journal
Sensors
Published
2026-09-11
DOI
https://doi.org/10.3390/s26185782
Primary Topic
High voltage insulation and dielectric phenomena
Type
article
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article

Coupled Multi-Physics Study on SF6 Decomposition Gas Diffusion and Sensor Placement Optimization in GIS Busbars

Qian Shi, Yadi Xie, Ruyue Mai, Tong Li et al.
Sensors
High voltage insulation and dielectric phenomena
article

Coupled Multi-Physics Study on SF6 Decomposition Gas Diffusion and Sensor Placement Optimization in GIS Busbars

Qian Shi, Yadi Xie, Ruyue Mai, Tong Li, Niyar Di, Shan Li, Duohu Gong
article en

Abstract

Traditional fault diagnosis methods for gas-insulated switchgear (GIS) equipment primarily rely on offline detection and periodic maintenance, which suffer from limitations such as poor real-time performance and localization difficulties, thereby compromising the safe and stable operation of ultra-high-voltage power grids. To enhance the accurate identification and localization capabilities of defects within GIS equipment, this study first establishes a multi-physics coupled simulation model integrating temperature field, flow field, and concentration field to analyze gas diffusion characteristics under varying conditions of fault source locations, decomposition product types, and initial concentrations. Subsequently, a GIS busbar gas chamber experimental platform is constructed to validate the simulation model. Finally, a response time matrix, a peak concentration matrix, and a fault coverage index are developed, and a weighted comprehensive evaluation method is employed to optimize sensor placement schemes. The findings reveal that fault source location significantly influences concentration response speed and spatial distribution patterns; SO2, HF, H2S, and SOF2 exhibit distinct diffusion characteristics due to their differing physical properties; and initial concentration primarily affects the non-uniformity during the early diffusion stage. The simulation results demonstrate good agreement with experimental data, with a maximum root-mean-square error of 3.936 × 10−4. Monitoring point M4 achieves the highest comprehensive score, making it the preferred location for single-sensor deployment. These results provide a theoretical foundation and technical guidance for GIS online monitoring and fault diagnosis.

SensorsVol. 26(18)
Inner Mongolia Electric Power (China) (CN)
Openalex Percentile: Top 24%
High voltage insulation and dielectric phenomena
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