Regression Model for Calculating Steady-State Internal Key Point Temperatures in High-Voltage Vacuum Circuit Breaker

The enclosed structure of vacuum circuit breakers (VCBs) prevents the temperature measurement at internal key points. This study develops a regression model for a 126 kV VCB that leverages load current, ambient temperature, and contact resistance to estimate key point temperatures. Samples were designed using the Latin Hypercube Sampling Design method, and data sampling was conducted through a multi-physics field simulation approach. A second-order polynomial regression model was developed based on the collected data to predict the key point temperature. The developed model demonstrates high accuracy, with a validation maximum error of less than 1.29%. The research shows that, with other input features at their rated values, the temperature at the key point 2 exceeds the temperature rise limit if the load current exceeds 3275 A. This research calculates internal temperatures of VCB using external parameters, ensuring temperature rise meets design and operational standards.

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Publication Details

Published
2024-11-10
DOI
https://doi.org/10.1109/icepe-st61894.2024.10792593
Citations
1
Primary Topic
Vacuum and Plasma Arcs
Type
article
Field-Weighted Citation Impact
0.34
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article

Regression Model for Calculating Steady-State Internal Key Point Temperatures in High-Voltage Vacuum Circuit Breaker

Tianchi Tang, Yingsan Geng, Yuanzhao Li, Jianhua Wang et al.
1 citations
Vacuum and Plasma Arcs
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article

Regression Model for Calculating Steady-State Internal Key Point Temperatures in High-Voltage Vacuum Circuit Breaker

Tianchi Tang, Yingsan Geng, Yuanzhao Li, Jianhua Wang, Hui Ma, Lei Huang, Yuanbing Zhang
article en
1 citations

Abstract

The enclosed structure of vacuum circuit breakers (VCBs) prevents the temperature measurement at internal key points. This study develops a regression model for a 126 kV VCB that leverages load current, ambient temperature, and contact resistance to estimate key point temperatures. Samples were designed using the Latin Hypercube Sampling Design method, and data sampling was conducted through a multi-physics field simulation approach. A second-order polynomial regression model was developed based on the collected data to predict the key point temperature. The developed model demonstrates high accuracy, with a validation maximum error of less than 1.29%. The research shows that, with other input features at their rated values, the temperature at the key point 2 exceeds the temperature rise limit if the load current exceeds 3275 A. This research calculates internal temperatures of VCB using external parameters, ensuring temperature rise meets design and operational standards.

State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University (CN)
Affordable and clean energy
Openalex Percentile: Top 37%
Vacuum and Plasma Arcs
0.34
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