| Issue |
SHS Web Conf.
Volume 219, 2025
2025 International Conference on Management and Intelligent Society Development (MISD2025)
|
|
|---|---|---|
| Article Number | 02007 | |
| Number of page(s) | 4 | |
| Section | Intelligent Technology Application | |
| DOI | https://doi.org/10.1051/shsconf/202521902007 | |
| Published online | 04 July 2025 | |
GIS isolation switch contact temperature wireless monitoring
1 State Grid Liaoning Electric Power Co., Ltd. Chaoyang Power Supply Company, No.13, Section 3, Chaoyang Street, Shuangta District, Chaoyang, Liaoning, China, 122000
2 State Grid Liaoning Electric Power Co., Ltd. Electric Power Research Institute, No. 39-7, Siping Street, Heping District, Shenyang, Liaoning, China, 110000
3 Shenyang Institute of Engineering, 18 Puchang Road, Shenbei New District, Shenyang, Liaoning, China, 110136
* Corresponding author: 2078919429@qq.com
The contact temperature of GIS is an indicator that reflects contact fault information and requires real-time monitoring. There is currently no direct installation of sensors to monitor temperature. Therefore, this article proposes using multi-point temperature monitoring values on the outer shell to invert and calculate the internal temperature of GIS. In addition, the multi-point sensor on the casing has been optimized. Firstly, a finite element analysis model for the temperature field of the 500kV isolation switch chamber was established, analyzed the distribution of temperature field. The installation position of the sensor on the outer shell was determined. At the same time, conduct temperature rise tests and compare the test results with the simulation results to prove the accuracy of the simulation model. Then, SVR is used to train the correspondence between multiple temperatures of the casing, contact temperature, and external temperature. The measurement of the temperature on the shell multiplied by the ambient temperature is used for the conversion calculation of contact temperature. It was found that the average absolute error of monitoring is 0.47%. This method can save economic costs and achieve the required accuracy for engineering applications.
© The Authors, published by EDP Sciences, 2025
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