电器与能效管理技术 ›› 2023, Vol. 0 ›› Issue (8): 68-75.doi: 10.16628/j.cnki.2095-8188.2023.08.011

• 评估与预测技术 • 上一篇    下一篇

12 kV开关柜载流回路热分析与温度预测

时宝朋, 侯春光, 曹云东, 徐晓刚, 蒋幸伟   

  1. 教育部特种电机与高压电器重点实验室(沈阳工业大学), 辽宁 沈阳 110870
  • 收稿日期:2023-05-24 出版日期:2023-08-30 发布日期:2023-10-19
  • 作者简介:时宝朋(1996—),男,硕士研究生,研究方向为配电设备智能化和配电设备状态分析。|侯春光(1978—),男,副教授,研究方向为数字化电网、电力设备状态监测、配电设备智能化、人工智能。|曹云东(1963—),男,教授,研究方向为现代电器设计理论及应用、电器智能化。

Thermal Analysis and Temperature Prediction of 12 kV Switchgear Current-Carrying Loop

SHI Baopeng, HOU Chunguang, CAO Yundong, XU Xiaogang, JIANG Xingwei   

  1. Key Laboratory of Special Electric Machines and High Voltage Apparatus Ministry of Education(Shenyang University of Technology), Shenyang 110870, China
  • Received:2023-05-24 Online:2023-08-30 Published:2023-10-19

摘要:

准确掌握运行状态下开关柜内部载流回路的热分布和温升状况,可避免开关柜高温状态下绝缘性能劣化和使用寿命的降低。针对某型12 kV开关柜载流回路,展开热分析与温度预测的研究。首先针对所研究柜型关键发热部位和主载流回路建立温度分析模型,结合电器发热理论和传热学理论对模型进行仿真分析,结果表明载流回路温度分布与接触电阻有关。其次以仿真数据集作为基础,以最小二乘支持向量机算法搭建温度预测模型,对触头进行温度预测,结果表明在可接受的预测误差范围内所提预测模型预测结果的准确性。

关键词: 开关柜, 温度场, 温度预测, 最小二乘支持向量机

Abstract:

Accurately mastering the thermal distribution and temperature rise of the current carrying circuit inside the switchgear under operating conditions can avoid the deterioration of insulation performance and reduction of service life under high temperature conditions. The thermal analysis and temperature prediction of a 12 kV switchgear current-carrying circuit are studied. Firstly, the temperature analysis model is established for the key heating parts of the cabinet and the main current-carrying loop. The simulation analysis of the model is carried out in combination with the heating theory of electrical appliances and the heat transfer theory. The results show that the temperature distribution of current-carrying loop is related to the contact resistance. Secondly, based on the simulation dataset, a temperature prediction model is constructed using the least squares support vector machine algorithm to predict the contact temperature. The results show that the prediction model had accuracy within an acceptable prediction error range.

Key words: switchgear, temperature field, temperature prediction, least squares support vector machine (LS-SVM)

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