Flashover voltage prediction of polluted glass insulators based on the characteristics of leakage current

被引：0
|
作者：
Zhao, Shihua [1 ]
Jiang, Xingliang [2 ]
Zhang, Zhijin [2 ]
Hu, Jianlin [2 ]
机构：
[1] State Grid Hunan Electric Power Corporation Research Institute, Changsha 410007, Hunan Province
[2] State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044, Shapingba District
来源：
Dianwang Jishu/Power System Technology | 2014年 / 38卷 / 02期
关键词：
Contamination level; Flashover voltage prediction; Generalized regression neural network; Insulators; Leakage current; Relative humidity;
D O I：
10.13335/j.1000-3673.pst.2014.02.026
中图分类号：
学科分类号：
摘要：
Effective prediction of the flashover voltage of insulators is an important approach to the prevention of pollution flashover accidents, and the leakage current (LC) is an important factor to analyze and detect the flashover voltage of insulators. In order to predict the flashover voltage of insulators and prevent pollution flashover accidents, firstly, a large number of artificial pollution tests were investigated under different contamination levels and different relative humidity (RH). Secondly, based on the experimental data, four characteristics of the LC, namely the entropy of pulse amplitude (S), the maximum pulse amplitude (Ih), the energy ration (K) and the energy (E), were extracted. They reflect jointly how severe the contamination level of insulators and the RH are from different perspectives. Thirdly, the variation laws between the four characteristics and the contamination level, RH, were obtained. Finally, based on the relationship among them and generalized regression neural network (GRNN), the flashover voltage prediction GRNN model were presented, in which the four characteristics and the RH were used as the inputs of model, and the flashover voltage was used as the output of model. Comparison between prediction results and test results showed that relative errors are less than 7.33%. Therefore, the GRNN model is valid and reliable to predict the flashover voltage of insulators and it can provide a reliable guide for operators.
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页码：440 / 447
页数：7
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