Flashover Voltage Prediction of Composite Insulators Based on the Characteristics of Leakage Current

Effective prediction of flashover voltage (FOV) of insulators is an important approach to the prevention of pollution flashover accidents. In order to predict the FOV of insulators and prevent pollution flashover accidents, first, a large number of artificial pollution tests, which simulate the impa...

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Bibliographic Details
Published in:IEEE transactions on power delivery 2013-07, Vol.28 (3), p.1699-1708
Main Authors: Shihua Zhao, Xingliang Jiang, Zhijing Zhang, Jianlin Hu, Lichun Shu
Format: Article
Language:English
Subjects:
Applied sciences
Composite insulator
contamination level
Electrical engineering. Electrical power engineering
Exact sciences and technology
Flashover
flashover voltage prediction
hydrophobicity classification
Insulators
leakage current
Leakage currents
Materials
Pollution
Predictive models
Surface contamination
Various equipment and components
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Summary:Effective prediction of flashover voltage (FOV) of insulators is an important approach to the prevention of pollution flashover accidents. In order to predict the FOV of insulators and prevent pollution flashover accidents, first, a large number of artificial pollution tests, which simulate the impact of contamination level and hydrophobicity classification (HC) on FOV and leakage current, have been investigated. Second, based on the experimental data, the relationship between the FOV and contamination level, HC, has been obtained; the four characteristics of leakage current, namely, the entropy of pulse amplitude ( S ), the maximum pulse amplitude ( I h ), the energy ration ( K ) and the energy ( E ), have been extracted. They jointly reflect how severe the contamination level and the HC of composite insulators are from different perspectives. Third, the variation laws between the four characteristics and the contamination level, HC, have been obtained. Finally, the FOV prediction least squares-support vector machines (LS-SVM) model has been presented, in which the four characteristics are used as the inputs of model, and the FOV is used as the output of model. The prediction results are basically consistent with the test results. Therefore, the model is acceptable to predict the FOV of composite insulators and is of significance for the prevention of pollution flashover accidents.
ISSN:0885-8977
1937-4208
DOI:10.1109/TPWRD.2013.2257879