Abstract
This paper presents the forecasting of flashover mechanism on polymeric insulator using nonlinear support vector machine regression (NLSVMR). In transmission and distribution systems, insulator plays a vital role in steadiness of the power systems. Flashover of composite insulators makes the whole system into danger. For the past decades, owing to good hydrophobicity properties of composite insulators made a replacement of porcelain insulators in service. To analyze the performance of composite insulator for long-term process, it is necessary to predict their pollution performance behavior before the breakdown occurs. In this proposed work, 11 kV composite insulator with three straight shed with clevis end fitting (Type A) and three alternate sheds with ball end fitting (Type B) are taken into consideration for flashover prediction. For experimental analysis, solid layer method was used in artificial pollution test, in which coastal, desert, and industrial pollution layer is used for further analysis. Using even-rising method, the flashover voltage has been obtained for different equivalent salt deposit density (ESDD) values. Finally, radial basis function (RBF) SVMR shows better flashover prediction when compared to linear and polynomial NLSVMR.
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We acknowledge the Department of Electrical and Electronics Engineering, National Engineering College for the support by permitting to do this research work in high-voltage laboratory.
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Kumar, K., Vigneshwaran, B., Vishnu Priya, K., Chidambara Vadivoo, T.S. (2020). Prediction of Flashover Voltage on 11 kV Composite Insulator Using Kernel Support Vector Machine. In: Das, K., Bansal, J., Deep, K., Nagar, A., Pathipooranam, P., Naidu, R. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 1057. Springer, Singapore. https://doi.org/10.1007/978-981-15-0184-5_5
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