PREDICTION OF CRITICAL FLASHOVER VOLTAGE OF POLLUTED INSULATORS UNDER SEC AND RAIN CONDITIONS USING ANFIS
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https://doi.org/10.59287/ijanser.1496Keywords:
High Voltage, Flashover, Modelling, Polluted Insulator, ANFIS, GMDL, LSSVMAbstract
High voltage insulators are critical components of high voltage electric power transmission networks. Any failure in the satisfactory performance of high voltage insulators would result in significant capital loss, since various industries rely on the availability of an uninterrupted power supply. With the growth in transmission line voltage, the relevance of insulator contamination study has grown significantly. The researchers established a modeling to evaluate the flashover behavior of contaminated high voltage insulators and to uncover the physical factors that drive this phenomena. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model to estimate the critical flashover voltage (FOV) under rain and sec condition . The approach takes as input variable insulator properties such as diameter, height, creepage distance, and the number of pieces on an insulator chain, the data sets used to train and test the network are drawn from experimental results gathered from the literature. The approach's validity was tested by testing numerous insulators with varying shapes. The accuracy and quality of ANFIS are demonstrated by a comparison with the Grouping Multi-Duolateration Localization (GMDL) technique and LS-SVM. Furthermore, ANFIS provides a good estimate of findings that are confirmed by experimental experiments.
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