Flashover Voltage Estimation by Artificial Neural Network of Polluted Post Insulators Transmission Lines at High Altitude Area

In this work an attempt has been made to estimate the pollution flashover voltage under various meteorological factors using radial basis function (RBF) neural networks. Orthogonal least squares (OLS) learning method is used in order to improve the lines performance against the pollution flashover of the post insulators. The technique of RBF neural network is employed to model the relationship between pollution flashover voltage and the line parameters: diameter of shed, distance of leakage, pressure at different altitudes and salt deposit densities ESDD. The results show that a well trained RBF neural network achieved a better modelling accuracy and performance.