Artificial neural network for insulator leakage currents prediction from environmental data

The reliability of the power system mainly depends on the environmental and weather conditions which cause flashover on polluted insulators leading to system outages. It is generally recognized that the main causes leading to the contamination of insulators are marine pollution found in the immediate neighborhood of the coastal regions and solid pollution found in the dense industrial areas. This research is directed towards the study of contamination of insulator under marine pollution. The leakage currents of porcelain insulators were monitored together with environmental data at a coastal test site in south of Iran. In this paper it is shown how, using artificial neural network (ANN) as a function estimator; the daily variation of leakage current can be predicted accurately from temperature, humidity, wind velocity and ultraviolet radiance.