Modeling of various meteorological effects on contamination level for suspension type of high voltage insulators using ANN

The performance of polluted insulators is very much dependent on the degree of contamination. For the high voltage insulators to be installed in areas especially near the coast, determination of the contamination level becomes the major task to design the insulators appropriately. The aim of this paper is to obtain accurate information about the degree of contamination which the high voltage insulators are exposed to when they are installed in coastal areas. Regression technique has been used successfully in estimating the level of contamination on high voltage insulators surfaces in terms of equivalent salt deposit density (ESDD). This paper has also used artificial neural network algorithm to model ESDD as a function of various meteorological parameters. A comparative analysis has also been carried out between the two methods in this work.