Combined DWT and Naive Bayes based fault classifier for protection of double circuit transmission line

Abstract

This paper describes combined discrete wavelet transform (DWT) and Naive Bayes (NB) fault classifier for protection of double circuit transmission line. Three phase currents of both circuits and zero sequence current are given as input to the NB network for classification of fault. Inputs are pre-processed using approximate coefficient of DWT. NB classifier uses Gaussian distribution function for classification. Seven classifiers are designed for fault classification for each phase A1, B1, C1, A2, B2, C2 and ground G. Advantage of using Naive Bayes classifier is that it take few seconds for training no matter how big the data is. Different cases of fault are studied like phase faults, phase to ground faults, inter-circuit faults, cross country faults, fault near boundaries, different fault location, different inception angle and different fault resistance with high fault resistance. Accuracy of the proposed method is 99% and reach setting is also 99% of line length.