Detection and Classification of Open Conductor Faults in Six-Phase Transmission Line Using Wavelet Transform and Naive Bayes Classifier

The rapidly rising per capita consumption of electrical energy have put question mark on the present power network to meet the demand. The six-phase transmission can be an alternative solution to cope up with the increasing power demand having the additional power transmission capability of 73 % with the existing transmission network without any major modifications. The probable occurrence of large number of faults makes the protection task highly challenging. In this context, this paper presents a Naive Bayes classifier (NBC) based scheme to perform the task of fault detection/classification of series faults in six-phase transmission system. The NBC based classification approach is known to provide simple and efficient solution for complicated classification problems. The performance of the proposed scheme have been validated with random test cases generated under widely varying fault parameters. The test results reflect the immunity of the proposed approach to variation in fault parameters.