Intelligent techniques for fault diagnosis in transmission lines — An overview

Abstract

This paper presents survey and review of research and development in the field of faults detection, classification and their location that occurs in the transmission network. Transmission lines are integral part of the power system network and its main aim is to transmit the generated power to the consumer with least interruption. With an ever-increasing demand of electric power day by day because of increasing industrialization and urbanization of life style, fast and accurate fault analysis is very essential for better performance and minimal interruptions in power system. Fast detection and clearing of faults in transmission lines is very important for maintaining the normal operation of power system network. This paper presents a comprehensive review of various algorithms that have been developed and used over the last few years for the detection and classification of faults in transmission lines and mainly concentrate on following algorithm and their implementation for fault analysis such as, wavelet transform (WT), discrete wavelet transform (DWT), multi-resolution analysis (MRA), Wavelet energy entropy, artificial neural network (ANN), wavelet-neuro-fuzzy approach and support vector machine (SVM).