Classification of Faults in a Transmission Line using Artificial Neural Network

Abstract

The electrical power transmitted from source to load through a large transmission and distribution network as the conductors are uncovered, so there is a high chance of faults in the transmission and distribution line. Faults leads to discontinue of power supply and loss in power generated and economy. Fast detection of faults increases the system reliability, efficiency and security of the network. In this paper, classification of fault is done by using artificial neural network in a transmission line. For the fault detector classifier back propagation algorithm is used. Modeling of transmission line is done by using MATLAB. The magnitude of voltages and currents are extracted for the training and testing of the classifier. The correct percentage of classification is up to 97.9%. Simulation result shows the efficiency of the proposed method in a transmission line. By using confusion matrix and the Mean Square Error (MSE), the performance of the suggested method is estimated.