Classification of Line to Ground Fault in Transmission Line Using Artificial Neural Network

This paper focuses on Artificial Neural Networks (ANN) based technique to find out the line to ground faults in a transmission line. Modelling of transmission line is modelled using MATLAB software. For the proposed method data collection, single line to ground (LG) faults with various sets of load power, the suggested fault classification technique is followed. ANN provided correct classification up to 92.6%. The extracted voltages from point of common coupling are taken out for the training and testing of the classifier. To classify faults on the transmission line, ANN technique uses voltage magnitude as training data. The ANN tool can accurately classify and identify faults. The outcome of the simulation displays the accuracy of the suggested method in a transmission line. The performance of the suggested method is showing good accuracy which is validated by performance plot and confusion matrix. The simulation results indicate that this method is extremely reliable and accurate in the system’s tested operating conditions.