Artificial Neural Network Applications in Transmission Line Fault Diagnosis

This study proposes an intelligent fault detection mechanism using artificial neural networks (ANNs) to detect faults on power system transmission lines. A prototype of Kaduna-to-Kano transmission line network was modeled in Simulink, and voltage and current data were extracted and trained using the Levenberg-Marquardt backpropagation algorithm. The results show that the ANN can detect both symmetrical and non-symmetrical faults, with validation plots and regression plots demonstrating its effectiveness. This technique is highly recommended for power system transmission line networks and can be extended to distribution networks.