ANN-based Fault Location in 11 kV Power Distribution Line using MATLAB

Abstract

Artificial Neural Networks (ANN) have been making a significant impact in the field of electrical engineering, particularly in the realm of power systems. This study explores the use of ANN for fault detection and location in a power distribution line, providing valuable insights into the potential of this technology for power systems management. This research is important to investigate the use of ANN to detect and locate faults in power distribution lines to improve the efficiency and accuracy of fault detection in power systems. The problem this work aims to address is finding a more accurate and faster method for detecting and locating faults in power distribution lines. The study uses MATLAB and the Levenberg-Marquardt algorithm to design and train an ANN model using preprocessed data. The ANN model was configured with various hidden layers and neuron configurations. The study's results showed that the ANN model had a high accuracy in identifying and locating faults in the power distribution line, outperforming traditional fault detection methods in terms of accuracy and speed. The findings of this study demonstrate the potential of ANN for fault detection and location in power systems. The results suggest that further research in this area could lead to even more efficient and accurate fault detection methods, improving the management and maintenance of power systems.