# Fault Detection Method based on Artificial Neural Network for 330kV Nigerian Transmission Line

“Fault Detection Method based on Artificial Neural Network for 330kV Nigerian Transmission Line” (2024), by Alhassan Musa Oruma et al. Engineering research paper. Original abstract below, unchanged. No free PDF was found.

- Authors: Alhassan Musa Oruma, Ismaila Mahmud, Umar Alhaji Adamu, Simon Wakawa, Gambo Idris, Mahmud Mustapha
- Published: April 26, 2024
- Field: Engineering
- DOI: https://doi.org/10.38124/ijisrt/ijisrt24apr651
- Source: https://doi.org/10.38124/ijisrt/ijisrt24apr651

## Abstract

This research focused on identifying various types of faults occurring on 330kV transmission lines through the use of artificial neural networks (ANN). A MATLAB model for the Gwagwalada-Katampe 330kV transmission line in Nigeria was implemented to generate fault datasets. Voltage and current fault parameters were utilized to train and simulate the ANN network architecture selected for each stage of fault detection. Four types of faults were considered, along with a fifth condition representing no fault. The results illustrated the success of the developed model in identifying various fault conditions and system parameters on the Gwagwalada-Katampe 330kV transmission line, modelled using MATLAB Simulink.

Canonical page: https://nerdi.pages.dev/paper/W4395669330
Read three real papers a day in Nerdi (iPhone): https://apps.apple.com/app/apple-store/id6813826387?pt=128757794&ct=web-paper&mt=8