Power System Fault Detection using Artificial Neural Network

Authors

  • Pranay Neve Student, Department of Electrical Engineering, Atharva College of Engineering, Mumbai, India
  • Mayur Bhalekar Student, Department of Electrical Engineering, Atharva College of Engineering, Mumbai, India
  • Meghana Doke Student, Department of Electrical Engineering, Atharva College of Engineering, Mumbai, India
  • Sangeeta Kotecha Professor, Department of Electrical Engineering, Atharva College of Engineering, Mumbai, India

Keywords:

Artificial Neural Networks, fault detection, hidden layers, MATLAB Simulink, power systems

Abstract

The project is centered on the utilization of Artificial Neural Networks (ANNs) to detect faults in power systems. Feed-forward neural networks have been employed and trained with back-propagation algorithms. To validate the proposed fault detection system, a single test system has been modelled in MATLAB/Simulink. The normal state of the model was initially observed; then, different types of faults were simulated on all lines of the model. The voltage and current magnitudes acquired from the fault simulation were used as inputs for the ANN. The output of the ANN should be able to provide information regarding the fault type if a fault occurs.

Downloads

Download data is not yet available.

Downloads

Published

30-03-2023

Issue

Vol. 6 No. 3 (2023)

Section

Articles

License

Copyright (c) 2023 Pranay Neve, Mayur Bhalekar, Meghana Doke, Sangeeta Kotecha

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
P. Neve, M. Bhalekar, M. Doke, and S. Kotecha, “Power System Fault Detection using Artificial Neural Network”, IJRESM, vol. 6, no. 3, pp. 144–147, Mar. 2023, Accessed: Dec. 21, 2024. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/2629