High Impedance Fault Detection Using Neural Networks

Authors

  • Deepak Joshi  EC Department, IIMT College of Engineering, Greater Noida, Uttar Pradesh, India
  • Ashish Kumar Singh  EC Department, IIMT College of Engineering, Greater Noida, Uttar Pradesh, India
  • Avinash Sinha  EC Department, IIMT College of Engineering, Greater Noida, Uttar Pradesh, India

Keywords:

ANN, High Impedance Faults

Abstract

This paper presents the detection of the high impedance fault occurring on radial distribution system using neural network. A multilayer perceptron is used for distinguishing the linear and nonlinear high impedance faults by taking the feature vector as input. R.M.S value of third and fifth harmonic components of feeder voltage and feeder current are used as a feature vector obtained by applying the Fast Fourier Transform on the feeder voltage and feeder current. A variety of faults and system conditions have been simulated to evaluate the reliability and sensitivity of the proposed technique.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2017-12-31

Issue

Volume 3, Issue 8, November-December-2017

Section

Research Articles

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Copyright (c) IJSRSET

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

How to Cite

[1]
Deepak Joshi, Ashish Kumar Singh, Avinash Sinha "High Impedance Fault Detection Using Neural Networks" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 8, pp.759-763, November-December-2017.