Reliable High Impedance Fault Detection with Experimental Investigation in Distribution Systems

Authors

  • Mostafa Satea Department of Building and Construction Techniques Engineering, Technical College Musayyib, Al Furat Al Awsat Technical University, Iraq
  • Mahmoud Elsadd Electrical Engineering Department, College of Engineering, Damanhour University, Egypt
  • Mohamed Zaky Department of Electrical Engineering, College of Engineering, Northern Border University, Arar, 1321, Saudi Arabia
  • Mahmoud Elgamasy Electrical Engineering Department, Faculty of Engineering, Menoufia University, 32511, Shebin Elkom, Egypt
Volume: 14 | Issue: 5 | Pages: 17248-17255 | October 2024 | https://doi.org/10.48084/etasr.8292

Abstract

An approach for high-impedance fault detection is introduced in this paper. This technique discriminates between high-impedance faults and switching conditions by utilizing changes in the third harmonic current/voltage magnitude in conjunction with the conventional wavelet algorithm. The concept of discrimination is based on the observation that switching conditions typically do not involve changes in the zero-sequence third harmonic magnitude. However, in the case of high-impedance arcing faults, a noticeable change in the third harmonic current or voltage magnitude occurs. The performance of the proposed technique is examined through a detailed simulation of an actual medium voltage radial distribution feeder. In this simulation, high-impedance faults are represented by an arc model. The simulation, conducted in MATLAB for different fault cases, reveals that all fault cases are detected using the proposed technique. Furthermore, the experimental validation of the reliability of the proposed technique is accomplished using the same actual distribution feeder.

Keywords:

recursive Fourier transform, discrete wavelet transform, high impedance faults, MV network

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References

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How to Cite

[1]
Satea, M., Elsadd, M., Zaky, M. and Elgamasy, M. 2024. Reliable High Impedance Fault Detection with Experimental Investigation in Distribution Systems. Engineering, Technology & Applied Science Research. 14, 5 (Oct. 2024), 17248–17255. DOI:https://doi.org/10.48084/etasr.8292.

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