High impedance fault detection in distribution network based on morphological gradient

Articles in Press

Document Type : Original Article

Authors

1 Department of Electrical Engineering, Technical and Vocational University, Iran

2 Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran

10.48301/kssa.2023.392193.2510

Abstract

High impedance fault (HIF) detection is one of the biggest challenges in power distribution network. HIF usually occurs when conductors in the distribution network are broken and touch the ground or a tree branch. The current of this fault is close to the load current level and cannot be detected by over current relays. In this paper, a new method for detecting HIF from other similar phenomena in the distribution network such as capacitor switching, load switching, inrush current and CT saturation is presented. The proposed method uses morphological gradient edge detection (MGED) to process voltage signals. Using MGED, the edges or transient changes in the signal and its features after two cycles from the beginning of the fault are extracted. Based on these features, an fault detection index (FDI) is introduced for distinguishing and classifying HIF, capacitor switching, load switching, inrush current and CT saturation. The simulation results for different HIF fault conditions and similar phenomena in a 20 kV sample feeder and IEEE 34 bus distribution system in EMTP software environment confirm the fast and accurate performance of the proposed method.The simulation results for different HIF fault conditions and similar phenomena in a 20 kV sample feeder in EMTP software environment confirm the fast and accurate performance of the proposed method.

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Main Subjects

Karafan Quarterly Scientific Journal

Articles in Press, Accepted Manuscript
Available Online from 06 July 2023

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History

  • Receive Date: 11 April 2023
  • Revise Date: 29 May 2023
  • Accept Date: 02 July 2023

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