Detection of High Impedance Fault in Distribution Networks

This paper presents a new detection methodology for High Impedance Faults (HIFs) in power distribution networks based on Mathematical Morphology (MM). In the proposed method, the current signals are observed from the distribution feeder to detect HIFs. MM is used to extract the features in a time do...

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Main Authors: Sekar Kavaskar, Nalin Kant Mohanty
Format: Article
Language:English
Published: Elsevier 2019-03-01
Series:Ain Shams Engineering Journal
Online Access:http://www.sciencedirect.com/science/article/pii/S209044791830087X
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author Sekar Kavaskar
Nalin Kant Mohanty
author_facet Sekar Kavaskar
Nalin Kant Mohanty
author_sort Sekar Kavaskar
collection DOAJ
description This paper presents a new detection methodology for High Impedance Faults (HIFs) in power distribution networks based on Mathematical Morphology (MM). In the proposed method, the current signals are observed from the distribution feeder to detect HIFs. MM is used to extract the features in a time domain and a simple rule based algorithm to classify HIFs from other power system disturbances. An electric power distribution system was used to generate data such as HIFs, Low Impedance Faults (LIFs) and other switching transients using MATLAB/SIMULINK. From the results of the proposed method, it is found that the method could detect and differentiate HIFs from other disturbances in less time compared to other methods with high security and dependability. The function of the proposed method is not affected by various conditions such as the location, inception time, and type of fault. Keywords: High Impedance Fault, Mathematical Morphology, Distribution system, Power system disturbances, Non-linear load
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spelling doaj.art-9158a60d6df74436a43c319b58d069052022-12-21T18:51:26ZengElsevierAin Shams Engineering Journal2090-44792019-03-01101513Detection of High Impedance Fault in Distribution NetworksSekar Kavaskar0Nalin Kant Mohanty1Department of Electrical and Electronics Engineering, Panimalar Engineering College, Affiliated to Anna University, Chennai 600123, Tamil Nadu, India; Corresponding author.Department of Electrical and Electronics Engineering, Sri Venkateswara College of Engineering, Sriperumbudur 602 117, Tamil Nadu, IndiaThis paper presents a new detection methodology for High Impedance Faults (HIFs) in power distribution networks based on Mathematical Morphology (MM). In the proposed method, the current signals are observed from the distribution feeder to detect HIFs. MM is used to extract the features in a time domain and a simple rule based algorithm to classify HIFs from other power system disturbances. An electric power distribution system was used to generate data such as HIFs, Low Impedance Faults (LIFs) and other switching transients using MATLAB/SIMULINK. From the results of the proposed method, it is found that the method could detect and differentiate HIFs from other disturbances in less time compared to other methods with high security and dependability. The function of the proposed method is not affected by various conditions such as the location, inception time, and type of fault. Keywords: High Impedance Fault, Mathematical Morphology, Distribution system, Power system disturbances, Non-linear loadhttp://www.sciencedirect.com/science/article/pii/S209044791830087X
spellingShingle Sekar Kavaskar
Nalin Kant Mohanty
Detection of High Impedance Fault in Distribution Networks
Ain Shams Engineering Journal
title Detection of High Impedance Fault in Distribution Networks
title_full Detection of High Impedance Fault in Distribution Networks
title_fullStr Detection of High Impedance Fault in Distribution Networks
title_full_unstemmed Detection of High Impedance Fault in Distribution Networks
title_short Detection of High Impedance Fault in Distribution Networks
title_sort detection of high impedance fault in distribution networks
url http://www.sciencedirect.com/science/article/pii/S209044791830087X
work_keys_str_mv AT sekarkavaskar detectionofhighimpedancefaultindistributionnetworks
AT nalinkantmohanty detectionofhighimpedancefaultindistributionnetworks