Fault Location in Active Distribution Networks Using Improved Whale Optimization Algorithm

To realize the self-healing concept of smart grids, an accurate and reliable fault locator is a prerequisite. This paper presents a new fault location method for active power distribution networks which is based on measured voltage sag and use of whale optimization algorithm (WOA). The fault induced...

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Main Authors: A. Bahmanyar, H. Borhani-Bahabadi, S. Jamali
Format: Article
Language:English
Published: Iran University of Science and Technology 2020-09-01
Series:Iranian Journal of Electrical and Electronic Engineering
Subjects:
Online Access:http://ijeee.iust.ac.ir/article-1-1684-en.html
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spelling doaj-628f90f44191455e8369fdca4bcb5c692020-11-25T03:37:50ZengIran University of Science and TechnologyIranian Journal of Electrical and Electronic Engineering1735-28272383-38902020-09-01163302312Fault Location in Active Distribution Networks Using Improved Whale Optimization AlgorithmA. Bahmanyar0H. Borhani-Bahabadi1S. Jamali2 Center of Excellence for Power System Automation and Operation, Iran University of Science and Technology (IUST), School of Electrical Engineering, Tehran, Iran. Center of Excellence for Power System Automation and Operation, Iran University of Science and Technology (IUST), School of Electrical Engineering, Tehran, Iran. Center of Excellence for Power System Automation and Operation, Iran University of Science and Technology (IUST), School of Electrical Engineering, Tehran, Iran. To realize the self-healing concept of smart grids, an accurate and reliable fault locator is a prerequisite. This paper presents a new fault location method for active power distribution networks which is based on measured voltage sag and use of whale optimization algorithm (WOA). The fault induced voltage sag depends on the fault location and resistance. Therefore, the fault location can be found by investigation of voltage sags recorded throughout the distribution network. However, this approach requires a considerable effort to check all possible fault location and resistance values to find the correct solution. In this paper, an improved version of the WOA is proposed to find the fault location as an optimization problem. This optimization technique employs a number of agents (whales) to search for a bunch of fish in the optimal position, i.e. the fault location and its resistance. The method is applicable to different distribution network configurations. The accuracy of the method is verified by simulation tests on a distribution feeder and comparative analysis with two other deterministic methods reported in the literature. The simulation results indicate that the proposed optimized method gives more accurate and reliable results.http://ijeee.iust.ac.ir/article-1-1684-en.htmlfault locationoptimizationself-healingsmart gridswhale optimization algorithm.
collection DOAJ
language English
format Article
sources DOAJ
author A. Bahmanyar
H. Borhani-Bahabadi
S. Jamali
spellingShingle A. Bahmanyar
H. Borhani-Bahabadi
S. Jamali
Fault Location in Active Distribution Networks Using Improved Whale Optimization Algorithm
Iranian Journal of Electrical and Electronic Engineering
fault location
optimization
self-healing
smart grids
whale optimization algorithm.
author_facet A. Bahmanyar
H. Borhani-Bahabadi
S. Jamali
author_sort A. Bahmanyar
title Fault Location in Active Distribution Networks Using Improved Whale Optimization Algorithm
title_short Fault Location in Active Distribution Networks Using Improved Whale Optimization Algorithm
title_full Fault Location in Active Distribution Networks Using Improved Whale Optimization Algorithm
title_fullStr Fault Location in Active Distribution Networks Using Improved Whale Optimization Algorithm
title_full_unstemmed Fault Location in Active Distribution Networks Using Improved Whale Optimization Algorithm
title_sort fault location in active distribution networks using improved whale optimization algorithm
publisher Iran University of Science and Technology
series Iranian Journal of Electrical and Electronic Engineering
issn 1735-2827
2383-3890
publishDate 2020-09-01
description To realize the self-healing concept of smart grids, an accurate and reliable fault locator is a prerequisite. This paper presents a new fault location method for active power distribution networks which is based on measured voltage sag and use of whale optimization algorithm (WOA). The fault induced voltage sag depends on the fault location and resistance. Therefore, the fault location can be found by investigation of voltage sags recorded throughout the distribution network. However, this approach requires a considerable effort to check all possible fault location and resistance values to find the correct solution. In this paper, an improved version of the WOA is proposed to find the fault location as an optimization problem. This optimization technique employs a number of agents (whales) to search for a bunch of fish in the optimal position, i.e. the fault location and its resistance. The method is applicable to different distribution network configurations. The accuracy of the method is verified by simulation tests on a distribution feeder and comparative analysis with two other deterministic methods reported in the literature. The simulation results indicate that the proposed optimized method gives more accurate and reliable results.
topic fault location
optimization
self-healing
smart grids
whale optimization algorithm.
url http://ijeee.iust.ac.ir/article-1-1684-en.html
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AT hborhanibahabadi faultlocationinactivedistributionnetworksusingimprovedwhaleoptimizationalgorithm
AT sjamali faultlocationinactivedistributionnetworksusingimprovedwhaleoptimizationalgorithm
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