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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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 |
work_keys_str_mv |
AT abahmanyar faultlocationinactivedistributionnetworksusingimprovedwhaleoptimizationalgorithm AT hborhanibahabadi faultlocationinactivedistributionnetworksusingimprovedwhaleoptimizationalgorithm AT sjamali faultlocationinactivedistributionnetworksusingimprovedwhaleoptimizationalgorithm |
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