Metaheuristic Method for a Wind-Integrated Distribution Network to Support Voltage Stabilisation Employing Electric Vehicle Loads

Distributed generation (DG) has been incorporated into the distribution networks and, despite the rising prevalence of electric vehicle (EV) loads that are uncertain and cause substantial challenges in their operation, it is necessary to enhance the voltage profile, reduce power losses, and conseque...

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Published in:Applied Sciences
Main Authors: Nasir Rehman, Mairaj-Ud Din Mufti, Neeraj Gupta
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2023
Subjects:
Online Access:https://doi.org/10.3390/app13042254
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spelling ftmdpi:oai:mdpi.com:/2076-3417/13/4/2254/ 2023-08-20T04:05:34+02:00 Metaheuristic Method for a Wind-Integrated Distribution Network to Support Voltage Stabilisation Employing Electric Vehicle Loads Nasir Rehman Mairaj-Ud Din Mufti Neeraj Gupta agris 2023-02-09 application/pdf https://doi.org/10.3390/app13042254 EN eng Multidisciplinary Digital Publishing Institute Energy Science and Technology https://dx.doi.org/10.3390/app13042254 https://creativecommons.org/licenses/by/4.0/ Applied Sciences; Volume 13; Issue 4; Pages: 2254 distributed generations electric vehicle beluga whale optimisation optimal location wind turbine generating system Text 2023 ftmdpi https://doi.org/10.3390/app13042254 2023-08-01T08:44:02Z Distributed generation (DG) has been incorporated into the distribution networks and, despite the rising prevalence of electric vehicle (EV) loads that are uncertain and cause substantial challenges in their operation, it is necessary to enhance the voltage profile, reduce power losses, and consequently improve the stability of whole networks. The recently proposed beluga whale optimisation algorithm is explored in the optimisation framework to determine the most suitable size of wind turbine generating systems (WTGS), while the optimum placements are determined by minimising the placement index (P-Index) using the distribution load flow (DLF) method. The voltage stability factor (VSF) is employed to formulate the P-Index to enhance voltage sensitivity in distribution systems. The main purpose of this article is to assess the influence of voltage-dependent, uncertain ZIP-form EV loads in order to analyse their potential in the active and reactive power operations of the distribution network while retaining the system voltage within a specified limit by significantly reducing system losses and taking distribution network-level constraints into account. The efficacy of the methodology is validated on the standard IEEE-33 test system by formulating two performance indices to determine a significant enhancement in convergence characteristics and a reduction in system losses. Text Beluga Beluga whale Beluga* MDPI Open Access Publishing Applied Sciences 13 4 2254
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic distributed generations
electric vehicle
beluga whale optimisation
optimal location
wind turbine generating system
spellingShingle distributed generations
electric vehicle
beluga whale optimisation
optimal location
wind turbine generating system
Nasir Rehman
Mairaj-Ud Din Mufti
Neeraj Gupta
Metaheuristic Method for a Wind-Integrated Distribution Network to Support Voltage Stabilisation Employing Electric Vehicle Loads
topic_facet distributed generations
electric vehicle
beluga whale optimisation
optimal location
wind turbine generating system
description Distributed generation (DG) has been incorporated into the distribution networks and, despite the rising prevalence of electric vehicle (EV) loads that are uncertain and cause substantial challenges in their operation, it is necessary to enhance the voltage profile, reduce power losses, and consequently improve the stability of whole networks. The recently proposed beluga whale optimisation algorithm is explored in the optimisation framework to determine the most suitable size of wind turbine generating systems (WTGS), while the optimum placements are determined by minimising the placement index (P-Index) using the distribution load flow (DLF) method. The voltage stability factor (VSF) is employed to formulate the P-Index to enhance voltage sensitivity in distribution systems. The main purpose of this article is to assess the influence of voltage-dependent, uncertain ZIP-form EV loads in order to analyse their potential in the active and reactive power operations of the distribution network while retaining the system voltage within a specified limit by significantly reducing system losses and taking distribution network-level constraints into account. The efficacy of the methodology is validated on the standard IEEE-33 test system by formulating two performance indices to determine a significant enhancement in convergence characteristics and a reduction in system losses.
format Text
author Nasir Rehman
Mairaj-Ud Din Mufti
Neeraj Gupta
author_facet Nasir Rehman
Mairaj-Ud Din Mufti
Neeraj Gupta
author_sort Nasir Rehman
title Metaheuristic Method for a Wind-Integrated Distribution Network to Support Voltage Stabilisation Employing Electric Vehicle Loads
title_short Metaheuristic Method for a Wind-Integrated Distribution Network to Support Voltage Stabilisation Employing Electric Vehicle Loads
title_full Metaheuristic Method for a Wind-Integrated Distribution Network to Support Voltage Stabilisation Employing Electric Vehicle Loads
title_fullStr Metaheuristic Method for a Wind-Integrated Distribution Network to Support Voltage Stabilisation Employing Electric Vehicle Loads
title_full_unstemmed Metaheuristic Method for a Wind-Integrated Distribution Network to Support Voltage Stabilisation Employing Electric Vehicle Loads
title_sort metaheuristic method for a wind-integrated distribution network to support voltage stabilisation employing electric vehicle loads
publisher Multidisciplinary Digital Publishing Institute
publishDate 2023
url https://doi.org/10.3390/app13042254
op_coverage agris
genre Beluga
Beluga whale
Beluga*
genre_facet Beluga
Beluga whale
Beluga*
op_source Applied Sciences; Volume 13; Issue 4; Pages: 2254
op_relation Energy Science and Technology
https://dx.doi.org/10.3390/app13042254
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/app13042254
container_title Applied Sciences
container_volume 13
container_issue 4
container_start_page 2254
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