DNR optimization for loss reduction and voltage stability considering EV charging load

In recent years, electric vehicles (EVs) have been a countermeasure to the serious carbon emission problem in the transportation sector. However, despite being one of the essential infrastructures in the EV ecosystem, the EV charging load causes voltage instability and increases power losses in the...

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Main Authors: Saedi, Azrin, Mohd Shahrin, Abu Hanifah, Hilmi Hela, Ladin, Mohamad Heerwan, Peeie, Halim, Ghafar
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/39112/
http://umpir.ump.edu.my/id/eprint/39112/1/DNR%20optimization%20for%20loss%20reduction%20and%20voltage%20stability%20considering%20EV.pdf
http://umpir.ump.edu.my/id/eprint/39112/2/DNR%20optimization%20for%20loss%20reduction%20and%20voltage%20stability%20considering%20EV%20charging%20load_ABS.pdf
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author Saedi, Azrin
Mohd Shahrin, Abu Hanifah
Hilmi Hela, Ladin
Mohamad Heerwan, Peeie
Halim, Ghafar
author_facet Saedi, Azrin
Mohd Shahrin, Abu Hanifah
Hilmi Hela, Ladin
Mohamad Heerwan, Peeie
Halim, Ghafar
author_sort Saedi, Azrin
building UMP Institutional Repository
collection Online Access
description In recent years, electric vehicles (EVs) have been a countermeasure to the serious carbon emission problem in the transportation sector. However, despite being one of the essential infrastructures in the EV ecosystem, the EV charging load causes voltage instability and increases power losses in the distribution network. Thus, this paper proposed optimizing distribution network reconfiguration (DNR) to solve the problem. The best two metaheuristic methods, Cuckoo Search Algorithm (CSA) and Particle Swarm Optimization (PSO) were compared to get the optimum solution. It was tested on the IEEE 33-bus system in the MATLAB environment with various cases of charging activity. As a result, the CSA showed better consistency with better power loss reduction and voltage stability compared to PSO.
first_indexed 2025-11-15T03:32:52Z
format Conference or Workshop Item
id ump-39112
institution Universiti Malaysia Pahang
institution_category Local University
language English
English
last_indexed 2025-11-15T03:32:52Z
publishDate 2022
publisher Institute of Electrical and Electronics Engineers Inc.
recordtype eprints
repository_type Digital Repository
spelling ump-391122023-11-14T04:00:03Z http://umpir.ump.edu.my/id/eprint/39112/ DNR optimization for loss reduction and voltage stability considering EV charging load Saedi, Azrin Mohd Shahrin, Abu Hanifah Hilmi Hela, Ladin Mohamad Heerwan, Peeie Halim, Ghafar T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics In recent years, electric vehicles (EVs) have been a countermeasure to the serious carbon emission problem in the transportation sector. However, despite being one of the essential infrastructures in the EV ecosystem, the EV charging load causes voltage instability and increases power losses in the distribution network. Thus, this paper proposed optimizing distribution network reconfiguration (DNR) to solve the problem. The best two metaheuristic methods, Cuckoo Search Algorithm (CSA) and Particle Swarm Optimization (PSO) were compared to get the optimum solution. It was tested on the IEEE 33-bus system in the MATLAB environment with various cases of charging activity. As a result, the CSA showed better consistency with better power loss reduction and voltage stability compared to PSO. Institute of Electrical and Electronics Engineers Inc. 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39112/1/DNR%20optimization%20for%20loss%20reduction%20and%20voltage%20stability%20considering%20EV.pdf pdf en http://umpir.ump.edu.my/id/eprint/39112/2/DNR%20optimization%20for%20loss%20reduction%20and%20voltage%20stability%20considering%20EV%20charging%20load_ABS.pdf Saedi, Azrin and Mohd Shahrin, Abu Hanifah and Hilmi Hela, Ladin and Mohamad Heerwan, Peeie and Halim, Ghafar (2022) DNR optimization for loss reduction and voltage stability considering EV charging load. In: 2022 IEEE International Conference on Power and Energy : Advancement in Power and Energy Systems towards Sustainable and Resilient Energy Supply, PECon 2022Pages 203 - 2082022; 9th IEEE International Conference on Power and Energy, PECon 2022 , 5 - 6 December 2022 , Langkawi, Kedah. pp. 351-355. (185592). ISBN 978-166540990-2 (Published) https://doi.org/10.1109/PECon54459.2022.9988963
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TL Motor vehicles. Aeronautics. Astronautics
Saedi, Azrin
Mohd Shahrin, Abu Hanifah
Hilmi Hela, Ladin
Mohamad Heerwan, Peeie
Halim, Ghafar
DNR optimization for loss reduction and voltage stability considering EV charging load
title DNR optimization for loss reduction and voltage stability considering EV charging load
title_full DNR optimization for loss reduction and voltage stability considering EV charging load
title_fullStr DNR optimization for loss reduction and voltage stability considering EV charging load
title_full_unstemmed DNR optimization for loss reduction and voltage stability considering EV charging load
title_short DNR optimization for loss reduction and voltage stability considering EV charging load
title_sort dnr optimization for loss reduction and voltage stability considering ev charging load
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TL Motor vehicles. Aeronautics. Astronautics
url http://umpir.ump.edu.my/id/eprint/39112/
http://umpir.ump.edu.my/id/eprint/39112/
http://umpir.ump.edu.my/id/eprint/39112/1/DNR%20optimization%20for%20loss%20reduction%20and%20voltage%20stability%20considering%20EV.pdf
http://umpir.ump.edu.my/id/eprint/39112/2/DNR%20optimization%20for%20loss%20reduction%20and%20voltage%20stability%20considering%20EV%20charging%20load_ABS.pdf