Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle

Currently, there is a remarkable focus on green technologies for taking steps towards more use of renewable energy sources within the sector of transportation and also decreasing pollution. At this point, employment of plug-in hybrid electric vehicles (PHEVs) needs sufficient charging allocation str...

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Main Authors: Vasant, P., Marmolejo, J.A., Litvinchev, I., Aguilar, R.R.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.29898 /
Published: Springer 2020
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066101178&doi=10.1007%2fs11276-019-01993-w&partnerID=40&md5=471dbdf820260cad982edaa31169233a
http://eprints.utp.edu.my/29898/
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id utp-eprints.29898
recordtype eprints
spelling utp-eprints.298982022-03-25T03:05:40Z Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle Vasant, P. Marmolejo, J.A. Litvinchev, I. Aguilar, R.R. Currently, there is a remarkable focus on green technologies for taking steps towards more use of renewable energy sources within the sector of transportation and also decreasing pollution. At this point, employment of plug-in hybrid electric vehicles (PHEVs) needs sufficient charging allocation strategy, by running smart charging infrastructures and smart grid systems. In order to daily usage of PHEVs, daytime charging stations are required and at this point, only an appropriate charging control and a management of the infrastructure can lead to wider employment of PHEVs. In this study, four swarm intelligence based optimization techniques: particle swarm optimization (PSO), gravitational search algorithm (GSA), accelerated particle swarm optimization, and hybrid version of PSO and GSA (PSOGSA) have been applied for the state-of-charge optimization of PHEVs. In this research, hybrid PSOGSA has performed very well in producing better results than other stand-alone optimization techniques. © 2019, Springer Science+Business Media, LLC, part of Springer Nature. Springer 2020 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066101178&doi=10.1007%2fs11276-019-01993-w&partnerID=40&md5=471dbdf820260cad982edaa31169233a Vasant, P. and Marmolejo, J.A. and Litvinchev, I. and Aguilar, R.R. (2020) Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle. Wireless Networks, 26 (7). pp. 4753-4766. http://eprints.utp.edu.my/29898/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Currently, there is a remarkable focus on green technologies for taking steps towards more use of renewable energy sources within the sector of transportation and also decreasing pollution. At this point, employment of plug-in hybrid electric vehicles (PHEVs) needs sufficient charging allocation strategy, by running smart charging infrastructures and smart grid systems. In order to daily usage of PHEVs, daytime charging stations are required and at this point, only an appropriate charging control and a management of the infrastructure can lead to wider employment of PHEVs. In this study, four swarm intelligence based optimization techniques: particle swarm optimization (PSO), gravitational search algorithm (GSA), accelerated particle swarm optimization, and hybrid version of PSO and GSA (PSOGSA) have been applied for the state-of-charge optimization of PHEVs. In this research, hybrid PSOGSA has performed very well in producing better results than other stand-alone optimization techniques. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
format Article
author Vasant, P.
Marmolejo, J.A.
Litvinchev, I.
Aguilar, R.R.
spellingShingle Vasant, P.
Marmolejo, J.A.
Litvinchev, I.
Aguilar, R.R.
Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle
author_sort Vasant, P.
title Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle
title_short Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle
title_full Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle
title_fullStr Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle
title_full_unstemmed Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle
title_sort nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle
publisher Springer
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066101178&doi=10.1007%2fs11276-019-01993-w&partnerID=40&md5=471dbdf820260cad982edaa31169233a
http://eprints.utp.edu.my/29898/
_version_ 1741197316789895168
score 11.62408

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