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Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm

Plug in Hybrid Electric Vehicle (PHEV) is predicted to increase on the road as for users appreciate the benefits that a PHEV can provide. Every PHEV has a battery storage and needs to be recharged. The increase of charging Plug in Hybrid Electric Vehicle on the distribution system due to the increas...

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Main Author: Lee, Clement Yuon Sien
Format: Undergraduates Project Papers
Language:English
Published: 2016
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/18012/1/Optimal%20charging%20strategy%20for%20plug-in%20hybrid%20electric%20vehicle%20using%20evolutionary%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/18012/
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spelling my.ump.umpir.180122022-12-14T02:56:07Z http://umpir.ump.edu.my/id/eprint/18012/ Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm Lee, Clement Yuon Sien TK Electrical engineering. Electronics Nuclear engineering Plug in Hybrid Electric Vehicle (PHEV) is predicted to increase on the road as for users appreciate the benefits that a PHEV can provide. Every PHEV has a battery storage and needs to be recharged. The increase of charging Plug in Hybrid Electric Vehicle on the distribution system due to the increase in number of PHEV on the road will cause overload in the system. Upon this study, a control charging system is needed to control the charging so that the distribution network is not overloaded. An optimal charging strategy for plug-in hybrid electric vehicle (PHEV) is proposed and developed by using evolutionary algorithm to obtain the most suitable charging condition for each PHEV charging. The charging strategy controls the charging time on the vehicle charging load profile (VCLP). VCLP is developed using MATLAB from the real vehicle travel data from National Household Travel Survey (NHTS). The profile is test on IEEE bus-30 system. The results showed that the developed charging strategy achieved the required battery capacity and has reduced peak load and improved load factor thus reduces impacts on power system networks. 2016-11 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/18012/1/Optimal%20charging%20strategy%20for%20plug-in%20hybrid%20electric%20vehicle%20using%20evolutionary%20algorithm.pdf Lee, Clement Yuon Sien (2016) Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm. Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang.
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Lee, Clement Yuon Sien
Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm
description Plug in Hybrid Electric Vehicle (PHEV) is predicted to increase on the road as for users appreciate the benefits that a PHEV can provide. Every PHEV has a battery storage and needs to be recharged. The increase of charging Plug in Hybrid Electric Vehicle on the distribution system due to the increase in number of PHEV on the road will cause overload in the system. Upon this study, a control charging system is needed to control the charging so that the distribution network is not overloaded. An optimal charging strategy for plug-in hybrid electric vehicle (PHEV) is proposed and developed by using evolutionary algorithm to obtain the most suitable charging condition for each PHEV charging. The charging strategy controls the charging time on the vehicle charging load profile (VCLP). VCLP is developed using MATLAB from the real vehicle travel data from National Household Travel Survey (NHTS). The profile is test on IEEE bus-30 system. The results showed that the developed charging strategy achieved the required battery capacity and has reduced peak load and improved load factor thus reduces impacts on power system networks.
format Undergraduates Project Papers
author Lee, Clement Yuon Sien
author_facet Lee, Clement Yuon Sien
author_sort Lee, Clement Yuon Sien
title Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm
title_short Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm
title_full Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm
title_fullStr Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm
title_full_unstemmed Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm
title_sort optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm
publishDate 2016
url http://umpir.ump.edu.my/id/eprint/18012/1/Optimal%20charging%20strategy%20for%20plug-in%20hybrid%20electric%20vehicle%20using%20evolutionary%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/18012/
_version_ 1753788542294687744
score 13.211869

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