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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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2016
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| Online Access: | http://umpir.ump.edu.my/id/eprint/18012/ http://umpir.ump.edu.my/id/eprint/18012/1/Optimal%20charging%20strategy%20for%20plug-in%20hybrid%20electric%20vehicle%20using%20evolutionary%20algorithm.pdf |
| _version_ | 1848820568360484864 |
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| author | Lee, Clement Yuon Sien |
| author_facet | Lee, Clement Yuon Sien |
| author_sort | Lee, Clement Yuon Sien |
| building | UMP Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T02:11:31Z |
| format | Undergraduates Project Papers |
| id | ump-18012 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:11:31Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-180122023-10-19T03:20:50Z 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. |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Lee, Clement Yuon Sien Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm |
| title | 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_short | 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 |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/18012/ http://umpir.ump.edu.my/id/eprint/18012/1/Optimal%20charging%20strategy%20for%20plug-in%20hybrid%20electric%20vehicle%20using%20evolutionary%20algorithm.pdf |