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Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review

Hybrid Vehicles have experienced major modifications since the last decade. Smart grid success with combination of renewable energy exclusively depends upon the large-scale penetration of Plug-in Hybrid Electric Vehicles (PHEVs) for a sustainable and carbon-free transportation. Recent technical stud...

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Main Authors: Rahman, Imran, Vasant, Pandian, Mahinder Singh, Balbir Singh, Abdullah-Al-Wadud, M.
Format: Citation Index Journal
Published: 2016
Subjects:
QA Mathematics
QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
TL Motor vehicles. Aeronautics. Astronautics
Online Access:http://eprints.utp.edu.my/11905/1/idt-10-idt245.pdf
http://eprints.utp.edu.my/11905/
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spelling my.utp.eprints.119052016-10-07T01:42:37Z Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review Rahman, Imran Vasant, Pandian Mahinder Singh, Balbir Singh Abdullah-Al-Wadud, M. QA Mathematics QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering TL Motor vehicles. Aeronautics. Astronautics Hybrid Vehicles have experienced major modifications since the last decade. Smart grid success with combination of renewable energy exclusively depends upon the large-scale penetration of Plug-in Hybrid Electric Vehicles (PHEVs) for a sustainable and carbon-free transportation. Recent technical studies regarding various optimization strategies related to PHEV integrated smart grid; such as control and battery charging, vehicle-to-grid (V2G), unit commitment, charging infrastructures, integration of solar and wind energy and demand management prove that electrification of transportation as a rapidly growing field of research. This work presents a holistic review of all substantial research applying metaheuritics optimization for plug-in hybrid electric vehicles. A summary on future perspective of metaheuristic algorithms is also provided, covering Cuckoo Search(CS), Harmony Search (HS), Artificial Bee Colony (ABC), etc. with a comprehensive reviews on previously applied methods and their performance for solving different real-world problems in the domain of PHEVs. Moreover, significant shifts towards hybrid and hyper metaheuristics are also highlighted. 2016-03 Citation Index Journal PeerReviewed application/pdf http://eprints.utp.edu.my/11905/1/idt-10-idt245.pdf Rahman, Imran and Vasant, Pandian and Mahinder Singh, Balbir Singh and Abdullah-Al-Wadud, M. (2016) Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review. [Citation Index Journal] http://eprints.utp.edu.my/11905/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic QA Mathematics
QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
TL Motor vehicles. Aeronautics. Astronautics
spellingShingle QA Mathematics
QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
TL Motor vehicles. Aeronautics. Astronautics
Rahman, Imran
Vasant, Pandian
Mahinder Singh, Balbir Singh
Abdullah-Al-Wadud, M.
Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review
description Hybrid Vehicles have experienced major modifications since the last decade. Smart grid success with combination of renewable energy exclusively depends upon the large-scale penetration of Plug-in Hybrid Electric Vehicles (PHEVs) for a sustainable and carbon-free transportation. Recent technical studies regarding various optimization strategies related to PHEV integrated smart grid; such as control and battery charging, vehicle-to-grid (V2G), unit commitment, charging infrastructures, integration of solar and wind energy and demand management prove that electrification of transportation as a rapidly growing field of research. This work presents a holistic review of all substantial research applying metaheuritics optimization for plug-in hybrid electric vehicles. A summary on future perspective of metaheuristic algorithms is also provided, covering Cuckoo Search(CS), Harmony Search (HS), Artificial Bee Colony (ABC), etc. with a comprehensive reviews on previously applied methods and their performance for solving different real-world problems in the domain of PHEVs. Moreover, significant shifts towards hybrid and hyper metaheuristics are also highlighted.
format Citation Index Journal
author Rahman, Imran
Vasant, Pandian
Mahinder Singh, Balbir Singh
Abdullah-Al-Wadud, M.
author_facet Rahman, Imran
Vasant, Pandian
Mahinder Singh, Balbir Singh
Abdullah-Al-Wadud, M.
author_sort Rahman, Imran
title Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review
title_short Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review
title_full Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review
title_fullStr Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review
title_full_unstemmed Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: A holistic review
title_sort novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: a holistic review
publishDate 2016
url http://eprints.utp.edu.my/11905/1/idt-10-idt245.pdf
http://eprints.utp.edu.my/11905/
_version_ 1738655989516730368
score 13.211869

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