Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm

Plug-in Hybrid Electric Vehicle (PHEV) has gained immense popularity ever since it offers many advantages as compared to conventional internal combustion engine (ICE) vehicle. One millions of PHEVs are estimated to be in the USA market by 2015. Uncoordinated PHEV charging will cause significant impa...

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Main Authors:	Mohd Redzuan, Ahmad, Ismail, Musirin, M. M., Othman
Format:	Conference or Workshop Item
Language:	English
Published:	2014
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/6443/ http://umpir.ump.edu.my/id/eprint/6443/ http://umpir.ump.edu.my/id/eprint/6443/1/Optimal_charging_strategy_for_Plug-in_Hybrid_Electric_Vehicle_using_evolutionary_algorithm.pdf

id	ump-6443
recordtype	eprints
spelling	ump-64432018-02-05T01:03:01Z http://umpir.ump.edu.my/id/eprint/6443/ Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm Mohd Redzuan, Ahmad Ismail, Musirin M. M., Othman TK Electrical engineering. Electronics Nuclear engineering Plug-in Hybrid Electric Vehicle (PHEV) has gained immense popularity ever since it offers many advantages as compared to conventional internal combustion engine (ICE) vehicle. One millions of PHEVs are estimated to be in the USA market by 2015. Uncoordinated PHEV charging will cause significant impacts to the power grid; i.e. lines and transformers overload and voltage drops. Appropriate charging methods should be used to minimize the impacts of PHEV charging activities and at the same time minimize daily charging cost. This paper presents methods used to charge the PHEV battery namely price-based charging, load-based charging and SOC-based charging. Evolutionary programming (EP) is then used to optimize the charging rate and SOC thus minimizing the charging cost. Charging cost is calculated based on real time electricity price i.e. Locational Marginal Price (LMP). Since the data pattern for LMP is similar throughout the week, the day-ahead price model is used to calculate charging cost. Results from the study indicated that charging strategies used produces different impacts to the grid. Moreover charging cost may vary from one method to another. Optimization of charging rate and SOC hence minimized charging cost is done by EP. 2014 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6443/1/Optimal_charging_strategy_for_Plug-in_Hybrid_Electric_Vehicle_using_evolutionary_algorithm.pdf Mohd Redzuan, Ahmad and Ismail, Musirin and M. M., Othman (2014) Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm. In: IEEE 8th International Power Engineering and Optimization Conference (PEOCO 2014), 24-25 March 2014 , Langkawi. pp. 557-562.. http://dx.doi.org/10.1109/PEOCO.2014.6814491
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Mohd Redzuan, Ahmad Ismail, Musirin M. M., Othman Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm
description	Plug-in Hybrid Electric Vehicle (PHEV) has gained immense popularity ever since it offers many advantages as compared to conventional internal combustion engine (ICE) vehicle. One millions of PHEVs are estimated to be in the USA market by 2015. Uncoordinated PHEV charging will cause significant impacts to the power grid; i.e. lines and transformers overload and voltage drops. Appropriate charging methods should be used to minimize the impacts of PHEV charging activities and at the same time minimize daily charging cost. This paper presents methods used to charge the PHEV battery namely price-based charging, load-based charging and SOC-based charging. Evolutionary programming (EP) is then used to optimize the charging rate and SOC thus minimizing the charging cost. Charging cost is calculated based on real time electricity price i.e. Locational Marginal Price (LMP). Since the data pattern for LMP is similar throughout the week, the day-ahead price model is used to calculate charging cost. Results from the study indicated that charging strategies used produces different impacts to the grid. Moreover charging cost may vary from one method to another. Optimization of charging rate and SOC hence minimized charging cost is done by EP.
format	Conference or Workshop Item
author	Mohd Redzuan, Ahmad Ismail, Musirin M. M., Othman
author_facet	Mohd Redzuan, Ahmad Ismail, Musirin M. M., Othman
author_sort	Mohd Redzuan, Ahmad
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	2014
url	http://umpir.ump.edu.my/id/eprint/6443/ http://umpir.ump.edu.my/id/eprint/6443/ http://umpir.ump.edu.my/id/eprint/6443/1/Optimal_charging_strategy_for_Plug-in_Hybrid_Electric_Vehicle_using_evolutionary_algorithm.pdf
first_indexed	2023-09-18T22:02:11Z
last_indexed	2023-09-18T22:02:11Z
_version_	1777414471742914560

Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm

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