Estimation of Required EVs Battery Capacity for Leveling Demand Energy Considering Parking Durations

Tomoya Imanishi; Hiroaki Nishi

doi:10.1007/s13177-016-0129-8

Estimation of Required EVs Battery Capacity for Leveling Demand Energy Considering Parking Durations

Tomoya Imanishi, Hiroaki Nishi

Department of System Design Engineering

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

Vehicle-to-grid (V2G) is a key technology that is receiving significant attention as a method for achieving an efficient energy management system (EMS) by connecting electric vehicles (EVs) to an electric power grid. In this study, a fuzzy control method and an optimization control method were proposed as effective control methods for reducing the installation battery capacity and the electric charge in one day by leveling the electric load. As the result, the required battery capacity was 429 kWh for IEVBS model, and 480 kWh for MEVBS model using optimization control method. The control method could save at most $17.98 of an electric bill and achieve power leveling.

Original language	English
Pages (from-to)	155-165
Number of pages	11
Journal	International Journal of Intelligent Transportation Systems Research
Volume	15
Issue number	3
DOIs	https://doi.org/10.1007/s13177-016-0129-8
Publication status	Published - 2017 Sept 1

Keywords

Batteries
Electric vehicles
Energy management
Smart grid

ASJC Scopus subject areas

Software
Control and Systems Engineering
Neuroscience(all)
Information Systems
Automotive Engineering
Aerospace Engineering
Computer Science Applications
Applied Mathematics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s13177-016-0129-8

Cite this

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title = "Estimation of Required EVs Battery Capacity for Leveling Demand Energy Considering Parking Durations",

abstract = "Vehicle-to-grid (V2G) is a key technology that is receiving significant attention as a method for achieving an efficient energy management system (EMS) by connecting electric vehicles (EVs) to an electric power grid. In this study, a fuzzy control method and an optimization control method were proposed as effective control methods for reducing the installation battery capacity and the electric charge in one day by leveling the electric load. As the result, the required battery capacity was 429 kWh for IEVBS model, and 480 kWh for MEVBS model using optimization control method. The control method could save at most $17.98 of an electric bill and achieve power leveling.",

keywords = "Batteries, Electric vehicles, Energy management, Smart grid",

author = "Tomoya Imanishi and Hiroaki Nishi",

note = "Funding Information: This work was partially supported by the funds of SECOM Science and Technology Foundation, by MEXT/JSPS KAKENHI Grant (B) Number 24,360,230/25,280,033, and by the Japanese Ministry of Land, Infrastructure, transport and Tourism funds for development of advanced technology in housing and buildings construction. Publisher Copyright: {\textcopyright} 2016, Springer Science+Business Media New York.",

year = "2017",

month = sep,

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doi = "10.1007/s13177-016-0129-8",

language = "English",

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journal = "International Journal of Intelligent Transportation Systems Research",

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T1 - Estimation of Required EVs Battery Capacity for Leveling Demand Energy Considering Parking Durations

AU - Imanishi, Tomoya

AU - Nishi, Hiroaki

N1 - Funding Information: This work was partially supported by the funds of SECOM Science and Technology Foundation, by MEXT/JSPS KAKENHI Grant (B) Number 24,360,230/25,280,033, and by the Japanese Ministry of Land, Infrastructure, transport and Tourism funds for development of advanced technology in housing and buildings construction. Publisher Copyright: © 2016, Springer Science+Business Media New York.

PY - 2017/9/1

Y1 - 2017/9/1

N2 - Vehicle-to-grid (V2G) is a key technology that is receiving significant attention as a method for achieving an efficient energy management system (EMS) by connecting electric vehicles (EVs) to an electric power grid. In this study, a fuzzy control method and an optimization control method were proposed as effective control methods for reducing the installation battery capacity and the electric charge in one day by leveling the electric load. As the result, the required battery capacity was 429 kWh for IEVBS model, and 480 kWh for MEVBS model using optimization control method. The control method could save at most $17.98 of an electric bill and achieve power leveling.

AB - Vehicle-to-grid (V2G) is a key technology that is receiving significant attention as a method for achieving an efficient energy management system (EMS) by connecting electric vehicles (EVs) to an electric power grid. In this study, a fuzzy control method and an optimization control method were proposed as effective control methods for reducing the installation battery capacity and the electric charge in one day by leveling the electric load. As the result, the required battery capacity was 429 kWh for IEVBS model, and 480 kWh for MEVBS model using optimization control method. The control method could save at most $17.98 of an electric bill and achieve power leveling.

KW - Batteries

KW - Electric vehicles

KW - Energy management

KW - Smart grid

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JO - International Journal of Intelligent Transportation Systems Research

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ER -

Estimation of Required EVs Battery Capacity for Leveling Demand Energy Considering Parking Durations

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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