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

システムデザイン工学科

研究成果: Article › 査読

2 被引用数 (Scopus)

抄録

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.

本文言語	English
ページ（範囲）	155-165
ページ数	11
ジャーナル	International Journal of Intelligent Transportation Systems Research
巻	15
号	3
DOI	https://doi.org/10.1007/s13177-016-0129-8
出版ステータス	Published - 2017 9月 1

ASJC Scopus subject areas

ソフトウェア
制御およびシステム工学
神経科学（全般）
情報システム
自動車工学
航空宇宙工学
コンピュータサイエンスの応用
応用数学

UN SDG

この成果は、次の持続可能な開発目標に貢献しています

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10.1007/s13177-016-0129-8

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引用スタイル

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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",

volume = "15",

pages = "155--165",

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

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TY - JOUR

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

JF - International Journal of Intelligent Transportation Systems Research

SN - 1868-8659

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

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ASJC Scopus subject areas

UN SDG

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