Vehicle-to-grid management for multi-time scale grid power balancing

doi:10.1016/j.energy.2021.121201

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	Vehicle-to-grid management for multi-time scale grid power balancing
	Li, Shuangqi 1; Gu, Chenghong 1; Zeng, Xianwu 1; Zhao, Pengfei 2; Pei, Xiaoze 1; Cheng, Shuang 1
发表期刊	ENERGY
ISSN	0360-5442
	2021-11-01
卷号	234 页码:9
通讯作者	Gu, Chenghong(C.Gu@bath.ac.uk)
摘要	The mitigation of peak-valley difference and transient power fluctuation are both of great significance to the economy and stability of the power grid. This paper proposes a novel vehicle-to-grid behavior management method that can provide peak-shaving and fast power balancing service to the grid simultaneously. Firstly, a multi-time scale vehicle-to-grid behavior management framework is designed to enable large-scale optimization and real-time control at the same time in vehicle-to-grid scheduling. Then, the grid peak-shaving requirement is modeled as an optimization problem in a centralized V2G state coordinator, where the charging behavior of all grid-connected electric vehicles can be synergis-tically scheduled. The optimization variable is designed as a group of vehicle-to-grid state control signals that can respond to grid peak-shaving requirements. Further, a V2G power controller is designed to manage the vehicle charging power in real time based on the sampled grid frequency state and discrete state control signals. In the developed scheduling method, the charging power of grid-connected electric vehicles is scheduled by the cooperation between the V2G state coordinator and the power controller. The effectiveness of the proposed methodologies is verified on a microgrid system, and results indicate that the V2G scheduling can achieve multi-time scale grid power balancing. This work can bring dual benefits, enabling system operators to use cheap solutions to manage energy networks and allowing vehicle owners to gain profits from providing V2G services to the grid. (c) 2021 Elsevier Ltd. All rights reserved.
关键词	Electric vehicle Multi-time scale scheduling Vehicle to grid Grid energy storage Peak management Power balancing
DOI	10.1016/j.energy.2021.121201
关键词[WOS]	IN ELECTRIC VEHICLES ; FREQUENCY CONTROL ; CONTROL STRATEGY ; SYSTEMS ; COORDINATION ; OPTIMIZATION ; OPERATION ; DEMAND ; IMPACT
收录类别	SCI
语种	英语
WOS研究方向	Thermodynamics ; Energy & Fuels
WOS类目	Thermodynamics ; Energy & Fuels
WOS记录号	WOS:000692114600009
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：18[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/46005
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全
通讯作者	Gu, Chenghong
作者单位	1.Univ Bath, Dept Elect & Elect Engn, Bath, Avon, England 2.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Li, Shuangqi,Gu, Chenghong,Zeng, Xianwu,et al. Vehicle-to-grid management for multi-time scale grid power balancing[J]. ENERGY,2021,234:9.
APA	Li, Shuangqi,Gu, Chenghong,Zeng, Xianwu,Zhao, Pengfei,Pei, Xiaoze,&Cheng, Shuang.(2021).Vehicle-to-grid management for multi-time scale grid power balancing.ENERGY,234,9.
MLA	Li, Shuangqi,et al."Vehicle-to-grid management for multi-time scale grid power balancing".ENERGY 234(2021):9.