Research on optimization of EV energy storage V2G strategy based on user preference

doi:10.19799/j.cnki.2095-4239.2023.0173

Abstract

Abstract:

In recent years, the electric vehicle industry in our country has developed rapidly, with emerging technologies such as vehicle-to-grid (V2G) gaining prominence in China's new electric power system and energy internet. V2G presents a future development trend owing to its low cost, scalability, and promising safety performance. Currently, the V2G technology is not fully developed, leading to a shortage of pilot projects, limited user engagement in V2G discharge behavior data, and insufficient analysis of V2G participation in the power market. To simulate electric vehicle discharge behavior more accurately and evaluate the economic and social benefits of V2G, electric vehicle (EV) users are further divided based on their idle time and willingness to accept discharge cutoff capacity. This allows us to establish discharge load curves for EV users with different preferences. Aiming at aggregator income, an optimization function model is established. Through the analysis of examples, we observed that different scheduling plans have varying demands for different types of EVs. Classification scheduling for different user groups is more beneficial than single-group modeling scheduling. Additionally, the optimization effect of different combinations of EV types is better than that of a single type. The carbon emission of EVs participating in V2G was evaluated and achieved a carbon reduction rate of 20% through optimization. Consequently, the optimized strategy enhances economic and social benefits compared with the original model.

Key words: electric vehicles, V2G, carbon emission, benefit evaluation

CLC Number:

TM 73

Ruijie HONG, Danzhen GU, Ruanqing MO, Sinan CAI, Chaolin ZHANG. Research on optimization of EV energy storage V2G strategy based on user preference[J]. Energy Storage Science and Technology, 2023, 12(8): 2659-2667.

Figures/Tables 10

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项目	A	B	C	D	E	F
对放电截止电池容量需求	20%	20%	30%	30%	40%	40%
电动汽车空闲时间	3～5 h	>5 h	3～5 h	>5 h	3～5 h	>5 h

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