User-needs-oriented shared DC charging resources optimal configuration and operation for improving EV penetration in old residential communities

被引:0
|
作者
Tu, Jiayang [1 ]
Yu, Hang [1 ,2 ]
Zhong, Jiahao [1 ,2 ]
Jian, Linni [1 ,2 ]
机构
[1] Southern Univ Sci & Technol, Dept Elect & Elect Engn, 1088 Xueyuan Ave, Shenzhen 518055, Peoples R China
[2] Southern Univ Sci & Technol, Jiaxing Res Inst, Jiaxing 314000, Peoples R China
关键词
Old residential communities (ORCs); Charging station; PV and energy storage system; Dynamic pricing; Demand response; Coordinated charging strategy; IN ELECTRIC VEHICLES; IMPACT; GRIDS;
D O I
10.1016/j.scs.2024.105796
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The charging limitation of electric vehicles (EVs) in old residential communities (ORCs) derived from insufficient electricity capacity and parking spaces significantly impacts residents' quality of life and impedes urban sustainability. Considering economic and social factors, ORCs are likely to persist worldwide for the foreseeable future. To tackle these challenges, this paper proposes the scheme of shared DC fast charging stations to address the EV charging issues in ORCs. Specific methods involve minimizing the charging station spaces and charging infrastructure investment, while optimizing the photovoltaic (PV) and energy storage capacity. Additionally, a coordinated charging strategy based on dynamic price is designed to guide users in choosing the initial charging time, enhancing EV charging infrastructure utilization and EV penetration. This work is predominantly driven by human needs, integrating surveys on human behavior related to charging station locations and charging times. This case study is based on a real-life ORC in Shenzhen, China. By utilizing the proposed dynamic-pricing coordinated charging strategy tailored to the station capacity, the maximum EV penetration rate is to be achieved with satisfying EV charging demand. Furthermore, the implementation of dynamic pricing effectively guides users to adjust charging behavior, achieving the peak-shaving and valley-filling performance of load curves.
引用
收藏
页数:18
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