Optimal Dispatching Strategy for Shared Battery Station of Electric Vehicle by Divisional Battery Control

被引:28
|
作者
Yang, Jie [1 ]
Wang, Weiqiang [1 ]
Ma, Kai [1 ]
Yang, Bo [2 ]
机构
[1] Yanshan Univ, Sch Elect Engn, Qinhuangdao 066004, Hebei, Peoples R China
[2] Shanghai Jiao Tong Univ, Key Lab Syst Control & Informat Proc, Minist Educ, Shanghai 200240, Peoples R China
来源
IEEE ACCESS | 2019年 / 7卷
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Shared battery station; dispatching strategy; electric vehicle; peak shaving and valley filling; divisional battery control; ENERGY MANAGEMENT; SYSTEMS; DEMAND; MODEL; OPTIMIZATION;
D O I
10.1109/ACCESS.2019.2906488
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With increasing application of electric vehicle (EV), the battery swapping station (BSS) and battery charging station (BCS) have gradually gained recognition by electric vehicle users. With the stations, it is possible to refuel within several minutes, which promotes the EV popularization greatly. In this paper, a shared battery station (SBS) model is proposed, which is a multi-functional facility having the ability to charge, discharging, sleeping, and swapping abilities. Just like other shared economic, the customer has temporary access to the battery and pays corresponding fees according to swapping energy. Different from the traditional BCS and BSS, the SBS has a new business model. Besides, based on divisional battery control method, a battery dispatching strategy is proposed to control the charging, discharging, sleeping, and swapping processes. Through the divisional battery control method, the number of variables can be reduced greatly. Hence, the large-scale battery dispatching problem can be solved reasonably and quickly. From the view of the operator, an optimization objective function to maximize the revenue is established to optimize the number of batteries in each segment in each time slot. The dispatching strategy and the objective function cooperate with each other during the SBS operation to satisfy customers' battery demand, to ensure a sustainable and safe operation, and to participate in peak shaving and valley filling. Using the genetic algorithm, we perform extensive simulations to validate the optimization model and to demonstrate the efficiency of the dispatching strategy.
引用
收藏
页码:38224 / 38235
页数:12
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