摘要
以电动汽车充换电服务为研究背景,通过计算调度车辆和用户车辆的充电损耗,并结合站点和电网间的储能共享,分析了时变路况下电池调度的路径优化问题。首先,提出了基于荷电状态和时速的调度行驶数学模型,并建立电池充电模型;然后,为精确计算充电损耗,考虑在时变功率下的电能损耗,提出了基于电池容量修正的电池损耗模型。此外,为实现储能利用,提出在充换电站与电网之间进行储能电池共享,从而建立了以充电损耗和共享收入为调度成本的目标函数。最后,在传统的站点流量和电池容量等约束下,又考虑了基于储能利用的站点电源功率约束,并采用遗传算法求解。实验结果表明,所提方法能有效减少调度过程中的充电损耗,研究成果为充换电站和电网之间的共享储能提供了理论指导。
Under the background of charging and swapping services of electric vehicles, the path optimization problem of dispatching battery under time-varying road conditions is analyzed by calculating the charging loss of dispatching vehicles, user vehicles, and the energy storage sharing of the stations. First, a mathematical model of dispatching driving based on the state of charge and speed is proposed. The battery charging model is constructed. Then, in order to accurately calculate the charging loss, the power loss under time-varying power is considered. Based on the correctional battery capacity, the battery loss model is proposed. Moreover, to realize the utilization of energy storage, the sharing energy storages between the charging and swapping station and the grid are proposed. Hence an objective function with the charging loss and the sharing revenue as the dispatching cost is established. Finally, based on energy storage utilization, under the traditional constraints of stations traffic and battery capacity, the constraints of stations power are considered. In addition, the genetic algorithm is used to solve the path optimization problem. The experimental results show that the method proposed in this paper can effectively` reduce the charging loss during the dispatching process. The research results provide theoretical guidance for the energy storage sharing between the charging and swapping station and the grid.
作者
金珈辉
刘永慧
苏庆堂
JIN Jia-hui;LIU Yong hui;SU Qing-tang(School of Electrical Engineering,Shanghai Dianji University,Shanghai 201306,China;School of Information and Electrical Engineering,Ludong University,Yantai 264025,China)
出处
《控制工程》
CSCD
北大核心
2022年第9期1658-1666,共9页
Control Engineering of China
基金
国家自然科学基金资助项目(61803253,61771231)。
关键词
充换电站
充电损耗
电池容量修正
储能利用
遗传算法
Charging and swapping station
charging loss
battery capacity correction
energy storage utilization
genetic algorithm
