Optimal battery purchasing and charging strategy at electric vehicle battery swap stations

Optimal battery purchasing and charging strategy at electric vehicle battery swap stations
复制标题

DOI:
10.1016/j.ejor.2019.06.019
复制
发表时间:
2019-12
期刊:
Eur. J. Oper. Res.
影响因子:
--
通讯作者:
Bo Sun;Xu Sun;D. Tsang;W. Whitt
Bo Sun;Xu Sun;D. Tsang;W. Whitt
中科院分区:
其他
文献类型:
--
作者:
Bo Sun;Xu Sun;D. Tsang;W. Whitt

文献摘要

被引文献

相似文献

电池交换站(BSS)是电动汽车车主可以快速将耗尽的电池更换为充满电的电池的设施。为了使电池更换具有经济性,BSS运营商必须对设施中充电托架的数量做出长期决策,对系统中电池的数量做出中期决策,以及对何时以及多少电池进行充电做出短期决策。在本文中,我们引入了一个周期性的流体模型来描述充电业务在BSS面临时变需求的电池交换和时变价格的空电池充电,找到一个最佳的电池购买和充电政策,最好的权衡电池投资成本和运营成本,包括充电成本和客户等待成本的目标。我们考虑一个两阶段的优化问题:在第一阶段确定电池液的最佳量。在第二阶段中,通过求解连续时间最优控制问题来确定最优充电规则。我们通过庞特里亚金的最大值原理的最优充电策略的特点,并推导出一个明确的上限的最佳量的电池液,使我们能够量化的需求模式和电力价格对电池投资决策的联合影响。特别地,当这些周期函数的峰和谷在不同时间出现时,需要较少的电池。
A battery swap station (BSS) is a facility where electric vehicle owners can quickly exchange their depleted battery for a fully-charged one. In order for battery swap to be economically sound, the BSS operator must make a long-term decision on the number of charging bays in the facility, a medium-term decision on the number of batteries in the system, and short-term decisions on when and how many batteries to recharge. In this paper, we introduce a periodic fluid model to describe charging operations at a BSS facing time-varying demand for battery swap and time-varying prices for charging empty batteries, with the objective of finding an optimal battery purchasing and charging policy that best trades off battery investment cost and operating cost including charging cost and cost of customer waiting. We consider a two-stage optimization problem: An optimal amount of battery fluid is identified in the first stage. In the second stage, an optimal charging rule is determined by solving a continuous-time optimal control problem. We characterize the optimal charging policy via Pontryagin’s maximum principle and derive an explicit upper bound for the optimal amount of battery fluid which allows us to quantify the joint effect of demand patterns and electricity prices on battery investment decisions. In particular, fewer batteries are needed when the peaks and the troughs of these periodic functions occur at different times.