Optimal charging strategies for electrical vehicles under real time pricing

M. M. Karbasioun, I. Lambadaris, G. Shaikhet, E. Kranakis
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引用次数: 15

Abstract

We address the problem of serving plug-in hybrid electric vehicles (PHEVs) in a charging station using a local storage energy unit, with finite capacity. Our goal is to find a control policy minimizing the operational cost of the charging station. We assume that the price of the electrical power unit is determined by a Real Time Pricing scheme, in which, the price of the electrical power is continuously updated with respect to the state of the grid at each time instance. We first model the charging station as a continuous time Markov Decision Process with three control actions: the probability of blocking new arrivals, the rate of charging the battery and the proportion of cars being served by the battery. By using dynamic programming, we prove the existence of the optimal policy minimizing a discounted cost over an infinite time horizon. We also show that it is stationary and bang-bang, i.e. the admissible action set in the optimal policy assumes only the extreme values in the action set.
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实时定价下电动汽车最优充电策略
我们解决了在充电站使用有限容量的本地储能单元为插电式混合动力汽车(phev)提供服务的问题。我们的目标是找到一个控制策略,使充电站的运行成本最小化。我们假设电力单位的价格是由实时定价方案确定的,在实时定价方案中,电力价格是根据每个时间实例的电网状态不断更新的。我们首先将充电站建模为具有三个控制动作的连续时间马尔可夫决策过程:阻塞新到达的概率,电池充电的速率和电池服务的汽车比例。利用动态规划方法,证明了在无限时间范围内使贴现成本最小化的最优策略的存在性。我们还证明了它是平稳的和bang-bang的,即最优策略中的可容许行动集只假设行动集中的极值。
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