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首页> 外文期刊>International journal of electrical power and energy systems >A receding horizon approach to peak power minimization for EV charging stations in the presence of uncertainty
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A receding horizon approach to peak power minimization for EV charging stations in the presence of uncertainty

机译:在存在不确定性存在下EV充电站峰值功率最小化的解序方法

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摘要

The increasing penetration of plug-in electric vehicles in recent years asks for specific solutions concerning the charging policies to be used in parking lots equipped with charging stations. In fact, simple policies based on uncoordinated charge of vehicles lead, in general, to high peak power demand, which may cause high costs to the car park owner. In this paper, the problem of minimizing the daily peak power of a charging station is addressed. Three sources of uncertainty affect the incoming vehicles: the arrival time, the departure time and the demanded energy to be charged. To assess the quality of the charging service under such uncertainties, a suitable customer satisfaction policy is employed. Depending on the information available on the uncertain variables, two algorithms based on a receding horizon approach are designed. Such algorithms require the solution of linear programs and provide the charging power for each plugged-in vehicle. Numerical simulations are provided to assess performance and computational burden of the algorithms, showing the effectiveness and feasibility of the proposed techniques.
机译:近年来插入电动汽车的渗透性越来越多,要求有关在配备充电站的停车场中使用的充电政策的具体解决方案。事实上,基于车辆的不协调负责的简单政策总的来说,一般而言,高峰功率需求,这可能导致停车位的高成本。在本文中,解决了最小化充电站的每日峰值功率的问题。三个不确定性来源影响进货车辆:到达时间,出发时间和所需的能源要充电。根据此类不确定性评估收费服务的质量,采用合适的客户满意度。根据不确定变量的信息,设计了基于后退地平线方法的两种算法。这种算法需要线性程序的解决方案并为每个插入车辆提供充电电力。提供数值模拟,以评估性能和的算法的计算负担,表现出的所提出的技术的有效性和可行性。

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