Scheduling of electrical vehicle charging for a charging facility with single charger

I. Vidanalage, B. Venkatesh, R. Torquato, W. Freitas
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引用次数: 2

Abstract

This paper proposes an algorithm to develop an optimum Electric Vehicle (EV) charging schedule for a charging facility with a single charger. Although there are many researches to address the developing of an optimum schedule for EV charging, current methods do not address this problem from the charging facility owner's perspective. We use a hybrid system framework to capture the tradeoff between demand charges proportional to the peak demand and speed of charging. However, this hybrid framework leads to a nonconvex and non-differentiable problem. This challenge is overcome by decomposing the problem into multiple smaller and simpler constrained convex optimization problems. With the resulting convex model proposed here, the minimum cost day ahead EV charging schedule can be determined from the charging facility owner's perspective. By using this tool, a day ahead, charging facility owner has the ability to set up prices based on the cost and customer has the ability to know the prices, the total waiting and the charging time at the charging facility. The nonlinear cost optimization model was developed by using a backward recursive algorithm. The proposed algorithm has been analyzed for different penalty factors which were imposed on total waiting time of each EV. Final results are analyzed and discussed.
单充电器充电设施下的电动汽车充电调度
本文提出了一种基于单充电器充电设施的电动汽车最佳充电计划求解算法。虽然有很多研究都在研究电动汽车的最佳充电计划,但目前的方法并没有从充电设施所有者的角度来解决这个问题。我们使用混合系统框架来捕获与峰值需求成比例的需求收费和充电速度之间的权衡。然而,这种混合框架导致了一个非凸不可微问题。通过将问题分解为多个更小、更简单的约束凸优化问题,可以克服这一挑战。利用本文提出的凸模型,可以从充电设施所有者的角度确定电动汽车充电计划的最小成本。通过使用该工具,充电设施所有者可以提前一天根据成本设置价格,客户可以了解充电设施的价格、总等待时间和充电时间。采用反向递归算法建立了非线性成本优化模型。分析了对每辆电动汽车总等待时间施加不同惩罚因子的算法。最后对结果进行了分析和讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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