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Reducing the Impact of EV Charging Operations on the Distribution Network

机译：减少电动汽车充电操作对配电网络的影响

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摘要

A key assumption made in this paper is that electric vehicle (EV) battery charging profiles are rectangular. This requires a specific and new formulation of the charging problem, involving discrete action sets for the EVs in particular. The considered cost function comprises of three components: 1) the distribution transformer aging; 2) the distribution energy losses; and 3) a component inherent to the EV itself (e.g., the battery charging monetary cost). Charging start times are determined by the proposed distributed algorithm, whose analysis is conducted by using game-theoretic tools such as ordinal potential games. Convergence of the proposed algorithm is shown to be guaranteed for some important special cases. Remarkably, the performance loss with respect to the centralized solution is shown to be small. Simulations, based on realistic public data, allow one to gain further insights on the issues of convergence and optimality loss, and provide clear messages about the tradeoff associated with the presence of the three components in the considered cost function. While simulations show that the proposed charging policy performs quite similarly to existing (continuous) charging policies such as valley-filling-type solutions when the non-EV demand forecast is perfect, they reveal an additional asset of rectangular profiles in presence of forecasting errors.
机译：本文做出的一个关键假设是，电动汽车（EV）的电池充电曲线是矩形的。这就需要对充电问题进行具体的新的表述，特别是涉及电动汽车的离散操作集。所考虑的成本函数包括三个部分：1）配电变压器的老化； 2）分配能量损失；和3）电动汽车本身固有的组件（例如，电池充电货币成本）。计费开始时间由所提出的分布式算法确定，该分布式算法通过使用有序理论游戏等博弈论工具进行分析。在某些重要的特殊情况下，可以保证所提算法的收敛性。值得注意的是，相对于集中式解决方案而言，性能损失很小。基于现实的公共数据进行的模拟可以使人们对趋同性和最优性损失问题有更深入的了解，并提供有关在考虑的成本函数中与三个要素的存在相关的权衡的清晰信息。虽然仿真显示，当非电动汽车需求预测完美时，拟议的收费政策与现有（连续）收费政策（如山谷填埋式解决方案）的性能非常相似，但它们却揭示了存在预测误差的矩形轮廓的其他资产。

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