基于最小充电阈值的电动汽车充电离线和在线调度

Martijn H. H. Schoot Uiterkamp, T. V. D. Klauw, Marco E. T. Gerards, J. Hurink
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引用次数: 8

摘要

随着电动汽车(ev)的日益普及,需要开发智能充电策略,以适应这些电动汽车对配电网不断增加的负荷。许多现有的充电策略假设电动汽车可以在给定的最大充电速率下以任何速率充电。然而,在实践中,低费率收费是低效的,往往甚至是不可能的。因此,本文提出了一种在分散能源管理系统中调度电动汽车的有效算法,该系统只允许在给定阈值以上充电。结果表明,最优电动汽车计划具有激活水平和填充水平的特征。此外,基于这一结果,我们推导出一种在线方法,该方法不需要预测不可控负载作为输入,而仅仅是预测这两个特征值。仿真结果表明,在线算法对这些值的预测误差具有较强的鲁棒性,可以产生近似最优的在线解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Offline and online scheduling of electric vehicle charging with a minimum charging threshold
The increasing penetration of electric vehicles (EVs) requires the development of smart charging strategies that accommodate the increasing load of these EVs on the distribution grid. Many existing charging strategies assume that an EV is allowed to charge at any rate up to a given maximum rate. However, in practice, charging at low rates is inefficient and often even impossible. Therefore, this paper presents an efficient algorithm for scheduling an EV within a decentralized energy management system that allows only charging above a given threshold. We show that the resulting optimal EV schedule is characterized by an activation level and a fill-level. Moreover, based on this result, we derive an online approach that does not require predictions of uncontrollable loads as input, but merely a prediction of these two characterizing values. Simulation results show that the online algorithm is robust against prediction errors in these values and can produce near-optimal online solutions.
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