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Preserving fairness in EV charging under time-varying congestion levels

机译:在时变拥挤水平下保持电动汽车充电的公平性

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This paper concerns facilities for charging Electrical Vehicles at parking lots. We work under the assumption that power capacity may be insufficient to simultaneously charge all stations, and thus some scheduling must be performed. In previous work we analyzed the case of a stationary customer demand, developing a fluid model which characterizes the performance of different scheduling policies in overload. A new policy termed Least Laxity Ratio was proposed to improve fairness in service. In this paper we wish to incorporate the fact that congestion levels are not stationary in practice, rather they obey daily use cycles. We study the behavior of the different policies with load obtained from a real set of parking lot data. Empirical results show that the conclusions of the stationary analysis remain valid. In particular, during intervals of congestion, LLR achieves the best results in terms of proportional fairness.
机译:本文涉及在停车场为电动汽车充电的设施。我们在假设功率容量不足以同时为所有站点同时充电的情况下工作,因此必须执行一些调度。在先前的工作中,我们分析了稳定的客户需求的情况,开发了一个流体模型,该模型描述了过载情况下不同调度策略的性能。为了提高服务的公平性,提出了一项新的政策,即最低宽松率。在本文中,我们希望纳入这样一个事实,即拥堵程度在实践中不是固定的,而是服从日常使用周期。我们通过从一组实际停车场数据中获得的负载来研究不同策略的行为。实证结果表明,平稳分析的结论仍然有效。特别是在拥挤的时间间隔内,LLR在比例公平性方面获得了最佳结果。

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