A weighted fair queuing algorithm for charging electric vehicles on a smart grid

Yingjie Zhou, N. Maxemchuk, Xiangying Qian, Yasser Mohammed
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引用次数: 6

Abstract

We are concerned with charging electric vehicles at home. The energy demand from electric vehicles can increase more rapidly than our ability to increase the generating capacity or the distribution facilities in the electric network. Our objective is to use a smart power distribution algorithm to reduce the inconvenience to electric vehicle owners. When there isn't sufficient capacity to charge all of the vehicles simultaneously, we will select different subsets of vehicles to charge in each 5 minute interval. The smart grid will control a switch on each charger. The order in which we charge the vehicles has a significant effect on the number of vehicles that are delayed when they would like to leave the charging station, and the amount of time that they are delayed. By reducing these measures, electric vehicles can be deployed more rapidly. We compare a weighted fair queuing algorithm for selecting the charging order and compare it with a first-come-first-served algorithm and a round robin charging rule. The weights are selected based on the battery level when vehicles arrive at their charging stations. We assume that there is a correlation between day-to-day driving distances, and charge vehicles that require more charge more rapidly. The three charging rules are evaluated using measured data on the power usage, commuting characteristics, and the distribution of commuting times.
智能电网电动汽车充电的加权公平排队算法
我们关心的是在家里给电动汽车充电。电动汽车的能源需求增长速度可能会超过我们增加发电能力或电网配电设施的能力。我们的目标是使用智能配电算法来减少给电动汽车车主带来的不便。当没有足够的容量同时为所有车辆充电时,我们将每隔5分钟选择不同的车辆子集进行充电。智能电网将控制每个充电器上的开关。我们给车辆充电的顺序对车辆在想要离开充电站时被延迟的数量以及被延迟的时间有很大的影响。通过减少这些措施,电动汽车可以更快地部署。我们比较了一种加权公平排队算法来选择收费顺序,并将其与先到先得算法和轮循收费规则进行了比较。权重是根据车辆到达充电站时的电池电量来选择的。我们假设日常行驶距离之间存在相关性,并且需要更多充电的车辆充电速度更快。利用电能使用、通勤特性和通勤时间分布的实测数据对这三种充电规则进行了评估。
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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