电动汽车车队智能充电方式比较

A. Rutgers
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引用次数: 0

摘要

为电动汽车充电需要昂贵的充电基础设施和电网升级;然而,成本可以通过智能充电来降低——随着时间的推移规划充电功率。与私家车相比,电动汽车车队面临着独特的智能充电挑战和机遇。智能充电的复杂程度各不相同,从指示停车地点到监控车辆和公用事业价格的集成软件系统,以及实时指导停车和充电过程。本文介绍了一系列可用于智能充电的输入和输出,对智能充电系统的级别进行了分类,并使用ChargeSim车队充电分析和仿真软件评估了每个级别的潜在成本节约。在这个例子中,非管理充电的成本可能比储能系统的理论最低成本高出70%,然而,即使是一个简单的智能充电系统,也只能将多余的成本降低到13%。
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Comparison of electric vehicle fleet smart charging methods
Charging Electric Vehicle Fleets requires expensive charging infrastructure and electricity grid upgrades; however, the costs can be mitigated by smart charging – planning the charging power over time. EV fleets present unique smart charging challenges and opportunities compared to private cars. Smart Charging varies in complexity from instructions on where to park returning vehicles, to integrated software systems monitoring the vehicles and utility prices and directing the parking and charging process real time. This paper presents a range of inputs and outputs which can be used for smart charging, presents a categorization of the levels of smart charging systems, and evaluates the potential cost savings for each level in an example case using ChargeSim fleet charging analysis and simulation software. In the example case, unmanaged charging could cost 70% more than theoretical minimum achievable with an energy storage system, however even a simple smart charging system could reduce the excess cost to only 13%.
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