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Large-Scale Adaptive Electric Vehicle Charging

机译:大规模自适应电动汽车充电

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摘要

Large-scale charging infrastructure will play an important role in supporting the adoption of electric vehicles. In this paper, we address the prohibitively high capital cost of installing large numbers of charging stations within a parking facility by oversubscribing key pieces of electrical infrastructure. We describe a unique physical testbed for large-scale, high- density EV charging research which we call the Adaptive Charging Network (ACN). We describe the architecture of the ACN including its hardware and software components. We also present a practical framework for online scheduling, which is based on model predictive control and convex optimization. Based on our experience with practical EV charging systems, we introduce constraints to the EV charging problem which have not been considered in the literature, such as those imposed by unbalanced three-phase infrastructure. We use simulations based on real data collected from the ACN to illustrate the trade-offs involved in selecting models for infrastructure constraints and accounting for non-ideal charging behavior.
机译:大型充电基础设施将在支持采用电动汽车方面发挥重要作用。在本文中,我们通过过度订购关键的电气基础设施来解决在停车设施中安装大量充电站的高昂资本成本。我们描述了用于大规模,高密度EV充电研究的独特物理测试台,我们称其为Adaptive Charging Network(ACN)。我们描述了ACN的体系结构,包括其硬件和软件组件。我们还提出了一种基于模型预测控制和凸优化的在线调度实用框架。根据我们在实际EV充电系统上的经验,我们介绍了EV充电问题的约束条件,这些约束条件在文献中并未考虑,例如由不平衡的三相基础设施造成的约束。我们使用基于从ACN收集的真实数据的模拟来说明选择基础设施约束模型和考虑非理想充电行为所涉及的权衡。

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