Large-Scale Adaptive Electric Vehicle Charging

被引:0
|
作者
Lee, Zachary J. [1 ]
Chang, Daniel [1 ]
Jin, Cheng [2 ]
Lee, George S. [2 ]
Lee, Rand [1 ]
Lee, Ted [2 ]
Low, Steven H. [1 ,2 ]
机构
[1] CALTECH, Div Engn & Appl Sci, Pasadena, CA 91125 USA
[2] PowerFlex Syst, Los Altos, CA USA
基金
美国国家科学基金会;
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
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.
引用
收藏
页数:7
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