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Large-Scale Adaptive Electric Vehicle Charging

Lee, Zachary J. and Chang, Daniel and Jin, Cheng and Lee, George S. and Lee, Rand and Lee, Ted and Low, Steven H. (2018) Large-Scale Adaptive Electric Vehicle Charging. In: 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). IEEE , pp. 1-7. ISBN 9781538679548.

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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.

Item Type:Book Section
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Low, Steven H.0000-0001-6476-3048
Additional Information:© 2018 IEEE. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1745301, NSF AIR-TT under Grant No. 1602119, and NSF CTT under Grant No. 1637598.
Funding AgencyGrant Number
NSF Graduate Research FellowshipDGE-1745301
Record Number:CaltechAUTHORS:20190104-154430902
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Official Citation:Z. J. Lee et al., "Large-Scale Adaptive Electric Vehicle Charging," 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Aalborg, Denmark, 2018, pp. 1-7. doi: 10.1109/SmartGridComm.2018.8587550
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92097
Deposited By: George Porter
Deposited On:05 Jan 2019 00:18
Last Modified:16 Nov 2021 03:46

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