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Pricing EV charging service with demand charge

Lee, Zachary J. and Pang, John Z. F. and Low, Steven H. (2020) Pricing EV charging service with demand charge. Electric Power Systems Research, 189 . Art. No. 106694. ISSN 0378-7796. doi:10.1016/j.epsr.2020.106694.

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Pricing electric vehicle (EV) charging services is difficult when the electricity tariff includes both time-of-use energy cost and demand charge based on peak power draw. In this paper, we propose a pricing scheme that assigns a session-specific energy price to each charging session at the end of the billing period. The session price precisely captures the costs of energy, demand charge, and infrastructure congestion for which that session is responsible in that month while optimizing the trade-off between inexpensive time-of-use pricing and peak power draw. While our pricing scheme is calculated offline at the end of the billing period, we propose an online scheduling algorithm based on model predictive control to determine charging rates for each EV in real-time. We provide theoretical justification for our proposal and support it with simulations using real data collected from charging facilities at Caltech and JPL. Our simulation results suggest that the online algorithm can approximate the offline optimal reasonably well, e.g., the cost paid by the operator in the online setting is higher than the offline optimal cost by 9.2% and 6.5% at Caltech and JPL respectively. In the case of JPL, congestion rents are enough to cover this increase in costs, while at Caltech, this results in a negligible average loss of $18 per month.

Item Type:Article
Related URLs:
URLURL TypeDescription
Lee, Zachary J.0000-0002-5358-2388
Pang, John Z. F.0000-0002-6485-7922
Low, Steven H.0000-0001-6476-3048
Additional Information:© 2020 Elsevier B.V. Received 5 October 2019, Revised 20 April 2020, Accepted 1 August 2020, Available online 4 September 2020. This material is based upon work supported by NSF through grants CCF 1637598, ECCS 1619352, and CPS including grant 1739355, as well fellowship support through the NSF Graduate Research Fellowship Program 1745301 and Resnick Sustainability Institute. Declaration of Competing Interest: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Steven Low is a co-founder of Caltech startup PowerFlex Systems, Inc. that deploys and operates ACN. Zachary Lee is a consultant for PowerFlex Systems, Inc. that deploys and operates ACN.
Group:Resnick Sustainability Institute
Funding AgencyGrant Number
NSF Graduate Research FellowshipDGE-1745301
Resnick Sustainability InstituteUNSPECIFIED
Subject Keywords:Demand charge; EV Charging; Pricing; Smart charging; Online scheduling
Record Number:CaltechAUTHORS:20210107-153400550
Persistent URL:
Official Citation:Zachary J. Lee, John Z.F. Pang, Steven H. Low, Pricing EV charging service with demand charge, Electric Power Systems Research, Volume 189, 2020, 106694, ISSN 0378-7796, (
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107378
Deposited By: Tony Diaz
Deposited On:08 Jan 2021 16:52
Last Modified:16 Nov 2021 19:02

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