Sustainable Electric Vehicle Charging using Adaptive Pricing

Forthcoming, Production and Operations Management

40 Pages Posted: 6 Mar 2020 Last revised: 2 Apr 2020

See all articles by Konstantina Valogianni

Konstantina Valogianni

IE Business School - IE University

Wolfgang Ketter

University of Cologne - Institute of Energy Economics; Erasmus University Rotterdam (EUR) - Department of Technology and Operations Management; Erasmus Research Institute of Management (ERIM)

John Collins

University of Minnesota - Twin Cities

Dmitry Zhdanov

Georgia State University - J. Mack Robinson College of Business

Date Written: February 9, 2020

Abstract

A transition to electric vehicles (EVs) is widely assumed to be an important step along the road to environmental sustainability. However, large scale adoption of EVs may put electricity grids under critical strain, since peaks in electricity demand are likely to increase radically. Efforts to manage demand peaks through pricing schemes may create new peaks at low-price periods, if large numbers of EV owners use smart charging to benefit from low prices. This effect is expected to be amplified when EV owners adopt smart decision support to assist them with optimal charging decisions. Therefore, energy policymakers are interested in advanced pricing schemes that can smooth demand or induce demand that comes as close as possible to a desired profile. We show, through simulations calibrated with real-world data, that current approaches to electricity pricing are limited in their ability to induce desired demand profiles. To address this challenge, we present adaptive pricing, a method to learn from EV owner reactions to prices and adjust announced prices accordingly. Our method draws on the Green Information Systems principles and can assist grid operators in ensuring the reliable operation of the grid. We evaluate our results in simulations, where we find that adaptive pricing outperforms current electricity pricing schemes, yielding results close to the theoretically optimal ones. We test our method in inducing both flat and extremely volatile demand profiles, and we see that in both cases it manages to induce EV charging close to the ideal scenario under perfect information.

Keywords: adaptive pricing, electric vehicles, electricity markets, smart grid, sustainability

Suggested Citation

Valogianni, Konstantina and Ketter, Wolfgang and Collins, John and Zhdanov, Dmitry, Sustainable Electric Vehicle Charging using Adaptive Pricing (February 9, 2020). Forthcoming, Production and Operations Management, Available at SSRN: https://ssrn.com/abstract=3535114

Konstantina Valogianni (Contact Author)

IE Business School - IE University ( email )

Calle Maria de Molina 12
Madrid, Madrid 28006
Spain

Wolfgang Ketter

University of Cologne - Institute of Energy Economics ( email )

Alte Wagenfabrik
Vogelsanger Strasse 321a
Cologne, 50827
Germany

HOME PAGE: http://ewi.uni-koeln.de/en/

Erasmus University Rotterdam (EUR) - Department of Technology and Operations Management ( email )

RSM Erasmus University
PO Box 1738
3000 DR Rotterdam
Netherlands

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

HOME PAGE: http://www.rsm.nl/energy

John Collins

University of Minnesota - Twin Cities ( email )

420 Delaware St. SE
Minneapolis, MN 55455
United States

Dmitry Zhdanov

Georgia State University - J. Mack Robinson College of Business ( email )

P.O. Box 4015
Atlanta, GA 30302-4015
United States

HOME PAGE: http://https://robinson.gsu.edu/profile/dmitry-zhdanov/

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