Optimizing Resource Usage in an Unobtrusive Way Through Smart Aggregation: The Case of Electric Vehicle Charging in Amsterdam

Kees Montfort (), Halldora Thorsdottir and René Bohnsack
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Kees Montfort: Urban Technology, University of Applied Science Amsterdam
Halldora Thorsdottir: Urban Technology, University of Applied Science Amsterdam
René Bohnsack: School of Business and Economics, Universidade Católica Portuguesa

A chapter in Regulations in the Energy Industry, 2020, pp 243-261 from Springer

Abstract: Abstract The increasing popularity of electric vehicles (EVs) is known to amplify the already present peaks in electricity demand. The possibility to remotely control and influence the charging of many EVs using the Internet of Things (IoT) via an aggregator has been proposed to optimize resource usage, to alleviate peak problems, and to exploit revenues that may be harnessed from fluctuating electricity prices. However, so far, the potential hinged on the acceptance of users, particularly the willingness to change their charging behavior. In this study, we develop an unobtrusive and easily implementable optimization method. Its effectiveness is tested on 360,000 charging sessions at public charging points in Amsterdam during the year 2015, providing a realistic assessment of the effects of optimization in terms of reduced costs, change in peak demand, and long occupancy of charging points. Based on the model, an average reduction of electricity costs between 20% and 30% can be achieved, depending on the day of the week. We also show that changing EV owner’s charging preferences such as starting earlier or later can benefit certain groups of EV drivers substantially and reduce electricity charging costs up to 35%.

Keywords: Electric vehicles; Smart charging; Optimization (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-32296-0_13

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DOI: 10.1007/978-3-030-32296-0_13

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