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Location-scheduling optimization problem to design private charging infrastructure for electric vehicles
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport Planning, Economics and Engineering.ORCID iD: 0000-0002-8499-0843
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2018 (English)In: 6th International Conference on Operations Research and Enterprise Systems, ICORES 2017, Springer, 2018, p. 151-169Conference paper, Published paper (Refereed)
Abstract [en]

We propose optimization model to design a charging infrastructure for a fleet of electric vehicles. Applicable examples include a fleet of vans used in the city logistics, a fleet of taxicabs or a fleet of shared vehicles operating in urban areas. Fleet operator is wishing to replace vehicles equipped with an internal combustion engine with fully electric vehicles. To eliminate interaction with other electric vehicles it is required to design a private network of charging stations that is specifically adjusted to the fleet operation. First, to derive a suitable set of candidate locations from GPS data, we propose a practical procedure where the outcomes can be simply controlled by setting few parameter values. Second, we formulate a mathematical model that combines location and scheduling decisions to ensure that requirements of vehicles can be satisfied. We validate the applicability of our approach by applying it to data characterizing a large taxicab fleet operating in the city of Stockholm. The model assumes that all vehicles posses complete information about all other vehicles. To study the role of available information, we evaluate the resulting designs considering the coordinated charging when vehicle drivers, for example, reveal to each other departure times, and the uncoordinated charging when vehicle drivers know only actual occupation of charging points. Our results indicate that this approach can be used to estimate the minimal requirements to set up the charging infrastructure.

Place, publisher, year, edition, pages
Springer, 2018. p. 151-169
Keywords [en]
Charging infrastructure, Electric vehicles, GPS traces, Urban areas, Charging (batteries), Internal combustion engines, Location, Operations research, Optimization, Scheduling, Taxicabs, Trucks, Charging infrastructures, Complete information, Coordinated charging, Optimization modeling, Practical procedures, Scheduling optimization, Fleet operations
National Category
Vehicle Engineering
Identifiers
URN: urn:nbn:se:kth:diva-236417DOI: 10.1007/978-3-319-94767-9_8Scopus ID: 2-s2.0-85049696864ISBN: 9783319947662 (print)OAI: oai:DiVA.org:kth-236417DiVA, id: diva2:1258999
Conference
6th ICORES 23 February 2017 through 25 February 2017
Note

QC 20181026

Available from: 2018-10-26 Created: 2018-10-26 Last updated: 2019-08-27Bibliographically approved

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Cebecauer, Matej

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
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  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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  • asciidoc
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