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A Model of Charging Service Demand for the Czech Republic

Author

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  • Jan Pekárek

    (Department of Informatics, Faculty of Business and Management, Brno University of Technology, Kolejní 2906/4, 612 00 Brno, Czech Republic)

Abstract

The paper introduces a standalone model of electric vehicle charging demand based on large-scale travel survey data of the Czech Republic. This demand model has been intended as a comprehensive input model for following charging infrastructure problem, where a spatial view of charging demand is usually needed. The model uses publicly available data, whose mutual incompatibility and information richness had to be overcome. The necessary data transformations are described and final data representation in the form of a mathematical graph allows the introduction of a point-defined (vertex-defined) charging demand model. Several drawbacks of the model are identified and their effect, as well as an application of whole model, is demonstrated on the large-scale numerical example. Sound demand model is a cornerstone for demand-related problems, such as general large-scale charging infrastructure problem, which is a common issue for countries that stand at the very beginning of the electric vehicle adoption process.

Suggested Citation

  • Jan Pekárek, 2017. "A Model of Charging Service Demand for the Czech Republic," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(5), pages 1741-1750.
  • Handle: RePEc:mup:actaun:actaun_2017065051741
    DOI: 10.11118/actaun201765051741
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    References listed on IDEAS

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    1. Madina, Carlos & Zamora, Inmaculada & Zabala, Eduardo, 2016. "Methodology for assessing electric vehicle charging infrastructure business models," Energy Policy, Elsevier, vol. 89(C), pages 284-293.
    2. Zhu, Zhi-Hong & Gao, Zi-You & Zheng, Jian-Feng & Du, Hao-Ming, 2016. "Charging station location problem of plug-in electric vehicles," Journal of Transport Geography, Elsevier, vol. 52(C), pages 11-22.
    3. Lim, Seow & Kuby, Michael, 2010. "Heuristic algorithms for siting alternative-fuel stations using the Flow-Refueling Location Model," European Journal of Operational Research, Elsevier, vol. 204(1), pages 51-61, July.
    4. Yi, Zonggen & Bauer, Peter H., 2016. "Optimization models for placement of an energy-aware electric vehicle charging infrastructure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 227-244.
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