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Optimal charging infrastructure planning based on a charging convenience buffer

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  • Davidov, Sreten

Abstract

In this paper, novelty is finding the optimal mix of charging technology types to be placed at optimal locations with regards to the Time of Convenience limitation acting as a charging convenience buffer of the users’ charging behavior. It constraints the optimization with the preparedness of users to wait when in request for charging and thus effect the optimal charging technology type selection. This paper is a step forward by combining two optimization constraints in providing the charging reliability and convenience needed to engage unlimited mobility of electric vehicles. For that purpose, discrete location model based on set-covering is involved to include electric vehicle users’ behavior reflected by their mobility trajectories, the technology charging times and the wait time required by the users’ when arriving at charging location. To show the general applicability of the model, a discrete 10 × 10 road network is considered. The numeric results show the optimal locations and the charging technology type to be placed. While the charging reliability provided, the part of faster charging technology installed prevails among optimal locations if the charging convenience buffer is shorter and vice-versa for the slower charging technology types.

Suggested Citation

  • Davidov, Sreten, 2020. "Optimal charging infrastructure planning based on a charging convenience buffer," Energy, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:energy:v:192:y:2020:i:c:s0360544219323503
    DOI: 10.1016/j.energy.2019.116655
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    References listed on IDEAS

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    Cited by:

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    2. Khaleghikarahrodi, Mehrsa & Macht, Gretchen A., 2023. "Patterns, no patterns, that is the question: Quantifying users’ electric vehicle charging," Transport Policy, Elsevier, vol. 141(C), pages 291-304.

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