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Electric Vehicle Charging Facility Configuration Method for Office Buildings

Autor(en):

ORCID


Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 4, v. 13
Seite(n): 906
DOI: 10.3390/buildings13040906
Abstrakt:

With the advent of advanced battery technology, EVs are gradually gaining momentum. An appropriate decision-making method for the number of charging piles is in need to meet charging needs, and concurrently, to avoid the waste of infrastructure investment. In this study, an optimal charging pile configuration method for office building parking lots is proposed. With the determination of the design period of charging facilities, a charging load prediction model is established under a collection of charging scenarios. Taking the average utilization rate of charging facilities and the average satisfaction rate of charging demand as the objective functions, the distribution of the optimal number of piles is obtained with the genetic algorithm. The benefits of the configuration method are also explored under the building demand response process. The results show that the optimal configuration of charging piles in office buildings with different volumes have similar characteristics. When the design period is 5 years and 10 years, the comprehensive indicator of the utilization rate of the charging facilities and the satisfaction rate of the charging demand can, respectively, be improved by 8.18% and 17.45%. Moreover, the reasonable scheduling strategy can realize the load regulation response with a maximum load transfer rate of 25.55%.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10728226
  • Veröffentlicht am:
    30.05.2023
  • Geändert am:
    01.06.2023
 
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