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Evaluation of Electric Vehicle Charging Station Network Planning via a Co-Evolution Approach

Author

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  • Hassan S. Hayajneh

    (College of Engineering, Texas A&M University-Kingsville, Kingsville, TX 78363, USA)

  • Xuewei Zhang

    (College of Engineering, Texas A&M University-Kingsville, Kingsville, TX 78363, USA)

Abstract

The optimal planning of electric vehicle charging infrastructure has attracted extensive research interest in recent years. Most of the optimization problems were formulated by assuming that the configurations will be fixed at the optimal solution while overlooking the fact that the charging stations and the electric vehicles are “evolving” over time and have mutual impacts. On the other hand, little attention has been paid to evaluate the performance of the solutions in such a dynamic environment. Motivated by these gaps, this work develops a simulation model that captures the interactions between charging station configurations and electric vehicle population (and the preference of electric vehicles when choosing charging station). This modeling framework is then implemented to evaluate the performance of planned charging infrastructure in providing services to electric vehicles. Two indicators are calculated, i.e., usage rate and rejection rate. The former measures the “waste” due to abundant facilities installed; the latter measures the inadequacy of planned facilities, especially when the electric vehicle population is larger. The simulation results presented in this work validate the model and show the potential of the model not only to evaluate designs but also to be used for optimal planning in subsequent works.

Suggested Citation

  • Hassan S. Hayajneh & Xuewei Zhang, 2019. "Evaluation of Electric Vehicle Charging Station Network Planning via a Co-Evolution Approach," Energies, MDPI, vol. 13(1), pages 1-11, December.
    • Handle: RePEc:gam:jeners:v:13:y:2019:i:1:p:25-:d:299660
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    References listed on IDEAS

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    Cited by:

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