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A Planning Method for Charging Station Based on Long-Term Charging Load Forecasting of Electric Vehicles

Author

Listed:
  • Boyu Xiang

    (School of Electronic and Information Engineering, Chongqing Three Gorges University, Wanzhou 404020, China)

  • Zhengyang Zhou

    (School of Electronic and Information Engineering, Chongqing Three Gorges University, Wanzhou 404020, China)

  • Shukun Gao

    (School of Electronic and Information Engineering, Chongqing Three Gorges University, Wanzhou 404020, China)

  • Guoping Lei

    (School of Electronic and Information Engineering, Chongqing Three Gorges University, Wanzhou 404020, China)

  • Zefu Tan

    (School of Electronic and Information Engineering, Chongqing Three Gorges University, Wanzhou 404020, China)

Abstract

During the planning and construction of electric vehicle charging stations (EVCSs), consideration of the long-term operating revenue loss for investors is often lacking. To address this issue, this study proposes an EVCS planning method that takes into account the potential loss of long-term operating revenues associated with charging facilities. First, the method combines the Bass model with electric vehicle (EV) user travel characteristics to generate a charging load dataset. Then, the cost of profit loss—which represents the EVCS utilization rate—is incorporated into the construction of the objective function. Additionally, a parallel computing method is introduced into the solution algorithm to generate the EVCS planning scheme. Finally, the cost-to-profit ratio of the EVCSs is used as a filtering condition to obtain the optimal EVCS planning scheme. The results show that the EVCS planning scheme considering the profit loss reduces the annual comprehensive cost by 24.25% and 16.93%, and increases the net profit by 22.14% and 24.49%, respectively, when compared to the traditional planning scheme under high and low oil prices. In particular, the charging station strategy proposed in this study has the best effect in the case of high oil prices.

Suggested Citation

  • Boyu Xiang & Zhengyang Zhou & Shukun Gao & Guoping Lei & Zefu Tan, 2024. "A Planning Method for Charging Station Based on Long-Term Charging Load Forecasting of Electric Vehicles," Energies, MDPI, vol. 17(24), pages 1-20, December.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:24:p:6437-:d:1548760
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    References listed on IDEAS

    as
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