Volume 41 Issue 4
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Article Navigation >  Journal of Transport Information and Safety  > 2023  >  41(4): 154-162
LIANG Lu, HAN Fei. A Site Selection Model for Electric Vehicle Charging Stations Considering Queuing Time and Charging Cost[J]. Journal of Transport Information and Safety, 2023, 41(4): 154-162. doi: 10.3963/j.jssn.1674-4861.2023.04.016
Citation: LIANG Lu, HAN Fei. A Site Selection Model for Electric Vehicle Charging Stations Considering Queuing Time and Charging Cost[J]. Journal of Transport Information and Safety, 2023, 41(4): 154-162. doi: 10.3963/j.jssn.1674-4861.2023.04.016
shu

A Site Selection Model for Electric Vehicle Charging Stations Considering Queuing Time and Charging Cost

doi: 10.3963/j.jssn.1674-4861.2023.04.016

  • College of Transport Engineering, Chang'an University, Xi'an 710064, China

  • Received Date: 2023-01-18
    Available Online: 2023-11-23
    Abstract
  • A reasonable layout of electric vehicle charging stations plays a crucial role in reducing range anxiety, improving travel comfort, and promoting the adoption of electric vehicles. To overcome the limitations of existing studies that overlooks the consideration of queuing time and charging cost, an improved site selection model for charging stations is established with the objectives of minimizing range anxiety and charging costs. This model explicitly considers queueing and detouring behaviors in charging. The characteristics of charging behavior of electric vehicles are analyzed, and a distance constraint for allowable path deviations is introduced to establish a limit on detour distances in charging paths, thereby reducing the scale of the set of deviation paths in the road network. The characteristics of the charging station queueing system are analyzed, and an analytical expression for the average queueing time of the system is derived with constraints such as acceptable queueing time threshold and budget cost. Considering the patterns of range anxiety and the stepped electricity pricing, a site selection model for charging stations is proposed to minimize range anxiety and charging costs, and the Lingo software is used to solve the model. A case study is conducted on a partial road network in the city of Xi'an. The results show that based on the proposed model, a total queue time and a total charging cost are 5.84 h and 1 440 Yuan, respectively. Compared to the model without considering queue time and charging costs, the system queue time and the total charging cost are decreased by 1.19 h and 240 Yuan, respectively. An Analysis of the charging station budget cost B shows that when B ≤ 500 million Yuan, the total range anxiety and charging costs decrease as B increases. However, when B > 500 million Yuan, further increase in B does not result in further reduction of total range anxiety and charging costs. Under the conditions of budget costs B = 300 million, 400 million, and 500 million Yuan, respectively, the impact of path deviation distance η on the optimization objective is analyzed. As the path deviation distance η increases from 0 km to 4 km, the total range anxiety and charging costs show a decreasing trend.

     

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