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Economic planning of electric vehicle charging stations considering traffic constraints and load profile templates

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  • Xiang, Yue
  • Liu, Junyong
  • Li, Ran
  • Li, Furong
  • Gu, Chenghong
  • Tang, Shuoya

Abstract

This paper develops a novel solution to integrate electric vehicles and optimally determine the siting and sizing of charging stations (CSs), considering the interactions between power and transportation industries. Firstly, the origin–destination (OD) traffic flow data is optimally assigned to the transportation network, which is then utilized to determine the capacity of charging stations. Secondly, the charging demand of charging infrastructures is integrated into a cost-based model to evaluate the economics of candidate plans. Furthermore, load capability constraints are proposed to evaluate whether the candidate CSs deployment and tie line plans could be adopted. Different scenarios generated by load profile templates are innovatively integrated into the economic planning model to deal with uncertain operational states. The models and framework are demonstrated and verified by a test case, which offers a perspective for effectively realizing optimal planning of the CSs considering the constraints from both transportation and distribution networks.

Suggested Citation

  • Xiang, Yue & Liu, Junyong & Li, Ran & Li, Furong & Gu, Chenghong & Tang, Shuoya, 2016. "Economic planning of electric vehicle charging stations considering traffic constraints and load profile templates," Applied Energy, Elsevier, vol. 178(C), pages 647-659.
    • Handle: RePEc:eee:appene:v:178:y:2016:i:c:p:647-659
    DOI: 10.1016/j.apenergy.2016.06.021
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    References listed on IDEAS

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    1. Sadeghi-Barzani, Payam & Rajabi-Ghahnavieh, Abbas & Kazemi-Karegar, Hosein, 2014. "Optimal fast charging station placing and sizing," Applied Energy, Elsevier, vol. 125(C), pages 289-299.
    2. Iversen, Emil B. & Morales, Juan M. & Madsen, Henrik, 2014. "Optimal charging of an electric vehicle using a Markov decision process," Applied Energy, Elsevier, vol. 123(C), pages 1-12.
    3. Guo, Sen & Zhao, Huiru, 2015. "Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective," Applied Energy, Elsevier, vol. 158(C), pages 390-402.
    4. Mu, Yunfei & Wu, Jianzhong & Jenkins, Nick & Jia, Hongjie & Wang, Chengshan, 2014. "A Spatial–Temporal model for grid impact analysis of plug-in electric vehicles," Applied Energy, Elsevier, vol. 114(C), pages 456-465.
    5. Zhang, Li & Shaffer, Brendan & Brown, Tim & Scott Samuelsen, G., 2015. "The optimization of DC fast charging deployment in California," Applied Energy, Elsevier, vol. 157(C), pages 111-122.
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