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From user to operator: Rationalizing the charging infrastructure deployment. A case study of Berlin

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  • Metais, M.O.
  • Jouini, O.
  • Perez, Y.
  • Berrada, J.

Abstract

The urge to develop greener transportation necessitates a shift from internal combustion engine vehicles to electric vehicles (EVs). Ensuring user acceptance of EVs through adequate charging infrastructure is crucial for this transition. We hypothesize that a user-oriented, time and space-coherent deployment of charging stations can reduce range anxiety and enhance EV adoption. We present a new multi-criteria deployment model and apply it through a MATSim multi-agent simulation to the Berlin region, observing the effects of different user behaviors on the charging infrastructure deployment. Results indicate that slow chargers are more cost-efficient and that residential charging is vital for user acceptance of EVs. The study concludes that a well-planned deployment schedule significantly reduces range anxiety and supports a coherent charging infrastructure helping EV democratization.

Suggested Citation

  • Metais, M.O. & Jouini, O. & Perez, Y. & Berrada, J., 2024. "From user to operator: Rationalizing the charging infrastructure deployment. A case study of Berlin," Applied Energy, Elsevier, vol. 376(PB).
  • Handle: RePEc:eee:appene:v:376:y:2024:i:pb:s0306261924015162
    DOI: 10.1016/j.apenergy.2024.124133
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    References listed on IDEAS

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    1. 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.
    2. Wang, Ying-Wei & Wang, Chuan-Ren, 2010. "Locating passenger vehicle refueling stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(5), pages 791-801, September.
    3. Wang, Hua & Zhao, De & Meng, Qiang & Ong, Ghim Ping & Lee, Der-Horng, 2019. "A four-step method for electric-vehicle charging facility deployment in a dense city: An empirical study in Singapore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 224-237.
    4. Nathan Delacrétaz & Bruno Lanz & Jeremy van Dijk, 2020. "The chicken or the egg: Technology adoption and network infrastructure in the market for electric vehicles," IRENE Working Papers 20-08, IRENE Institute of Economic Research.
    5. Ahmad Almaghrebi & Fares Aljuheshi & Mostafa Rafaie & Kevin James & Mahmoud Alahmad, 2020. "Data-Driven Charging Demand Prediction at Public Charging Stations Using Supervised Machine Learning Regression Methods," Energies, MDPI, vol. 13(16), pages 1-21, August.
    6. Troy R. Hawkins & Bhawna Singh & Guillaume Majeau‐Bettez & Anders Hammer Strømman, 2013. "Comparative Environmental Life Cycle Assessment of Conventional and Electric Vehicles," Journal of Industrial Ecology, Yale University, vol. 17(1), pages 53-64, February.
    7. Upchurch, Christopher & Kuby, Michael, 2010. "Comparing the p-median and flow-refueling models for locating alternative-fuel stations," Journal of Transport Geography, Elsevier, vol. 18(6), pages 750-758.
    8. Cavadas, Joana & Homem de Almeida Correia, Gonçalo & Gouveia, João, 2015. "A MIP model for locating slow-charging stations for electric vehicles in urban areas accounting for driver tours," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 188-201.
    9. Sanchari Deb & Kari Tammi & Karuna Kalita & Pinakeswar Mahanta, 2018. "Review of recent trends in charging infrastructure planning for electric vehicles," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 7(6), November.
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