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Electric Vehicles Charging Infrastructure Demand and Deployment: Challenges and Solutions

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  • Praveen Prakash Singh

    (Electrical Engineering Department, Tallinn University of Technology (TalTech), 12616 Tallinn, Estonia)

  • Fushuan Wen

    (Electrical Engineering Department, Tallinn University of Technology (TalTech), 12616 Tallinn, Estonia)

  • Ivo Palu

    (Electrical Engineering Department, Tallinn University of Technology (TalTech), 12616 Tallinn, Estonia)

  • Sulabh Sachan

    (Electrical Engineering Department, GLA University, Mathura 281406, India)

  • Sanchari Deb

    (School of Power and Control, University of Warwick, Coventry CV4 7AL, UK)

Abstract

Present trends indicate that electrical vehicles (EVs) are favourable technology for road network transportation. The lack of easily accessible charging stations will be a negative growth driver for EV adoption. Consequently, the charging station placement and scheduling of charging activity have gained momentum among researchers all over the world. Different planning and scheduling models have been proposed in the literature. Each model is unique and has both advantages and disadvantages. Moreover, the performance of the models also varies and is location specific. A model suitable for a developing country may not be appropriate for a developed country and vice versa. This paper provides a classification and overview of charging station placement and charging activity scheduling as well as the global scenario of charging infrastructure planning. Further, this work provides the challenges and solutions to the EV charging infrastructure demand and deployment. The recommendations and future scope of EV charging infrastructure are also highlighted in this paper.

Suggested Citation

  • Praveen Prakash Singh & Fushuan Wen & Ivo Palu & Sulabh Sachan & Sanchari Deb, 2022. "Electric Vehicles Charging Infrastructure Demand and Deployment: Challenges and Solutions," Energies, MDPI, vol. 16(1), pages 1-21, December.
  • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:7-:d:1008697
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    References listed on IDEAS

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    1. He, Fang & Wu, Di & Yin, Yafeng & Guan, Yongpei, 2013. "Optimal deployment of public charging stations for plug-in hybrid electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 47(C), pages 87-101.
    2. Rahman, Imran & Vasant, Pandian M. & Singh, Balbir Singh Mahinder & Abdullah-Al-Wadud, M. & Adnan, Nadia, 2016. "Review of recent trends in optimization techniques for plug-in hybrid, and electric vehicle charging infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1039-1047.
    3. Sanchari Deb & Xiao-Zhi Gao, 2022. "Prediction of Charging Demand of Electric City Buses of Helsinki, Finland by Random Forest," Energies, MDPI, vol. 15(10), pages 1-18, May.
    4. 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.
    5. Hoarau, Quentin & Perez, Yannick, 2018. "Interactions between electric mobility and photovoltaic generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 510-522.
    6. Shepero, Mahmoud & Munkhammar, Joakim & Widén, Joakim & Bishop, Justin D.K. & Boström, Tobias, 2018. "Modeling of photovoltaic power generation and electric vehicles charging on city-scale: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 61-71.
    7. Tao, Ye & Huang, Miaohua & Yang, Lan, 2018. "Data-driven optimized layout of battery electric vehicle charging infrastructure," Energy, Elsevier, vol. 150(C), pages 735-744.
    8. Chen, Zhibin & He, Fang & Yin, Yafeng, 2016. "Optimal deployment of charging lanes for electric vehicles in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 344-365.
    9. Sanchari Deb & Kari Tammi & Karuna Kalita & Pinakeshwar Mahanta, 2018. "Impact of Electric Vehicle Charging Station Load on Distribution Network," Energies, MDPI, vol. 11(1), pages 1-25, January.
    10. Rogge, Matthias & van der Hurk, Evelien & Larsen, Allan & Sauer, Dirk Uwe, 2018. "Electric bus fleet size and mix problem with optimization of charging infrastructure," Applied Energy, Elsevier, vol. 211(C), pages 282-295.
    11. Kester, Johannes & Noel, Lance & Zarazua de Rubens, Gerardo & Sovacool, Benjamin K., 2018. "Policy mechanisms to accelerate electric vehicle adoption: A qualitative review from the Nordic region," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 719-731.
    12. Jorge García Álvarez & Miguel Ángel González & Camino Rodríguez Vela & Ramiro Varela, 2018. "Electric Vehicle Charging Scheduling by an Enhanced Artificial Bee Colony Algorithm," Energies, MDPI, vol. 11(10), pages 1-19, October.
    13. Chao Luo & Yih-Fang Huang & Vijay Gupta, 2018. "Dynamic Pricing and Energy Management Strategy for EV Charging Stations under Uncertainties," Papers 1801.02783, arXiv.org.
    14. Xie, Fei & Liu, Changzheng & Li, Shengyin & Lin, Zhenhong & Huang, Yongxi, 2018. "Long-term strategic planning of inter-city fast charging infrastructure for battery electric vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 261-276.
    15. 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.
    16. Jian, Linni & Zheng, Yanchong & Shao, Ziyun, 2017. "High efficient valley-filling strategy for centralized coordinated charging of large-scale electric vehicles," Applied Energy, Elsevier, vol. 186(P1), pages 46-55.
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