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The optimization of DC fast charging deployment in California

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  • Zhang, Li
  • Shaffer, Brendan
  • Brown, Tim
  • Scott Samuelsen, G.

Abstract

Battery electric vehicles (BEVs) are important for reducing fuel consumption and vehicle operating cost, and have the potential to reduce GHG and pollutant emissions. However, the range limits and long recharging times serve as obstacles to mass deployment. Well planned Level 3 DC fast charging stations are a potential solution to satisfy long distance travel demand instead of an expansive Level 2 non-home charging infrastructure. This paper identifies candidate charging routes and uses freeway exits and highway intersections as approximate candidate charging locations, and consequently solves a set covering problem to minimize the number of charging stations. Results show that 290 Level 3 charging locations are required for the State of California based on the 2000 California Travel Survey and BEVs with 60 mile range. With this optimized station network, electric light duty vehicle miles travelled (VMT) can reach 92% and BEVs can be used by 98% of drivers. If BEVs with 100 or 200 mile range are used, 126 or 31 Level 3 charging locations are required, respectively. This study also assesses the temporal utilization of charging stations. Congestion at several stations suggests extra chargers are required. A reservation system can benefit both the BEV drivers and station operators by reducing the wait times, decreasing the extra chargers needed, and more evenly utilizing all the stations. Related policies are also discussed to better deploy fast charging stations.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:157:y:2015:i:c:p:111-122
    DOI: 10.1016/j.apenergy.2015.07.057
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    References listed on IDEAS

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    Cited by:

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    2. Zenginis, Ioannis & Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2016. "Analysis and quality of service evaluation of a fast charging station for electric vehicles," Energy, Elsevier, vol. 112(C), pages 669-678.
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    5. Ji, Zhenya & Huang, Xueliang, 2018. "Plug-in electric vehicle charging infrastructure deployment of China towards 2020: Policies, methodologies, and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 710-727.
    6. Luo, Lizi & Gu, Wei & Zhou, Suyang & Huang, He & Gao, Song & Han, Jun & Wu, Zhi & Dou, Xiaobo, 2018. "Optimal planning of electric vehicle charging stations comprising multi-types of charging facilities," Applied Energy, Elsevier, vol. 226(C), pages 1087-1099.
    7. Neaimeh, Myriam & Salisbury, Shawn D. & Hill, Graeme A. & Blythe, Philip T. & Scoffield, Don R. & Francfort, James E., 2017. "Analysing the usage and evidencing the importance of fast chargers for the adoption of battery electric vehicles," Energy Policy, Elsevier, vol. 108(C), pages 474-486.
    8. Graham Town & Seyedfoad Taghizadeh & Sara Deilami, 2022. "Review of Fast Charging for Electrified Transport: Demand, Technology, Systems, and Planning," Energies, MDPI, vol. 15(4), pages 1-30, February.
    9. Funke, Simon Árpád & Plötz, Patrick & Wietschel, Martin, 2019. "Invest in fast-charging infrastructure or in longer battery ranges? A cost-efficiency comparison for Germany," Applied Energy, Elsevier, vol. 235(C), pages 888-899.
    10. Pagani, M. & Korosec, W. & Chokani, N. & Abhari, R.S., 2019. "User behaviour and electric vehicle charging infrastructure: An agent-based model assessment," Applied Energy, Elsevier, vol. 254(C).
    11. Cuiyu Kong & Raka Jovanovic & Islam Safak Bayram & Michael Devetsikiotis, 2017. "A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations," Energies, MDPI, vol. 10(5), pages 1-20, May.
    12. Wang, Hua & Zhao, De & Cai, Yutong & Meng, Qiang & Ong, Ghim Ping, 2021. "Taxi trajectory data based fast-charging facility planning for urban electric taxi systems," Applied Energy, Elsevier, vol. 286(C).
    13. Noel, Lance & Papu Carrone, Andrea & Jensen, Anders Fjendbo & Zarazua de Rubens, Gerardo & Kester, Johannes & Sovacool, Benjamin K., 2019. "Willingness to pay for electric vehicles and vehicle-to-grid applications: A Nordic choice experiment," Energy Economics, Elsevier, vol. 78(C), pages 525-534.
    14. Francisco Haces-Fernandez, 2023. "Risk Assessment Framework for Electric Vehicle Charging Station Development in the United States as an Ancillary Service," Energies, MDPI, vol. 16(24), pages 1-17, December.
    15. Forrest, Kate & Mac Kinnon, Michael & Tarroja, Brian & Samuelsen, Scott, 2020. "Estimating the technical feasibility of fuel cell and battery electric vehicles for the medium and heavy duty sectors in California," Applied Energy, Elsevier, vol. 276(C).
    16. 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.
    17. Muratori, Matteo & Elgqvist, Emma & Cutler, Dylan & Eichman, Joshua & Salisbury, Shawn & Fuller, Zachary & Smart, John, 2019. "Technology solutions to mitigate electricity cost for electric vehicle DC fast charging," Applied Energy, Elsevier, vol. 242(C), pages 415-423.
    18. Christos Karolemeas & Stefanos Tsigdinos & Panagiotis G. Tzouras & Alexandros Nikitas & Efthimios Bakogiannis, 2021. "Determining Electric Vehicle Charging Station Location Suitability: A Qualitative Study of Greek Stakeholders Employing Thematic Analysis and Analytical Hierarchy Process," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    19. Motoaki, Yutaka & Shirk, Matthew G., 2017. "Consumer behavioral adaption in EV fast charging through pricing," Energy Policy, Elsevier, vol. 108(C), pages 178-183.
    20. Hassan S. Hayajneh & Xuewei Zhang, 2019. "Evaluation of Electric Vehicle Charging Station Network Planning via a Co-Evolution Approach," Energies, MDPI, vol. 13(1), pages 1-11, December.
    21. Zhang, Tianyang & Pota, Himanshu & Chu, Chi-Cheng & Gadh, Rajit, 2018. "Real-time renewable energy incentive system for electric vehicles using prioritization and cryptocurrency," Applied Energy, Elsevier, vol. 226(C), pages 582-594.
    22. Marcelo Becerra-Rozas & Felipe Cisternas-Caneo & Broderick Crawford & Ricardo Soto & José García & Gino Astorga & Wenceslao Palma, 2022. "Embedded Learning Approaches in the Whale Optimizer to Solve Coverage Combinatorial Problems," Mathematics, MDPI, vol. 10(23), pages 1-18, November.
    23. Noel, Lance & Sovacool, Benjamin K., 2016. "Why Did Better Place Fail?: Range anxiety, interpretive flexibility, and electric vehicle promotion in Denmark and Israel," Energy Policy, Elsevier, vol. 94(C), pages 377-386.
    24. Flores, Robert J. & Shaffer, Brendan P. & Brouwer, Jacob, 2017. "Electricity costs for a Level 3 electric vehicle fueling station integrated with a building," Applied Energy, Elsevier, vol. 191(C), pages 367-384.

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