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Analysis and quality of service evaluation of a fast charging station for electric vehicles

Author

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  • Zenginis, Ioannis
  • Vardakas, John S.
  • Zorba, Nizar
  • Verikoukis, Christos V.

Abstract

Electrification of transportation is considered as one of the most promising ways to mitigate climate change and reduce national security risks from oil and gasoline imports. Fast charging stations that provide high quality of service will facilitate the wide market penetration of electric vehicles. In this paper, the operation of a fast charging station is analyzed by employing a novel queuing model. The proposed analysis considers that the various electric vehicle models are classified by their battery size, and computes the customers' mean waiting time in the queue by taking into account the available charging spots, as well as the stochastic arrival process and the stochastic recharging needs of the various electric vehicle classes. Furthermore, a charging strategy is proposed according to which the drivers are motivated to limit their energy demands. The implementation of the proposed strategy allows the charging station to serve more customers without any increase in the queue waiting time. The high precision of the present analytical model is confirmed through simulations. Therefore, it may be utilized by existing fast charging station operators that need to provide high quality of service, or by future investors that need to design an efficient installation.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:112:y:2016:i:c:p:669-678
    DOI: 10.1016/j.energy.2016.06.066
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Yue & Zhang, Qi & Farnoosh, Arash & Chen, Siyuan & Li, Yan, 2019. "GIS-Based Multi-Objective Particle Swarm Optimization of charging stations for electric vehicles," Energy, Elsevier, vol. 169(C), pages 844-853.
    3. Rajeshkumar Ramraj & Ehsan Pashajavid & Sanath Alahakoon & Shantha Jayasinghe, 2023. "Quality of Service and Associated Communication Infrastructure for Electric Vehicles," Energies, MDPI, vol. 16(20), pages 1-28, October.
    4. Zhao, Zhonghao & Lee, Carman K.M. & Huo, Jiage, 2023. "EV charging station deployment on coupled transportation and power distribution networks via reinforcement learning," Energy, Elsevier, vol. 267(C).
    5. Motoaki, Yutaka & Yi, Wenqi & Salisbury, Shawn, 2018. "Empirical analysis of electric vehicle fast charging under cold temperatures," Energy Policy, Elsevier, vol. 122(C), pages 162-168.
    6. Qingyou Yan & Hua Dong & Meijuan Zhang, 2021. "Service Evaluation of Electric Vehicle Charging Station: An Application of Improved Matter-Element Extension Method," Sustainability, MDPI, vol. 13(14), pages 1-25, July.
    7. Salman, Waleed & Qi, Lingfei & Zhu, Xin & Pan, Hongye & Zhang, Xingtian & Bano, Shehar & Zhang, Zutao & Yuan, Yanping, 2018. "A high-efficiency energy regenerative shock absorber using helical gears for powering low-wattage electrical device of electric vehicles," Energy, Elsevier, vol. 159(C), pages 361-372.
    8. 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.
    9. Partha Mishra & Eric Miller & Shriram Santhanagopalan & Kevin Bennion & Andrew Meintz, 2022. "A Framework to Analyze the Requirements of a Multiport Megawatt-Level Charging Station for Heavy-Duty Electric Vehicles," Energies, MDPI, vol. 15(10), pages 1-18, May.
    10. Shi You & Junjie Hu & Charalampos Ziras, 2016. "An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †," Energies, MDPI, vol. 9(11), pages 1-18, November.
    11. Zhang, Lihui & Zhao, Zhenli & Yang, Meng & Li, Songrui, 2020. "A multi-criteria decision method for performance evaluation of public charging service quality," Energy, Elsevier, vol. 195(C).
    12. Jianmin Dang & Xiaozhen Wang & Ying Xie & Ziyi Fu, 2023. "The Location Optimization of Urban Shared New Energy Vehicles Based on P-Median Model: The Example of Xuzhou City, China," Sustainability, MDPI, vol. 15(12), pages 1-16, June.
    13. Motoaki, Yutaka & Shirk, Matthew G., 2017. "Consumer behavioral adaption in EV fast charging through pricing," Energy Policy, Elsevier, vol. 108(C), pages 178-183.
    14. Zenginis, Ioannis & Vardakas, John S. & Echave, Cynthia & Morató, Moisés & Abadal, Jordi & Verikoukis, Christos V., 2017. "Cooperation in microgrids through power exchange: An optimal sizing and operation approach," Applied Energy, Elsevier, vol. 203(C), pages 972-981.
    15. Amin Aghalari & Darweesh Ehssan Salamah & Carlos Marino & Mohammad Marufuzzaman, 2023. "Electric vehicles fast charger location-routing problem under ambient temperature," Annals of Operations Research, Springer, vol. 324(1), pages 721-759, May.

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