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Optimization of Electric Vehicle Charging Points Based on Efficient Use of Chargers and Providing Private Charging Spaces

Author

Listed:
  • Lukáš Dvořáček

    (Department of Economics, Management and Humanities, Faculty of Electrical Engineering, Czech Technical University in Prague, 16627 Prague, Czech Republic)

  • Martin Horák

    (Department of Economics, Management and Humanities, Faculty of Electrical Engineering, Czech Technical University in Prague, 16627 Prague, Czech Republic)

  • Michaela Valentová

    (Department of Economics, Management and Humanities, Faculty of Electrical Engineering, Czech Technical University in Prague, 16627 Prague, Czech Republic)

  • Jaroslav Knápek

    (Department of Economics, Management and Humanities, Faculty of Electrical Engineering, Czech Technical University in Prague, 16627 Prague, Czech Republic)

Abstract

Electric vehicles are a mobility innovation that can help significantly reduce greenhouse gas emissions and mitigate climate change. However, increasing numbers of electric vehicles require the construction of a dense charging infrastructure with a sufficient number of chargers. Based on the identified requirements for existing electric vehicle users and potential new customers, the paper proposes a charging point model for an urban area equipped with a local transformer station and a sufficient number of low-power chargers. In particular, the model focuses on efficient use of chargers throughout the day, considering private rental of chargers paid by residents in the evening. The model uses an optimization method that compares the non-covered fixed costs due to unsold electricity to nonresidents and the annualized costs of building an additional transformer. The proposed optimal charging point solution was tested in a case study using real data capturing users’ habits and their arrivals in and departures from the car park. As our model results show, the great benefit of a park-and-ride car park equipped with chargers consists of a simple increase in car park efficiency, ensuring sufficient numbers of private charging lots, optimizing operating costs, and supporting the development of electromobility.

Suggested Citation

  • Lukáš Dvořáček & Martin Horák & Michaela Valentová & Jaroslav Knápek, 2020. "Optimization of Electric Vehicle Charging Points Based on Efficient Use of Chargers and Providing Private Charging Spaces," Energies, MDPI, vol. 13(24), pages 1-28, December.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6750-:d:465887
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    References listed on IDEAS

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    1. Lopez-Behar, Diana & Tran, Martino & Froese, Thomas & Mayaud, Jerome R. & Herrera, Omar E. & Merida, Walter, 2019. "Charging infrastructure for electric vehicles in Multi-Unit Residential Buildings: Mapping feedbacks and policy recommendations," Energy Policy, Elsevier, vol. 126(C), pages 444-451.
    2. Taljegard, M. & Göransson, L. & Odenberger, M. & Johnsson, F., 2019. "Impacts of electric vehicles on the electricity generation portfolio – A Scandinavian-German case study," Applied Energy, Elsevier, vol. 235(C), pages 1637-1650.
    3. Ruijiu Jin & Xiangfeng Zhang & Zhijie Wang & Wengang Sun & Xiaoxin Yang & Zhong Shi, 2019. "RETRACTED: Blockchain-Enabled Charging Right Trading Among EV Charging Stations," Energies, MDPI, vol. 12(20), pages 1, October.
    4. Pareschi, Giacomo & Küng, Lukas & Georges, Gil & Boulouchos, Konstantinos, 2020. "Are travel surveys a good basis for EV models? Validation of simulated charging profiles against empirical data," Applied Energy, Elsevier, vol. 275(C).
    5. Yue Zhang & Qi Zhang & Arash Farnoosh & Siyuan Chen & Yan Li, 2019. "GIS-Based Multi-Objective Particle Swarm Optimization of charging stations for electric vehicles," Post-Print hal-02009151, HAL.
    6. Xu, Fangyuan & Chen, Xujie & Zhang, Miao & Zhou, Ya & Cai, Yanpeng & Zhou, Yang & Tang, Ruixin & Wang, Yifei, 2020. "A sharing economy market system for private EV parking with consideration of demand side management," Energy, Elsevier, vol. 190(C).
    7. Yanyan Xu & Serdar Çolak & Emre C. Kara & Scott J. Moura & Marta C. González, 2018. "Planning for electric vehicle needs by coupling charging profiles with urban mobility," Nature Energy, Nature, vol. 3(6), pages 484-493, June.
    8. Xiao, Haohan & Xu, Meng & Yang, Hai, 2020. "Pricing strategies for shared parking management with double auction approach: Differential price vs. uniform price," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    9. Xin Huang & Xueqin Long & Jianjun Wang & Lan He, 2020. "Research on parking sharing strategies considering user overtime parking," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-22, June.
    10. 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.
    11. Patt, Anthony & Aplyn, David & Weyrich, Philippe & van Vliet, Oscar, 2019. "Availability of private charging infrastructure influences readiness to buy electric cars," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 1-7.
    12. Mark Friesen & Giuliano Mingardo, 2020. "Is Parking in Europe Ready for Dynamic Pricing? A Reality Check for the Private Sector," Sustainability, MDPI, vol. 12(7), pages 1-11, March.
    13. Yifei Cai & Jun Chen & Chu Zhang & Bin Wang, 2018. "A Parking Space Allocation Method to Make a Shared Parking Strategy for Appertaining Parking Lots of Public Buildings," Sustainability, MDPI, vol. 11(1), pages 1-20, December.
    14. 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.
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