IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v192y2020ics0360544219323503.html
   My bibliography  Save this article

Optimal charging infrastructure planning based on a charging convenience buffer

Author

Listed:
  • Davidov, Sreten

Abstract

In this paper, novelty is finding the optimal mix of charging technology types to be placed at optimal locations with regards to the Time of Convenience limitation acting as a charging convenience buffer of the users’ charging behavior. It constraints the optimization with the preparedness of users to wait when in request for charging and thus effect the optimal charging technology type selection. This paper is a step forward by combining two optimization constraints in providing the charging reliability and convenience needed to engage unlimited mobility of electric vehicles. For that purpose, discrete location model based on set-covering is involved to include electric vehicle users’ behavior reflected by their mobility trajectories, the technology charging times and the wait time required by the users’ when arriving at charging location. To show the general applicability of the model, a discrete 10 × 10 road network is considered. The numeric results show the optimal locations and the charging technology type to be placed. While the charging reliability provided, the part of faster charging technology installed prevails among optimal locations if the charging convenience buffer is shorter and vice-versa for the slower charging technology types.

Suggested Citation

  • Davidov, Sreten, 2020. "Optimal charging infrastructure planning based on a charging convenience buffer," Energy, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:energy:v:192:y:2020:i:c:s0360544219323503
    DOI: 10.1016/j.energy.2019.116655
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219323503
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.116655?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Liu, Jin-peng & Zhang, Teng-xi & Zhu, Jiang & Ma, Tian-nan, 2018. "Allocation optimization of electric vehicle charging station (EVCS) considering with charging satisfaction and distributed renewables integration," Energy, Elsevier, vol. 164(C), pages 560-574.
    3. Davidov, Sreten & Pantoš, Miloš, 2017. "Stochastic expansion planning of the electric-drive vehicle charging infrastructure," Energy, Elsevier, vol. 141(C), pages 189-201.
    4. Davidov, Sreten & Pantoš, Miloš, 2017. "Impact of stochastic driving range on the optimal charging infrastructure expansion planning," Energy, Elsevier, vol. 141(C), pages 603-612.
    5. 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.
    6. Wang, Ying-Wei & Lin, Chuah-Chih, 2013. "Locating multiple types of recharging stations for battery-powered electric vehicle transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 58(C), pages 76-87.
    7. Guo, Fang & Yang, Jun & Lu, Jianyi, 2018. "The battery charging station location problem: Impact of users’ range anxiety and distance convenience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 1-18.
    8. Davidov, Sreten & Pantoš, Miloš, 2017. "Planning of electric vehicle infrastructure based on charging reliability and quality of service," Energy, Elsevier, vol. 118(C), pages 1156-1167.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alan Jenn, 2024. "Charging forward: deploying EV infrastructure for Uber and Lyft in California," Transportation, Springer, vol. 51(5), pages 1663-1678, October.
    2. Jakov Topić & Jure Soldo & Filip Maletić & Branimir Škugor & Joško Deur, 2020. "Virtual Simulation of Electric Bus Fleets for City Bus Transport Electrification Planning," Energies, MDPI, vol. 13(13), pages 1-24, July.
    3. Khaleghikarahrodi, Mehrsa & Macht, Gretchen A., 2023. "Patterns, no patterns, that is the question: Quantifying users’ electric vehicle charging," Transport Policy, Elsevier, vol. 141(C), pages 291-304.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gönül, Ömer & Duman, A. Can & Güler, Önder, 2024. "A comprehensive framework for electric vehicle charging station siting along highways using weighted sum method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    2. Metais, M.O. & Jouini, O. & Perez, Y. & Berrada, J. & Suomalainen, E., 2022. "Too much or not enough? Planning electric vehicle charging infrastructure: A review of modeling options," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    3. 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.
    4. Golsefidi, Atefeh Hemmati & Hüttel, Frederik Boe & Peled, Inon & Samaranayake, Samitha & Pereira, Francisco Câmara, 2023. "A joint machine learning and optimization approach for incremental expansion of electric vehicle charging infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    5. Davidov, Sreten & Pantoš, Miloš, 2019. "Optimization model for charging infrastructure planning with electric power system reliability check," Energy, Elsevier, vol. 166(C), pages 886-894.
    6. Csiszár, Csaba & Csonka, Bálint & Földes, Dávid & Wirth, Ervin & Lovas, Tamás, 2020. "Location optimisation method for fast-charging stations along national roads," Journal of Transport Geography, Elsevier, vol. 88(C).
    7. Verónica Anadón Martínez & Andreas Sumper, 2023. "Planning and Operation Objectives of Public Electric Vehicle Charging Infrastructures: A Review," Energies, MDPI, vol. 16(14), pages 1-41, July.
    8. Anjos, Miguel F. & Gendron, Bernard & Joyce-Moniz, Martim, 2020. "Increasing electric vehicle adoption through the optimal deployment of fast-charging stations for local and long-distance travel," European Journal of Operational Research, Elsevier, vol. 285(1), pages 263-278.
    9. Hosseini, Meysam & MirHassani, S.A., 2015. "Refueling-station location problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 84(C), pages 101-116.
    10. Yıldız, Barış & Arslan, Okan & Karaşan, Oya Ekin, 2016. "A branch and price approach for routing and refueling station location model," European Journal of Operational Research, Elsevier, vol. 248(3), pages 815-826.
    11. Park, Hyunwoo & Lee, Chungmok, 2024. "An exact algorithm for maximum electric vehicle flow coverage problem with heterogeneous chargers, nonlinear charging time and route deviations," European Journal of Operational Research, Elsevier, vol. 315(3), pages 926-951.
    12. Muhammad Shahzad Sardar & Nabila Asghar & Mubbasher Munir & Reda Alhajj & Hafeez ur Rehman, 2022. "Moderation of Services’ EKC through Transportation Competitiveness: PQR Model in Global Prospective," IJERPH, MDPI, vol. 20(1), pages 1-17, December.
    13. Fescioglu-Unver, Nilgun & Yıldız Aktaş, Melike, 2023. "Electric vehicle charging service operations: A review of machine learning applications for infrastructure planning, control, pricing and routing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    14. Scheiper, Barbara & Schiffer, Maximilian & Walther, Grit, 2019. "The flow refueling location problem with load flow control," Omega, Elsevier, vol. 83(C), pages 50-69.
    15. Faping Wang & Rui Chen & Lixin Miao & Peng Yang & Bin Ye, 2019. "Location Optimization of Electric Vehicle Mobile Charging Stations Considering Multi-Period Stochastic User Equilibrium," Sustainability, MDPI, vol. 11(20), pages 1-19, October.
    16. Arslan, Okan & Yıldız, Barış & Karaşan, Oya Ekin, 2015. "Minimum cost path problem for Plug-in Hybrid Electric Vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 123-141.
    17. Vazifeh, Mohammad M. & Zhang, Hongmou & Santi, Paolo & Ratti, Carlo, 2019. "Optimizing the deployment of electric vehicle charging stations using pervasive mobility data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 75-91.
    18. Schiffer, Maximilian & Walther, Grit, 2017. "The electric location routing problem with time windows and partial recharging," European Journal of Operational Research, Elsevier, vol. 260(3), pages 995-1013.
    19. Joonho Ko & Tae-Hyoung Tommy Gim & Randall Guensler, 2017. "Locating refuelling stations for alternative fuel vehicles: a review on models and applications," Transport Reviews, Taylor & Francis Journals, vol. 37(5), pages 551-570, September.
    20. Mubarak, Mamdouh & Üster, Halit & Abdelghany, Khaled & Khodayar, Mohammad, 2021. "Strategic network design and analysis for in-motion wireless charging of electric vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:192:y:2020:i:c:s0360544219323503. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.