IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v283y2023ics0360544223018303.html
   My bibliography  Save this article

Identifying charging zones to allocate public charging stations for electric vehicles

Author

Listed:
  • Faustino, Fausta J.
  • Lopes, José Calixto
  • Melo, Joel D.
  • Sousa, Thales
  • Padilha-Feltrin, Antonio
  • Brito, José A.S.
  • Garcia, Claudio O.

Abstract

In recent years, several techniques have been presented in the specialized literature to identify the best location for installing public charging stations, considering the demand for charging the batteries of electric vehicles that travel along the main roads in urban areas. However, in cities with different travel patterns for electric vehicle drivers, such consideration may result in charging equipment serving few electric vehicles during high recharging demand. Thus, planning by zone can determine more chargers per station with greater utilization during the operation of charging stations. For this, this work presents a methodology that uses the concept of a charging zone, defined as a circular geographic space with charging equipment that will satisfy the charging demand of electric vehicles in their surroundings. Identifying the centroids of these zones is formulated as a p-median problem, solved by the Teitz-Bart algorithm to provide more coverage to the demands for electric charging in large urban areas. The proposed methodology was applied in a Brazilian city with approximately 3 million inhabitants to find the spatial distribution of public charging zones, considering six scenarios of the global penetration of electric vehicles. Furthermore, we compared the allocation of the centroids in these zones with the solution determined by commercial geoprocessing software. This comparison shows that the proposal determines a spatial distribution of 10% more of these zones with a load factor closer to 0.5 than the results of the commercial geoprocessing software. More zones with this load factor value contribute to better use of the power distribution network installations. In addition, the proposed methodology finds an average reduction of 319 kW of peak demand in regions with a low flow of electric vehicles to meet their charging needs in each analyzed scenario. This peak-demand reduction may allow less investment in connecting future charging stations to the power distribution network. Therefore, the proposed methodology can help public and private agents to disseminate electric mobility, finding public charging areas with greater utilization of chargers per station during the operation of charging stations.

Suggested Citation

  • Faustino, Fausta J. & Lopes, José Calixto & Melo, Joel D. & Sousa, Thales & Padilha-Feltrin, Antonio & Brito, José A.S. & Garcia, Claudio O., 2023. "Identifying charging zones to allocate public charging stations for electric vehicles," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223018303
    DOI: 10.1016/j.energy.2023.128436
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223018303
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.128436?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. Cilio, Luca & Babacan, Oytun, 2021. "Allocation optimisation of rapid charging stations in large urban areas to support fully electric taxi fleets," Applied Energy, Elsevier, vol. 295(C).
    2. Khardenavis, Amaiya & Hewage, Kasun & Perera, Piyaruwan & Shotorbani, Amin Mohammadpour & Sadiq, Rehan, 2021. "Mobile energy hub planning for complex urban networks: A robust optimization approach," Energy, Elsevier, vol. 235(C).
    3. 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).
    4. Ding, Xuefeng & Gan, Qihong & Shaker, Mir Pasha, 2023. "Optimal management of parking lots as a big data for electric vehicles using internet of things and Long–Short term Memory," Energy, Elsevier, vol. 268(C).
    5. Michael B. Teitz & Polly Bart, 1968. "Heuristic Methods for Estimating the Generalized Vertex Median of a Weighted Graph," Operations Research, INFORMS, vol. 16(5), pages 955-961, October.
    6. S. L. Hakimi, 1964. "Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph," Operations Research, INFORMS, vol. 12(3), pages 450-459, June.
    7. Huang, Xingjun & Lin, Yun & Lim, Ming K. & Zhou, Fuli & Ding, Rui & Zhang, Zusheng, 2022. "Evolutionary dynamics of promoting electric vehicle-charging infrastructure based on public–private partnership cooperation," Energy, Elsevier, vol. 239(PD).
    8. Zhuang, Ran & Jiang, Difei & Wang, Yuan, 2023. "An approach to optimize building area ratios scheme of urban complex in different climatic conditions based on comprehensive energy performance evaluation," Applied Energy, Elsevier, vol. 329(C).
    9. S. L. Hakimi, 1965. "Optimum Distribution of Switching Centers in a Communication Network and Some Related Graph Theoretic Problems," Operations Research, INFORMS, vol. 13(3), pages 462-475, June.
    10. Lin, Jian & Zhong, Xiaoyi & Wang, Jing & Huang, Yuan & Bai, Xuetao & Wang, Xiaonan & Shah, Nilay & Xie, Shan & Zhao, Yingru, 2021. "Relative optimization potential: A novel perspective to address trade-off challenges in urban energy system planning," Applied Energy, Elsevier, vol. 304(C).
    11. Rawan Shabbar & Anemone Kasasbeh & Mohamed M. Ahmed, 2021. "Charging Station Allocation for Electric Vehicle Network Using Stochastic Modeling and Grey Wolf Optimization," Sustainability, MDPI, vol. 13(6), pages 1-20, March.
    12. Rodrigues, João L. & Bolognesi, Hugo M. & Melo, Joel D. & Heymann, Fabian & Soares, F.J., 2019. "Spatiotemporal model for estimating electric vehicles adopters," Energy, Elsevier, vol. 183(C), pages 788-802.
    13. Jack Brimberg & John M. Hodgson, 2011. "Heuristics for Location Models," International Series in Operations Research & Management Science, in: H. A. Eiselt & Vladimir Marianov (ed.), Foundations of Location Analysis, chapter 0, pages 335-355, Springer.
    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. Salman, Muhammad & Caceres-Najarro, Lismer Andres & Seo, Young-Duk & Noh, Youngtae, 2024. "WiSOM: WiFi-enabled self-adaptive system for monitoring the occupancy in smart buildings," Energy, Elsevier, vol. 294(C).

    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. Rolland, Erik & Schilling, David A. & Current, John R., 1997. "An efficient tabu search procedure for the p-Median Problem," European Journal of Operational Research, Elsevier, vol. 96(2), pages 329-342, January.
    2. Vladimir Marianov & Daniel Serra, 2009. "Median problems in networks," Economics Working Papers 1151, Department of Economics and Business, Universitat Pompeu Fabra.
    3. Mark S. Daskin, 2008. "What you should know about location modeling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(4), pages 283-294, June.
    4. K.E. Rosing & C.S. ReVelle, 1997. "Heuristic Concentration and Tabu Search: A Nose to Nose Comparison," Tinbergen Institute Discussion Papers 97-058/3, Tinbergen Institute.
    5. Bell, Michael G.H. & Fonzone, Achille & Polyzoni, Chrisanthi, 2014. "Depot location in degradable transport networks," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 148-161.
    6. Ningchuan Xiao, 2012. "A Parallel Cooperative Hybridization Approach to the p-Median Problem," Environment and Planning B, , vol. 39(4), pages 755-774, August.
    7. T Drezner & Z Drezner & S Salhi, 2006. "A multi-objective heuristic approach for the casualty collection points location problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(6), pages 727-734, June.
    8. Michael Brusco & J Dennis Cradit & Douglas Steinley, 2021. "A comparison of 71 binary similarity coefficients: The effect of base rates," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-19, April.
    9. Schilling, D. A. & Rosing, K. E. & ReVelle, C. S., 2000. "Network distance characteristics that affect computational effort in p-median location problems," European Journal of Operational Research, Elsevier, vol. 127(3), pages 525-536, December.
    10. ReVelle, C. S. & Eiselt, H. A., 2005. "Location analysis: A synthesis and survey," European Journal of Operational Research, Elsevier, vol. 165(1), pages 1-19, August.
    11. Rosing, K. E. & ReVelle, C. S. & Rolland, E. & Schilling, D. A. & Current, J. R., 1998. "Heuristic concentration and Tabu search: A head to head comparison," European Journal of Operational Research, Elsevier, vol. 104(1), pages 93-99, January.
    12. H K Smith & G Laporte & P R Harper, 2009. "Locational analysis: highlights of growth to maturity," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 140-148, May.
    13. Hribar, Michelle & Daskin, Mark S., 1997. "A dynamic programming heuristic for the P-median problem," European Journal of Operational Research, Elsevier, vol. 101(3), pages 499-508, September.
    14. Daniel Serra & Vladimir Marianov, 1996. "The P-median problem in a changing network: The case of Barcelona," Economics Working Papers 180, Department of Economics and Business, Universitat Pompeu Fabra.
    15. ReVelle, C.S. & Eiselt, H.A. & Daskin, M.S., 2008. "A bibliography for some fundamental problem categories in discrete location science," European Journal of Operational Research, Elsevier, vol. 184(3), pages 817-848, February.
    16. Drezner, Tammy & Drezner, Zvi, 2007. "The gravity p-median model," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1239-1251, June.
    17. Rosing, K. E. & ReVelle, C. S., 1997. "Heuristic concentration: Two stage solution construction," European Journal of Operational Research, Elsevier, vol. 97(1), pages 75-86, February.
    18. Antiopi Panteli & Basilis Boutsinas & Ioannis Giannikos, 2021. "On solving the multiple p-median problem based on biclustering," Operational Research, Springer, vol. 21(1), pages 775-799, March.
    19. Daoqin Tong & Alan T. Murray, 2009. "Maximising coverage of spatial demand for service," Papers in Regional Science, Wiley Blackwell, vol. 88(1), pages 85-97, March.
    20. Zhizhu Lai & Qun Yue & Zheng Wang & Dongmei Ge & Yulong Chen & Zhihong Zhou, 2022. "The min-p robust optimization approach for facility location problem under uncertainty," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1134-1160, September.

    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:283:y:2023:i:c:s0360544223018303. 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.