IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i13p7566-d844063.html
   My bibliography  Save this article

Application of Clustering Algorithms in the Location of Electric Taxi Charging Stations

Author

Listed:
  • Qing Li

    (College of Mathematics and System, Shandong University of Science and Technology, Qingdao 266590, China)

  • Xue Li

    (College of Mathematics and System, Shandong University of Science and Technology, Qingdao 266590, China)

  • Zuyu Liu

    (College of Mathematics and System, Shandong University of Science and Technology, Qingdao 266590, China)

  • Yaping Qi

    (College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China)

Abstract

The reasonable layout of charging stations is an important measure to improve the penetration rate of the electric taxi market. Based on the multi-type clustering algorithm, a widely applicable electric taxi charging stations locating method is proposed. By analyzing the massive gasoline taxi GPS trajectory data, the parking information and charging requirements of electric taxis are extracted, and the research area is divided into reasonable grids. Then, the divided grids are respectively subjected to multiple same-type clustering and multiple multi-type clustering algorithms, so as to help find out the location of the charging station, and a comparative analysis is performed. The empirical analysis shows that the positioning results of the multiple multi-type clustering algorithms are more reasonable than the multiple same-type clustering algorithms, which can effectively prolong the driving distance of electric taxis and save the travel time of drivers.

Suggested Citation

  • Qing Li & Xue Li & Zuyu Liu & Yaping Qi, 2022. "Application of Clustering Algorithms in the Location of Electric Taxi Charging Stations," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7566-:d:844063
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/13/7566/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/13/7566/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Suganya, S. & Raja, S. Charles & Venkatesh, P., 2017. "Simultaneous coordination of distinct plug-in Hybrid Electric Vehicle charging stations: A modified Particle Swarm Optimization approach," Energy, Elsevier, vol. 138(C), pages 92-102.
    2. Apostolaki-Iosifidou, Elpiniki & Codani, Paul & Kempton, Willett, 2017. "Measurement of power loss during electric vehicle charging and discharging," Energy, Elsevier, vol. 127(C), pages 730-742.
    3. 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.
    4. Ruifeng Shi & Jiahua Liu & Zhenhong Liao & Li Niu & Eke Ibrahim & Fang Fu, 2019. "An Electric Taxi Charging Station Planning Scheme Based on an Improved Destination Choice Method," Energies, MDPI, vol. 12(19), pages 1-21, October.
    5. Gilanifar, Mostafa & Parvania, Masood, 2021. "Clustered multi-node learning of electric vehicle charging flexibility," Applied Energy, Elsevier, vol. 282(PB).
    6. Danny García Sánchez & Alejandra Tabares & Lucas Teles Faria & Juan Carlos Rivera & John Fredy Franco, 2022. "A Clustering Approach for the Optimal Siting of Recharging Stations in the Electric Vehicle Routing Problem with Time Windows," Energies, MDPI, vol. 15(7), pages 1-19, March.
    7. Xu, Min & Meng, Qiang, 2020. "Optimal deployment of charging stations considering path deviation and nonlinear elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 135(C), pages 120-142.
    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. Wilfredo F. Yushimito & Sebastian Moreno & Daniela Miranda, 2023. "The Potential of Battery Electric Taxis in Santiago de Chile," Sustainability, MDPI, vol. 15(11), pages 1-15, May.

    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. 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).
    2. Miao, Hongzhi & Jia, Hongfei & Li, Jiangchen & Qiu, Tony Z., 2019. "Autonomous connected electric vehicle (ACEV)-based car-sharing system modeling and optimal planning: A unified two-stage multi-objective optimization methodology," Energy, Elsevier, vol. 169(C), pages 797-818.
    3. 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.
    4. Jin, Ruiyang & Zhou, Yuke & Lu, Chao & Song, Jie, 2022. "Deep reinforcement learning-based strategy for charging station participating in demand response," Applied Energy, Elsevier, vol. 328(C).
    5. Ghotge, Rishabh & van Wijk, Ad & Lukszo, Zofia, 2021. "Off-grid solar charging of electric vehicles at long-term parking locations," Energy, Elsevier, vol. 227(C).
    6. Shafqat Jawad & Junyong Liu, 2020. "Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends," Energies, MDPI, vol. 13(13), pages 1-24, July.
    7. Raja S, Charles & Kumar N M, Vijaya & J, Senthil kumar & Nesamalar J, Jeslin Drusila, 2021. "Enhancing system reliability by optimally integrating PHEV charging station and renewable distributed generators: A Bi-Level programming approach," Energy, Elsevier, vol. 229(C).
    8. Oluwasola O. Ademulegun & Paul MacArtain & Bukola Oni & Neil J. Hewitt, 2022. "Multi-Stage Multi-Criteria Decision Analysis for Siting Electric Vehicle Charging Stations within and across Border Regions," Energies, MDPI, vol. 15(24), pages 1-28, December.
    9. Milan Straka & Pasquale De Falco & Gabriella Ferruzzi & Daniela Proto & Gijs van der Poel & Shahab Khormali & v{L}ubov{s} Buzna, 2019. "Predicting popularity of EV charging infrastructure from GIS data," Papers 1910.02498, arXiv.org.
    10. Alexandre F. M. Correia & Pedro Moura & Aníbal T. de Almeida, 2022. "Technical and Economic Assessment of Battery Storage and Vehicle-to-Grid Systems in Building Microgrids," Energies, MDPI, vol. 15(23), pages 1-23, November.
    11. Jianxin Qin & Jing Qiu & Yating Chen & Tao Wu & Longgang Xiang, 2022. "Charging Stations Selection Using a Graph Convolutional Network from Geographic Grid," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    12. Amaro García-Suárez & José-Luis Guisado-Lizar & Fernando Diaz-del-Rio & Francisco Jiménez-Morales, 2021. "A Cellular Automata Agent-Based Hybrid Simulation Tool to Analyze the Deployment of Electric Vehicle Charging Stations," Sustainability, MDPI, vol. 13(10), pages 1-14, May.
    13. Rémy Cleenwerck & Hakim Azaioud & Majid Vafaeipour & Thierry Coosemans & Jan Desmet, 2023. "Impact Assessment of Electric Vehicle Charging in an AC and DC Microgrid: A Comparative Study," Energies, MDPI, vol. 16(7), pages 1-17, April.
    14. Robin Smit & Daniel William Kennedy, 2022. "Greenhouse Gas Emissions Performance of Electric and Fossil-Fueled Passenger Vehicles with Uncertainty Estimates Using a Probabilistic Life-Cycle Assessment," Sustainability, MDPI, vol. 14(6), pages 1-29, March.
    15. Kang Miao Tan & Vigna K. Ramachandaramurthy & Jia Ying Yong & Sanjeevikumar Padmanaban & Lucian Mihet-Popa & Frede Blaabjerg, 2017. "Minimization of Load Variance in Power Grids—Investigation on Optimal Vehicle-to-Grid Scheduling," Energies, MDPI, vol. 10(11), pages 1-21, November.
    16. Pirouzi, Sasan & Aghaei, Jamshid & Niknam, Taher & Shafie-khah, Miadreza & Vahidinasab, Vahid & Catalão, João P.S., 2017. "Two alternative robust optimization models for flexible power management of electric vehicles in distribution networks," Energy, Elsevier, vol. 141(C), pages 635-651.
    17. Hoarau, Quentin & Perez, Yannick, 2018. "Interactions between electric mobility and photovoltaic generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 510-522.
    18. Rishabh Ghotge & Yitzhak Snow & Samira Farahani & Zofia Lukszo & Ad van Wijk, 2020. "Optimized Scheduling of EV Charging in Solar Parking Lots for Local Peak Reduction under EV Demand Uncertainty," Energies, MDPI, vol. 13(5), pages 1-18, March.
    19. 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).
    20. Xie, Fei & Lin, Zhenhong, 2021. "Integrated U.S. nationwide corridor charging infrastructure planning for mass electrification of inter-city trips," Applied Energy, Elsevier, vol. 298(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:gam:jsusta:v:14:y:2022:i:13:p:7566-:d:844063. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.