IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v632y2023ip1s0378437123008841.html
   My bibliography  Save this article

Optimizing the configuration of electric vehicle charging piles in public parking lots based on a multi-agent model

Author

Listed:
  • Mei, Zhenyu
  • Que, Zuchen
  • Qiu, Hai
  • Zhu, Zheng
  • Cai, Zhengyi

Abstract

With the rapid development of electric vehicles, how to improve the charging efficiency of electric vehicles has become a challenge. The Chinese government has made great efforts to build charging piles. At present, the most popular construction mode is to build charging piles on a fixed proportion of spaces in existing parking lots. The proportions of charging piles recommended by the government, which is known as a one-size-fits-all strategy. Challenges have arisen with the growth of electric vehicles, such as how to keep hot charging piles from overheating. This paper mainly simulates the actual demand and optimizes the configuration of charging piles to reduce the uneven spatial distribution of charging demand, to improve the overall utilization efficiency of regional charging stations. In particular, based on agent-based simulation technology, a multi-agent system of the road network, vehicles, and charging stations is constructed to simulate the charging behavior in the mixed scenario of electric vehicles and traditional fuel vehicles. The optimization model aims to design the configuration of charging piles to minimize the sum of electric vehicle queueing time, gasoline vehicle queueing time, and vehicle transfer time to idle parking lots. The model is solved by the genetic algorithm. This paper takes the Wulin Square business district in Hangzhou as a real-world example. The simulation results show that by optimizing the number of charging piles, the objective function is reduced by 17.1% compared with the initial number of charging piles, which effectively improves the operation efficiency of the parking system. To this end, this paper predicts the electric vehicle charging demand in the city and optimizes the configuration of charging facilities, which is conducive to maximizing social benefits in the transportation system and has good practical engineering application value.

Suggested Citation

  • Mei, Zhenyu & Que, Zuchen & Qiu, Hai & Zhu, Zheng & Cai, Zhengyi, 2023. "Optimizing the configuration of electric vehicle charging piles in public parking lots based on a multi-agent model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    • Handle: RePEc:eee:phsmap:v:632:y:2023:i:p1:s0378437123008841
    DOI: 10.1016/j.physa.2023.129329
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123008841
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2023.129329?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. Ho-Yin Mak & Ying Rong & Zuo-Jun Max Shen, 2013. "Infrastructure Planning for Electric Vehicles with Battery Swapping," Management Science, INFORMS, vol. 59(7), pages 1557-1575, July.
    2. Habich-Sobiegalla, Sabrina & Kostka, Genia & Anzinger, Niklas, 2019. "Citizens’ electric vehicle purchase intentions in China: An analysis of micro-level and macro-level factors," Transport Policy, Elsevier, vol. 79(C), pages 223-233.
    3. Zhang, Xingping & Liang, Yanni & Yu, Enhai & Rao, Rao & Xie, Jian, 2017. "Review of electric vehicle policies in China: Content summary and effect analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 698-714.
    4. Mei, Zhenyu & Feng, Chi & Ding, Wenchao & Zhang, Lihui & Wang, Dianhai, 2019. "Better lucky than rich? Comparative analysis of parking reservation and parking charge," Transport Policy, Elsevier, vol. 75(C), pages 47-56.
    5. Thompson, Russell G. & Richardson, Anthony J., 1998. "A Parking Search Model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(3), pages 159-170, April.
    Full references (including those not matched with items on IDEAS)

    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. Wen, W. & Yang, S. & Zhou, P. & Gao, S.Z., 2021. "Impacts of COVID-19 on the electric vehicle industry: Evidence from China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    2. Liang, Yanni & Cai, Hua & Zou, Guilin, 2021. "Configuration and system operation for battery swapping stations in Beijing," Energy, Elsevier, vol. 214(C).
    3. Lee, Chungmok & Han, Jinil, 2017. "Benders-and-Price approach for electric vehicle charging station location problem under probabilistic travel range," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 130-152.
    4. Xiong, Siqin & Yuan, Yi & Yao, Jia & Bai, Bo & Ma, Xiaoming, 2023. "Exploring consumer preferences for electric vehicles based on the random coefficient logit model," Energy, Elsevier, vol. 263(PA).
    5. Huang, Youlin & Qian, Lixian, 2021. "Consumer adoption of electric vehicles in alternative business models," Energy Policy, Elsevier, vol. 155(C).
    6. Zhang, Xinying & Pitera, Kelly & Wang, Yuanqing, 2024. "Exploring parking choices under the coexistence of autonomous and conventional vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    7. Bergantino, Angela Stefania & De Carlo, Angela & Morone, Andrea, 2015. "Individuals’ behaviour with respect to parking alternatives: a laboratory experiment," MPRA Paper 63815, University Library of Munich, Germany.
    8. Wang, Jiaxing & Matsumoto, Shigeru, 2022. "Can subsidy programs lead consumers to select “greener” products?: Evidence from the Eco-car program in Japan," Research in Transportation Economics, Elsevier, vol. 91(C).
    9. Yang, Jun & Guo, Fang & Zhang, Min, 2017. "Optimal planning of swapping/charging station network with customer satisfaction," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 174-197.
    10. Shuaian Wang & Dan Zhuge & Lu Zhen & Chung-Yee Lee, 2021. "Liner Shipping Service Planning Under Sulfur Emission Regulations," Transportation Science, INFORMS, vol. 55(2), pages 491-509, March.
    11. Sun, Hao & Yang, Jun & Yang, Chao, 2019. "A robust optimization approach to multi-interval location-inventory and recharging planning for electric vehicles," Omega, Elsevier, vol. 86(C), pages 59-75.
    12. Liu, Chang & Liu, Yuan & Zhang, Dayong & Xie, Chunping, 2022. "The capital market responses to new energy vehicle (NEV) subsidies: An event study on China," Energy Economics, Elsevier, vol. 105(C).
    13. Srinivas, Sharan & Ramachandiran, Surya & Rajendran, Suchithra, 2022. "Autonomous robot-driven deliveries: A review of recent developments and future directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    14. Wang, Ning & Tang, Linhao & Zhang, Wenjian & Guo, Jiahui, 2019. "How to face the challenges caused by the abolishment of subsidies for electric vehicles in China?," Energy, Elsevier, vol. 166(C), pages 359-372.
    15. Oleg Bazaluk & Valerii Havrysh & Vitalii Nitsenko & Tomas Baležentis & Dalia Streimikiene & Elena A. Tarkhanova, 2020. "Assessment of Green Methanol Production Potential and Related Economic and Environmental Benefits: The Case of China," Energies, MDPI, vol. 13(12), pages 1-25, June.
    16. Hsieh, I-Yun Lisa & Pan, Menghsuan Sam & Chiang, Yet-Ming & Green, William H., 2019. "Learning only buys you so much: Practical limits on battery price reduction," Applied Energy, Elsevier, vol. 239(C), pages 218-224.
    17. Hsieh, I-Yun Lisa & Pan, Menghsuan Sam & Green, William H., 2020. "Transition to electric vehicles in China: Implications for private motorization rate and battery market," Energy Policy, Elsevier, vol. 144(C).
    18. Shaohua Cui & Hui Zhao & Cuiping Zhang, 2018. "Locating Charging Stations of Various Sizes with Different Numbers of Chargers for Battery Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-22, November.
    19. Micha Kahlen & Karsten Schroer & Wolfgang Ketter & Alok Gupta, 2024. "Smart Markets for Real-Time Allocation of Multiproduct Resources: The Case of Shared Electric Vehicles," Information Systems Research, INFORMS, vol. 35(2), pages 871-889, June.
    20. Nie, Yu (Marco) & Ghamami, Mehrnaz & Zockaie, Ali & Xiao, Feng, 2016. "Optimization of incentive polices for plug-in electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 103-123.

    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:phsmap:v:632:y:2023:i:p1:s0378437123008841. 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/physica-a-statistical-mechpplications/ .

    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.