IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v304y2024ics0360544224019169.html
   My bibliography  Save this article

Location-routing optimization problem for electric vehicle charging stations in an uncertain transportation network: An adaptive co-evolutionary clustering algorithm

Author

Listed:
  • Wu, Jiabin
  • Li, Qihang
  • Bie, Yiming
  • Zhou, Wei

Abstract

The rapid growth of Electric Vehicles (EVs) has led to issues such as insufficient and unevenly distributed charging stations, posing an increasingly severe challenge. This not only means higher economic and time costs for EV users traveling to charging stations, but also indicates that EVs need to incur additional energy consumption. To address these challenges, this paper first establishes an extended space-time-state network to describe the temporal variability and uncertainty of the traffic environment. Secondly, considering the impact of the energy consumption incurred by EVs traveling to charging stations (CSs) on the layout of CSs, a co-evolutionary optimization model of the location-routing problem is proposed. To solve the model, a two-stage Adaptive Co-evolutionary Clustering Algorithm (ACECA) integrating an adaptive clustering framework and a co-evolutionary mechanism is designed. Finally, the experiment results indicate that there exists a game between a short-term economic investment and long-term benefits of energy conservation and emission reduction. Moreover, ACECA demonstrates stronger solution performance and robustness compared to other algorithms, with the resulting CS location schemes showing superior advantages in energy conservation and in cost saving for users. The research findings can provide theoretical support for the planning of charging station locations for electric vehicles.

Suggested Citation

  • Wu, Jiabin & Li, Qihang & Bie, Yiming & Zhou, Wei, 2024. "Location-routing optimization problem for electric vehicle charging stations in an uncertain transportation network: An adaptive co-evolutionary clustering algorithm," Energy, Elsevier, vol. 304(C).
    • Handle: RePEc:eee:energy:v:304:y:2024:i:c:s0360544224019169
    DOI: 10.1016/j.energy.2024.132142
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224019169
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.132142?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. 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. Ferro, G. & Minciardi, R. & Robba, M., 2020. "A user equilibrium model for electric vehicles: Joint traffic and energy demand assignment," Energy, Elsevier, vol. 198(C).
    3. Liu, Ke & Liu, Yanli, 2023. "Stochastic user equilibrium based spatial-temporal distribution prediction of electric vehicle charging load," Applied Energy, Elsevier, vol. 339(C).
    4. Ma, Jie & Meng, Qiang & Cheng, Lin & Liu, Zhiyuan, 2022. "General stochastic ridesharing user equilibrium problem with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 162-194.
    5. Ren, Xianqiang & Zhang, Huiming & Hu, Ruohan & Qiu, Yueming, 2019. "Location of electric vehicle charging stations: A perspective using the grey decision-making model," Energy, Elsevier, vol. 173(C), pages 548-553.
    6. Zhang, Jing & Yan, Jie & Liu, Yongqian & Zhang, Haoran & Lv, Guoliang, 2020. "Daily electric vehicle charging load profiles considering demographics of vehicle users," Applied Energy, Elsevier, vol. 274(C).
    7. Zhang, Zhenying & Wang, Jiayu & Feng, Xu & Chang, Li & Chen, Yanhua & Wang, Xingguo, 2018. "The solutions to electric vehicle air conditioning systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 443-463.
    8. Guo, Shiliang & Li, Pengpeng & Ma, Kai & Yang, Bo & Yang, Jie, 2022. "Robust energy management for industrial microgrid considering charging and discharging pressure of electric vehicles," Applied Energy, Elsevier, vol. 325(C).
    9. 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.
    10. Zhou, Guangyou & Zhu, Zhiwei & Luo, Sumei, 2022. "Location optimization of electric vehicle charging stations: Based on cost model and genetic algorithm," Energy, Elsevier, vol. 247(C).
    11. He, Sylvia Y. & Kuo, Yong-Hong & Sun, Ka Kit, 2022. "The spatial planning of public electric vehicle charging infrastructure in a high-density city using a contextualised location-allocation model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 21-44.
    12. Hu, Xiao-Bing & Zhang, Ming-Kong & Zhang, Qi & Liao, Jian-Qin, 2017. "Co-Evolutionary path optimization by Ripple-Spreading algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 411-432.
    13. Guiwu Wei & Fan Lei & Rui Lin & Rui Wang & Yu Wei & Jiang Wu & Cun Wei, 2020. "Algorithms for probabilistic uncertain linguistic multiple attribute group decision making based on the GRA and CRITIC method: application to location planning of electric vehicle charging stations," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 33(1), pages 828-846, January.
    14. Xu, Xiangdong & Chen, Anthony & Cheng, Lin & Lo, Hong K., 2014. "Modeling distribution tail in network performance assessment: A mean-excess total travel time risk measure and analytical estimation method," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 32-49.
    15. 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.
    16. Zhou, Guanyu & Dong, Qianyu & Zhao, Yuming & Wang, Han & Jian, Linni & Jia, Youwei, 2023. "Bilevel optimization approach to fast charging station planning in electrified transportation networks," Applied Energy, Elsevier, vol. 350(C).
    17. Zhao, Yang & Wang, Zhenpo & Shen, Zuo-Jun Max & Sun, Fengchun, 2021. "Data-driven framework for large-scale prediction of charging energy in electric vehicles," Applied Energy, Elsevier, vol. 282(PB).
    18. Erbaş, Mehmet & Kabak, Mehmet & Özceylan, Eren & Çetinkaya, Cihan, 2018. "Optimal siting of electric vehicle charging stations: A GIS-based fuzzy Multi-Criteria Decision Analysis," Energy, Elsevier, vol. 163(C), pages 1017-1031.
    19. Huang, Ruqing & Han, Lee D. & Huang, Zhongxiang, 2022. "A new network equilibrium flow model: User-equilibrium with quantity adjustment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    20. Li, Yanbin & Wang, Jiani & Wang, Weiye & Liu, Chang & Li, Yun, 2023. "Dynamic pricing based electric vehicle charging station location strategy using reinforcement learning," Energy, Elsevier, vol. 281(C).
    21. Asamer, Johannes & Reinthaler, Martin & Ruthmair, Mario & Straub, Markus & Puchinger, Jakob, 2016. "Optimizing charging station locations for urban taxi providers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 233-246.
    22. Li, Tongfei & Ge, Yao & Xiong, Jie & Xu, Min & Wu, Jianjun & Sun, Huijun, 2024. "Ridesharing user equilibrium model without the en-route transfer: An OD-based link-node formulation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    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. Pichamon Keawthong & Veera Muangsin & Chupun Gowanit, 2022. "Location Selection of Charging Stations for Electric Taxis: A Bangkok Case," Sustainability, MDPI, vol. 14(17), pages 1-23, September.
    2. Panagiotis Skaloumpakas & Evangelos Spiliotis & Elissaios Sarmas & Alexios Lekidis & George Stravodimos & Dimitris Sarigiannis & Ioanna Makarouni & Vangelis Marinakis & John Psarras, 2022. "A Multi-Criteria Approach for Optimizing the Placement of Electric Vehicle Charging Stations in Highways," Energies, MDPI, vol. 15(24), pages 1-13, December.
    3. Li, Yanbin & Wang, Jiani & Wang, Weiye & Liu, Chang & Li, Yun, 2023. "Dynamic pricing based electric vehicle charging station location strategy using reinforcement learning," Energy, Elsevier, vol. 281(C).
    4. Lin, Haiyang & Bian, Caiyun & Wang, Yu & Li, Hailong & Sun, Qie & Wallin, Fredrik, 2022. "Optimal planning of intra-city public charging stations," Energy, Elsevier, vol. 238(PC).
    5. Liu, Ke & Liu, Yanli, 2023. "Stochastic user equilibrium based spatial-temporal distribution prediction of electric vehicle charging load," Applied Energy, Elsevier, vol. 339(C).
    6. Zhang, Lihui & Zhao, Zhenli & Yang, Meng & Li, Songrui, 2020. "A multi-criteria decision method for performance evaluation of public charging service quality," Energy, Elsevier, vol. 195(C).
    7. Mansur Arief & Yan Akhra & Iwan Vanany, 2023. "A Robust and Efficient Optimization Model for Electric Vehicle Charging Stations in Developing Countries under Electricity Uncertainty," Papers 2307.05470, arXiv.org.
    8. Men, Jinkun & Zhao, Chunmeng, 2024. "A Type-2 fuzzy hybrid preference optimization methodology for electric vehicle charging station location," Energy, Elsevier, vol. 293(C).
    9. Morro-Mello, Igoor & Padilha-Feltrin, Antonio & Melo, Joel D. & Calviño, Aida, 2019. "Fast charging stations placement methodology for electric taxis in urban zones," Energy, Elsevier, vol. 188(C).
    10. Park, Junseok & Moon, Ilkyeong, 2023. "A facility location problem in a mixed duopoly on networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    11. Davidov, Sreten, 2020. "Optimal charging infrastructure planning based on a charging convenience buffer," Energy, Elsevier, vol. 192(C).
    12. 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.
    13. 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.
    14. Hamza El Hafdaoui & Hamza El Alaoui & Salma Mahidat & Zakaria El Harmouzi & Ahmed Khallaayoun, 2023. "Impact of Hot Arid Climate on Optimal Placement of Electric Vehicle Charging Stations," Energies, MDPI, vol. 16(2), pages 1-19, January.
    15. Ouyang, Xu & Xu, Min, 2022. "Promoting green transportation under the belt and Road Initiative: Locating charging stations considering electric vehicle users’ travel behavior," Transport Policy, Elsevier, vol. 116(C), pages 58-80.
    16. Wang, Ning & Tian, Hangqi & Wu, Huahua & Liu, Qiaoqian & Luan, Jie & Li, Yuan, 2023. "Cost-oriented optimization of the location and capacity of charging stations for the electric Robotaxi fleet," Energy, Elsevier, vol. 263(PC).
    17. Jian Chen & Fangyi Li & Ranran Yang & Dawei Ma, 2020. "Impacts of Increasing Private Charging Piles on Electric Vehicles’ Charging Profiles: A Case Study in Hefei City, China," Energies, MDPI, vol. 13(17), pages 1-17, August.
    18. Zhang, Xiaofeng & Kong, Xiaoying & Yan, Renshi & Liu, Yuting & Xia, Peng & Sun, Xiaoqin & Zeng, Rong & Li, Hongqiang, 2023. "Data-driven cooling, heating and electrical load prediction for building integrated with electric vehicles considering occupant travel behavior," Energy, Elsevier, vol. 264(C).
    19. Fu, Jiali & Nåbo, Arne & Bhatti, Harrison John, 2024. "Locating charging infrastructure for freight transport using multiday travel data," Transport Policy, Elsevier, vol. 152(C), pages 21-28.
    20. Qingyou Yan & Hua Dong & Meijuan Zhang, 2021. "Service Evaluation of Electric Vehicle Charging Station: An Application of Improved Matter-Element Extension Method," Sustainability, MDPI, vol. 13(14), pages 1-25, July.

    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:304:y:2024:i:c:s0360544224019169. 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.