IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v401y2025ipcs030626192501548x.html

A spatial-temporal scheduling framework for EV charging with multi-mode coordination and user subjective uncertainty

Author

Listed:
  • Zhang, Zihan
  • Liu, Xiao-Kang
  • Xiao, Jiang-Wen
  • He, Yan
  • Wang, Yan-Wu

Abstract

With the growing popularity of electric vehicles (EVs) and diversified user demands, charging stations (CS) require multiple charging modes to accommodate diverse needs. This paper proposes a comprehensive spatial-temporal scheduling model for EVs incorporating three charging modes: plug-in charging, battery-swapping, and mobile charging vehicle (MPV) services. The original multi-objective optimization model is solved via a weighted-sum approach. To address non-convexity in the EV charging sub-model, a coordinate descent method (CDM) is developed to transform it into tractable convex sub-problems. Effective scheduling of battery and MPV operations not only enhances the station’s load capacity but also achieves peak shaving and valley filling. User demand diversity is modeled through cost-driven subjective uncertainty, classifying users into three urgency-related categories. Simulation results validate the model’s effectiveness, while comparative studies analyze the impact of user types on scheduling outcomes under varying urgency scenarios.

Suggested Citation

  • Zhang, Zihan & Liu, Xiao-Kang & Xiao, Jiang-Wen & He, Yan & Wang, Yan-Wu, 2025. "A spatial-temporal scheduling framework for EV charging with multi-mode coordination and user subjective uncertainty," Applied Energy, Elsevier, vol. 401(PC).
    • Handle: RePEc:eee:appene:v:401:y:2025:i:pc:s030626192501548x
    DOI: 10.1016/j.apenergy.2025.126818
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626192501548X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.126818?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Lu & Zhou, Kaile, 2022. "Electric vehicle charging scheduling considering urgent demand under different charging modes," Energy, Elsevier, vol. 249(C).
    2. Li, Zhikang & Ma, Chengbin, 2022. "A temporal–spatial charging coordination scheme incorporating probability of EV charging availability," Applied Energy, Elsevier, vol. 325(C).
    3. Gull, Muhammad Shuzub & Khalid, Muhammad & Arshad, Naveed, 2024. "Multi-objective optimization of battery swapping station to power up mobile and stationary loads," Applied Energy, Elsevier, vol. 374(C).
    4. Jones, Ben & Elliott, Robert J.R. & Nguyen-Tien, Viet, 2020. "The EV revolution: The road ahead for critical raw materials demand," Applied Energy, Elsevier, vol. 280(C).
    5. Cortés-Murcia, David L. & Prodhon, Caroline & Murat Afsar, H., 2019. "The electric vehicle routing problem with time windows, partial recharges and satellite customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 184-206.
    6. Wang, Zongfei & Sasse, Jan-Philipp & Trutnevyte, Evelina, 2025. "Home or workplace charging? Spatio-temporal flexibility of electric vehicles within Swiss electricity system," Energy, Elsevier, vol. 320(C).
    7. Wu, Fuzhang & Yang, Jun & Li, Bin & Crisostomi, Emanuele & Rafiq, Hogir & Rashed, Ghamgeen Izat, 2024. "Uncertain scheduling potential of charging stations under multi-attribute uncertain charging decisions of electric vehicles," Applied Energy, Elsevier, vol. 374(C).
    8. Wu, Hongbin & Lan, Xinjie & He, Ye & Wu, Andrew Y. & Ding, Ming, 2025. "Orderly charging of electric vehicles: A two-stage spatial-temporal scheduling method based on user-personalized navigation," Applied Energy, Elsevier, vol. 378(PA).
    9. Cui, Jingshi & Jiang, Wenqian & Wu, Chenye, 2025. "Pricing mechanism design for future EV charging station with hybrid fixed and mobile charging modes," Applied Energy, Elsevier, vol. 380(C).
    10. Afshar, Shahab & Macedo, Pablo & Mohamed, Farog & Disfani, Vahid, 2021. "Mobile charging stations for electric vehicles — A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    11. Nayak, Dhyaan Sandeep & Misra, Shamik, 2024. "An operational scheduling framework for Electric Vehicle Battery Swapping Station under demand uncertainty," Energy, Elsevier, vol. 290(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. Li, Xiaofeng & Yu, Xinlian & Pu, Ziyuan & Chen, Jingxu, 2025. "Electric vehicle charging optimization with coordinated mobile and fixed chargers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 204(C).
    2. Yang Gao & Xiaohong Zhang & Qingyuan Yan & Yanxue Li, 2025. "Demand Response Strategies for Electric Vehicle Charging and Discharging Behavior Based on Road–Electric Grid Interaction and User Psychology," Sustainability, MDPI, vol. 17(6), pages 1-27, March.
    3. Li, Jing & Lin, Xueru & Huang, Hao & Wang, Rui & Zhong, Wei & Lin, Xiaojie & Wei, Wei, 2026. "Optimal operation of grid-friendly megawatt-level ultra-fast EV charging stations: A review on constraints, objectives and algorithms for grid-interactive operation," Applied Energy, Elsevier, vol. 405(C).
    4. Du, Pengcheng & Jiang, Meihui & Yang, Bowen & Chen, Baian & Zhu, Hongyu & Mengke, Qilao & Du, Yu & Kong, Fannie & Liu, Tianhao & Huang, Chao & Zhao, Haisen & Goh, Hui Hwang & Zhang, Dongdong, 2025. "Two-layer decomposition-fused hybrid deep learning enables data-driven electricity demand forecasting for battery swapping station," Energy, Elsevier, vol. 332(C).
    5. Zhao, Zhonghao & Lee, Carman K.M. & Ren, Jingzheng, 2024. "A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile," Applied Energy, Elsevier, vol. 355(C).
    6. Maria Grazia Marchesano & Valentina Popolo & Anastasiia Rozhok & Gianluca Cavalaglio, 2024. "Performance Evaluation of Battery Swapping Stations for EVs: A Multi-Method Simulation Approach," Energies, MDPI, vol. 17(23), pages 1-25, November.
    7. Hemmati, Reza & Mahdavi, Sajad & Mehrjerdi, Hasan, 2025. "A resilient microgrid formation framework: Mobile battery-swapping station deployment for effective load restoration and voltage collapse prevention," Energy, Elsevier, vol. 318(C).
    8. Qingyuan Yan & Zhaoyi Wang & Ling Xing & Chenchen Zhu, 2024. "Optimal Economic Analysis of Battery Energy Storage System Integrated with Electric Vehicles for Voltage Regulation in Photovoltaics Connected Distribution System," Sustainability, MDPI, vol. 16(19), pages 1-44, September.
    9. Casale, Marco & Gambino, Francesca & Borghi, Alessandro & Beltramo, Riccardo & Vesce, Enrica & Varì, Cristina & Giardino, Marco & Dino, Giovanna Antonella, 2024. "A sustainable integration of mining activity in a tourist mountain territory: The case of GermanascaValley," Resources Policy, Elsevier, vol. 98(C).
    10. Tamakloe, Reuben & Caesar, Livingstone Divine & Kim, Inhi, 2026. "Determinants of battery electric vehicle adoption concerns: insights from commercial fleet owners," Transportation Research Part A: Policy and Practice, Elsevier, vol. 205(C).
    11. Duan, Sudong & Zhang, Zhonghui & Wang, Zhaojun & Xiong, Xiaoyue & Chen, Xinhan & Que, Xiaoyu, 2025. "A study on mobile charging station combined with integrated energy system: Emphasis on energy dispatch strategy and multi-scenario analysis," Renewable Energy, Elsevier, vol. 239(C).
    12. Arenas-Vasco, Alejandro & Alcázar, Daniela & Villegas, Juan G., 2025. "A meta-analysis of set partitioning/set covering based matheuristics for vehicle routing problems," Operations Research Perspectives, Elsevier, vol. 15(C).
    13. Adil, Muhammad & Mahmud, M.A. Parvez & Kouzani, Abbas Z. & Khoo, Sui Yang, 2024. "Three-stage energy trading framework for retailers, charging stations, and electric vehicles: A game-theoretic approach," Energy, Elsevier, vol. 301(C).
    14. Atefeh Alirezazadeh & Vahid Disfani, 2025. "Deep Reinforcement Learning-Based Optimization of Mobile Charging Station and Battery Recharging Under Grid Constraints," Energies, MDPI, vol. 18(20), pages 1-21, October.
    15. Li, Yingli & Huang, Jianbai & Zhang, Hongwei, 2022. "The impact of country risks on cobalt trade patterns from the perspective of the industrial chain," Resources Policy, Elsevier, vol. 77(C).
    16. Fan, Zhi-Ping & Cao, Yue & Huang, Chun-Yong & Li, Yongli, 2020. "Pricing strategies of domestic and imported electric vehicle manufacturers and the design of government subsidy and tariff policies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    17. Narayanan, Santhanakrishnan & Antoniou, Constantinos, 2022. "Electric cargo cycles - A comprehensive review," Transport Policy, Elsevier, vol. 116(C), pages 278-303.
    18. Gleb V. Savin, 2021. "The smart city transport and logistics system: Theory, methodology and practice," Upravlenets, Ural State University of Economics, vol. 12(6), pages 67-86, October.
    19. Dreucci, Damiano & Yu, Yunhe & Chandra Mouli, Gautham Ram & Shekhar, Aditya & Bauer, Pavol, 2025. "Centralised distribution grid congestion management through EV charging control considering fairness and priority," Applied Energy, Elsevier, vol. 384(C).
    20. Lumbumba Taty-Etienne Nyamayoka & Lesedi Masisi & David Dorrell & Shuo Wang, 2025. "Techno-Economic Feasibility and Optimal Design Approach of Grid-Connected Hybrid Power Generation Systems for Electric Vehicle Battery Swapping Station," Energies, MDPI, vol. 18(5), pages 1-30, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:appene:v:401:y:2025:i:pc:s030626192501548x. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.