IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v328y2025ics0360544225022376.html

An electric vehicle charging station operation model with hourly capacity mechanism

Author

Listed:
  • Tong, Yuxing
  • Shao, Chengcheng
  • Xu, Jinlong

Abstract

With the increasing penetration of electric vehicles (EVs), the EV charging load (EVCL), characterized by high power demand and uncertainty, consumes grid capacity and increases the operational cost of the distribution network (DN), posing challenges for EV charging stations (EVCSs) and limiting the integration of other loads. This paper proposes an hourly capacity mechanism to guide EVCS operation in the DN. Compared to traditional models, the proposed approach innovatively incorporates an hourly capacity payment and establishes a bi-level model based on hourly capacity and time-varying prices. A tailored algorithmic solution is developed to efficiently solve the bi-level optimization problem. Case studies on a modified IEEE 33-bus system show that the proposed model reduces EVCS hourly capacity by an average of 24.33 %, and lowers operational costs for the EVCS and DN by 11.38 % and 1.15 %, respectively, while ensuring secure grid operation and preventing voltage deviation. Sensitivity and scalability analyses confirm the model's robustness under increasing EV arrival rates. The computational burden is also evaluated, demonstrating the approach's practicality and engineering value.

Suggested Citation

  • Tong, Yuxing & Shao, Chengcheng & Xu, Jinlong, 2025. "An electric vehicle charging station operation model with hourly capacity mechanism," Energy, Elsevier, vol. 328(C).
  • Handle: RePEc:eee:energy:v:328:y:2025:i:c:s0360544225022376
    DOI: 10.1016/j.energy.2025.136595
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225022376
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.136595?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. Wang, Can & Liu, Yuzheng & Zhang, Yu & Xi, Lei & Yang, Nan & Zhao, Zhuoli & Lai, Chun Sing & Lai, Loi Lei, 2025. "Strategy for optimizing the bidirectional time-of-use electricity price in multi-microgrids coupled with multilevel games," Energy, Elsevier, vol. 323(C).
    2. P, Balakumar & Ramu, Senthil Kumar & T, Vinopraba, 2024. "Optimizing electric vehicle charging in distribution networks: A dynamic pricing approach using internet of things and Bi-directional LSTM model," Energy, Elsevier, vol. 294(C).
    3. Zheng, Yanchong & Wang, Yubin & Yang, Qiang, 2023. "Bidding strategy design for electric vehicle aggregators in the day-ahead electricity market considering price volatility: A risk-averse approach," Energy, Elsevier, vol. 283(C).
    4. Meng, Weiqi & Song, Dongran & Huang, Liansheng & Chen, Xiaojiao & Yang, Jian & Dong, Mi & Talaat, M. & Elkholy, M.H., 2024. "Distributed energy management of electric vehicle charging stations based on hierarchical pricing mechanism and aggregate feasible regions," Energy, Elsevier, vol. 291(C).
    5. Chen, Yu & Lin, Boqiang, 2022. "Are consumers in China’s major cities happy with charging infrastructure for electric vehicles?," Applied Energy, Elsevier, vol. 327(C).
    6. Yao, Zhaosheng & Wang, Zhiyuan & Ran, Lun, 2023. "Smart charging and discharging of electric vehicles based on multi-objective robust optimization in smart cities," Applied Energy, Elsevier, vol. 343(C).
    7. Torres, S. & Durán, I. & Marulanda, A. & Pavas, A. & Quirós-Tortós, J., 2022. "Electric vehicles and power quality in low voltage networks: Real data analysis and modeling," Applied Energy, Elsevier, vol. 305(C).
    8. Shu, Tony & Papageorgiou, Dimitri J. & Harper, Michael R. & Rajagopalan, Srinivasan & Rudnick, Iván & Botterud, Audun, 2023. "From coal to variable renewables: Impact of flexible electric vehicle charging on the future Indian electricity sector," Energy, Elsevier, vol. 269(C).
    9. Ansarin, Mohammad & Ghiassi-Farrokhfal, Yashar & Ketter, Wolfgang & Collins, John, 2022. "A review of equity in electricity tariffs in the renewable energy era," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    10. Schlereth, Christian & Skiera, Bernd & Schulz, Fabian, 2018. "Why do consumers prefer static instead of dynamic pricing plans? An empirical study for a better understanding of the low preferences for time-variant pricing plans," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1165-1179.
    11. Menghwar, Mohan & Yan, Jie & Chi, Yongning & Asim Amin, M. & Liu, Yongqian, 2024. "A market-based real-time algorithm for congestion alleviation incorporating EV demand response in active distribution networks," Applied Energy, Elsevier, vol. 356(C).
    12. Zhang, Kaizhe & Xu, Yinliang & Sun, Hongbin, 2024. "Bilevel optimal coordination of active distribution network and charging stations considering EV drivers' willingness," Applied Energy, Elsevier, vol. 360(C).
    13. Jiang, Yuzheng & Dong, Jun & Huang, Hexiang, 2024. "Optimal bidding strategy for the price-maker virtual power plant in the day-ahead market based on multi-agent twin delayed deep deterministic policy gradient algorithm," Energy, Elsevier, vol. 306(C).
    14. R. Misener & C. A. Floudas, 2010. "Piecewise-Linear Approximations of Multidimensional Functions," Journal of Optimization Theory and Applications, Springer, vol. 145(1), pages 120-147, April.
    15. Li, Junkai & Ge, Shaoyun & Liu, Hong & Du, Yongmei & Wang, Chengshan & Tian, Weidong, 2024. "A network-secure two-stage framework for hierarchical energy management of EVs, charging stations, and distribution network," Applied Energy, Elsevier, vol. 371(C).
    16. Yin, Wanjun & Liang, Wenbin & Ji, Jianbo, 2024. "Study on charge and discharge control strategy of improved PSO for EV," Energy, Elsevier, vol. 304(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. Zhu, Jie & Xu, Yinliang & Tai, Nengling & Sun, Hongbin, 2025. "Joint chance-constrained energy-reserve co-optimization for distribution networks with flexible resource aggregators," Applied Energy, Elsevier, vol. 388(C).
    2. Ghanbari Motlagh, Saheb & Oladigbolu, Jamiu & Li, Li, 2025. "A review on electric vehicle charging station operation considering market dynamics and grid interaction," Applied Energy, Elsevier, vol. 392(C).
    3. Fang, Debin & Wang, Pengyu, 2023. "Optimal real-time pricing and electricity package by retail electric providers based on social learning," Energy Economics, Elsevier, vol. 117(C).
    4. Codas, Andrés & Camponogara, Eduardo, 2012. "Mixed-integer linear optimization for optimal lift-gas allocation with well-separator routing," European Journal of Operational Research, Elsevier, vol. 217(1), pages 222-231.
    5. Iqra Nazir & Nermish Mushtaq & Waqas Amin, 2025. "Smart Grid Systems: Addressing Privacy Threats, Security Vulnerabilities, and Demand–Supply Balance (A Review)," Energies, MDPI, vol. 18(19), pages 1-77, September.
    6. Gu, Bo & Li, Fangxing & Mao, Chengxiong & Wang, Dan & Fan, Hua & Liu, Bin & Li, Wenhao, 2025. "A Bilevel robust coordination model for community integrated energy system with access to HFCEVs and EVs," Applied Energy, Elsevier, vol. 390(C).
    7. Kim, Kyungah & Choi, Jihye & Lee, Jihee & Lee, Jongsu & Kim, Junghun, 2023. "Public preferences and increasing acceptance of time-varying electricity pricing for demand side management in South Korea," Energy Economics, Elsevier, vol. 119(C).
    8. Mariuzzo, Ivan & Fina, Bernadette & Stroemer, Stefan & Corinaldesi, Carlo & Raugi, Marco, 2025. "Grid-friendly optimization of energy communities through enhanced multiple participation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 208(C).
    9. Wang, Yubin & Dong, Wei & Yang, Qiang, 2022. "Multi-stage optimal energy management of multi-energy microgrid in deregulated electricity markets," Applied Energy, Elsevier, vol. 310(C).
    10. Dario Benavides & Paul Arévalo-Cordero & Danny Ochoa-Correa & David Torres & Alberto Ríos, 2025. "Predictive Energy Storage Management with Redox Flow Batteries in Demand-Driven Microgrids," Sustainability, MDPI, vol. 17(19), pages 1-24, October.
    11. Guo, Wenhao & Tian, Jin & Li, Minqiang, 2023. "Price-aware enhanced dynamic recommendation based on deep learning," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    12. Savelli, Iacopo & Morstyn, Thomas, 2021. "Electricity prices and tariffs to keep everyone happy: A framework for fixed and nodal prices coexistence in distribution grids with optimal tariffs for investment cost recovery," Omega, Elsevier, vol. 103(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. Martin Spann & Bernd Skiera, 2020. "Dynamische Preisgestaltung in der digitalisierten Welt [Dynamic Pricing in a Digitized World]," Schmalenbach Journal of Business Research, Springer, vol. 72(3), pages 321-342, September.
    15. Sandile Johannes Buthelezi & Taurai Hungwe & Solly Matshonisa Seeletse & Vimbai Mbirimi-Hungwe, 2024. "Non-life insurance: The state of the art of determining the superior method for pricing automobile insurance premiums using archival technique," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 13(2), pages 180-188, March.
    16. Freier, Julia & von Loessl, Victor, 2022. "Dynamic electricity tariffs: Designing reasonable pricing schemes for private households," Energy Economics, Elsevier, vol. 112(C).
    17. Di Persio, Luca & Garbelli, Matteo & Giordano, Luca Maria, 2025. "Reinforcement learning for bidding strategy optimization in day-ahead energy market," Energy Economics, Elsevier, vol. 149(C).
    18. Kang, Keyi & Jia, Heping & Hui, Hongxun & Liu, Dunnan, 2025. "Two-stage optimization configuration of shared energy storage for multi-distributed photovoltaic clusters in rural distribution networks considering self-consumption and self-sufficiency," Applied Energy, Elsevier, vol. 394(C).
    19. Zhiwei Liao & Bowen Wang & Wenjuan Tao & Ye Liu & Qiyun Hu, 2024. "Research on Decision Optimization and the Risk Measurement of the Power Generation Side Based on Quantile Data-Driven IGDT," Energies, MDPI, vol. 17(7), pages 1-21, March.
    20. Sulaima, Mohamad Fani & Dahlan, Nofri Yenita & Yasin, Zuhaila Mat & Rosli, Marlinda Mohd & Omar, Zulkiflee & Hassan, Mohammad Yusri, 2019. "A review of electricity pricing in peninsular Malaysia: Empirical investigation about the appropriateness of Enhanced Time of Use (ETOU) electricity tariff," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 348-367.

    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:energy:v:328:y:2025:i:c:s0360544225022376. 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.