IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v236y2024ics0960148124015799.html

Unveiling electric vehicle (EV) charging patterns and their transformative role in electricity balancing and delivery: Insights from real-world data in Sweden

Author

Listed:
  • Huang, Pei
  • Ma, Zhenliang

Abstract

Accurately estimating the charging behaviours of electric vehicles (EVs) is crucial for various applications, such as charging station planning and grid impact estimation. However, the analysis of EV charging behaviours using real-world data remains limited due to (confidential) data availability constraints. Furthermore, while existing modelling studies have demonstrated EVs as effective tools for electricity balancing and delivery between locations, their potential remains unexplored empirically. This study aims to bridge the research gap by studying EV charging behaviours and their capacity for electricity balancing and delivery. Using data from 179,665 real-world charging sessions in Sweden, we employed statistical and clustering analysis to scrutinize charging behaviours comprehensively. Synthetic weekly charging load profiles are generated for both residential areas and workplaces, considering varying charging power levels, which can be used as inputs for large-scale EV charging load modelling. Furthermore, performance indicators are proposed to quantify the potential of EVs for electricity balancing and delivery. Results show that EVs exhibit significant potential for electricity balancing (up to 51.5 kWh daily). Many EV owners underutilize their EV battery capacity, providing an opportunity for active electricity delivery across locations. This study can help understand EV charging behaviours and recognize their significant potentials for electricity regulation and integrating more renewables in the future power system.

Suggested Citation

  • Huang, Pei & Ma, Zhenliang, 2024. "Unveiling electric vehicle (EV) charging patterns and their transformative role in electricity balancing and delivery: Insights from real-world data in Sweden," Renewable Energy, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:renene:v:236:y:2024:i:c:s0960148124015799
    DOI: 10.1016/j.renene.2024.121511
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124015799
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2024.121511?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. Sandström, Maria & Huang, Pei & Bales, Chris & Dotzauer, Erik, 2023. "Evaluation of hosting capacity of the power grid for electric vehicles – A case study in a Swedish residential area," Energy, Elsevier, vol. 284(C).
    2. Zhou, Yuekuan, 2022. "Energy sharing and trading on a novel spatiotemporal energy network in Guangdong-Hong Kong-Macao Greater Bay Area," Applied Energy, Elsevier, vol. 318(C).
    3. Huang, Pei & Ma, Zhenjun & Xiao, Longzhu & Sun, Yongjun, 2019. "Geographic Information System-assisted optimal design of renewable powered electric vehicle charging stations in high-density cities," Applied Energy, Elsevier, vol. 255(C).
    4. Alexandra Märtz & Uwe Langenmayr & Sabrina Ried & Katrin Seddig & Patrick Jochem, 2022. "Charging Behavior of Electric Vehicles: Temporal Clustering Based on Real-World Data," Energies, MDPI, vol. 15(18), pages 1-26, September.
    5. Li, Xiaohui & Wang, Zhenpo & Zhang, Lei & Sun, Fengchun & Cui, Dingsong & Hecht, Christopher & Figgener, Jan & Sauer, Dirk Uwe, 2023. "Electric vehicle behavior modeling and applications in vehicle-grid integration: An overview," Energy, Elsevier, vol. 268(C).
    6. Powell, Siobhan & Cezar, Gustavo Vianna & Rajagopal, Ram, 2022. "Scalable probabilistic estimates of electric vehicle charging given observed driver behavior," Applied Energy, Elsevier, vol. 309(C).
    7. Huang, Pei & Lovati, Marco & Zhang, Xingxing & Bales, Chris, 2020. "A coordinated control to improve performance for a building cluster with energy storage, electric vehicles, and energy sharing considered," Applied Energy, Elsevier, vol. 268(C).
    8. Barone, G. & Buonomano, A. & Calise, F. & Forzano, C. & Palombo, A., 2019. "Building to vehicle to building concept toward a novel zero energy paradigm: Modelling and case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 625-648.
    9. Yu, Hang & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jia, Youwei & Jian, Linni, 2022. "Electric vehicles integration and vehicle-to-grid operation in active distribution grids: A comprehensive review on power architectures, grid connection standards and typical applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    10. Palm, J. & Kojonsaari, A.-R. & Öhrlund, I. & Fowler, N. & Bartusch, C., 2023. "Drivers and barriers to participation in Sweden's local flexibility markets for electricity," Utilities Policy, Elsevier, vol. 82(C).
    11. Board, Anthony & Sun, Yongjun & Huang, Pei & Xu, Tao, 2024. "Community-to-vehicle-to-community (C2V2C) for inter-community electricity delivery and sharing via electric vehicle: Performance evaluation and robustness analysis," Applied Energy, Elsevier, vol. 363(C).
    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. Huang, Pei & Sandström, Maria, 2025. "Do smart charging and vehicle-to-grid strengthen or strain power grids with rising EV adoption? Insights from a Swedish residential network," Applied Energy, Elsevier, vol. 401(PB).
    2. Dey, Bishwajit & Khumanleima Chanu, Laishram & Sharma, Gulshan & Bokoro, Pitshou N. & Bansal, Ramesh C. & Kumar, Rajesh, 2025. "Economic operation of a microgrid system with amalgamated load shifting/curtailing policy and smart PHEV charging," Energy, Elsevier, vol. 334(C).

    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. Board, Anthony & Sun, Yongjun & Huang, Pei & Xu, Tao, 2024. "Community-to-vehicle-to-community (C2V2C) for inter-community electricity delivery and sharing via electric vehicle: Performance evaluation and robustness analysis," Applied Energy, Elsevier, vol. 363(C).
    2. Huang, Pei & Sandström, Maria, 2025. "Do smart charging and vehicle-to-grid strengthen or strain power grids with rising EV adoption? Insights from a Swedish residential network," Applied Energy, Elsevier, vol. 401(PB).
    3. Zhou, Yuekuan, 2024. "AI-driven battery ageing prediction with distributed renewable community and E-mobility energy sharing," Renewable Energy, Elsevier, vol. 225(C).
    4. Syed Taha Taqvi & Ali Almansoori & Azadeh Maroufmashat & Ali Elkamel, 2022. "Utilizing Rooftop Renewable Energy Potential for Electric Vehicle Charging Infrastructure Using Multi-Energy Hub Approach," Energies, MDPI, vol. 15(24), pages 1-21, December.
    5. Jian Zhang & Shujun Li & Lili Li & Guoqiang Zu & Yongchun Wang & Ting Yang, 2025. "A Bi-Level Method for Flexibility Feature Extraction and User Clustering Based on Real-World Data from Independent Smart Meters of Residential Electric Vehicle Users," Energies, MDPI, vol. 18(4), pages 1-23, February.
    6. Zhou, Yuekuan, 2022. "Energy sharing and trading on a novel spatiotemporal energy network in Guangdong-Hong Kong-Macao Greater Bay Area," Applied Energy, Elsevier, vol. 318(C).
    7. Zhou, Yuekuan, 2023. "A dynamic self-learning grid-responsive strategy for battery sharing economy—multi-objective optimisation and posteriori multi-criteria decision making," Energy, Elsevier, vol. 266(C).
    8. Lu, M.L. & Sun, Y.J. & Kokogiannakis, G. & Ma, Z.J., 2024. "Design of flexible energy systems for nearly/net zero energy buildings under uncertainty characteristics: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 205(C).
    9. Xiao, Zhiyang & He, Yindong & Liao, Wei & Xu, Peng & Li, Ji & Liu, Xiaohua & Peng, Jinqing, 2025. "A systematized framework to optimize grid-interactive charging process of electric vehicles integrated with buildings and distributed renewable sources," Energy, Elsevier, vol. 335(C).
    10. Siyao Wang & Chongzhi Liu & Fu Chen, 2025. "Evaluation of Peak Shaving and Valley Filling Efficiency of Electric Vehicle Charging Piles in Power Grids," Energies, MDPI, vol. 18(19), pages 1-19, October.
    11. Zhou, Yuekuan & Liu, Xiaohua & Zhao, Qianchuan, 2024. "A stochastic vehicle schedule model for demand response and grid flexibility in a renewable-building-e-transportation-microgrid," Renewable Energy, Elsevier, vol. 221(C).
    12. Dan, Zhaohui & Zhou, Bingling & Zhou, Yuekuan, 2025. "Optimal infrastructures and integrative energy networks for sustainable and energy-resilient city renaissance," Applied Energy, Elsevier, vol. 387(C).
    13. Dou, Zhenyu & Pan, Kai & Xu, Yang & Cao, Sunliang, 2025. "Unlock the energy flexibility resources of zero-emission vehicles to simultaneously alleviate the negative impact on grid and traffic between remote buildings with predictive controls," Applied Energy, Elsevier, vol. 400(C).
    14. Hou, Min & Liu, Xinrui & Li, Ming & Li, Yushuai & Wang, Rui & Li, Zhengmao & Sun, Qiuye, 2025. "Towards intelligent cooperation of urban electric-traffic coupling network: A distributionally robust hierarchical optimization method with dependency of uncertainties," Energy, Elsevier, vol. 338(C).
    15. Moon-Jong Jang & Taehoon Kim & Eunsung Oh, 2023. "Data-Driven Modeling of Vehicle-to-Grid Flexibility in Korea," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    16. 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).
    17. Zhou, Yuekuan, 2023. "Sustainable energy sharing districts with electrochemical battery degradation in design, planning, operation and multi-objective optimisation," Renewable Energy, Elsevier, vol. 202(C), pages 1324-1341.
    18. Liu, Can & Guo, Yuntao & Qian, Xinwu & Li, Xinghua & Liu, Haobing & Zhong, Minghui, 2025. "Understanding spatiotemporal dynamics of V2G participation in megacities: A data-driven study," Applied Energy, Elsevier, vol. 401(PC).
    19. Peng, Chang & Xu, Chengcheng & Jiao, Lijuan, 2025. "Variational spatiotemporal factorized graph neural networks for integrated electric vehicle usage prediction and pattern recognition with missing data on regional networks," Energy, Elsevier, vol. 335(C).
    20. Bin Zhang & Qingyao Xin & Siyuan Chen & Zhaohua Wang & Yang Lu & Niu Niu & Fang Zhang & Guangchuan Liu & Prateek Bansal, 2026. "Behavioral uncertainty in EV charging drives heterogeneous grid load variability under climate goals," Nature Communications, Nature, vol. 17(1), pages 1-12, December.

    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:renene:v:236:y:2024:i:c:s0960148124015799. 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/renewable-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.