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Dynamic rolling horizon optimization for network-constrained V2X value stacking of electric vehicles under uncertainties

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  • Jiang, Canchen
  • Liebman, Ariel
  • Jie, Bo
  • Wang, Hao

Abstract

Electric vehicle (EV) coordination can provide significant benefits through vehicle-to-everything (V2X) by interacting with the grid, buildings, and other EVs. This work aims to develop a V2X value-stacking framework, including vehicle-to-building (V2B), vehicle-to-grid (V2G), and energy trading, to maximize economic benefits for residential communities while maintaining distribution voltage. This work also seeks to quantify the impact of prediction errors related to building load, renewable energy, and EV arrivals. A dynamic rolling-horizon optimization (RHO) method is employed to leverage multiple revenue streams and maximize the potential of EV coordination. To address energy uncertainties, including hourly local building load, local photovoltaic (PV) generation, and EV arrivals, this work develops a Transformer-based forecasting model named Gated Recurrent Units-Encoder-Temporal Fusion Decoder (GRU-EN-TFD). The simulation results, using real data from Australia’s National Electricity Market, and the Independent System Operators in New England and New York in the US, reveal that V2X value stacking can significantly reduce energy costs. The proposed GRU-EN-TFD model outperforms the benchmark forecast model. Uncertainties in EV arrivals have a more substantial impact on value-stacking performance, highlighting the significance of its accurate forecast. This work provides new insights into the dynamic interactions among residential communities, unlocking the full potential of EV batteries.

Suggested Citation

  • Jiang, Canchen & Liebman, Ariel & Jie, Bo & Wang, Hao, 2025. "Dynamic rolling horizon optimization for network-constrained V2X value stacking of electric vehicles under uncertainties," Renewable Energy, Elsevier, vol. 244(C).
    • Handle: RePEc:eee:renene:v:244:y:2025:i:c:s0960148125003301
    DOI: 10.1016/j.renene.2025.122668
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    References listed on IDEAS

    as
    1. Su, Jun & Lie, T.T. & Zamora, Ramon, 2020. "A rolling horizon scheduling of aggregated electric vehicles charging under the electricity exchange market," Applied Energy, Elsevier, vol. 275(C).
    2. Zheng, Peijun & Zhou, Heng & Liu, Jiang & Nakanishi, Yosuke, 2023. "Interpretable building energy consumption forecasting using spectral clustering algorithm and temporal fusion transformers architecture," Applied Energy, Elsevier, vol. 349(C).
    3. Thompson, Andrew W. & Perez, Yannick, 2020. "Vehicle-to-Everything (V2X) energy services, value streams, and regulatory policy implications," Energy Policy, Elsevier, vol. 137(C).
    4. Zaneti, Letícia A.L. & Arias, Nataly Bañol & de Almeida, Madson C. & Rider, Marcos J., 2022. "Sustainable charging schedule of electric buses in a University Campus: A rolling horizon approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    5. Li, Yinan & Yang, Wentao & He, Ping & Chen, Chang & Wang, Xiaonan, 2019. "Design and management of a distributed hybrid energy system through smart contract and blockchain," Applied Energy, Elsevier, vol. 248(C), pages 390-405.
    6. Hoque, Md Murshadul & Khorasany, Mohsen & Azim, M. Imran & Razzaghi, Reza & Jalili, Mahdi, 2024. "A framework for prosumer-centric peer-to-peer energy trading using network-secure export–import limits," Applied Energy, Elsevier, vol. 361(C).
    7. Wu, Chuanshen & Gao, Shan & Liu, Yu & Song, Tiancheng E. & Han, Haiteng, 2021. "A model predictive control approach in microgrid considering multi-uncertainty of electric vehicles," Renewable Energy, Elsevier, vol. 163(C), pages 1385-1396.
    8. Sagaria, Shemin & van der Kam, Mart & Boström, Tobias, 2025. "Vehicle-to-grid impact on battery degradation and estimation of V2G economic compensation," Applied Energy, Elsevier, vol. 377(PB).
    9. Kong, Yan & Xu, Nan & Liu, Qiao & Sui, Yan & Jia, Yifan, 2024. "Variable horizon-based predictive energy management strategy for plug-in hybrid electric vehicles and determination of a suitable predictive horizon," Energy, Elsevier, vol. 294(C).
    10. Moradi Amani, A. & Sajjadi, S.S. & Al Khafaf, N. & Song, H. & Jalili, M. & Yu, X. & Meegahapola, L. & McTaggart, P., 2023. "Technology balancing for reliable EV uptake in distribution grids: An Australian case study," Renewable Energy, Elsevier, vol. 206(C), pages 939-948.
    11. Islam, Shirazul & Iqbal, Atif & Marzband, Mousa & Khan, Irfan & Al-Wahedi, Abdullah M.A.B., 2022. "State-of-the-art vehicle-to-everything mode of operation of electric vehicles and its future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    12. Wang, Shuangxin & Shi, Jiarong & Yang, Wei & Yin, Qingyan, 2024. "High and low frequency wind power prediction based on Transformer and BiGRU-Attention," Energy, Elsevier, vol. 288(C).
    13. Nimalsiri, Nanduni I. & Ratnam, Elizabeth L. & Mediwaththe, Chathurika P. & Smith, David B. & Halgamuge, Saman K., 2021. "Coordinated charging and discharging control of electric vehicles to manage supply voltages in distribution networks: Assessing the customer benefit," Applied Energy, Elsevier, vol. 291(C).
    14. Li, Ruiqi & Ren, Hongbo & Wu, Qiong & Li, Qifen & Gao, Weijun, 2024. "Cooperative economic dispatch of EV-HV coupled electric-hydrogen integrated energy system considering V2G response and carbon trading," Renewable Energy, Elsevier, vol. 227(C).
    15. Luo, Jianing & Yuan, Yanping & Joybari, Mahmood Mastani & Cao, Xiaoling, 2024. "Development of a prediction-based scheduling control strategy with V2B mode for PV-building-EV integrated systems," Renewable Energy, Elsevier, vol. 224(C).
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