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Study on orderly charging strategy of EV with load forecasting

Author

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  • Yin, Wanjun
  • Ji, Jianbo
  • Wen, Tao
  • Zhang, Chao

Abstract

The development and popularization of electric vehicles (EVs) is of great significance to environmental protection, energy saving and emission reduction. With the wide popularization of EV, the EV's disorderly charging brings the security hidden trouble to the grid. Firstly, according to the safe operation of power grid and the charging requirements of EVs, an optimal scheduling model based on grid loss is established, then, the optimal scheduling model is transformed by second-order cone relaxation technology. Secondly, because the orderly charging schedule of EV is based on accurate charging load forecasting, this paper based on LSTM-XGBoost dynamic combination forecasting, the dynamic combination model of LSTM and XGBoost is optimized by using Bayesian optimization method, and more accurate charging load forecasting results are obtained. Finally, the accuracy of the prediction method and the effectiveness of the optimal scheduling strategy are verified by the charging data of the EV in the actual area.

Suggested Citation

  • Yin, Wanjun & Ji, Jianbo & Wen, Tao & Zhang, Chao, 2023. "Study on orderly charging strategy of EV with load forecasting," Energy, Elsevier, vol. 278(C).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:c:s0360544223012124
    DOI: 10.1016/j.energy.2023.127818
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    References listed on IDEAS

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    4. Mohammad Aldossary & Hatem A. Alharbi & Nasir Ayub, 2024. "Optimizing Electric Vehicle (EV) Charging with Integrated Renewable Energy Sources: A Cloud-Based Forecasting Approach for Eco-Sustainability," Mathematics, MDPI, vol. 12(17), pages 1-29, August.
    5. Chen, Yunxiao & Lin, Chaojing & Zhang, Yilan & Liu, Jinfu & Yu, Daren, 2024. "Day-ahead load forecast based on Conv2D-GRU_SC aimed to adapt to steep changes in load," Energy, Elsevier, vol. 302(C).
    6. Luo, Yichen & Xu, Xiao & Yang, Yuyan & Liu, Youbo & Liu, Junyong, 2025. "Impact of electric vehicle disordered charging on urban electricity consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    7. Yin, Wanjun & Ji, Jianbo & Qin, Xuan, 2023. "Study on optimal configuration of EV charging stations based on second-order cone," Energy, Elsevier, vol. 284(C).
    8. Chen, Fangjian & Wang, Yubin & Deng, Hang & Sun, Qianhao & Chen, Qifang & Xia, Mingchao, 2025. "Probabilistic prediction of electric vehicle load in service area incorporating highway spatiotemporal traffic information," Energy, Elsevier, vol. 329(C).
    9. Zheng, Wen & Xu, Xiao & Huang, Yuan & Zhu, Feng & Yang, Yuyan & Liu, Junyong & Hu, Weihao, 2023. "Adaptive robust scheduling optimization of a smart commercial building considering joint energy and reserve markets," Energy, Elsevier, vol. 283(C).
    10. Zhang, Lei & Huang, Zhijia & Wang, Zhenpo & Li, Xiaohui & Sun, Fengchun, 2024. "An urban charging load forecasting model based on trip chain model for private passenger electric vehicles: A case study in Beijing," Energy, Elsevier, vol. 299(C).
    11. Mohamed El-Hendawi & Zhanle Wang & Raman Paranjape & James Fick & Shea Pederson & Darcy Kozoriz, 2024. "Impact of Electric Vehicles Charging on Urban Residential Power Distribution Networks," Energies, MDPI, vol. 17(23), pages 1-22, November.
    12. Jianhong Hao & Ting Huang & Qiuming Xu & Yi Sun, 2023. "Robust Optimal Scheduling of Microgrid with Electric Vehicles Based on Stackelberg Game," Sustainability, MDPI, vol. 15(24), pages 1-15, December.
    13. Yin, Wanjun & Ji, Jianbo, 2024. "Research on EV charging load forecasting and orderly charging scheduling based on model fusion," Energy, Elsevier, vol. 290(C).
    14. Yu, Hao & Zhang, Yulong & Qu, Jiahui & Ji, Haoran & Yu, Jiancheng & Song, Guanyu & Sun, Bing & Zhao, Jinli, 2025. "A privacy-protected distributed operation method for flexible distribution networks with EV charging load clusters," Energy, Elsevier, vol. 327(C).
    15. Mao, Yaqi & Yu, Xiaobing & Wang, Feng & Zhu, Junhua, 2026. "Electric vehicle charging demand forecasting: A data-driven integrated learning approach," Renewable Energy, Elsevier, vol. 256(PD).
    16. Meng, Weiqi & Song, Dongran & Huang, Liansheng & Chen, Xiaojiao & Yang, Jian & Dong, Mi & Talaat, M., 2024. "A Bi-level optimization strategy for electric vehicle retailers based on robust pricing and hybrid demand response," Energy, Elsevier, vol. 289(C).
    17. Shiqian Wang & Bo Liu & Qiuyan Li & Ding Han & Jianshu Zhou & Yue Xiang, 2025. "EV Charging Behavior Analysis and Load Prediction via Order Data of Charging Stations," Sustainability, MDPI, vol. 17(5), pages 1-16, February.
    18. Guo, Hongxia & Chen, Lingxuan & Wang, Zhaocai & Li, Lin, 2025. "Day-ahead prediction of electric vehicle charging demand based on quadratic decomposition and dual attention mechanisms," Applied Energy, Elsevier, vol. 381(C).
    19. Tancredi Testasecca & Francesco Bellesini & Diego Arnone & Marco Beccali, 2025. "A Digital Twin for Real-Time and Predictive Optimization of Electric Vehicle Charging in Microgrids Integrating Renewable Energy Sources," Energies, MDPI, vol. 18(21), pages 1-26, October.

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