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A bi-level joint scheduling model for charging and delivery of mobile charging robots serving for electric vehicles on highway networks under peak demand during holidays

Author

Listed:
  • Zhang, Shuo
  • Xie, Xiaoting
  • Li, Yingzi
  • Wang, Yuxin

Abstract

Mobile charging robots (MCRs), serving as charging units, have evolved the charging service support for electric vehicles (EVs). Nevertheless, the bottleneck of joint scheduling for charging and delivery(C&D) is a key issue for MCRs, which impact their flexible charging especially during holiday. Hence, a bi-level joint scheduling model for C&D of MCRs serving for EVs on highway networks under peak demand during holidays is put forward in this paper. Firstly, a framework encompassing the grid side, robot side, and service area side is established. This framework covers both C&D of robots. Secondly, A bi-level joint scheduling model is constructed with the optimal consumption of green power and the minimization of costs as the objective functions. Finally, case study is designed with the Beijing region of China to verify the effectiveness and sensitivity analyses are conducted in four aspects including number of MCRs, peak-valley difference electricity prices, maximum number of vehicle loads, and demand of service areas. The results demonstrate that the model has practical and theoretical significance for flexible scheduling services of MCRs. The model is able to address the surplus charging demand of EVs while relieving the pressure on the grid during peak periods, providing decision makers with effective C&D decisions of MCRs.

Suggested Citation

  • Zhang, Shuo & Xie, Xiaoting & Li, Yingzi & Wang, Yuxin, 2026. "A bi-level joint scheduling model for charging and delivery of mobile charging robots serving for electric vehicles on highway networks under peak demand during holidays," Renewable Energy, Elsevier, vol. 256(PD).
    • Handle: RePEc:eee:renene:v:256:y:2026:i:pd:s0960148125017872
    DOI: 10.1016/j.renene.2025.124123
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    References listed on IDEAS

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