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<p>The widespread adoption of the Internet and 5G, coupled with global carbon neutrality goals, has generated significant interest in shared electric vehicles (SEVs) for their flexibility, convenience, and environmental benefits. However, a major industry challenge is optimizing charging and discharging schedules while accommodating dynamic user demand. Ineffective strategies can diminish shared electric vehicle operator (SEVO) profitability and exacerbate grid energy losses and node overloads, thereby threatening the economic efficiency and security of power grid operations. To address this problem, this paper proposes a charging–discharging strategy for SEVs guided by real-time nodal prices. An optimization model is developed with the objective of maximizing operator revenue. This model enables SEVOs to formulate charging, discharging, and relocation plans that account for electricity price fluctuations and user demand, thereby increasing their revenue while supporting grid economics and security. Finally, through case analysis, it is demonstrated that the proposed method increases the operators’ revenue by 19.91%, reduces the total network loss by 9.84%, and decreases the total overloaded periods by 17.06%. This verifies the effectiveness of the proposed pricing guidance approach and the feasibility of SEVs participating in grid dispatch.</p>

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Optimal scheduling of shared electric vehicles based on real-time nodal price guidance

  • 期刊论文

  • 发表日期：

    2026年3月18日

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  • Tianze Zheng,
  • Hengli Zhang,
  • Jiaqi Hong,
  • Faqiao Yang,
  • Yinuo Huang,
  • Kai Wang

摘要

The widespread adoption of the Internet and 5G, coupled with global carbon neutrality goals, has generated significant interest in shared electric vehicles (SEVs) for their flexibility, convenience, and environmental benefits. However, a major industry challenge is optimizing charging and discharging schedules while accommodating dynamic user demand. Ineffective strategies can diminish shared electric vehicle operator (SEVO) profitability and exacerbate grid energy losses and node overloads, thereby threatening the economic efficiency and security of power grid operations. To address this problem, this paper proposes a charging–discharging strategy for SEVs guided by real-time nodal prices. An optimization model is developed with the objective of maximizing operator revenue. This model enables SEVOs to formulate charging, discharging, and relocation plans that account for electricity price fluctuations and user demand, thereby increasing their revenue while supporting grid economics and security. Finally, through case analysis, it is demonstrated that the proposed method increases the operators’ revenue by 19.91%, reduces the total network loss by 9.84%, and decreases the total overloaded periods by 17.06%. This verifies the effectiveness of the proposed pricing guidance approach and the feasibility of SEVs participating in grid dispatch.