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Mechanism design of EVs fast charging rights for enhanced vehicle-to-grid regulation

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  • Qian, Tao
  • Xu, Yadong
  • Jin, Xu
  • Hu, Qinran

Abstract

With the advancement of policy initiatives and technological developments, vehicle-to-grid (V2G) interactions have emerged as a critical focus within power system research. Despite numerous current studies on V2G, the exploration of incentive mechanisms to encourage user participation in these systems remains comparatively underdeveloped. This study proposes an innovative demand response (DR) incentive mechanism for electric vehicles (EVs) grounded in the regulation of fast charging powers via strategically assigning and allocating virtual points defined as fast charging right (FCR). The primary objective of this mechanism is to meet the power regulation requirements of DR while simultaneously balancing the grid’s response costs and accommodating the charging demands of EV users. Through simulation and comparative analysis with the existing pilot DR incentive mechanisms, the results demonstrate that the proposed mechanism outperforms the current model in three critical aspects: power regulation efficacy, cost-effectiveness, and user experience. In addition, this paper investigates the performance of the incentive mechanisms in both online and offline scheduling environments. The findings reveal that the FCR mechanism maintains robust power regulation performance even under online scheduling conditions.

Suggested Citation

  • Qian, Tao & Xu, Yadong & Jin, Xu & Hu, Qinran, 2025. "Mechanism design of EVs fast charging rights for enhanced vehicle-to-grid regulation," Applied Energy, Elsevier, vol. 377(PB).
    • Handle: RePEc:eee:appene:v:377:y:2025:i:pb:s0306261924017756
    DOI: 10.1016/j.apenergy.2024.124392
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    References listed on IDEAS

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    1. Xiaohong Dong & Yang Ma & Xiaodan Yu & Xiangyu Wei & Yanqi Ren & Xin Zhang, 2023. "Secondary Frequency Regulation Control Strategy with Electric Vehicles Considering User Travel Uncertainty," Energies, MDPI, vol. 16(9), pages 1-18, April.
    2. Luo, Lizi & Wu, Zhi & Gu, Wei & Huang, He & Gao, Song & Han, Jun, 2020. "Coordinated allocation of distributed generation resources and electric vehicle charging stations in distribution systems with vehicle-to-grid interaction," Energy, Elsevier, vol. 192(C).
    3. Zhao, Zhonghao & Lee, Carman K.M. & Yan, Xiaoyuan & Wang, Haonan, 2024. "Reinforcement learning for electric vehicle charging scheduling: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 190(C).
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    1. Ghanbari Motlagh, Saheb & Oladigbolu, Jamiu & Li, Li, 2025. "A review on electric vehicle charging station operation considering market dynamics and grid interaction," Applied Energy, Elsevier, vol. 392(C).
    2. Xia, Baozhou & Ye, Min & Wei, Meng & Wang, Qiao & Lian, Gaoqi & Li, Yan, 2025. "SOH estimation of lithium-ion batteries with local health indicators in multi-stage fast charging protocols," Energy, Elsevier, vol. 334(C).

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