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Game-based scheduling of mobile charging robots for electric vehicle charging: A relay-like scheme

Author

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  • Fang, Qiuyang
  • Zhang, Chunyan
  • Wang, Chen
  • Xie, Guangming
  • Zhang, Jianlei

Abstract

The growing demand for electric-vehicle (EV) charging poses substantial challenges for power grids. In response, mobile charging robots (MCRs) have emerged as a promising solution for flexible, on-demand energy delivery. This paper proposes a novel relay-like EV-charging scheme for public parking facilities, in which long-duration charging tasks are decomposed into sequential time slots and collaboratively managed by multiple MCRs. The coordination problem is cast as an overlapping coalition formation (OCF) game with a holistic-altruistic preference order, enabling MCRs to autonomously allocate energy and cooperatively fulfill charging tasks while balancing self-interest and social welfare. Based on this framework, we develop a simulated annealing–inspired, decentralized OCF (SA-OCF) algorithm that effectively explores the solution space under stringent energy and time-window constraints and converges to a stable overlapping coalition structure. Simulation results show that the proposed approach outperforms baseline methods in social welfare and energy delivered. Furthermore, the algorithm exhibits strong scalability across scenarios with heterogeneous EV-charging behaviors.

Suggested Citation

  • Fang, Qiuyang & Zhang, Chunyan & Wang, Chen & Xie, Guangming & Zhang, Jianlei, 2026. "Game-based scheduling of mobile charging robots for electric vehicle charging: A relay-like scheme," Applied Energy, Elsevier, vol. 402(PB).
    • Handle: RePEc:eee:appene:v:402:y:2026:i:pb:s0306261925016861
    DOI: 10.1016/j.apenergy.2025.126956
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    References listed on IDEAS

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    1. Zhao, Zhonghao & Lee, Carman K.M. & Huo, Jiage, 2023. "EV charging station deployment on coupled transportation and power distribution networks via reinforcement learning," Energy, Elsevier, vol. 267(C).
    2. Jinyue Yan & Ying Yang & Pietro Elia Campana & Jijiang He, 2019. "City-level analysis of subsidy-free solar photovoltaic electricity price, profits and grid parity in China," Nature Energy, Nature, vol. 4(8), pages 709-717, August.
    3. Zhaojie Wang & Feifeng Zheng & Ming Liu, 2025. "Charging Scheduling of Electric Vehicles Considering Uncertain Arrival Times and Time-of-Use Price," Sustainability, MDPI, vol. 17(3), pages 1-22, January.
    4. Ouyang, Kechen & Wang, David Z.W., 2025. "Optimal operation strategies for freight transport with electric vehicles considering wireless charging lanes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 193(C).
    5. Park, Keonwoo & Moon, Ilkyeong, 2022. "Multi-agent deep reinforcement learning approach for EV charging scheduling in a smart grid," Applied Energy, Elsevier, vol. 328(C).
    6. Wang, Dawei & Guo, Jingwei & Zhang, Yongxiang & Zhong, Qingwei & Xu, Hongke, 2025. "Optimizing expressway battery electric vehicle charging and mobile storage energy truck scheduling: A two-stage approach to improve photovoltaic generation utilization," Energy, Elsevier, vol. 320(C).
    7. An, Sihai & Qiu, Jing & Lin, Jiafeng & Yao, Zongyu & Liang, Qijun & Lu, Xin, 2025. "Planning of a multi-agent mobile robot-based adaptive charging network for enhancing power system resilience under extreme conditions," Applied Energy, Elsevier, vol. 395(C).
    8. Ameer, Hamza & Wang, Yujie & Fan, Xiaofei & Chen, Zonghai, 2025. "Hybrid optimization of EV charging station placement and pricing using Bender’s decomposition and NSGA-II algorithm," Applied Energy, Elsevier, vol. 397(C).
    9. Afshar, Shahab & Pecenak, Zachary K. & Barati, Masoud & Disfani, Vahid, 2022. "Mobile charging stations for EV charging management in urban areas: A case study in Chattanooga," Applied Energy, Elsevier, vol. 325(C).
    10. Steffen Limmer, 2019. "Dynamic Pricing for Electric Vehicle Charging—A Literature Review," Energies, MDPI, vol. 12(18), pages 1-24, September.
    11. He, Xiaoping & Jiang, Shuo & Yu, Yuxuan & Su, Siyi, 2025. "Impact of novel infrastructure investments on productivity: Evidence from public procurement of EV charging facilities in China," Energy, Elsevier, vol. 334(C).
    12. Cui, Jingshi & Jiang, Wenqian & Wu, Chenye, 2025. "Pricing mechanism design for future EV charging station with hybrid fixed and mobile charging modes," Applied Energy, Elsevier, vol. 380(C).
    13. Graber, Giuseppe & Calderaro, Vito & Mancarella, Pierluigi & Galdi, Vincenzo, 2020. "Two-stage stochastic sizing and packetized energy scheduling of BEV charging stations with quality of service constraints," Applied Energy, Elsevier, vol. 260(C).
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