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Multi-agent deep reinforcement learning approach for EV charging scheduling in a smart grid

Citations

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Cited by:

  1. Park, Junseok & Moon, Ilkyeong, 2023. "A facility location problem in a mixed duopoly on networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
  2. Emily van Huffelen & Roel Brouwer & Marjan van den Akker, 2025. "Grid-Constrained Online Scheduling of Flexible Electric Vehicle Charging," Energies, MDPI, vol. 18(19), pages 1-20, September.
  3. Hajialigol, Parisa & Nweye, Kingsley & Aghaei, Mohammadreza & Najafi, Behzad & Moazami, Amin & Nagy, Zoltan, 2025. "Enhancing self-consumption ratio in a smart microgrid by applying a reinforcement learning-based energy management system," Energy, Elsevier, vol. 335(C).
  4. Niphon Kaewdornhan & Chitchai Srithapon & Rittichai Liemthong & Rongrit Chatthaworn, 2023. "Real-Time Multi-Home Energy Management with EV Charging Scheduling Using Multi-Agent Deep Reinforcement Learning Optimization," Energies, MDPI, vol. 16(5), pages 1-25, March.
  5. Yang, Meng & Chen, Yue & Huang, Shihan & Chen, Laijun, 2025. "Recent advances in coordination and optimization of power-transportation systems: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 220(C).
  6. Li, Yujing & Zhang, Zhisheng & Xing, Qiang, 2025. "Real-time online charging control of electric vehicle charging station based on a multi-agent deep reinforcement learning," Energy, Elsevier, vol. 319(C).
  7. Hongbin Sun & Zhenyu Duan & Anyun Yang, 2024. "Microgrid Optimization Strategy for Charging and Swapping Power Stations with New Energy Based on Multi-Agent Reinforcement Learning," Sustainability, MDPI, vol. 16(23), pages 1-19, December.
  8. Jiankai Gao & Yang Li & Bin Wang & Haibo Wu, 2023. "Multi-Microgrid Collaborative Optimization Scheduling Using an Improved Multi-Agent Soft Actor-Critic Algorithm," Energies, MDPI, vol. 16(7), pages 1-21, April.
  9. Panagiotis Michailidis & Iakovos Michailidis & Elias Kosmatopoulos, 2025. "Reinforcement Learning for Electric Vehicle Charging Management: Theory and Applications," Energies, MDPI, vol. 18(19), pages 1-50, October.
  10. 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).
  11. Chen, Guibin & Yang, Lun & Cao, Xiaoyu, 2025. "A deep reinforcement learning-based charging scheduling approach with augmented Lagrangian for electric vehicles," Applied Energy, Elsevier, vol. 378(PA).
  12. Yin, Wanjun & Ji, Jianbo, 2025. "Prediction of EV charging load based on federated learning," Energy, Elsevier, vol. 316(C).
  13. Zhao, Zhonghao & Lee, Carman K.M. & Ren, Jingzheng, 2024. "A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile," Applied Energy, Elsevier, vol. 355(C).
  14. Çakıl, Fatih & Aksoy, Necati, 2025. "Reinforcement learning-based multi-objective smart energy management for electric vehicle charging stations with priority scheduling," Energy, Elsevier, vol. 322(C).
  15. Abid, Md. Shadman & Apon, Hasan Jamil & Hossain, Salman & Ahmed, Ashik & Ahshan, Razzaqul & Lipu, M.S. Hossain, 2024. "A novel multi-objective optimization based multi-agent deep reinforcement learning approach for microgrid resources planning," Applied Energy, Elsevier, vol. 353(PA).
  16. Zhang, Fan & Lv, Huitao & Liu, Yang & Yang, Ying & Wong, Melvin & Qu, Xiaobo, 2025. "Optimizing battery-swapping systems management for electric micro-mobility: A reinforcement learning approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 195(C).
  17. Truong, Van Binh & Le, Long Bao, 2024. "Electric vehicle charging design: The factored action based reinforcement learning approach," Applied Energy, Elsevier, vol. 359(C).
  18. Cheng, Xiu & Li, Wenbo & Yang, Jiameng & Zhang, Linling, 2023. "How convenience and informational tools shape waste separation behavior: A social network approach," Resources Policy, Elsevier, vol. 86(PB).
  19. Song, Ge & Xie, Hongbin & Zhang, Jingyuan & Fu, Hongdi & Shi, Zhuoran & Feng, Defan & Song, Xuan & Zhang, Haoran, 2025. "Long-term efficient energy management for multi-station collaborative electric vehicle charging: A transformer-based multi-agent reinforcement learning approach," Applied Energy, Elsevier, vol. 397(C).
  20. Zhou, Yanting & Ma, Zhongjing & Shi, Xingyu & Zou, Suli, 2024. "Multi-agent optimal scheduling for integrated energy system considering the global carbon emission constraint," Energy, Elsevier, vol. 288(C).
  21. Lin, Mingqiang & Zhong, Ming & Meng, Jinhao & Wang, Wei & Wu, Ji, 2025. "EV charging scheduling under limited charging constraints by an improve proximal policy optimization algorithm," Energy, Elsevier, vol. 333(C).
  22. Cao, Tingwei & Xu, Yinliang & Liu, Guowei & Tao, Shengyu & Tang, Wenjun & Sun, Hongbin, 2024. "Feature-enhanced deep learning method for electric vehicle charging demand probabilistic forecasting of charging station," Applied Energy, Elsevier, vol. 371(C).
  23. P, Balakumar & Ramu, Senthil Kumar & T, Vinopraba, 2024. "Optimizing electric vehicle charging in distribution networks: A dynamic pricing approach using internet of things and Bi-directional LSTM model," Energy, Elsevier, vol. 294(C).
  24. 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.
  25. Xu, Xuesong & Xu, Kai & Zeng, Ziyang & Tang, Jiale & He, Yuanxing & Shi, Guangze & Zhang, Tao, 2024. "Collaborative optimization of multi-energy multi-microgrid system: A hierarchical trust-region multi-agent reinforcement learning approach," Applied Energy, Elsevier, vol. 375(C).
  26. Zhang, Tianren & Huang, Yuping & Liao, Hui & Liang, Yu, 2023. "A hybrid electric vehicle load classification and forecasting approach based on GBDT algorithm and temporal convolutional network," Applied Energy, Elsevier, vol. 351(C).
  27. Xu, Hairun & Zhang, Ao & Wang, Qingle & Hu, Yang & Fang, Fang & Cheng, Long, 2025. "Quantum Reinforcement Learning for real-time optimization in Electric Vehicle charging systems," Applied Energy, Elsevier, vol. 383(C).
  28. 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).
  29. Dan, Zhaohui & Zhou, Bingling & Zhou, Yuekuan, 2025. "Optimal infrastructures and integrative energy networks for sustainable and energy-resilient city renaissance," Applied Energy, Elsevier, vol. 387(C).
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