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Optimization of the Operation and Maintenance of renewable energy systems by Deep Reinforcement Learning

Citations

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Cited by:

  1. Si, Guojin & Xia, Tangbin & Li, Yaping & Wang, Dong & Chen, Zhen & Pan, Ershun & Xi, Lifeng, 2023. "Resource allocation and maintenance scheduling for distributed multi-center renewable energy systems considering dynamic scope division," Renewable Energy, Elsevier, vol. 217(C).
  2. Pylorof, Dimitrios & Garcia, Humberto E., 2026. "Unified system intelligence: Learning energy strategies for optimizing operations, maintenance, and market outcomes," Applied Energy, Elsevier, vol. 402(PB).
  3. Cheng, Jianda & Cheng, Minghui & Liu, Yan & Wu, Jun & Li, Wei & Frangopol, Dan M., 2024. "Knowledge transfer for adaptive maintenance policy optimization in engineering fleets based on meta-reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
  4. Zhang, Bin & Hu, Weihao & Xu, Xiao & Li, Tao & Zhang, Zhenyuan & Chen, Zhe, 2022. "Physical-model-free intelligent energy management for a grid-connected hybrid wind-microturbine-PV-EV energy system via deep reinforcement learning approach," Renewable Energy, Elsevier, vol. 200(C), pages 433-448.
  5. He, Rui & Tian, Zhigang & Wang, Yifei & Zuo, Mingjian & Guo, Ziwei, 2023. "Condition-based maintenance optimization for multi-component systems considering prognostic information and degraded working efficiency," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
  6. Hao, Zhaojun & Di Maio, Francesco & Zio, Enrico, 2023. "A sequential decision problem formulation and deep reinforcement learning solution of the optimization of O&M of cyber-physical energy systems (CPESs) for reliable and safe power production and supply," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
  7. Pinciroli, Luca & Hosseini, Seyed Ali & Chen, Mei & Mesa, Maria Valentina Clavijo & Coscia, Thomas Matteo & Futalef, Juan-Pablo & Marchetti, Stefano & Miqueles, Leonardo & Menza, Santiago Taguado & Zi, 2026. "Risk assessment for modern industry," Reliability Engineering and System Safety, Elsevier, vol. 269(C).
  8. Chen, Jiangxi & Zhou, Xiaojun, 2026. "A GNN-boosted reinforcement learning framework for maintenance optimization in multi-dependency manufacturing system," Reliability Engineering and System Safety, Elsevier, vol. 269(C).
  9. Zhang, Guozhou & Hu, Weihao & Cao, Di & Zhou, Dao & Huang, Qi & Chen, Zhe & Blaabjerg, Frede, 2023. "Coordinated active and reactive power dynamic dispatch strategy for wind farms to minimize levelized production cost considering system uncertainty: A soft actor-critic approach," Renewable Energy, Elsevier, vol. 218(C).
  10. Abdulla, Hind & Sleptchenko, Andrei & Nayfeh, Ammar, 2024. "Photovoltaic systems operation and maintenance: A review and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 195(C).
  11. Sadeghian, Omid & Mohammadpour Shotorbani, Amin & Mohammadi-Ivatloo, Behnam, 2026. "Maintenance scheduling optimization in renewable and conventional power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 229(C).
  12. Zhang, Qin & Liu, Yu & Xiang, Yisha & Xiahou, Tangfan, 2024. "Reinforcement learning in reliability and maintenance optimization: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
  13. McMorland, J. & Collu, M. & McMillan, D. & Carroll, J. & Coraddu, A., 2023. "Opportunistic maintenance for offshore wind: A review and proposal of future framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
  14. Hugo Gaspar Hernandez-Palma & Vladimir Sousa Santos & Adalberto Ospino Castro & Angélica Jiménez Coronado & Roberto Morales Espinoza & Jonny Rafael Plazas Alvarado, 2024. "Sustainable Projects Based on the Intersection of Clean Energy with the Health Sector: A Bibliometric Review," International Journal of Energy Economics and Policy, Econjournals, vol. 14(3), pages 489-496, May.
  15. Saleh, Ali & Chiachío, Manuel & Salas, Juan Fernández & Kolios, Athanasios, 2023. "Self-adaptive optimized maintenance of offshore wind turbines by intelligent Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
  16. Najafi, Seyedvahid & Lee, Chi-Guhn, 2023. "A deep reinforcement learning approach for repair-based maintenance of multi-unit systems using proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
  17. Zhang, Guozhou & Hu, Weihao & Zhao, Yincheng & Cui, Zhengjie & Chen, Jianjun & Tang, Chao & Chen, Zhe, 2024. "Meta-learning and proximal policy optimization driven two-stage emergency allocation strategy for multi-energy system against typhoon disasters," Renewable Energy, Elsevier, vol. 237(PC).
  18. Antoni Guerrero & Angel A. Juan & Alvaro Garcia-Sanchez & Luis Pita-Romero, 2024. "Optimizing Maintenance of Energy Supply Systems in City Logistics with Heuristics and Reinforcement Learning," Mathematics, MDPI, vol. 12(19), pages 1-21, October.
  19. Van Giao Nguyen & Ranjna Sirohi & Minh Ho Tran & Thanh Hai Truong & Minh Thai Duong & Minh Tuan Pham & Dao Nam Cao, 2025. "Renewable energy role in low-carbon economy and net-zero goal: Perspectives and prospects," Energy & Environment, , vol. 36(5), pages 2248-2287, August.
  20. He, Yuxuan & Su, Huai & Zio, Enrico & Peng, Shiliang & Fan, Lin & Yang, Zhaoming & Yang, Zhe & Zhang, Jinjun, 2023. "A systematic method of remaining useful life estimation based on physics-informed graph neural networks with multisensor data," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
  21. Lee, Namkyoung & Woo, Joohyun & Kim, Sungryul, 2025. "A deep reinforcement learning ensemble for maintenance scheduling in offshore wind farms," Applied Energy, Elsevier, vol. 377(PA).
  22. Tao, Zijian & Zhu, Ronghua & Hu, Jiajun & Wang, Mingchuan & Chen, Qinghai & Wang, Chizhong, 2025. "A novel hierarchical failure analysis approach targeting the operation and maintenance of floating offshore wind turbines," Renewable Energy, Elsevier, vol. 241(C).
  23. Zuo, Jian & Steiner, Nadia Yousfi & Li, Zhongliang & Hissel, Daniel, 2024. "Health management review for fuel cells: Focus on action phase," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).
  24. Wu, Xiankui & Li, Penghua & Zhang, Yangming & Zhou, Jingjing & Xiang, Sheng & Hou, Jie & Wang, Guodong & Dustdar, Schahram, 2025. "Knowledge distillation-based lightweight deformable network for remaining useful life prognostics of vehicle power battery," Energy, Elsevier, vol. 337(C).
  25. Zuo, Jian & Steiner, Nadia Yousfi & Li, Zhongliang & Cadet, Catherine & Bérenguer, Christophe & Hissel, Daniel, 2025. "Reinforcement learning-based maintenance scheduling for a stochastic deteriorating fuel cell considering stack-to-stack heterogeneity," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
  26. Arsalan Masood & Ubaid Ahmed & Syed Zulqadar Hassan & Ahsan Raza Khan & Anzar Mahmood, 2025. "Economic Value Creation of Artificial Intelligence in Supporting Variable Renewable Energy Resource Integration to Power Systems: A Systematic Review," Sustainability, MDPI, vol. 17(6), pages 1-42, March.
  27. Yang, Yesen & Li, Zhengmao & Lo, Edmond Y., 2025. "Multi-timescale risk-averse restoration for interdependent water–power networks with joint reconfiguration and diverse uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
  28. He, Rui & Liu, Xingchen & Wang, Yifei & Tian, Zhigang & Zuo, Mingjian & Ye, Zhi-Sheng, 2026. "A generative modeling method to quantify the long-term benefit of neural-network-based RUL predictions to maintenance," Reliability Engineering and System Safety, Elsevier, vol. 268(C).
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