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Real-time optimal energy management of microgrid with uncertainties based on deep reinforcement learning

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  1. Alzahrani, Ahmad & Sajjad, Khizar & Hafeez, Ghulam & Murawwat, Sadia & Khan, Sheraz & Khan, Farrukh Aslam, 2023. "Real-time energy optimization and scheduling of buildings integrated with renewable microgrid," Applied Energy, Elsevier, vol. 335(C).
  2. Alireza Gorjian & Mohsen Eskandari & Mohammad H. Moradi, 2023. "Conservation Voltage Reduction in Modern Power Systems: Applications, Implementation, Quantification, and AI-Assisted Techniques," Energies, MDPI, vol. 16(5), pages 1-36, March.
  3. Amine, Hartani Mohamed & Aissa, Benhammou & Rezk, Hegazy & Messaoud, Hamouda & Othmane, Adbdelkhalek & Saad, Mekhilef & Abdelkareem, Mohammad Ali, 2023. "Enhancing hybrid energy storage systems with advanced low-pass filtration and frequency decoupling for optimal power allocation and reliability of cluster of DC-microgrids," Energy, Elsevier, vol. 282(C).
  4. Yang, Jingxian & Liu, Junyong & Qiu, Gao & Liu, Jichun & Jawad, Shafqat & Zhang, Shuai, 2023. "A spatio-temporality-enabled parallel multi-agent-based real-time dynamic dispatch for hydro-PV-PHS integrated power system," Energy, Elsevier, vol. 278(PB).
  5. Qiu, Dawei & Wang, Yi & Hua, Weiqi & Strbac, Goran, 2023. "Reinforcement learning for electric vehicle applications in power systems:A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
  6. Xue, Lin & Zhang, Yao & Wang, Jianxue & Li, Haotian & Li, Fangshi, 2024. "Privacy-preserving multi-level co-regulation of VPPs via hierarchical safe deep reinforcement learning," Applied Energy, Elsevier, vol. 371(C).
  7. Jia, Bin & Li, Fan & Sun, Bo, 2024. "Knowledge-network-embedded deep reinforcement learning: An innovative way to high-efficiently develop an energy management strategy for the integrated energy system with renewable energy sources and m," Energy, Elsevier, vol. 301(C).
  8. Wang, Yijian & Cui, Yang & Li, Yang & Xu, Yang, 2023. "Collaborative optimization of multi-microgrids system with shared energy storage based on multi-agent stochastic game and reinforcement learning," Energy, Elsevier, vol. 280(C).
  9. Zhu, Ziqing & Hu, Ze & Chan, Ka Wing & Bu, Siqi & Zhou, Bin & Xia, Shiwei, 2023. "Reinforcement learning in deregulated energy market: A comprehensive review," Applied Energy, Elsevier, vol. 329(C).
  10. Lu, Yu & Xiang, Yue & Huang, Yuan & Yu, Bin & Weng, Liguo & Liu, Junyong, 2023. "Deep reinforcement learning based optimal scheduling of active distribution system considering distributed generation, energy storage and flexible load," Energy, Elsevier, vol. 271(C).
  11. Yuwei, Liu & Li, Lingling & Jiaqi, Liu, 2024. "Hybrid scheduling strategy and improved marine predator optimizer for energy scheduling in integrated energy system to enhance economic and environmental protection capability," Renewable Energy, Elsevier, vol. 228(C).
  12. Hong, Yejin & Yoon, Sungmin & Choi, Sebin, 2023. "Operational signature-based symbolic hierarchical clustering for building energy, operation, and efficiency towards carbon neutrality," Energy, Elsevier, vol. 265(C).
  13. Wang, Yi & Qiu, Dawei & Sun, Mingyang & Strbac, Goran & Gao, Zhiwei, 2023. "Secure energy management of multi-energy microgrid: A physical-informed safe reinforcement learning approach," Applied Energy, Elsevier, vol. 335(C).
  14. Wilson Pavon & Esteban Inga & Silvio Simani & Maddalena Nonato, 2021. "A Review on Optimal Control for the Smart Grid Electrical Substation Enhancing Transition Stability," Energies, MDPI, vol. 14(24), pages 1-15, December.
  15. Khawaja Haider Ali & Mohammad Abusara & Asif Ali Tahir & Saptarshi Das, 2023. "Dual-Layer Q-Learning Strategy for Energy Management of Battery Storage in Grid-Connected Microgrids," Energies, MDPI, vol. 16(3), pages 1-17, January.
  16. Bio Gassi, Karim & Baysal, Mustafa, 2023. "Improving real-time energy decision-making model with an actor-critic agent in modern microgrids with energy storage devices," Energy, Elsevier, vol. 263(PE).
  17. Mi, Hanning & Chen, Sijie & Li, Qingxin & Shi, Ming & Hou, Shuoming & Zheng, Linfeng & Xu, Chengke & Yan, Zheng & Li, Canbing, 2024. "Strategic bidding by predicting locational marginal price with aggregated supply curve," Energy, Elsevier, vol. 304(C).
  18. Zhou, Yanting & Ma, Zhongjing & Zhang, Jinhui & Zou, Suli, 2022. "Data-driven stochastic energy management of multi energy system using deep reinforcement learning," Energy, Elsevier, vol. 261(PA).
  19. Soleimanzade, Mohammad Amin & Kumar, Amit & Sadrzadeh, Mohtada, 2022. "Novel data-driven energy management of a hybrid photovoltaic-reverse osmosis desalination system using deep reinforcement learning," Applied Energy, Elsevier, vol. 317(C).
  20. Omar Al-Ani & Sanjoy Das, 2022. "Reinforcement Learning: Theory and Applications in HEMS," Energies, MDPI, vol. 15(17), pages 1-37, September.
  21. Wang, Can & Zhang, Jiaheng & Wang, Aoqi & Wang, Zhen & Yang, Nan & Zhao, Zhuoli & Lai, Chun Sing & Lai, Loi Lei, 2024. "Prioritized sum-tree experience replay TD3 DRL-based online energy management of a residential microgrid," Applied Energy, Elsevier, vol. 368(C).
  22. Zhu, Dafeng & Yang, Bo & Liu, Yuxiang & Wang, Zhaojian & Ma, Kai & Guan, Xinping, 2022. "Energy management based on multi-agent deep reinforcement learning for a multi-energy industrial park," Applied Energy, Elsevier, vol. 311(C).
  23. Yin, Linfei & Li, Yu, 2022. "Hybrid multi-agent emotional deep Q network for generation control of multi-area integrated energy systems," Applied Energy, Elsevier, vol. 324(C).
  24. Fan, Likang & Wang, Jun & Peng, Yiqiang & Sun, Hongwei & Bao, Xiuchao & Zeng, Baoquan & Wei, Hongqian, 2024. "Real-time energy management strategy with dynamically updating equivalence factor for through-the-road (TTR) hybrid vehicles," Energy, Elsevier, vol. 298(C).
  25. Seyed Hasan Mirbarati & Najme Heidari & Amirhossein Nikoofard & Mir Sayed Shah Danish & Mahdi Khosravy, 2022. "Techno-Economic-Environmental Energy Management of a Micro-Grid: A Mixed-Integer Linear Programming Approach," Sustainability, MDPI, vol. 14(22), pages 1-14, November.
  26. 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).
  27. Dimitrios Vamvakas & Panagiotis Michailidis & Christos Korkas & Elias Kosmatopoulos, 2023. "Review and Evaluation of Reinforcement Learning Frameworks on Smart Grid Applications," Energies, MDPI, vol. 16(14), pages 1-38, July.
  28. Pinciroli, Luca & Baraldi, Piero & Compare, Michele & Zio, Enrico, 2023. "Optimal operation and maintenance of energy storage systems in grid-connected microgrids by deep reinforcement learning," Applied Energy, Elsevier, vol. 352(C).
  29. Zhang, Bin & Wu, Xuewei & Ghias, Amer M.Y.M. & Chen, Zhe, 2023. "Coordinated carbon capture systems and power-to-gas dynamic economic energy dispatch strategy for electricity–gas coupled systems considering system uncertainty: An improved soft actor–critic approach," Energy, Elsevier, vol. 271(C).
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