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Optimal energy management strategies for energy Internet via deep reinforcement learning approach

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  1. Qiang Shuai & Yue Yin & Shan Huang & Chao Chen, 2025. "Deep Reinforcement Learning-Based Real-Time Energy Management for an Integrated Electric–Thermal Energy System," Sustainability, MDPI, vol. 17(2), pages 1-17, January.
  2. Gideon Ude Nnachi & Yskandar Hamam & Coneth Graham Richards, 2022. "Appraising the Optimal Power Flow and Generation Capacity in Existing Power Grid Topology with Increase in Energy Demand," Energies, MDPI, vol. 15(7), pages 1-23, March.
  3. Xue, Lin & Wang, Jianxue & Zhang, Yao & Yong, Weizhen & Qi, Jie & Li, Haotian, 2023. "Model-data-event based community integrated energy system low-carbon economic scheduling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
  4. Samuel-Soma M. Ajibade & Festus Victor Bekun & Festus Fatai Adedoyin & Bright Akwasi Gyamfi & Anthonia Oluwatosin Adediran, 2023. "Machine Learning Applications in Renewable Energy (MLARE) Research: A Publication Trend and Bibliometric Analysis Study (2012–2021)," Clean Technol., MDPI, vol. 5(2), pages 1-21, April.
  5. 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.
  6. 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).
  7. Zhang, Yijie & Ma, Tao & Yang, Hongxing, 2022. "Grid-connected photovoltaic battery systems: A comprehensive review and perspectives," Applied Energy, Elsevier, vol. 328(C).
  8. Sasidhar, Punyam Rajendran Sai & Gebremedhin, Alemayehu & Norheim, Ian, 2025. "Multi-energy microgrid design and the role of coupling components—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 216(C).
  9. Di Liu & Junwei Cao & Mingshuang Liu, 2022. "Joint Optimization of Energy Storage Sharing and Demand Response in Microgrid Considering Multiple Uncertainties," Energies, MDPI, vol. 15(9), pages 1-20, April.
  10. Qi, Yunying & Xu, Xiao & Liu, Youbo & Pan, Li & Liu, Junyong & Hu, Weihao, 2024. "Intelligent energy management for an on-grid hydrogen refueling station based on dueling double deep Q network algorithm with NoisyNet," Renewable Energy, Elsevier, vol. 222(C).
  11. Malin Song & Heting Pan & Michael Vardanyan & Zhiyang Shen, 2023. "Evaluating the energy efficiency-enhancing potential of the digital economy: Evidence from China," Post-Print hal-04277444, HAL.
  12. Mauricio de Castro Tomé & Pedro H. J. Nardelli & Hafiz Majid Hussain & Sohail Wahid & Arun Narayanan, 2020. "A Cyber-Physical Residential Energy Management System via Virtualized Packets," Energies, MDPI, vol. 13(3), pages 1-18, February.
  13. Yuzhu Liang & Xiaotong Bi & Ruihan Shen & Zhengyang He & Yuqi Wang & Juntao Xu & Yao Zhang & Xinggang Fan, 2025. "When Mathematical Methods Meet Artificial Intelligence and Mobile Edge Computing," Mathematics, MDPI, vol. 13(11), pages 1-38, May.
  14. Shi, Tao & Xu, Chang & Dong, Wenhao & Zhou, Hangyu & Bokhari, Awais & Klemeš, Jiří Jaromír & Han, Ning, 2023. "Research on energy management of hydrogen electric coupling system based on deep reinforcement learning," Energy, Elsevier, vol. 282(C).
  15. Liu, Tianhao & Shan, Linke & Jiang, Meihui & Li, Fangning & Kong, Fannie & Du, Pengcheng & Zhu, Hongyu & Goh, Hui Hwang & Kurniawan, Tonni Agustiono & Huang, Chao & Zhang, Dongdong, 2025. "Multi-dimensional data processing and intelligent forecasting technologies for renewable energy generation," Applied Energy, Elsevier, vol. 398(C).
  16. Junwei Cao & Wanlu Zhang & Zeqing Xiao & Haochen Hua, 2019. "Reactive Power Optimization for Transient Voltage Stability in Energy Internet via Deep Reinforcement Learning Approach," Energies, MDPI, vol. 12(8), pages 1-17, April.
  17. Qi, Chunyang & Zhu, Yiwen & Song, Chuanxue & Yan, Guangfu & Xiao, Feng & Da wang, & Zhang, Xu & Cao, Jingwei & Song, Shixin, 2022. "Hierarchical reinforcement learning based energy management strategy for hybrid electric vehicle," Energy, Elsevier, vol. 238(PA).
  18. Guo, Sheng & Yang, Tao & Hua, Haochen & Cao, Junwei, 2021. "Coupling fault diagnosis of wind turbine gearbox based on multitask parallel convolutional neural networks with overall information," Renewable Energy, Elsevier, vol. 178(C), pages 639-650.
  19. Florentina Magda Enescu & Nicu Bizon & Adrian Onu & Maria Simona Răboacă & Phatiphat Thounthong & Alin Gheorghita Mazare & Gheorghe Șerban, 2020. "Implementing Blockchain Technology in Irrigation Systems That Integrate Photovoltaic Energy Generation Systems," Sustainability, MDPI, vol. 12(4), pages 1-30, February.
  20. Akhil Joseph & Patil Balachandra, 2020. "Energy Internet, the Future Electricity System: Overview, Concept, Model Structure, and Mechanism," Energies, MDPI, vol. 13(16), pages 1-26, August.
  21. 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).
  22. Liu, Di & Qin, Zhaoming & Hua, Haochen & Ding, Yi & Cao, Junwei, 2023. "Incremental incentive mechanism design for diversified consumers in demand response," Applied Energy, Elsevier, vol. 329(C).
  23. Qiu, Dawei & Ye, Yujian & Papadaskalopoulos, Dimitrios & Strbac, Goran, 2021. "Scalable coordinated management of peer-to-peer energy trading: A multi-cluster deep reinforcement learning approach," Applied Energy, Elsevier, vol. 292(C).
  24. Ma, Tao & Zhang, Yijie & Gu, Wenbo & Xiao, Gang & Yang, Hongxing & Wang, Shuxiao, 2022. "Strategy comparison and techno-economic evaluation of a grid-connected photovoltaic-battery system," Renewable Energy, Elsevier, vol. 197(C), pages 1049-1060.
  25. Zhu, Jiaoyiling & Hu, Weihao & Xu, Xiao & Liu, Haoming & Pan, Li & Fan, Haoyang & Zhang, Zhenyuan & Chen, Zhe, 2022. "Optimal scheduling of a wind energy dominated distribution network via a deep reinforcement learning approach," Renewable Energy, Elsevier, vol. 201(P1), pages 792-801.
  26. Yi Kuang & Xiuli Wang & Hongyang Zhao & Yijun Huang & Xianlong Chen & Xifan Wang, 2020. "Agent-Based Energy Sharing Mechanism Using Deep Deterministic Policy Gradient Algorithm," Energies, MDPI, vol. 13(19), pages 1-20, September.
  27. Li, Yang & Ma, Wenjie & Li, Yuanzheng & Li, Sen & Chen, Zhe & Shahidehpour, Mohammad, 2025. "Enhancing cyber-resilience in integrated energy system scheduling with demand response using deep reinforcement learning," Applied Energy, Elsevier, vol. 379(C).
  28. Zhang, Yijie & Ma, Tao & Elia Campana, Pietro & Yamaguchi, Yohei & Dai, Yanjun, 2020. "A techno-economic sizing method for grid-connected household photovoltaic battery systems," Applied Energy, Elsevier, vol. 269(C).
  29. 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).
  30. Zhang, Wei & Wang, Jixin & Xu, Zhenyu & Shen, Yuying & Gao, Guangzong, 2022. "A generalized energy management framework for hybrid construction vehicles via model-based reinforcement learning," Energy, Elsevier, vol. 260(C).
  31. Du, Yan & Zandi, Helia & Kotevska, Olivera & Kurte, Kuldeep & Munk, Jeffery & Amasyali, Kadir & Mckee, Evan & Li, Fangxing, 2021. "Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning," Applied Energy, Elsevier, vol. 281(C).
  32. 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).
  33. József Magyari & Krisztina Hegedüs & Botond Sinóros-Szabó, 2022. "Integration Opportunities of Power-to-Gas and Internet-of-Things Technical Advancements: A Systematic Literature Review," Energies, MDPI, vol. 15(19), pages 1-19, September.
  34. Ahmad, Tanveer & Chen, Huanxin, 2019. "Deep learning for multi-scale smart energy forecasting," Energy, Elsevier, vol. 175(C), pages 98-112.
  35. Seongwoo Lee & Joonho Seon & Byungsun Hwang & Soohyun Kim & Youngghyu Sun & Jinyoung Kim, 2024. "Recent Trends and Issues of Energy Management Systems Using Machine Learning," Energies, MDPI, vol. 17(3), pages 1-24, January.
  36. Shi, Zhongtuo & Yao, Wei & Li, Zhouping & Zeng, Lingkang & Zhao, Yifan & Zhang, Runfeng & Tang, Yong & Wen, Jinyu, 2020. "Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions," Applied Energy, Elsevier, vol. 278(C).
  37. Mendiola-Rodriguez, Tannia A. & Ricardez-Sandoval, Luis A., 2023. "Integration of design and control for renewable energy systems with an application to anaerobic digestion: A deep deterministic policy gradient framework," Energy, Elsevier, vol. 274(C).
  38. Yang, Ting & Zhao, Liyuan & Li, Wei & Wu, Jianzhong & Zomaya, Albert Y., 2021. "Towards healthy and cost-effective indoor environment management in smart homes: A deep reinforcement learning approach," Applied Energy, Elsevier, vol. 300(C).
  39. Jingbo Zhao & Zhengping Gao & Zhe Chen, 2025. "Energy Management of Electric–Hydrogen Coupled Integrated Energy System Based on Improved Proximal Policy Optimization Algorithm," Energies, MDPI, vol. 18(15), pages 1-17, July.
  40. Hassam Ishfaq & Sania Kanwal & Sadeed Anwar & Mubarak Abdussalam & Waqas Amin, 2025. "Enhancing Smart Grid Security and Efficiency: AI, Energy Routing, and T&D Innovations (A Review)," Energies, MDPI, vol. 18(17), pages 1-77, September.
  41. Mahmud, Sadab & Ponkiya, Binaka & Katikaneni, Sravya & Pandey, Srijana & Mattimadugu, Kranthikiran & Yi, Zonggen & Walker, Victor & Wang, Congjian & Westover, Tyler & Javaid, Ahmad Y. & Heben, Michael, 2024. "Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources," Energy, Elsevier, vol. 313(C).
  42. Zeyue Sun & Mohsen Eskandari & Chaoran Zheng & Ming Li, 2022. "Handling Computation Hardness and Time Complexity Issue of Battery Energy Storage Scheduling in Microgrids by Deep Reinforcement Learning," Energies, MDPI, vol. 16(1), pages 1-20, December.
  43. Sajjad Miran & Muhammad Tamoor & Tayybah Kiren & Faakhar Raza & Muhammad Imtiaz Hussain & Jun-Tae Kim, 2022. "Optimization of Standalone Photovoltaic Drip Irrigation System: A Simulation Study," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
  44. Kandasamy, Jeevitha & Ramachandran, Rajeswari & Veerasamy, Veerapandiyan & Irudayaraj, Andrew Xavier Raj, 2024. "Distributed leader-follower based adaptive consensus control for networked microgrids," Applied Energy, Elsevier, vol. 353(PA).
  45. Li, Yutong & Hou, Jian & Yan, Gangfeng, 2024. "Exploration-enhanced multi-agent reinforcement learning for distributed PV-ESS scheduling with incomplete data," Applied Energy, Elsevier, vol. 359(C).
  46. Haochen Hua & Yuchao Qin & Hanxuan Xu & Chuantong Hao & Junwei Cao, 2019. "Robust Control Method for DC Microgrids and Energy Routers to Improve Voltage Stability in Energy Internet," Energies, MDPI, vol. 12(9), pages 1-17, April.
  47. Dingyi Guo & Guangyin Lei & Huichao Zhao & Fang Yang & Qiang Zhang, 2024. "Quadruple Deep Q-Network-Based Energy Management Strategy for Plug-In Hybrid Electric Vehicles," Energies, MDPI, vol. 17(24), pages 1-21, December.
  48. Qi, Chunyang & Song, Chuanxue & Xiao, Feng & Song, Shixin, 2022. "Generalization ability of hybrid electric vehicle energy management strategy based on reinforcement learning method," Energy, Elsevier, vol. 250(C).
  49. Kang, Dongju & Kang, Doeun & Hwangbo, Sumin & Niaz, Haider & Lee, Won Bo & Liu, J. Jay & Na, Jonggeol, 2023. "Optimal planning of hybrid energy storage systems using curtailed renewable energy through deep reinforcement learning," Energy, Elsevier, vol. 284(C).
  50. Jeong, Jaeik & Kim, Hongseok, 2021. "DeepComp: Deep reinforcement learning based renewable energy error compensable forecasting," Applied Energy, Elsevier, vol. 294(C).
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