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Gigawatt-hour scale savings on a budget of zero: Deep reinforcement learning based optimal control of hot water systems

Citations

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Cited by:

  1. Ashitosh Rajesh Varne & Simon Blouin & Baxter Lorenzo McIntosh Williams & David Denkenberger, 2024. "The Impact of Abrupt Sunlight Reduction Scenarios on Renewable Energy Production," Energies, MDPI, vol. 17(20), pages 1-16, October.
  2. Baxter Williams & Daniel Bishop & Patricio Gallardo & J. Geoffrey Chase, 2023. "Demand Side Management in Industrial, Commercial, and Residential Sectors: A Review of Constraints and Considerations," Energies, MDPI, vol. 16(13), pages 1-28, July.
  3. Daeil Lee & Seoryong Koo & Inseok Jang & Jonghyun Kim, 2022. "Comparison of Deep Reinforcement Learning and PID Controllers for Automatic Cold Shutdown Operation," Energies, MDPI, vol. 15(8), pages 1-25, April.
  4. Heidari, Amirreza & Maréchal, François & Khovalyg, Dolaana, 2022. "Reinforcement Learning for proactive operation of residential energy systems by learning stochastic occupant behavior and fluctuating solar energy: Balancing comfort, hygiene and energy use," Applied Energy, Elsevier, vol. 318(C).
  5. Shen, Rendong & Zhong, Shengyuan & Wen, Xin & An, Qingsong & Zheng, Ruifan & Li, Yang & Zhao, Jun, 2022. "Multi-agent deep reinforcement learning optimization framework for building energy system with renewable energy," Applied Energy, Elsevier, vol. 312(C).
  6. Vázquez-Canteli, José R. & Nagy, Zoltán, 2019. "Reinforcement learning for demand response: A review of algorithms and modeling techniques," Applied Energy, Elsevier, vol. 235(C), pages 1072-1089.
  7. Wang, Zhe & Hong, Tianzhen, 2020. "Reinforcement learning for building controls: The opportunities and challenges," Applied Energy, Elsevier, vol. 269(C).
  8. Yin, Linfei & Xiong, Yi, 2024. "Fast-apply deep autoregressive recurrent proximal policy optimization for controlling hot water systems," Applied Energy, Elsevier, vol. 367(C).
  9. Yildiz, Baran & Bilbao, Jose I. & Roberts, Mike & Heslop, Simon & Dore, Jonathon & Bruce, Anna & MacGill, Iain & Egan, Renate J. & Sproul, Alistair B., 2021. "Analysis of electricity consumption and thermal storage of domestic electric water heating systems to utilize excess PV generation," Energy, Elsevier, vol. 235(C).
  10. Ceusters, Glenn & Rodríguez, Román Cantú & García, Alberte Bouso & Franke, Rüdiger & Deconinck, Geert & Helsen, Lieve & Nowé, Ann & Messagie, Maarten & Camargo, Luis Ramirez, 2021. "Model-predictive control and reinforcement learning in multi-energy system case studies," Applied Energy, Elsevier, vol. 303(C).
  11. Pinto, Giuseppe & Piscitelli, Marco Savino & Vázquez-Canteli, José Ramón & Nagy, Zoltán & Capozzoli, Alfonso, 2021. "Coordinated energy management for a cluster of buildings through deep reinforcement learning," Energy, Elsevier, vol. 229(C).
  12. Heidari, Amirreza & Maréchal, François & Khovalyg, Dolaana, 2022. "An occupant-centric control framework for balancing comfort, energy use and hygiene in hot water systems: A model-free reinforcement learning approach," Applied Energy, Elsevier, vol. 312(C).
  13. Chen, Zhe & Xing, Tian & Wang, Yu & Zhuang, Yunlin & Zheng, Meng & Zhao, Qianchuan & Jia, Qing-Shan, 2025. "Coupling time-scale reinforcement learning methods for building operational optimization with waste heat," Applied Energy, Elsevier, vol. 391(C).
  14. Heidari, Amirreza & Girardin, Luc & Dorsaz, Cédric & Maréchal, François, 2025. "A trustworthy reinforcement learning framework for autonomous control of a large-scale complex heating system: Simulation and field implementation," Applied Energy, Elsevier, vol. 378(PA).
  15. Kazmi, Hussain & Mehmood, Fahad & Tao, Zhenmin & Riaz, Zainab & Driesen, Johan, 2019. "Electricity load-shedding in Pakistan: Unintended consequences, opportunities and policy recommendations," Energy Policy, Elsevier, vol. 128(C), pages 411-417.
  16. Mooyoung Yoo, 2024. "Development of Energy Efficient Domestic Hot Water Loop System Integrated with a Chilled Water Plant in Commercial Building," Sustainability, MDPI, vol. 17(1), pages 1-16, December.
  17. Touzani, Samir & Prakash, Anand Krishnan & Wang, Zhe & Agarwal, Shreya & Pritoni, Marco & Kiran, Mariam & Brown, Richard & Granderson, Jessica, 2021. "Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency," Applied Energy, Elsevier, vol. 304(C).
  18. Yin, Linfei & Gao, Qi & Zhao, Lulin & Wang, Tao, 2020. "Expandable deep learning for real-time economic generation dispatch and control of three-state energies based future smart grids," Energy, Elsevier, vol. 191(C).
  19. Seppo Sierla & Heikki Ihasalo & Valeriy Vyatkin, 2022. "A Review of Reinforcement Learning Applications to Control of Heating, Ventilation and Air Conditioning Systems," Energies, MDPI, vol. 15(10), pages 1-25, May.
  20. de Gracia, Alvaro & Tarragona, Joan & Crespo, Alicia & Fernández, Cèsar, 2020. "Smart control of dynamic phase change material wall system," Applied Energy, Elsevier, vol. 279(C).
  21. Lei, Yue & Zhan, Sicheng & Ono, Eikichi & Peng, Yuzhen & Zhang, Zhiang & Hasama, Takamasa & Chong, Adrian, 2022. "A practical deep reinforcement learning framework for multivariate occupant-centric control in buildings," Applied Energy, Elsevier, vol. 324(C).
  22. Zhou, Xinlei & Du, Han & Xue, Shan & Ma, Zhenjun, 2024. "Recent advances in data mining and machine learning for enhanced building energy management," Energy, Elsevier, vol. 307(C).
  23. Perera, A.T.D. & Kamalaruban, Parameswaran, 2021. "Applications of reinforcement learning in energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
  24. Zahra Fallahi & Gregor P. Henze, 2019. "Interactive Buildings: A Review," Sustainability, MDPI, vol. 11(14), pages 1-26, July.
  25. Haji Hosseinloo, Ashkan & Ryzhov, Alexander & Bischi, Aldo & Ouerdane, Henni & Turitsyn, Konstantin & Dahleh, Munther A., 2020. "Data-driven control of micro-climate in buildings: An event-triggered reinforcement learning approach," Applied Energy, Elsevier, vol. 277(C).
  26. Correa-Jullian, Camila & López Droguett, Enrique & Cardemil, José Miguel, 2020. "Operation scheduling in a solar thermal system: A reinforcement learning-based framework," Applied Energy, Elsevier, vol. 268(C).
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