IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v238y2019icp466-480.html
   My bibliography  Save this item

Real time optimal control of district cooling system with thermal energy storage using neural networks

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Joe, Jaewan & Karava, Panagiota, 2019. "A model predictive control strategy to optimize the performance of radiant floor heating and cooling systems in office buildings," Applied Energy, Elsevier, vol. 245(C), pages 65-77.
  2. Jia, Lizhi & Liu, Junjie & Chong, Adrian & Dai, Xilei, 2022. "Deep learning and physics-based modeling for the optimization of ice-based thermal energy systems in cooling plants," Applied Energy, Elsevier, vol. 322(C).
  3. Lago, Jesus & De Ridder, Fjo & Mazairac, Wiet & De Schutter, Bart, 2019. "A 1-dimensional continuous and smooth model for thermally stratified storage tanks including mixing and buoyancy," Applied Energy, Elsevier, vol. 248(C), pages 640-655.
  4. Mu, Yunfei & Xu, Yanze & Zhang, Jiarui & Wu, Zeqing & Jia, Hongjie & Jin, Xiaolong & Qi, Yan, 2023. "A data-driven rolling optimization control approach for building energy systems that integrate virtual energy storage systems," Applied Energy, Elsevier, vol. 346(C).
  5. He, Zhaoyu & Guo, Weimin & Zhang, Peng, 2022. "Performance prediction, optimal design and operational control of thermal energy storage using artificial intelligence methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
  6. Eddouibi, Jaouad & Abderafi, Souad & Vaudreuil, Sébastien & Bounahmidi, Tijani, 2022. "Dynamic simulation of solar-powered ORC using open-source tools: A case study combining SAM and coolprop via Python," Energy, Elsevier, vol. 239(PA).
  7. Neri, Manfredi & Guelpa, Elisa & Verda, Vittorio, 2022. "Design and connection optimization of a district cooling network: Mixed integer programming and heuristic approach," Applied Energy, Elsevier, vol. 306(PA).
  8. Mingfei Wang & Wengang Zheng & Chunjiang Zhao & Yang Chen & Chunling Chen & Xin Zhang, 2023. "Energy-Saving Control Method for Factory Mushroom Room Air Conditioning Based on MPC," Energies, MDPI, vol. 16(22), pages 1-14, November.
  9. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu, 2023. "Globally optimal control of hybrid chilled water plants integrated with small-scale thermal energy storage for energy-efficient operation," Energy, Elsevier, vol. 262(PA).
  10. Yan, Biao & Yang, Wansheng & He, Fuquan & Huang, Kehua & Zeng, Wenhao & Zhang, Wenlong & Ye, Haiseng, 2022. "Strategical district cooling system operation in hub airport terminals, a research focusing on COVID-19 pandemic impact," Energy, Elsevier, vol. 255(C).
  11. Heine, Karl & Tabares-Velasco, Paulo Cesar & Deru, Michael, 2023. "Optimizing mixed cool thermal storage systems across a connected community," Energy, Elsevier, vol. 285(C).
  12. Cao, Hui & Lin, Jiajing & Li, Nan, 2023. "Optimal control and energy efficiency evaluation of district ice storage system," Energy, Elsevier, vol. 276(C).
  13. Maria Ferrara & Matteo Bilardo & Dragos-Ioan Bogatu & Doyun Lee & Mahmood Khatibi & Samira Rahnama & Jun Shinoda & Ying Sun & Yongjun Sun & Alireza Afshari & Fariborz Haghighat & Ongun B. Kazanci & Ry, 2024. "Review on Advanced Storage Control Applied to Optimized Operation of Energy Systems for Buildings and Districts: Insights and Perspectives," Energies, MDPI, vol. 17(14), pages 1-26, July.
  14. Coccia, Gianluca & Mugnini, Alice & Polonara, Fabio & Arteconi, Alessia, 2021. "Artificial-neural-network-based model predictive control to exploit energy flexibility in multi-energy systems comprising district cooling," Energy, Elsevier, vol. 222(C).
  15. Yang, Weijia & Huang, Yuping & Zhao, Daiqing, 2023. "A coupled hydraulic–thermal dynamic model for the steam network in a heat–electricity integrated energy system," Energy, Elsevier, vol. 263(PC).
  16. Zhang, Wei & Hong, Wenpeng & Jin, Xu, 2022. "Research on performance and control strategy of multi-cold source district cooling system," Energy, Elsevier, vol. 239(PB).
  17. Hou, Guolian & Xiong, Jian & Zhou, Guiping & Gong, Linjuan & Huang, Congzhi & Wang, Shunjiang, 2021. "Coordinated control system modeling of ultra-supercritical unit based on a new fuzzy neural network," Energy, Elsevier, vol. 234(C).
  18. Athanasios Anagnostis & Serafeim Moustakidis & Elpiniki Papageorgiou & Dionysis Bochtis, 2022. "A Hybrid Bimodal LSTM Architecture for Cascading Thermal Energy Storage Modelling," Energies, MDPI, vol. 15(6), pages 1-24, March.
  19. Dongsu Kim & Yongjun Lee & Kyungil Chin & Pedro J. Mago & Heejin Cho & Jian Zhang, 2023. "Implementation of a Long Short-Term Memory Transfer Learning (LSTM-TL)-Based Data-Driven Model for Building Energy Demand Forecasting," Sustainability, MDPI, vol. 15(3), pages 1-23, January.
  20. Dong, Zhe & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2020. "Multilayer perception based reinforcement learning supervisory control of energy systems with application to a nuclear steam supply system," Applied Energy, Elsevier, vol. 259(C).
  21. Marius Reich & Jonas Gottschald & Philipp Riegebauer & Mario Adam, 2020. "Predictive Control of District Heating System Using Multi-Stage Nonlinear Approximation with Selective Memory," Energies, MDPI, vol. 13(24), pages 1-25, December.
  22. Mu, Yunfei & Xu, Yurui & Cao, Yan & Chen, Wanqing & Jia, Hongjie & Yu, Xiaodan & Jin, Xiaolong, 2022. "A two-stage scheduling method for integrated community energy system based on a hybrid mechanism and data-driven model," Applied Energy, Elsevier, vol. 323(C).
  23. Walden, Jasper V.M. & Bähr, Martin & Glade, Anselm & Gollasch, Jens & Tran, A. Phong & Lorenz, Tom, 2023. "Nonlinear operational optimization of an industrial power-to-heat system with a high temperature heat pump, a thermal energy storage and wind energy," Applied Energy, Elsevier, vol. 344(C).
  24. Kim, Dongsu & Seomun, Gu & Lee, Yongjun & Cho, Heejin & Chin, Kyungil & Kim, Min-Hwi, 2024. "Forecasting building energy demand and on-site power generation for residential buildings using long and short-term memory method with transfer learning," Applied Energy, Elsevier, vol. 368(C).
  25. Heine, Karl & Tabares-Velasco, Paulo Cesar & Deru, Michael, 2021. "Design and dispatch optimization of packaged ice storage systems within a connected community," Applied Energy, Elsevier, vol. 298(C).
  26. Zhou, Yuekuan & Zheng, Siqian & Hensen, Jan L.M., 2024. "Machine learning-based digital district heating/cooling with renewable integrations and advanced low-carbon transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
  27. Boussaid, Taha & Rousset, François & Scuturici, Vasile-Marian & Clausse, Marc, 2024. "Enabling fast prediction of district heating networks transients via a physics-guided graph neural network," Applied Energy, Elsevier, vol. 370(C).
  28. Liu, Jiangyan & Zhang, Qing & Dong, Zhenxiang & Li, Xin & Li, Guannan & Xie, Yi & Li, Kuining, 2021. "Quantitative evaluation of the building energy performance based on short-term energy predictions," Energy, Elsevier, vol. 223(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.