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Large-scale industrial energy systems optimization under uncertainty: A data-driven robust optimization approach

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  1. Zhao, Dafang & Watari, Daichi & Ozawa, Yuki & Taniguchi, Ittetsu & Suzuki, Toshihiro & Shimoda, Yoshiyuki & Onoye, Takao, 2023. "Data-driven online energy management framework for HVAC systems: An experimental study," Applied Energy, Elsevier, vol. 352(C).
  2. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Optimisation modelling tools and solving techniques for integrated precinct-scale energy–water system planning," Applied Energy, Elsevier, vol. 318(C).
  3. Chen, Houhe & Shao, Junyan & Jiang, Tao & Li, Xue & Zhang, Rufeng, 2024. "Performance assessment of multiple-types co-located storage for uncertainty mitigation in integrated electric-gas system using generalized polynomial chaos," Applied Energy, Elsevier, vol. 374(C).
  4. Shen, Feifei & Zhao, Liang & Wang, Meihong & Du, Wenli & Qian, Feng, 2022. "Data-driven adaptive robust optimization for energy systems in ethylene plant under demand uncertainty," Applied Energy, Elsevier, vol. 307(C).
  5. Sun, Alexander Y., 2020. "Optimal carbon storage reservoir management through deep reinforcement learning," Applied Energy, Elsevier, vol. 278(C).
  6. Shaojian Qu & Yuting Xu & Ying Ji & Can Feng & Jinpeng Wei & Shan Jiang, 2022. "Data-Driven Robust Data Envelopment Analysis for Evaluating the Carbon Emissions Efficiency of Provinces in China," Sustainability, MDPI, vol. 14(20), pages 1-26, October.
  7. Cantu Rodriguez, Roman & Palacios-Garcia, Emilio J. & Deconinck, Geert, 2024. "Redesign for flexibility through electrification: Multi-objective optimization of the operation of a multi-energy industrial steam network," Applied Energy, Elsevier, vol. 362(C).
  8. Yang, Dan & Peng, Xin & Ye, Zhencheng & Lu, Yusheng & Zhong, Weimin, 2021. "Domain adaptation network with uncertainty modeling and its application to the online energy consumption prediction of ethylene distillation processes," Applied Energy, Elsevier, vol. 303(C).
  9. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Challenges, opportunities, and strategies for undertaking integrated precinct-scale energy–water system planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  10. Wang, Yubin & Dong, Wei & Yang, Qiang, 2022. "Multi-stage optimal energy management of multi-energy microgrid in deregulated electricity markets," Applied Energy, Elsevier, vol. 310(C).
  11. Zhang, Chaoyi & Jiao, Zaibin & Liu, Junshan & Ning, Keer, 2023. "Robust planning and economic analysis of park-level integrated energy system considering photovoltaic/thermal equipment," Applied Energy, Elsevier, vol. 348(C).
  12. Jing, Rui & Li, Yubing & Wang, Meng & Chachuat, Benoit & Lin, Jianyi & Guo, Miao, 2021. "Coupling biogeochemical simulation and mathematical optimisation towards eco-industrial energy systems design," Applied Energy, Elsevier, vol. 290(C).
  13. Jiang, Sheng-Long & Wang, Meihong & Bogle, I. David L., 2023. "Plant-wide byproduct gas distribution under uncertainty in iron and steel industry via quantile forecasting and robust optimization," Applied Energy, Elsevier, vol. 350(C).
  14. Wang, Yuqi & Liu, Tianyuan & Meng, Yue & Zhang, Di & Xie, Yonghui, 2022. "Integrated optimization for design and operation of turbomachinery in a solar-based Brayton cycle based on deep learning techniques," Energy, Elsevier, vol. 252(C).
  15. Tsao, Yu-Chung & Thanh, Vo-Van, 2021. "Toward blockchain-based renewable energy microgrid design considering default risk and demand uncertainty," Renewable Energy, Elsevier, vol. 163(C), pages 870-881.
  16. Gan, Wei & Yan, Mingyu & Yao, Wei & Guo, Jianbo & Ai, Xiaomeng & Fang, Jiakun & Wen, Jinyu, 2021. "Decentralized computation method for robust operation of multi-area joint regional-district integrated energy systems with uncertain wind power," Applied Energy, Elsevier, vol. 298(C).
  17. Zhao, Bo & Ren, Junzhi & Chen, Jian & Lin, Da & Qin, Ruwen, 2020. "Tri-level robust planning-operation co-optimization of distributed energy storage in distribution networks with high PV penetration," Applied Energy, Elsevier, vol. 279(C).
  18. Fang, Xin & Cui, Hantao & Du, Ershun & Li, Fangxing & Kang, Chongqing, 2021. "Characteristics of locational uncertainty marginal price for correlated uncertainties of variable renewable generation and demands," Applied Energy, Elsevier, vol. 282(PA).
  19. Hu, Yuting & Li, Shukai & Dessouky, Maged M. & Yang, Lixing & Gao, Ziyou, 2022. "Computationally efficient train timetable generation of metro networks with uncertain transfer walking time to reduce passenger waiting time: A generalized Benders decomposition-based method," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 210-231.
  20. Lin, Xiaojie & Mao, Yihui & Chen, Jiaying & Zhong, Wei, 2023. "Dynamic modeling and uncertainty quantification of district heating systems considering renewable energy access," Applied Energy, Elsevier, vol. 349(C).
  21. Ghaemi, Zahra & Tran, Thomas T.D. & Smith, Amanda D., 2022. "Comparing classical and metaheuristic methods to optimize multi-objective operation planning of district energy systems considering uncertainties," Applied Energy, Elsevier, vol. 321(C).
  22. Zhao, Ning & You, Fengqi, 2022. "Sustainable power systems operations under renewable energy induced disjunctive uncertainties via machine learning-based robust optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  23. Jiajia Li & Jinfu Liu & Peigang Yan & Xingshuo Li & Guowen Zhou & Daren Yu, 2021. "Operation Optimization of Integrated Energy System under a Renewable Energy Dominated Future Scene Considering Both Independence and Benefit: A Review," Energies, MDPI, vol. 14(4), pages 1-36, February.
  24. Ma, Haicheng & Lou, Gaoxiang & Fan, Tijun & Chan, Hing Kai & Chung, Sai Ho, 2021. "Conventional automotive supply chains under China's dual-credit policy: fuel economy, production and coordination," Energy Policy, Elsevier, vol. 151(C).
  25. Benoît Loger & Alexandre Dolgui & Fabien Lehuédé & Guillaume Massonnet, 2024. "Approximate Kernel Learning Uncertainty Set for Robust Combinatorial Optimization," INFORMS Journal on Computing, INFORMS, vol. 36(3), pages 900-917, May.
  26. Han, Biao & Shang, Chao & Huang, Dexian, 2021. "Multiple kernel learning-aided robust optimization: Learning algorithm, computational tractability, and usage in multi-stage decision-making," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1004-1018.
  27. Rissman, Jeffrey & Bataille, Chris & Masanet, Eric & Aden, Nate & Morrow, William R. & Zhou, Nan & Elliott, Neal & Dell, Rebecca & Heeren, Niko & Huckestein, Brigitta & Cresko, Joe & Miller, Sabbie A., 2020. "Technologies and policies to decarbonize global industry: Review and assessment of mitigation drivers through 2070," Applied Energy, Elsevier, vol. 266(C).
  28. Young Kwan Ko & Young Dae Ko, 2024. "Efficient Hub-Based Platooning Management Considering the Uncertainty of Information," Mathematics, MDPI, vol. 12(23), pages 1-13, December.
  29. Wu, Min & Xu, Jiazhu & Zeng, Linjun & Li, Chang & Liu, Yuxing & Yi, Yuqin & Wen, Ming & Jiang, Zhuohan, 2022. "Two-stage robust optimization model for park integrated energy system based on dynamic programming," Applied Energy, Elsevier, vol. 308(C).
  30. Urbano, Eva M. & Martinez-Viol, Victor & Kampouropoulos, Konstantinos & Romeral, Luis, 2021. "Energy equipment sizing and operation optimisation for prosumer industrial SMEs – A lifetime approach," Applied Energy, Elsevier, vol. 299(C).
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