Quantifying flexibility provisions of the ladle furnace refining process as cuttable loads in the iron and steel industry
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DOI: 10.1016/j.apenergy.2023.121178
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- Liu, Shuhan & Sun, Wenqiang, 2023. "Attention mechanism-aided data- and knowledge-driven soft sensors for predicting blast furnace gas generation," Energy, Elsevier, vol. 262(PA).
- Zhang, Hanxin & Sun, Wenqiang & Li, Weidong & Ma, Guangyu, 2022. "A carbon flow tracing and carbon accounting method for exploring CO2 emissions of the iron and steel industry: An integrated material–energy–carbon hub," Applied Energy, Elsevier, vol. 309(C).
- Ramin, D. & Spinelli, S. & Brusaferri, A., 2018. "Demand-side management via optimal production scheduling in power-intensive industries: The case of metal casting process," Applied Energy, Elsevier, vol. 225(C), pages 622-636.
- Ashok, S., 2006. "Peak-load management in steel plants," Applied Energy, Elsevier, vol. 83(5), pages 413-424, May.
- McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
- Sun, Wenqiang & Wang, Qiang & Zhou, Yue & Wu, Jianzhong, 2020. "Material and energy flows of the iron and steel industry: Status quo, challenges and perspectives," Applied Energy, Elsevier, vol. 268(C).
- Paulus, Moritz & Borggrefe, Frieder, 2011. "The potential of demand-side management in energy-intensive industries for electricity markets in Germany," Applied Energy, Elsevier, vol. 88(2), pages 432-441, February.
- Valdes, Javier & Masip Macia, Yunesky & Dorner, Wolfgang & Ramirez Camargo, Luis, 2021. "Unsupervised grouping of industrial electricity demand profiles: Synthetic profiles for demand-side management applications," Energy, Elsevier, vol. 215(PA).
- Herre, Lars & Tomasini, Federica & Paridari, Kaveh & Söder, Lennart & Nordström, Lars, 2020. "Simplified model of integrated paper mill for optimal bidding in energy and reserve markets," Applied Energy, Elsevier, vol. 279(C).
- Ma, Shuaiyin & Ding, Wei & Liu, Yang & Ren, Shan & Yang, Haidong, 2022. "Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries," Applied Energy, Elsevier, vol. 326(C).
- Abdelaziz, E.A. & Saidur, R. & Mekhilef, S., 2011. "A review on energy saving strategies in industrial sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 150-168, January.
- Golmohamadi, Hessam, 2022. "Demand-side management in industrial sector: A review of heavy industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
- Ma, Shuaiyin & Huang, Yuming & Liu, Yang & Kong, Xianguang & Yin, Lei & Chen, Gaige, 2023. "Edge-cloud cooperation-driven smart and sustainable production for energy-intensive manufacturing industries," Applied Energy, Elsevier, vol. 337(C).
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- Ma, Shuaiyin & Huang, Yuming & Liu, Yang & Liu, Haizhou & Chen, Yanping & Wang, Jin & Xu, Jun, 2023. "Big data-driven correlation analysis based on clustering for energy-intensive manufacturing industries," Applied Energy, Elsevier, vol. 349(C).
- Qiu, Ziyang & Sun, Jingchao & Du, Tao & Na, Hongming & Zhang, Lei & Yuan, Yuxing & Wang, Yisong, 2024. "Impact of hydrogen metallurgy on the current iron and steel industry: A comprehensive material-exergy-emission flow analysis," Applied Energy, Elsevier, vol. 356(C).
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Keywords
Flexibility; Ladle furnace (LF); Cuttable load; Industrial load; Iron and steel industry; Refining process;All these keywords.
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