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Site utility system optimization with operation adjustment under uncertainty

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  • Sun, Li
  • Gai, Limei
  • Smith, Robin

Abstract

Utility systems must satisfy process energy and power demands under varying conditions. The system performance is decided by the system configuration and individual equipment operating load for boilers, gas turbines, steam turbines, condensers, and let down valves. Steam mains conditions in terms of steam pressures and steam superheating also play important roles on steam distribution in the system and power generation by steam expansion in steam turbines, and should be included in the system optimization. Uncertainties such as process steam power demand changes and electricity price fluctuations should be included in the system optimization to eliminate as much as possible the production loss caused by steam power deficits due to uncertainties. In this paper, uncertain factors are classified into time-based and probability-based uncertain factors, and operation scheduling containing multi-period equipment load sharing, redundant equipment start up, and electricity import to compensate for power deficits, have been presented to deal with the happens of uncertainties, and are formulated as a multi-period item and a recourse item in the optimization model. There are two case studies in this paper. One case illustrates the system design to determine system configuration, equipment selection, and system operation scheduling at the design stage to deal with uncertainties. The other case provides operational optimization scenarios for an existing system, especially when the steam superheating varies. The proposed method can provide practical guidance to system energy efficiency improvement.

Suggested Citation

  • Sun, Li & Gai, Limei & Smith, Robin, 2017. "Site utility system optimization with operation adjustment under uncertainty," Applied Energy, Elsevier, vol. 186(P3), pages 450-456.
  • Handle: RePEc:eee:appene:v:186:y:2017:i:p3:p:450-456
    DOI: 10.1016/j.apenergy.2016.05.036
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    References listed on IDEAS

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    1. Carpaneto, Enrico & Chicco, Gianfranco & Mancarella, Pierluigi & Russo, Angela, 2011. "Cogeneration planning under uncertainty: Part I: Multiple time frame approach," Applied Energy, Elsevier, vol. 88(4), pages 1059-1067, April.
    2. Kravanja, Zdravko & Čuček, Lidija, 2013. "Multi-objective optimisation for generating sustainable solutions considering total effects on the environment," Applied Energy, Elsevier, vol. 101(C), pages 67-80.
    3. El-Halwagi, Mahmoud & Harell, Dustin & Dennis Spriggs, H., 2009. "Targeting cogeneration and waste utilization through process integration," Applied Energy, Elsevier, vol. 86(6), pages 880-887, June.
    4. Carpaneto, Enrico & Chicco, Gianfranco & Mancarella, Pierluigi & Russo, Angela, 2011. "Cogeneration planning under uncertainty. Part II: Decision theory-based assessment of planning alternatives," Applied Energy, Elsevier, vol. 88(4), pages 1075-1083, April.
    5. Sun, Li & Doyle, Steve & Smith, Robin, 2015. "Heat recovery and power targeting in utility systems," Energy, Elsevier, vol. 84(C), pages 196-206.
    6. Voll, Philip & Klaffke, Carsten & Hennen, Maike & Bardow, André, 2013. "Automated superstructure-based synthesis and optimization of distributed energy supply systems," Energy, Elsevier, vol. 50(C), pages 374-388.
    7. Duić, Neven & Guzović, Zvonimir & Kafarov, Vyatcheslav & Klemeš, Jiří Jaromír & Mathiessen, Brian vad & Yan, Jinyue, 2013. "Sustainable development of energy, water and environment systems," Applied Energy, Elsevier, vol. 101(C), pages 3-5.
    8. Voll, Philip & Jennings, Mark & Hennen, Maike & Shah, Nilay & Bardow, André, 2015. "The optimum is not enough: A near-optimal solution paradigm for energy systems synthesis," Energy, Elsevier, vol. 82(C), pages 446-456.
    9. Mitra, Sumit & Sun, Lige & Grossmann, Ignacio E., 2013. "Optimal scheduling of industrial combined heat and power plants under time-sensitive electricity prices," Energy, Elsevier, vol. 54(C), pages 194-211.
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    Cited by:

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    2. Yu Huang & Weizhen Hou & Yiran Huang & Jiayu Li & Qixian Li & Dongfeng Wang & Yan Zhang, 2020. "Multi-Objective Optimal Operation for Steam Power Scheduling Based on Economic and Exergetic Analysis," Energies, MDPI, vol. 13(8), pages 1-18, April.
    3. Boldyryev, Stanislav & Gil, Tatyana & Krajačić, Goran & Khussanov, Alisher, 2023. "Total site targeting with the simultaneous use of intermediate utilities and power cogeneration at the polymer plant," Energy, Elsevier, vol. 279(C).
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    5. Shen, Feifei & Zhao, Liang & Du, Wenli & Zhong, Weimin & Qian, Feng, 2020. "Large-scale industrial energy systems optimization under uncertainty: A data-driven robust optimization approach," Applied Energy, Elsevier, vol. 259(C).
    6. Park, Haryn & Kim, Jin-Kuk & Yi, Sung Chul, 2023. "Optimization of site utility systems for renewable energy integration," Energy, Elsevier, vol. 269(C).
    7. Khairulnadzmi Jamaluddin & Sharifah Rafidah Wan Alwi & Khaidzir Hamzah & Jiří Jaromír Klemeš, 2020. "A Numerical Pinch Analysis Methodology for Optimal Sizing of a Centralized Trigeneration System with Variable Energy Demands," Energies, MDPI, vol. 13(8), pages 1-35, April.
    8. Sakalis, George N. & Frangopoulos, Christos A., 2018. "Intertemporal optimization of synthesis, design and operation of integrated energy systems of ships: General method and application on a system with Diesel main engines," Applied Energy, Elsevier, vol. 226(C), pages 991-1008.
    9. Zailan, Roziah & Lim, Jeng Shiun & Manan, Zainuddin Abdul & Alwi, Sharifah Rafidah Wan & Mohammadi-ivatloo, Behnam & Jamaluddin, Khairulnadzmi, 2021. "Malaysia scenario of biomass supply chain-cogeneration system and optimization modeling development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
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