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Synthesis and optimization of work and heat exchange networks using an MINLP model with a reduced number of decision variables

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  • Santos, Lucas F.
  • Costa, Caliane B.B.
  • Caballero, José A.
  • Ravagnani, Mauro A.S.S.

Abstract

Integrating the energy available in industrial processes in the form of heat and work is fundamental to achieve higher energy efficiencies as well as to reduce process costs and environmental impacts. To perform this integration, a new framework for the optimal synthesis of work and heat exchange networks (WHEN) aiming to reduce capital and operating costs is presented. The main contribution of this paper is the elaboration of a new WHEN superstructure and mixed-integer nonlinear programming (MINLP) derived model. Strategies of changing variables are applied to reduce the number of decision variables from the model. The MINLP problem with a reduced number of decision variables is solved with a two-level meta-heuristic optimization approach, using Simulated Annealing in the combinatorial problem and Particle Swarm Optimization in the nonlinear programming problem. For the sake of validation, this methodology is applied to three case studies comprising two, five, and six process streams. Economic savings achieved outperform results reported in the literature from 1.0 to 7.2%. Also, the solutions obtained present non-intuitive WHENs that shows the importance of using superstructure-based mathematical programming for such a difficult decision-making task.

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  • Santos, Lucas F. & Costa, Caliane B.B. & Caballero, José A. & Ravagnani, Mauro A.S.S., 2020. "Synthesis and optimization of work and heat exchange networks using an MINLP model with a reduced number of decision variables," Applied Energy, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:appene:v:262:y:2020:i:c:s0306261919321294
    DOI: 10.1016/j.apenergy.2019.114441
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    References listed on IDEAS

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    1. Fu, Chao & Gundersen, Truls, 2016. "Correct integration of compressors and expanders in above ambient heat exchanger networks," Energy, Elsevier, vol. 116(P2), pages 1282-1293.
    2. Foumani, Mehdi & Smith-Miles, Kate, 2019. "The impact of various carbon reduction policies on green flowshop scheduling," Applied Energy, Elsevier, vol. 249(C), pages 300-315.
    3. Onishi, Viviani C. & Quirante, Natalia & Ravagnani, Mauro A.S.S. & Caballero, José A., 2018. "Optimal synthesis of work and heat exchangers networks considering unclassified process streams at sub and above-ambient conditions," Applied Energy, Elsevier, vol. 224(C), pages 567-581.
    4. Huang, Kefeng & Karimi, I.A., 2016. "Work-heat exchanger network synthesis (WHENS)," Energy, Elsevier, vol. 113(C), pages 1006-1017.
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    Cited by:

    1. Pavão, Leandro V. & Caballero, José A. & Ravagnani, Mauro A.S.S. & Costa, Caliane B.B., 2020. "A pinch-based method for defining pressure manipulation routes in work and heat exchange networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    2. Santos, Lucas F. & Costa, Caliane B.B. & Caballero, José A. & Ravagnani, Mauro A.S.S., 2022. "Framework for embedding black-box simulation into mathematical programming via kriging surrogate model applied to natural gas liquefaction process optimization," Applied Energy, Elsevier, vol. 310(C).
    3. Zhang, Qiao & Yang, Sen & Feng, Xiao, 2021. "Thermodynamic principle based work exchanger network integration for cost-effective refinery hydrogen networks," Energy, Elsevier, vol. 230(C).

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