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Parametric assessment and multi-objective optimization of an internal auto-cascade refrigeration cycle based on advanced exergy and exergoeconomic concepts

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  • Asgari, Sahar
  • Noorpoor, A.R.
  • Boyaghchi, Fateme Ahmadi

Abstract

This research deals with the advanced exergy and exergoeconomic analyses and multi-objective optimization of an internal auto-cascade refrigeration cycle. Butane is used as the refrigerant and all heat exchangers are modeled by considering pressure drops. Sensitivity study is carried out to assess the variation of exergetic and economic improvement potentials; namely, total avoidable exergy destruction, total avoidable exergy destruction cost and total avoidable investment cost rates to the compressor mass flow rate, condenser, refrigerator evaporator and freezer evaporator inlet temperatures. Parametric study indicates that the condenser inlet temperature growth improves the total avoidable exergy destruction within 88.19%, the total avoidable investment cost rate increases by about 126.92% and 3.68% as compressor inlet mass and refrigerator evaporator inlet temperature rise, respectively and the increment of refrigerator evaporator inlet temperature shows a positive effect on the total avoidable exergy destruction cost rate. In addition, improvement potentials are maximized by applying Non-dominated Sort Genetic Algorithm-II. The multi-objective optimization indicates 76.78%, 38.66% and 103.38% improvements in total avoidable exergy destruction rate, total avoidable investment and total avoidable exergy destruction cost rates, respectively relative to the base design point.

Suggested Citation

  • Asgari, Sahar & Noorpoor, A.R. & Boyaghchi, Fateme Ahmadi, 2017. "Parametric assessment and multi-objective optimization of an internal auto-cascade refrigeration cycle based on advanced exergy and exergoeconomic concepts," Energy, Elsevier, vol. 125(C), pages 576-590.
    • Handle: RePEc:eee:energy:v:125:y:2017:i:c:p:576-590
    DOI: 10.1016/j.energy.2017.02.158
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    References listed on IDEAS

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    Cited by:

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    3. Zhenzhen Liu & Jingde Jiang & Zilong Wang & Hua Zhang, 2023. "Thermodynamic Analysis of an Innovative Cold Energy Storage System for Auto-Cascade Refrigeration Applications," Energies, MDPI, vol. 16(5), pages 1-17, February.
    4. Mostafavi Sani, Mostafa & Noorpoor, Alireza & Shafie-Pour Motlagh, Majid, 2019. "Optimal model development of energy hub to supply water, heating and electrical demands of a cement factory," Energy, Elsevier, vol. 177(C), pages 574-592.
    5. Sun, Zhili & Wang, Qifan & Xie, Zhiyuan & Liu, Shengchun & Su, Dandan & Cui, Qi, 2019. "Energy and exergy analysis of low GWP refrigerants in cascade refrigeration system," Energy, Elsevier, vol. 170(C), pages 1170-1180.
    6. Zhang, Ruiyuan & Su, Wen & Lin, Xinxing & Zhou, Naijun & Zhao, Li, 2020. "Thermodynamic analysis and parametric optimization of a novel S–CO2 power cycle for the waste heat recovery of internal combustion engines," Energy, Elsevier, vol. 209(C).

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