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A theoretical global optimization method for vapor-compression refrigeration systems based on entransy theory

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  • Xu, Yun-Chao
  • Chen, Qun

Abstract

The vapor-compression refrigeration systems have been one of the essential energy conversion systems for humankind and exhausting huge amounts of energy nowadays. Surrounding the energy efficiency promotion of the systems, there are lots of effectual optimization methods but mainly relied on engineering experience and computer simulations rather than theoretical analysis due to the complex and vague physical essence. We attempt to propose a theoretical global optimization method based on in-depth physical analysis for the involved physical processes, i.e. heat transfer analysis for condenser and evaporator, through introducing the entransy theory and thermodynamic analysis for compressor and expansion valve. The integration of heat transfer and thermodynamic analyses forms the overall physical optimization model for the systems to describe the relation between all the unknown parameters and known conditions, which makes theoretical global optimization possible. With the aid of the mathematical conditional extremum solutions, an optimization equation group and the optimal configuration of all the unknown parameters are analytically obtained. Eventually, via the optimization of a typical vapor-compression refrigeration system with various working conditions to minimize the total heat transfer area of heat exchangers, the validity and superior of the newly proposed optimization method is proved.

Suggested Citation

  • Xu, Yun-Chao & Chen, Qun, 2013. "A theoretical global optimization method for vapor-compression refrigeration systems based on entransy theory," Energy, Elsevier, vol. 60(C), pages 464-473.
    • Handle: RePEc:eee:energy:v:60:y:2013:i:c:p:464-473
    DOI: 10.1016/j.energy.2013.08.016
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    References listed on IDEAS

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    Cited by:

    1. Xu, Yun-Chao & Chen, Qun & Guo, Zeng-Yuan, 2015. "Entransy dissipation-based constraint for optimization of heat exchanger networks in thermal systems," Energy, Elsevier, vol. 86(C), pages 696-708.
    2. Janghorban Esfahani, Iman & Kang, Yong Tae & Yoo, ChangKyoo, 2014. "A high efficient combined multi-effect evaporation–absorption heat pump and vapor-compression refrigeration part 1: Energy and economic modeling and analysis," Energy, Elsevier, vol. 75(C), pages 312-326.
    3. Edoardo Di Mattia & Agostino Gambarotta & Emanuela Marzi & Mirko Morini & Costanza Saletti, 2022. "Predictive Controller for Refrigeration Systems Aimed to Electrical Load Shifting and Energy Storage," Energies, MDPI, vol. 15(19), pages 1-22, September.
    4. Xu, Sheng-Zhi & Guo, Zeng-Yuan, 2021. "Entransy transfer analysis methodology for energy conversion systems operating with thermodynamic cycles," Energy, Elsevier, vol. 224(C).
    5. Chen, Xi & Chen, Qun & Chen, Hong & Xu, Ying-Gen & Zhao, Tian & Hu, Kang & He, Ke-Lun, 2019. "Heat current method for analysis and optimization of heat recovery-based power generation systems," Energy, Elsevier, vol. 189(C).
    6. Wei, Huimin & Wu, Tao & Ge, Zhihua & Yang, Lijun & Du, Xiaoze, 2019. "Entransy analysis optimization of cooling water flow distribution in a dry cooling tower of power plant under summer crosswinds," Energy, Elsevier, vol. 166(C), pages 1229-1240.
    7. Li, Xia & Chen, Qun & Chen, Xi & He, Ke-Lun & Hao, Jun-Hong, 2020. "Graph theory-based heat current analysis method for supercritical CO2 power generation system," Energy, Elsevier, vol. 194(C).

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