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Performance prediction of a solar driven ejector-absorption cycle using fuzzy logic

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  • Sözen, Adnan
  • Kurt, Mustafa
  • Akçayol, M.Ali
  • Özalp, Mehmet

Abstract

Theoretical performance analysis of the absorption systems is very complex because of analytic functions used for calculating the properties of fluid couples and simulation programs. To simplify this complex process, this paper proposes a new approach to performance analysis of solar driven ejector-absorption refrigeration system (EARS) operated aqua/ammonia. Performance of EARS was predicted using fuzzy logic controller at different working conditions instead of complex rules and mathematical routines. Fuzzy logic’s linguistic terms provide a feasible method for defining the operational characteristics of EARSs. Input data for fuzzy logic are experimental results performed in the climate condition of Ankara in Turkey. In the comparison of performance analysis results between analytic equations and by means of fuzzy logic controller, deviations coefficient of performance (COP), exergetic coefficient of performance (ECOP) and circulation ratio (F) for all working temperatures are less than 2, 5 and 0.2%, respectively. The statistical coefficient of multiple determinations (R2 value) equals to 1, 0.9996, 1 for the COP, ECOP and F, respectively. These accuracy degrees are acceptable in design of EARS. This study is considered to be helpful in predicting the performance of an EARS prior to its setting up in an environment where the temperatures are known. Also, this study provides a fast and accurate means of determining the performance under transient operating regimes without the need to resort to classical physical modeling.

Suggested Citation

  • Sözen, Adnan & Kurt, Mustafa & Akçayol, M.Ali & Özalp, Mehmet, 2004. "Performance prediction of a solar driven ejector-absorption cycle using fuzzy logic," Renewable Energy, Elsevier, vol. 29(1), pages 53-71.
    • Handle: RePEc:eee:renene:v:29:y:2004:i:1:p:53-71
    DOI: 10.1016/S0960-1481(03)00172-1
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    References listed on IDEAS

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    1. Levy, A. & Jelinek, M. & Borde, I., 2002. "Numerical study on the design parameters of a jet ejector for absorption systems," Applied Energy, Elsevier, vol. 72(2), pages 467-478, June.
    2. Jelinek, M. & Levy, A. & Borde, I., 2002. "Performance of a triple-pressure-level absorption cycle with R125-N,N'-dimethylethylurea," Applied Energy, Elsevier, vol. 71(3), pages 171-189, March.
    3. Sun, Da-Wen, 1996. "Variable geometry ejectors and their applications in ejector refrigeration systems," Energy, Elsevier, vol. 21(10), pages 919-929.
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    Cited by:

    1. Edilson León Moreno Cárdenas & Arley David Zapata-Zapata & Daehwan Kim, 2020. "Modeling Dark Fermentation of Coffee Mucilage Wastes for Hydrogen Production: Artificial Neural Network Model vs. Fuzzy Logic Model," Energies, MDPI, vol. 13(7), pages 1-13, April.
    2. Besagni, Giorgio & Mereu, Riccardo & Inzoli, Fabio, 2016. "Ejector refrigeration: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 373-407.
    3. Chen, Jianyong & Jarall, Sad & Havtun, Hans & Palm, Björn, 2015. "A review on versatile ejector applications in refrigeration systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 67-90.
    4. Shekarchian, M. & Moghavvemi, M. & Motasemi, F. & Mahlia, T.M.I., 2011. "Energy savings and cost-benefit analysis of using compression and absorption chillers for air conditioners in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1950-1960, May.
    5. Sözen, Adnan & Ali Akçayol, M., 2004. "Modelling (using artificial neural-networks) the performance parameters of a solar-driven ejector-absorption cycle," Applied Energy, Elsevier, vol. 79(3), pages 309-325, November.
    6. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.

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