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Exergy analysis and parametric optimization of three power and fresh water cogeneration systems using refrigeration chillers

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  • Janghorban Esfahani, I.
  • Yoo, C.K.

Abstract

Three power and fresh water cogeneration systems that combine a GT (gas turbine) power plant and a RO (reverse osmosis) desalination system were compared based on the exergy viewpoint. In the first system, the GT and RO systems were coupled mechanically to form a base system. In the second and third systems, a VCR (vapor-compression refrigeration) cycle and a single-effect ACWater–LiBr (water/lithium bromide absorption chiller) were used, respectively, to cool the compressor inlet air and preheat the RO intake seawater via waste heat recovery in the VCR condenser and ACWater–LiBr absorber. A parametric analysis-based exergy was conducted to evaluate the effects of the key thermodynamic parameters including the compressor inlet air temperature and the fuel-mass flow rate on the system exergy efficiency. Parameter optimization was achieved using a GA (genetic algorithm) to reach the maximum exergy efficiency, where the thermodynamic improvement potentials of the systems were identified. The optimum values of performance for the three cogeneration systems were compared under the same conditions. The results showed that the cogeneration system with the AC is the best system among the three systems, since it can increase exergy and energy efficiencies as well as net power generation by 3.79%, 4.21%, and 38%, respectively, compared to the base system.

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  • Janghorban Esfahani, I. & Yoo, C.K., 2013. "Exergy analysis and parametric optimization of three power and fresh water cogeneration systems using refrigeration chillers," Energy, Elsevier, vol. 59(C), pages 340-355.
    • Handle: RePEc:eee:energy:v:59:y:2013:i:c:p:340-355
    DOI: 10.1016/j.energy.2013.07.040
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    4. Janghorban Esfahani, Iman & Yoo, ChangKyoo, 2016. "An optimization algorithm-based pinch analysis and GA for an off-grid batteryless photovoltaic-powered reverse osmosis desalination system," Renewable Energy, Elsevier, vol. 91(C), pages 233-248.
    5. 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.
    6. Ali, Ramadan Hefny & Abdel Samee, Ahmed A. & Maghrabie, Hussein M., 2023. "Thermodynamic analysis of a cogeneration system in pulp and paper industry under singular and hybrid operating modes," Energy, Elsevier, vol. 263(PE).
    7. Long, R. & Bao, Y.J. & Huang, X.M. & Liu, W., 2014. "Exergy analysis and working fluid selection of organic Rankine cycle for low grade waste heat recovery," Energy, Elsevier, vol. 73(C), pages 475-483.
    8. Razmi, Amir Reza & Arabkoohsar, Ahmad & Nami, Hossein, 2020. "Thermoeconomic analysis and multi-objective optimization of a novel hybrid absorption/recompression refrigeration system," Energy, Elsevier, vol. 210(C).
    9. Baby-Jean Robert Mungyeko Bisulandu & Rami Mansouri & Adrian Ilinca, 2023. "Diffusion Absorption Refrigeration Systems: An Overview of Thermal Mechanisms and Models," Energies, MDPI, vol. 16(9), pages 1-36, April.
    10. Wei, Xiupeng & Xu, Guanglin & Kusiak, Andrew, 2014. "Modeling and optimization of a chiller plant," Energy, Elsevier, vol. 73(C), pages 898-907.
    11. Siddiqui, M.U. & Said, S.A.M., 2015. "A review of solar powered absorption systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 93-115.
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    13. Pietrasanta, Ariana M. & Mussati, Sergio F. & Aguirre, Pio A. & Morosuk, Tatiana & Mussati, Miguel C., 2022. "Optimization of a multi-generation power, desalination, refrigeration and heating system," Energy, Elsevier, vol. 238(PB).
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