Optimization of vapor compression refrigeration cycle considering a binary mixture of working fluids using evolutionary algorithms

Document Type : Research Paper


Department of Mechanical Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan Iran


The mixture of refrigerants including R32, R125, R134a, and R125 are applied in a vapor compression refrigeration cycle. Four design parameters are selected to optimize the total annual cost (TAC) and coefficient of performance (COP) in two steps. Firstly, the cycle is modeled by the mixture of R32 and R125, and secondly is done by a mixture of R134a and R125. It is revealed that COP and TAC are improved by an increase in the percent of R32. Moreover, COP and TAC are improved by an increase of R32 percentage. In the second step, the cycle has the highest COP and lowest TAC, where the pure R134a is applied, and the lowest COP is observed where the refrigerant is composed of 40% and 60% of R134a and R125, respectively. Finally, optimization is performed in the case of R410a (50% R32 and 50% R125), and the results are compared with the first step.


[1] Pan, M., Zhao, H., Liang, D., Zhu, Y., Liang, Y., & Bao, G. (2020). A Review of the Cascade Refrigeration System. Energies, 13(9), 2254.‏
[2] Worrell, E., Bernstein, L., Roy, J. et al. Industrial energy efficiency and climate change mitigation. Energy Efficiency 2, 109 (2009).
[3] Saleh, B., Aly, A. A., Alogla, A. F., Aljuaid, A. M., Alharthi, M. M., Ahmed, K. I., & Hamed, Y. S. (2019). Performance investigation of organic Rankine-vapor compression refrigeration integrated system activated by renewable energy. Mechanics & Industry, 20(2), 206.‏
[4] Churi N, Achenie LE. "The optimal design of refrigerant mixtures for a two-evaporator refrigeration system." Computers & chemical engineering 21 (1997): S349-S354.
[5] J. Sun, L. Fu, S. Zhang, A review of working fluids of absorption cycles, Renewable and Sustainable Energy Reviews, 2012:16, 1899-1906.
[6] A. Paurine, G.G. Maidment, I.W. Eames, J.F. Missenden, Development of a thermo-gravity pumping mechanism for circulating the working fluids in a novel LiBr–H2O vapour absorption refrigeration (VAR) system, Applied Thermal Engineering, 5 December 2012:47, 25-33.
[7] Kim, J., Kim, D. & Kim, Y. Thermodynamic analysis of a dual loop cycle coupled with a marine gas turbine for waste heat recovery system using low global warming potential working fluids. J Mech Sci Technol 33, 3531–3541 (2019).
[8] A. I. Papadopoulos, M. Stijepovic, P. Linke, P. Seferlis, S. Voutetakis, Molecular Design of Working Fluid Mixtures for Organic Rankine Cycles, Computer-Aided Chemical Engineering, 2013:32, 289-294.
[9] H. Sun, H. Zhu, F. Liu, H. Ding, Simulation and optimization of a novel Rankine power cycle for recovering cold energy from liquefied natural gas using a mixed working fluid, Energy, 2014:70, 317-324.
[10] X.She, Y. Yin, X. Zhang, Suggested solution concentration for an energy-efficient refrigeration system combined with condensation heat-driven liquid desiccant cycle, Renewable Energy, 2015:83, 553-564.
[11] X.B. Bu, H.S. Li, L.B. Wang, Performance analysis and working fluids selection of solar-powered organic Rankine-vapor compression ice maker, Solar Energy,2013:95,  271-278.
[12] Hajabdollahi, H., & Hosseini, Z. (2020). Dynamical modeling and thermo-economic optimization of a cold room assisted vapor-compression refrigeration cycle. Energy Equipment and Systems, 8(2), 153-167.‏
[13 Akbari, H., Sorin, M., & Marcos, B. (2018). An equivalent temperature-based approach for selection of the most appropriate working fluids for refrigeration cycles. Energy Conversion and Management, 174, 227-238.‏
[14] dos Santos Napoleao, D. A., Silveira, J. L., Giacaglia, G. E. O., de Queiroz Lamas, W., & Araujo, F. H. M. (2017). Diagrams of entropy for ammonia-water mixtures: Applications to absorption refrigeration systems. International Journal of Refrigeration, 82, 335-347
[15] B. Dai, M. Li, Y. Ma, Thermodynamic analysis of carbon dioxide blends with low GWP (global warming potential) working fluids-based transcritical Rankine cycles for low-grade heat energy recovery, Energy,2014:64, 942-952.
[16] Modi, A., & Haglind, F. (2017). A review of recent research on the use of zeotropic mixtures in power generation systems. Energy Conversion and Management, 138, 603-626.‏
[17] Andreasen, J. G., Kærn, M. R., & Haglind, F. (2019). Assessment of methods for performance comparison of pure and zeotropic working fluids for organic Rankine cycle power systems. Energies, 12(9), 1783.‏
[18] Y.Jia, C. Wenjian, Area ratio effects to the performance of air-cooled ejector refrigeration cycle with R134a refrigerant, Energy Conversion and Management, 2012:53, 240-246.
[19] L. Ouassila, M. Abedeslam Hassan, Z. Ahmed, K. Yacine, C. Thierry, Study of New Absorption Refrigeration Cycle Operating with Partially Miscible Fluids Pairs, Energy Procedia, 2012:18, 1013-1022.
[20] J. Yu, X. Song, M. Ma, Theoretical study on a novel R32 refrigeration cycle with a two-stage suction ejector, International Journal of Refrigeration, 2013:36, 166-172.
[21] X. Yang, L. Zhao, H. Li, Z. Yu, Theoretical analysis of a combined power and ejector refrigeration cycle using a zeotropic mixture, Applied Energy, In Press, Corrected Proof, Available online 16 May 2015.
[22] Duvedi A, Achenie LE. "On the design of environmentally benign refrigerant mixtures: a mathematical programming approach."Computers & chemical engineering 21, no. 8 (1997): 915-923.
[23] L. Zhao, W. Cai, X. Ding, W. Chang, Model-based optimization for vapor compression refrigeration cycle, Energy, 2013:55, 392-402.
[24] L. Zhao, W.J. Cai, X. d. Ding, W. c. Chang, Decentralized optimization for vapor compression refrigeration cycle, Applied Thermal Engineering, 2013:51, 753-763
[25] Zhang, L., Li, C., Li, Y. et al. Simultaneous optimization of multi parameters on a subcritical organic Rankine cycle system for low-grade waste heat recovery. J Mech Sci Technol 33, 447–458 (2019).
[26] Moghimi, M., Emadi, M., Ahmadi, P., & Moghadasi, H. (2018). 4E analysis and multi-objective optimization of a CCHP cycle based on gas turbine and ejector refrigeration. Applied Thermal Engineering, 141, 516-530.‏
[27] Khademi, M., Behzadi Forough, A., & Khosravi, A. (2019). Techno-economic operation optimization of an HRSG in combined cycle power plants based on evolutionary algorithms: A case study of Yazd, Iran. Energy Equipment and Systems, 7(1), 67-79.‏
[28] Hajabdollahi, H., & Esmaieli, A. (2017). Selection of the optimum prime mover and the working fluid in a regenerative organic Rankine cycle. Energy Equipment and Systems, 5(4), 325-339.‏
[29] Salim, M. S., & Kim, M. H. (2019). Multi-objective thermo-economic optimization of a combined organic Rankine cycle and vapour compression refrigeration cycle. Energy Conversion and Management, 199, 112054.‏
[30] Petrovic, A., Delibasic, B., Filipovic, J., Petrovic, A., & Lomovic, M. (2018). Thermoeconomic and environmental optimization of a geothermal water desalination plant with the ejector refrigeration system. Energy Conversion and Management, 178, 65-77.‏
[31] H. Abed, K. Atashkari, A. Niazmehr, A. Jamali, Thermodynamic optimization of combined power and refrigeration cycle using binary organic working fluid, International Journal of Refrigeration, 2013:36,  2160-2168.
[32] Kaşka, Ö., Yılmaz, C., Bor, O., & Tokgöz, N. (2018). The performance assessment of a combined organic Rankine-vapor compression refrigeration cycle aided hydrogen liquefaction. International Journal of Hydrogen Energy, 43(44), 20192-20202
[33] Ma, Y., Liu, M., Yan, J., & Liu, J. (2018). Performance investigation of a novel closed Brayton cycle using supercritical CO2-based mixture as working fluid integrated with a LiBr absorption chiller. Applied Thermal Engineering, 141, 531-547.‏
[34] Farzaneh. Hajabdollahi, Zahra. Hajabdollahi, Hassan. Hajabdollahi. Soft computing-based Multi-objective optimization of steam cycle power plant using NSGA-II and ANN.  Applied Soft Computing 2012: 123648-3655.
[35] Sayyaadi H, Amlashi EH, Amidpour M. Multi-objective optimization of a vertical ground source heat pump using an evolutionary algorithm. Energy Convers Manage 2009; 50:2035-46.
[36] Hajabdollahi, H., Ahmadi, P., & Dincer, I. (2011). Multi-objective optimization of plain fin-and-tube heat exchanger using an evolutionary algorithm. Journal of thermophysics and heat transfer, 25(3), 424-431.
[37] K. Deb, T. Goel. Controlled elitist non-dominated sorting genetic algorithms for better convergence. In: Proceedings of the first international conference on evolutionary multi-criterion optimization, Zurich; 2001. p. 385–99
[38] K. Deb. Multi-objective optimization using evolutionary algorithms. Chichester: John Wiley and Sons Ltd, 2001.
[39] Hajabdollahi, Z., Hajabdollahi, F., Tehrani, M. and Hajabdollahi, H. "Thermo-economic environmental optimization of Organic Rankine Cycle for diesel waste heat recovery." Energy 63 2013: 142-151.