Abstract
Conserving energy is an important factor in industry which could lead to reduce the operating costs of the system. Improving energy efficiency is a serious concern to many researchers and numerous studies have been conducted on this goal. A valuable method to locate the inefficient system components is the conventional exergy analysis. Furthermore, to estimate the cost efficiency of a thermodynamic system, exergo-economic analysis is indispensable. This study evaluates the ejector trans-critical \({{\text{CO}}}_{2}\) refrigeration cycle from exergo-economic viewpoint. The thermodynamic system was modeled using Engineering Equation Solver (EES) software. In order to utilize the waste heat of the gas cooler, a thermo-electric generator is introduced. Energy, exergy, and exergo-economic (3E) analysis has been performed. A parametric study was conducted of gas cooler pressure, low-pressure compressor outlet pressure, and evaporator pressure. Multi-criteria optimization has been conducted to optimize COP and refrigeration cost rate using NSGA-II (non-dominated sorting genetic algorithm). The results showed the system could provide a COP of 1.593 for the base case of the cycle operation. The high-priority components to improve were expansion valve, thermo-electric generator, and low-pressure compressor which had the highest exergy destruction ratio as 0.211, 0.180, and 0.158 respectively. The refrigeration cost rate was 2.898 $ h−1 for the base case of the system. Optimization results showed that the exergy efficiency and the exergy destruction ratio of the optimum design point are 0.284 and 0.574.
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Abbreviations
- e:
-
Specific exergy (kJ kg−1)
- \(\dot{E}\) :
-
Exergy rate \((kW)\)
- \(h\) :
-
Specific enthalpy \((kJ \, kg^{-1})\)
- \(\dot{m}\) :
-
Mass flow rate \((kg \, s^{-1})\)
- \(P\) :
-
Pressure \((kPa)\)
- \(P\) :
-
Power \((kW)\)
- \(\dot{W}\) :
-
Work \((kW)\)
- \(\dot{Q}\) :
-
Heat transfer \((kW)\)
- \(s\) :
-
Specific entropy \((kJ\, kg^{-1} \,K^{-1})\)
- \(T\) :
-
Temperature \((K)-(^\circ C)\)
- \(v\) :
-
Velocity \((m\,s^{-1})\)
- \(x\) :
-
Quality
- \(\dot{C}\) :
-
Cost rate ($ h−1)
- \(c\) :
-
Specific exergy cost ($ GJ−1)
- \(Z\) :
-
Investment cost of component \((\mathrm{\$})\)
- \(\dot{Z}\) :
-
Investment cost rate of component ($ h−1)
- \(\alpha\) :
-
Seebeck coefficient \((V \,K^{-1})\)
- \(\sigma\) :
-
Electrical conductivity \((S\,m^{-1})\)
- \(\lambda\) :
-
Thermal conductivity \((W\,m^{-1}\,K^{-1})\)
- \(\omega\) :
-
Entrainment ratio of ejector
- \(\eta\) :
-
Efficiency
- \(\delta\) :
-
Exergy destruction ratio
- \(T\) :
-
Thermal
- \(M\) :
-
Mechanical
- \(\text{do}\) :
-
Diffuser outlet
- \(\text{D}\) :
-
Destruction
- \(\text{hpc}\) :
-
High-pressure compressor
- \(\text{lpc}\) :
-
Low-pressure compressor
- \(\text{ex}\) :
-
Exergy
- \(\text{F}\) :
-
Fuel
- \(\text{P}\) :
-
Product
- \(\text{L}\) :
-
Loss
- \(\text{is}\) :
-
Isentropic
- \(\text{n}\) :
-
Nozzle
- \(\text{d}\) :
-
Diffuser
- \(\text{m}\) :
-
Mixing chamber
- \(\text{high}\) :
-
High-pressure stage
- \(\text{low}\) :
-
Low-pressure stage
- \(\text{in}\) :
-
Inlet
- \(\text{out}\) :
-
Outlet
- \(\text{teg}\) :
-
Thermo-electric generator
- \(0\) :
-
Reference parameter
References
Mosaffa AH, Farshi LG, Infante Ferreira CA, Rosen MA. Exergoeconomic and environmental analyses of CO2/NH3 cascade refrigeration systems equipped with different types of flash tank intercoolers. Energy Convers Manag. 2016;117:442–53. https://doi.org/10.1016/j.enconman.2016.03.053.
Haq MdZ, Ayon MdSR, Nouman MdWB, Bihani R. Thermodynamic analysis and optimisation of a novel transcritical CO2 cycle. Energy Convers Manag. 2022;273: 116407. https://doi.org/10.1016/j.enconman.2022.116407.
Yu B, Yang J, Wang D, Shi J, Chen J. An updated review of recent advances on modified technologies in transcritical CO2 refrigeration cycle. Energy. 2019;189: 116147. https://doi.org/10.1016/j.energy.2019.116147.
Dai B, Liu S, Zhu K, Sun Z, Ma Y. Thermodynamic performance evaluation of transcritical carbon dioxide refrigeration cycle integrated with thermoelectric subcooler and expander. Energy. 2017;122:787–800. https://doi.org/10.1016/j.energy.2017.01.029.
Qyyum MA, Naquash A, Sial NR, Lee M. CO2 precooled dual phase expander refrigeration cycles for offshore and small-scale LNG production: energy, exergy, and economic evaluation. Energy. 2023;262: 125378. https://doi.org/10.1016/j.energy.2022.125378.
Mansour A, Oberti R, Nesreddine H, Poncet S. Thermodynamic analysis of a transcritical CO2 heat pump integrating a vortex tube. Appl Therm Eng. 2023;224: 120076. https://doi.org/10.1016/j.applthermaleng.2023.120076.
Huang C, Li Z, Ye Z, Wang R. Thermodynamic study of carbon dioxide transcritical refrigeration cycle with dedicated subcooling and cascade recooling. Int J Refrig. 2022;137:80–90. https://doi.org/10.1016/j.ijrefrig.2022.02.004.
Dai B, Liu S, Sun Z, Ma Y. Thermodynamic performance analysis of CO2 transcritical refrigeration cycle assisted with mechanical subcooling. Energy Procedia. 2017;105:2033–8. https://doi.org/10.1016/j.egypro.2017.03.579.
Chen X, Yang Q, Chi W, Zhao Y, Liu G, Li L. Energy and exergy analysis of NH3/CO2 cascade refrigeration system with subcooling in the low-temperature cycle based on an auxiliary loop of NH3 refrigerants. Energy Rep. 2022;8:1757–67. https://doi.org/10.1016/j.egyr.2022.01.004.
Aghazadeh Dokandari D, Setayesh Hagh A, Mahmoudi SMS. Thermodynamic investigation and optimization of novel ejector-expansion CO2/NH3 cascade refrigeration cycles (novel CO2/NH3 cycle). Int J Refrig. 2014;46:26–36. https://doi.org/10.1016/j.ijrefrig.2014.07.012.
Braimakis K. Solar ejector cooling systems: a review. Renew Energy. 2021;164:566–602. https://doi.org/10.1016/j.renene.2020.09.079.
Liu J, Liu Y, Yu J. Performance analysis of a modified dual-ejector and dual-evaporator transcritical CO2 refrigeration cycle for supermarket application. Int J Refrig. 2021;131:109–18. https://doi.org/10.1016/j.ijrefrig.2021.06.010.
Eskandari Manjili F, Cheraghi M. Performance of a new two-stage transcritical CO2 refrigeration cycle with two ejectors. Appl Therm Eng. 2019;156:402–9. https://doi.org/10.1016/j.applthermaleng.2019.03.083.
Lee JS, Kim MS, Kim MS. Experimental study on the improvement of CO2 air conditioning system performance using an ejector. Int J Refrig. 2011;34(7):1614–25. https://doi.org/10.1016/j.ijrefrig.2010.07.025.
Liu J, Zhou L, Lyu N, Lin Z, Zhang S, Zhang X. Analysis of a modified transcritical CO2 two-stage ejector-compression cycle for domestic hot water production. Energy Convers Manag. 2022;269: 116094. https://doi.org/10.1016/j.enconman.2022.116094.
Wang Y, Yin Y, Cao F. Comprehensive evaluation of the transcritical CO2 ejector-expansion heat pump water heater. Int J Refrig. 2023;145:276–89. https://doi.org/10.1016/j.ijrefrig.2022.09.008.
Casi Á, Aranguren P, Araiz M, Sanchez D, Cabello R, Astrain D. Performance assessment of an experimental CO2 transcritical refrigeration plant working with a thermoelectric subcooler in combination with an internal heat exchanger. Energy Convers Manag. 2022;268: 115963. https://doi.org/10.1016/j.enconman.2022.115963.
Santini F, Bianchi G, Battista DD, Villante C, Orlandi M. Experimental investigations on a transcritical CO2 refrigeration plant and theoretical comparison with an ejector-based one. Energy Procedia. 2019;161:309–16. https://doi.org/10.1016/j.egypro.2019.02.097.
Aranguren P, Sánchez D, Casi A, Cabello R, Astrain D. Experimental assessment of a thermoelectric subcooler included in a transcritical CO2 refrigeration plant. Appl Therm Eng. 2021;190: 116826. https://doi.org/10.1016/j.applthermaleng.2021.116826.
Yang D, Jie Z, Zhang Q, Li Y, Xie J. Evaluation of the ejector two-stage compression refrigeration cycle with work performance from energy, conventional exergy and advanced exergy perspectives. Energy Rep. 2022;8:12944–57. https://doi.org/10.1016/j.egyr.2022.09.108.
Liu X, Fu R, Wang Z, Lin L, Sun Z, Li X. Thermodynamic analysis of transcritical CO2 refrigeration cycle integrated with thermoelectric subcooler and ejector. Energy Convers Manag. 2019;188:354–65. https://doi.org/10.1016/j.enconman.2019.02.088.
Chen G, Volovyk O, Zhu D, Ierin V, Shestopalov K. Theoretical analysis and optimization of a hybrid CO2 transcritical mechanical compression–ejector cooling cycle. Int J Refrig. 2017;74:86–94. https://doi.org/10.1016/j.ijrefrig.2016.10.002.
Wang X, Yu J, Zhou M, Lv X. Comparative studies of ejector-expansion vapor compression refrigeration cycles for applications in domestic refrigerator-freezers. Energy. 2014;70:635–42. https://doi.org/10.1016/j.energy.2014.04.076.
Liu Q, He Z, Liu Y, He Y. Thermodynamic and parametric analyses of a thermoelectric generator in a liquid air energy storage system. Energy Convers Manag. 2021;237: 114117. https://doi.org/10.1016/j.enconman.2021.114117.
Tian Z, Chen X, Zhang Y, Gao W, Chen W, Peng H. Energy, conventional exergy and advanced exergy analysis of cryogenic recuperative organic rankine cycle. Energy. 2023;268: 126648. https://doi.org/10.1016/j.energy.2023.126648.
Zheng L, Hu Y, Mi C, Deng J. Advanced exergy analysis of a CO2 two-phase ejector. Appl Therm Eng. 2022;209: 118247. https://doi.org/10.1016/j.applthermaleng.2022.118247.
Abdolalipouradl M, Mohammadkhani F, Khalilarya S, Yari M. Thermodynamic and exergoeconomic analysis of two novel tri-generation cycles for power, hydrogen and freshwater production from geothermal energy. Energy Convers Manag. 2020;226: 113544. https://doi.org/10.1016/j.enconman.2020.113544.
Liu J, Liu Y, Yan G, Yu J. Theoretical study on a modified single-stage autocascade refrigeration cycle with auxiliary phase separator. Int J Refrig. 2021;122:181–91. https://doi.org/10.1016/j.ijrefrig.2020.11.009.
Al-Rashed AAAA, Afrand M. Multi-criteria exergoeconomic optimization for a combined gas turbine-supercritical CO2 plant with compressor intake cooling fueled by biogas from anaerobic digestion. Energy. 2021;223: 119997. https://doi.org/10.1016/j.energy.2021.119997.
Baniasad Askari I, Shahsavar A. The exergo-economic analysis of two novel combined ejector heat pump/humidification-dehumidification desalination systems. Sustain Energy Technol Assess. 2022;53:102561. https://doi.org/10.1016/j.seta.2022.102561.
Khanmohammadi S, Musharavati F, Kizilkan O, Duc Nguyen D. Proposal of a new parabolic solar collector assisted power-refrigeration system integrated with thermoelectric generator using 3E analyses: energy, exergy, and exergo-economic. Energy Convers Manag. 2020;220:113055. https://doi.org/10.1016/j.enconman.2020.113055.
“Gasoline and diesel prices by country,” GlobalPetrolPrices.com. Accessed: Aug. 06, 2023. [Online]. Available: https://www.globalpetrolprices.com/
Jahromi FS, Beheshti M, Rajabi RF. Comparison between differential evolution algorithms and response surface methodology in ethylene plant optimization based on an extended combined energy - exergy analysis. Energy. 2018;164:1114–34. https://doi.org/10.1016/j.energy.2018.09.059.
Qudah A, Almerbati A, Mokheimer EMA. Novel approach for optimizing wind-PV hybrid system for RO desalination using differential evolution algorithm. Energy Convers Manag. 2024;300: 117949. https://doi.org/10.1016/j.enconman.2023.117949.
Karmakar R, Chatterjee S, Datta D, Chakraborty D. Application of harmony search algorithm in optimizing autoregressive integrated moving average: a study on a data set of Coronavirus Disease 2019. Syst Soft Comput. 2024;6: 200067. https://doi.org/10.1016/j.sasc.2023.200067.
Lee GH, Sadollah A, Park SH, Geem ZW. HS-Solver: Spreadsheet based harmony search algorithm solver for various optimization problems. SoftwareX. 2022;20: 101262. https://doi.org/10.1016/j.softx.2022.101262.
Cheng H, et al. Economic, environmental, exergy (3E) analysis and multi-objective genetic algorithm optimization of efficient and energy-saving separation of diethoxymethane/toluene/ethanol by extractive distillation with mixed extractants. Energy. 2023;284: 129262. https://doi.org/10.1016/j.energy.2023.129262.
Kaseb Z, Rahbar M. Towards CFD-based optimization of urban wind conditions: comparison of genetic algorithm, particle swarm optimization, and a hybrid algorithm. Sustain Cities Soc. 2022;77: 103565. https://doi.org/10.1016/j.scs.2021.103565.
Vuolio T, Visuri V-V, Sorsa A, Ollila S, Fabritius T. Application of a genetic algorithm based model selection algorithm for identification of carbide-based hot metal desulfurization. Appl Soft Comput. 2020;92: 106330. https://doi.org/10.1016/j.asoc.2020.106330.
Zhang L, et al. Integrated optimization for utilizing iron and steel industry’s waste heat with urban heating based on exergy analysis. Energy Convers Manag. 2023;295: 117593. https://doi.org/10.1016/j.enconman.2023.117593.
Erodotou P, Voutsas E, Sarimveis H. A genetic algorithm approach for parameter estimation in vapour-liquid thermodynamic modelling problems. Comput Chem Eng. 2020;134: 106684. https://doi.org/10.1016/j.compchemeng.2019.106684.
Deb K, Goel T. Controlled Elitist Non-dominated Sorting Genetic Algorithms for Better Convergence. In: Zitzler E, Thiele L, Deb K, Coello Coello CA, Corne D, editors. In: Evolutionary Multi-Criterion Optimization. Berlin, Heidelberg: Springer, Berlin Heidelberg; 2001.
Pan M, et al. Thermodynamic, exergoeconomic and multi-objective optimization analysis of new ORC and heat pump system for waste heat recovery in waste-to-energy combined heat and power plant. Energy Convers Manag. 2020;222: 113200. https://doi.org/10.1016/j.enconman.2020.113200.
Acknowledgements
Authors would like to acknowledge the financial support of Kermanshah University of Technology for this research under grant number S/T/P/1430.
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Khanmohammadi, S., Sharifinasab, M.R. 3E analysis and multi-objective optimization of a trans-critical ejector-assisted Co2 refrigeration cycle combined with thermo-electric generator. J Therm Anal Calorim 149, 3951–3964 (2024). https://doi.org/10.1007/s10973-024-12968-1
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DOI: https://doi.org/10.1007/s10973-024-12968-1