Skip to main content
Log in

Comparative investigation and multi objective design optimization of a cascaded vapor compression absorption refrigeration system operating with different refrigerants in the vapor compression cycle

  • Original
  • Published:
Heat and Mass Transfer Aims and scope Submit manuscript

Abstract

This study aims to comparatively investigate the performance of a cascaded vapor compression absorption refrigeration system (CVCARS) operated with different refrigerants such as R1234yf, R134a, R717 and R290 in vapor compression cycle. Two design objectives are considered for performance evaluations. Total annual cost is the first design objective which includes investment and operational cost along with the social cost associated with carbon emissions. Exergy efficiency is the second considered objective which is related to thermodynamic issues. These problem objectives are individually and concurrently optimized by means of Artifical Cooperative Search metaheuristic algorithm and best results are compared for each cycle configuration. Single objective optimization results reveal that CVCARS working with R717 in vapor compression cycle has the lowest total annual cost whereas the maximum second law efficiency is obtained by the refrigeration system operated with R290 in vapor compression cycle. Following that, multi objective optimization is applied to acquire the Pareto optimal solutions which are nondominated to each other and no solution between them prevails over the other. Reputed decision making method TOPSIS is applied to choose the final best answer among the Pareto curve. It is seen that solution found by TOPSIS is skewed towards the minimum total annual cost and second law efficiency for each cycle configuration. Sensitivity analysis is then put into practice to observe the influences of variations of decision variables on design objectives as well as performance coefficients of the different cycles in the refrigeration system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Abbreviations

A:

Heat exchanger surface area (m2)

ACS:

Artificial Cooperative Search

Celec :

Electricity cost ($/kWh)

C env :

Environmental cost ($/year)

Cfuel :

Fuel cost ($/kWh)

Cinv :

Investment cost ($)

Coper :

Operational cost ($)

C p :

Specific heat at constant pressure (kJ/kg.K)

C T :

Total annual cost ($/year)

COP:

Coefficient of performance

CRF:

Capital recovery factor

CVCARS:

Cascaded vapor compression absroption refrigeration system

d:

Tube diameter (m)

dH :

Hyrdaulic diameter of annulus (m)

f :

Friction factor

g:

Gravitational acceleration (m/s2)

H:

Total annual operation hours

h:

Entalphy (kj/kg), Convective heat transfer coefficient (W/m2K)

hfg :

Latent heat of vaporization (kj/kg)

i :

Interest rate

k:

Thermal conductivity (W/m.K)

\( \dot{m} \) :

Mass flow rate (kg/s)

\( {\dot{m}}_{CO_2} \) :

Amount of carbon dioxide emission (ton/year)

N:

Life time of the refrigeration system (N)

Ntube :

Number of tube in heat exchanger

Npass :

Number of shell pass in heat exchanger

P:

Pressure (Pa)

Pr:

Prandtl number

\( \dot{Q},q \) :

Heat transfer amount (kW)

R:

Fouling resistance (m2K/W)

Re:

Reynolds number

s:

Entropy (kJ/kg.K)

T:

Temperature (°C - K)

Tsat :

Saturation temperature (°C - K)

Twall :

Wall temperature (°C - K)

ΔTLMTD :

Logarithmic mean temperature difference

U:

Overall heat transfer coefficient (W/m2K)

v:

Working fluid velocity (m/s)

VARS:

Vapor Absorption Refrigeration System

VCRS:

Vapor Compression Refrigeration System

\( \dot{W} \) :

Compressor or pump work (kW)

x :

Mass concentration of absorbent in the solution

Z:

Capital cost ($)

Γ:

Mass flow rate of working unit per wetted length (kg/ms)

ε :

Heat exchanger efficiency

η II :

Second law efficiency

η m :

Mechanical efficiency

η el :

Electrical efficiency

η is :

Isentropic efficiency

\( {\theta}_{CO_2} \) :

Emission conversion factor

μ:

Dynamic viscosity (Pa.s)

v :

Kinematic viscosity (m2/s),

ρ:

Density (kg/m3)

ϕ:

Maintenance cost factor

abs:

Absorber

cascond:

Cascade condenser

comp:

Compressor

cond:

Condenser

eff:

Effective

evap:

Evaporator

gen:

Generator

in:

Inlet condition

l:

Liquid

out:

Outlet condition

overlap:

Degree of overlap

ref.:

Refrigerant

RHX:

Regenerative heat exchanger

sat:

Saturation

SHX:

Solution heat exchanger

sol,pump:

Solution pump

v:

Vapor

References

  1. Bakhtiari B, Fradette L, Legros R, Paris J (2011) A model for analysis and design H2O-LiBr absorption heat pumps. Energ Convers Manage 52:1439–1448

    Article  Google Scholar 

  2. Florides GA, Kalogirou SA, Tassou SA, Wrobel LC (2003) Design and construction of LiBr-water absorption machine. Energ Convers Manage 44:2483–2508

    Article  Google Scholar 

  3. Gebreslassie BH, Gosalbez GG, Jimenez L, Boer D (2009) Design of environmentally conscious absorption cooling systems via multi-objective optimization and life cycle assessment. Appl Energy 86:1712–1722

    Article  Google Scholar 

  4. Godarzi AA, Jalilian M, Samimi J, Jokar A, Vesaghi MA (2013) Design of a PCM storage system for a solar absorption chiller based on exergoeconomic analysis and genetic algorithm. Int J Refrig 36:88–101

    Article  Google Scholar 

  5. Sachdeva G, Jain V, Kachhwaha SS (2013) Exergy analysis of a vapor compression-vapor absorption cascade system. IJACR 21:1–10

    Google Scholar 

  6. Jain V, Sachdeva G, Kachhwaha SS, Patel B (2016) Thermo-economic and environmental analyses based multi-objective optimization of vapor compression-absorption cascaded refrigeration system using NSGA-II technique. Energ Convers Manage 113:232–242

    Article  Google Scholar 

  7. Chen Y, Han W, Sun L, Jin H (2015) A new absorption-compression refrigeration system using a mid-temperature heat source for freezing application. Energy Procedia 75:560–565

    Article  Google Scholar 

  8. Goktun S, Er ID (2001) Optimum performance of a solar assisted combined absorption-vapor compression system for air conditioning and space heating. Sol Energy 71:213–216

    Article  Google Scholar 

  9. Kairouani L, Nehdi E (2006) Cooling performance and energy saving of a compression-absorption refrigeration system assisted by geothermal energy. Appl Therm Eng 26:288–294

    Article  Google Scholar 

  10. Sun ZG (2008) Experimental investigation of integrated refrigeration system (IRS) with gas engine, compression chiller and absorption chiller. Energy 33:431–436

    Article  Google Scholar 

  11. Fernandez-Seara J, Sieres J, Vazquez M (2006) Compression-absorption cascade refrigeration system. Appl Therm Eng 26:502–512

    Article  Google Scholar 

  12. Jain V, Kachhwaha SS, Sachdeva G (2014) Exergy analysis of a vapour compression-absorption cascaded refrigeration system using modified Gouy-Stodola equation. Int J Exergy 15:1–23

    Article  Google Scholar 

  13. Jain V, Sachdeva G, Kachhwaha SS (2015) Thermodynamic modelling and parametric study of a low temperature vapour-compression absorption system based on modified Gouy-Stodola equation. Energy 79:407–418

    Article  Google Scholar 

  14. Jain V, Sachdeva G, Kachhwaha S (2015) Energy, exergy, economic and environmental (4E) analyses based comparative performance study and optimization of vapor compression-absorption integrated refrigeration system. Energy 76:816–832

    Article  Google Scholar 

  15. Cimsit C, Ozturk I, Kıncay O (2015) Thermoeconomic optimization of LiBr-H2O/R134a compression-absorption cascade refrigeration cycle. Appl Therm Eng 15:105–115

    Article  Google Scholar 

  16. Jain V, Sachdeva G, Kachhwaha S (2015) NLP model based thermoeconomic optimization of vapor compression-absorption cascaded refrigeration system. Energ Convers Manage 93:49–62

    Article  Google Scholar 

  17. Sayyadi H, Nejatolahi M (2011) Multiobjective optimization of a cooling tower assisted vapor compression refrigeration system. Int J Refrig 34:243–256

    Article  Google Scholar 

  18. Yang F, Cho H, Zhang H, Zhang J (2017) Thermoeconomic multi-objective optimization of a dual loop organic Rankine cycle (ORC) for CNG engine waste heat recovery. Appl Energy 205:1100–1118

    Article  Google Scholar 

  19. Keshtkar MM, Talebizadeh P (2017) Multi-objective optimization of cooling water package based on 3E analysis: a case study. Energy 134:840–849

    Article  Google Scholar 

  20. Duan C, Wang X, Shu S, Jing C, Chang H (2014) Thermodynamic design of Stirling engine using multi-objective particle swarm optimization algorithm. Energ Convers Manage 84:88–96

    Article  Google Scholar 

  21. Shamoushaki M, Ehyaei MA, Ghanatir F (2017) Exergy, economic and environmental analysis and multi objective optimization of a SOFC-GT power plant. Energy 134:515–531

    Article  Google Scholar 

  22. Patel V, Savsani V, Mudgal A (2017) Many-objective thermodynamic optimization of Stirling heat engine. Energy 125:629–642

    Article  Google Scholar 

  23. Aminyavari M, Mamghani AH, Sirazi A, Najafi B, Rinaldi F (2016) Exergetic, economic, and environmental evaluations and multi-objective optimization of an internal-reforming SOFC-gas turbine cycle coupled with a Rankine cycle. Appl Therm Eng 108:833–846

    Article  Google Scholar 

  24. Damavandi MD, Forouzanmehr M, Safikhani H (2017) Modeling and Pareto based multi objective optimization of wavy fin-and-elliptical tube heat exchangers using CFD and NSGA-II algorithm. Appl Therm Eng 111:325–339

    Article  Google Scholar 

  25. Raja BD, Jhala RL, Patel V (2017) Many-objective optimization of cross-flow plate-fin heat exchanger. Int J Therm Sci 118:320–339

    Article  Google Scholar 

  26. Liu C, Bu W, Xu D (2017) Multi objective shape optimization of a plate-fin heat exchanger using CFD and multi-objective genetic algorithm. Int J Heat Mass Transf 111:65–82

    Article  Google Scholar 

  27. Mirzaei M, Hajabdollahi H, Fadakar H (2017) Multi objective optimization of shell-and-tube exchanger by constructural theory. Appl Therm Eng 125:9–19

    Article  Google Scholar 

  28. Sanaye S, Hajabdollahi H (2010) Multi objective optimization of shell and tube heat exchangers. Appl Therm Eng 30:1937–1945

    Article  Google Scholar 

  29. Civicioglu P (2013) Artificial cooperative search algorithm for numerical optimization problems. Inform Sciences 229:58–76

    Article  MATH  Google Scholar 

  30. Colorado D, Rivera W (2015) Performance comparison between a conventional vapor compression and compression-absorption, single-stage and double-stage systems used for refrigeration. Appl Therm Eng 87:273–285

    Article  Google Scholar 

  31. Jain V, Sachdeva G, Kachhwaha S (2014) Performance analysis of a vapour compression-absorption cascaded refrigeration system with under sized evaporator and condenser. J Energy South Afr 25:23–36

    Google Scholar 

  32. Colorado D, Velazquez V (2013) Exergy analysis of a compression-absorption cascade system for refrigeration. Int J Energy Res 37:1851–1865

    Article  Google Scholar 

  33. Wang L, Ma A, Tan Y, Cui X, Cui H (2012) Study on solar-assisted cascade refrigeration system. Energy Procedia 16:1503–1509

    Article  Google Scholar 

  34. Garimella S, Brown A, Nagavarapu A (2011) Waste heat driven absorption/vapor-compression cascade refrigeration system for megawatt scale, high-flux, low-temperature cooling. Int J Refrig 34:1776–1785

    Article  Google Scholar 

  35. Chinnappa J, Crees M, Srinivasa Murthy S, Srinivasan K (1993) Solar-assisted vapor compression/absorption cascaded air-conditioning systems. Sol Energy 50:453–458

    Article  Google Scholar 

  36. Marimon M, Arias J, Lundqvist P, Bruno J, Coronas A (2011) Integration of trigeneration in an indirect cascade refrigeration system in supermarkets. Energy Build 43:1427–1434

    Article  Google Scholar 

  37. Jain V, Kachhwaha SS, Sacdeva G (2013) Thermodynamic performance analysis of a vapor compression-absorption cascaded refrigeration system. Energy Convers Manag 75:685–700

    Article  Google Scholar 

  38. Kotas TJ (1995) The exergy method of thermal plant analysis. Krieger Publishing Company, Florida

    Google Scholar 

  39. Arora CP (2000) Refrigeration and airconditioning. Tata Mcgraw Hill Publishing Company Limited, New Delhi

    Google Scholar 

  40. Maya CR, Ibarra JJP, Flores MB, Gobzalez SRG, Covarrubias CM (2012) NLP model of a LiBr-H2O absorption refrigeration system for the minimization of the annual operating cost. Appl Therm Eng 37:10–18

    Article  Google Scholar 

  41. Misra RD, Sahoo PK, Gupta A (2005) Thermoeconomic optimization of LiBr/H2O absorption chiller using structural method. J Energy Resour-Asme 127:119–124

    Article  Google Scholar 

  42. Mehr AS, Zare V, Mahmoudi SMS (2013) Standard GAX versus hybrid GAX absorption refrigeration cycle : from the view point of thermoeconomics. Energy Convers Manag 76:68–82

    Article  Google Scholar 

  43. Cimsit C, Ozturk IT (2012) Analysis of compression-absorption cascade refrigeration cycles. Appl Therm Eng 40:311–317

    Article  Google Scholar 

  44. Gomri R (2013) Simulation study on the performance of solar/natural gas absorption cooling chillers. Energy Convers Manag 65:675–681

    Article  Google Scholar 

  45. Khan J, Zubair S (1999) Design and performance evaluation of reciprocating refrigeration systems. Int J Refrig 22:235–243

    Article  Google Scholar 

  46. Aminyavari M, Najafi B, Shirazi A, Rinaldi F (2014) Exergetic, economic and environmental (3E) analyses, and multi-objective optimization of a CO2/NH3 cascade refrigeration system. Appl Therm Eng 65:42–50

    Article  Google Scholar 

  47. Rezayan O, Behbahaninia A (2011) Thermoeconomic optimization and exergy analysis of CO2/NH3 cascade refrigeration systems. Energy 36:888–895

    Article  Google Scholar 

  48. Bell IH, Wronski J, Quoilin S, Lemort V (2014) Pure and pseudo-pure fluid Thermophysical property evaluation and the open-source Thermophysical property library CoolProp. Ind Eng Chem Res 53:2498–2508

    Article  Google Scholar 

  49. Sanaye S, Shirazi A (2013) Four E analysis and multi objective optimization of an ice thermal storage for air-conditioning applications. Int J Refrig 36:828–841

    Article  Google Scholar 

  50. Wang J, Zhai Z, Jing Y, Zhang C (2010) Particle swarm optimization for redundant building cooling heating and power system. Appl Energy 87:3668–3679

    Article  Google Scholar 

  51. Gnielinski V (1976) New equations for heat and mass transfer in turbulent pipe and channel flow. Int Chem Eng 16:359–367

    Google Scholar 

  52. Incorpera FP, DeWitt DP (2002) Fundamental of mass transfer, 5th edn. John Wiley & Sons, New York

    Google Scholar 

  53. Chato JC (1962) Laminar condensation inside horizontal and inclined tubes. ASHRAE J 4:52–60

    Google Scholar 

  54. Song B (1989) Design and calculation of falling film evaporator for horizontal tube of thermodynamic steam. Technology of Water Treatment 15:39–44

    Google Scholar 

  55. Hofmann L, Greiter I, Wagner A, Weiss V, Alefeld G (1996) Experimental investigation of heat transfer in horizontal tube falling film absorber with aqueous solutions of LiBr with and without surfactants. Int J Refrig 19:331–341

    Article  Google Scholar 

  56. Turgut MS, Demir GK (2017) Quadratic approximation-based hybrid artificial cooperative search algorithm for economic emission load dispatch problems. Int Trans Electr Energ Syst 27:1–14

    Article  Google Scholar 

  57. Kumar R, Kaushik SC, Kumar R, Hans R (2016) Multi-objective thermodynamic optimization of an irreversible regenerative Brayton cycle using evolutionary algorithm and decision making. Ain Shams Eng J 7:741–753

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mert Sinan Turgut.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Turgut, M.S., Turgut, O.E. Comparative investigation and multi objective design optimization of a cascaded vapor compression absorption refrigeration system operating with different refrigerants in the vapor compression cycle. Heat Mass Transfer 55, 467–488 (2019). https://doi.org/10.1007/s00231-018-2430-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00231-018-2430-3

Navigation