Effect of subcooling and superheating on performance of a cascade refrigeration system with considering thermo- economic analysis and multi-objective optimization

Abstract

In present work, effect of degrees of subcooling and superheating based on thermoeconomic optimization is investigated in two stagecascade refrigeration system (TS-CRS). At the first step, by using R717 and R744 as refrigerants, a thermoeconomic analysis is applied to TS-CRS. Based on results of the first section and using the genetic algorithm (GA) optimizer implemented in MATLAB, the optimum operative conditions of a specific TS-CRS is determined. Finally, based on the Pareto frontier obtained from the GA optimization, a decision-making strategy is then used to determine a final solution by TOPSIS method. Two single-objective optimization strategies (SOS), i.e. exergetic optimization and cost optimization, are applied on TS-CRS. The aim of the first strategy is to maximize the exergetic efficiency and the aim of the second strategy is minimizing the total annual cost of the system. The case study results show that, compared to the base design, the use of SOS for maximizing of exergetic efficiency can be increases the exergetic efficiency 94.5%. In addition, the use of the second SOS can decrease the total system cost by 11%. Using MOS compared to base design, exergetic efficiency and the total system cost can be increase by 99.1% and 28.6% respectively.

Multi-Objective Optimization of a R744/R134a Cascade Refrigeration System: Exergetic, Economic, Environmental, and Sensitive Analysis (3es)

“…Parekh et al [16] studied a thermo-economic and cost optimizations using R404A-R508B and determined the cost of the products. Keshtkar [17] modeled and optimized a R744/R717 cascade refrigeration system using multi-objective optimization. Toghyani et al [18] investigated the efficiency and the power loss due to pressure drop into the heat exchangers for a Stirling system using non-ideal adiabatic analysis and the second-version Non-dominated Sorting Genetic Algorithm.…”

Investigation of the effect of superheating on the performance of a refrigeration system using low temperature different refrigerant blends in porous media

“…Paharia et al studied theoretically the effect of subcooling and superheating on vapor compression refrigeration systems using R‐22 as an alternative refrigerant to the refrigerants (R‐410A, R‐507A, and R‐407C). Keshtkar studied the effect of degrees of subcooling and degree of superheating based on thermoeconomic in two‐stage cascade refrigeration system performance, using computer simulation. Parmar and Randa conducted an experimental analysis of vapor compression refrigeration system with superheating by using R‐134a, R‐12, and R‐717 refrigerants.…”

Numerical analysis of transcritical carbon dioxide compression cycle: a case study

“…Coefficient of performance and efficiency of the second law of combined cycle in the same conditions compared with the density cycle increased 14.2 and 3.67% respectively. Keshtkar [5] investigated effect of degrees of subcooling and superheating based on thermoeconomic optimization in two stage-cascade refrigeration system by using R717 and R744 as refrigerants. At the another works, Keshtkar et al [6], [7] carried out a multi-objective optimization of cooling water package based on exergetic, economic and environmental analysis (3E) employing the non-dominated sorting genetic algorithm.…”