Abstract
This paper investigates the selection of the best suitable eco-friendly organic and in-organic refrigerants for heating, ventilation, and air conditioning (HVAC) and renewable energy devices. Inorganic and organic refrigerants are used to cool renewable energy devices, such as solar cells, photovoltaics, and electronic devices. Owing to the renewable energy community's importance, development in this area has rapidly improved over the past few years. R134a, R404, and R717 have become the most used refrigerants in the HVAC sector and supermarkets across the globe for both cooling and frozen food refrigeration. R134a and R404A have two significant drawbacks: (a) they do not attain optimal energy efficiency in many applications, and (b) they have a large global warming potential (GWP). Hence, optimization experiments were performed to select low global potential refrigerants for replacing R134a and R404A from the HVAC sector and supermarkets using multi-criteria making (MCDN) tools. The techniques used for investigation involved (i) the technique for order of preference by similarity to ideal solution (TOPSIS), (ii) evaluation based on distance from average solution (EDAS), and (iii) multi-objective optimization based on ratio analysis (MOORA). The assessment criteria of optimization involved (i) thermo-physical properties of refrigerants, (ii) environmental aspects of refrigerants, and (iii) economic status of refrigerants. Out of 27 refrigerants chosen for the study, R290 (PROPANE) aced the selection by all the three techniques, i.e., TOPSIS, EDAS, and MOORA, with assessment scores of 0.6056, 0.6761, and 0.466, respectively. R41 (FLUOROMETHANE) is the least preferred refrigerant by EDAS (assessment score-0.3967) and MOORA, while R407C is the least preferred by TOPSIS (assessment value-0.5123). The likelihood of making a bad refrigerant decision may be reduced by the effective evaluation of the MCDM analysis. In conclusion, the suggested MCDM technique provides a practical tool and systematic way for reducing the number of options and may be utilized to identify the ideal refrigerant.