MULTI-OBJECTIVE OPTIMIZATION OF AN AMMONIA-BASED MULTI-STAGE VAPOR COMPRESSION REFRIGERATION SYSTEM WITH FLASH INTERCOOLER CUM SUBCOOLER

Abstract

This work focuses on multi-objective optimization of an ammonia-based multi-stage vapor compression refrigeration system incorporated with a flash intercooler which also works as a sub-cooler. The study is carried out via thermo-economic optimization of the system in order to maximize the exergetic efficiency and minimize the total capital cost of the system. Evaporator temperature, condenser temperature, subcooling parameter, and de-superheating parameter are considered as the four design variables of optimization problem. Multi-objective Genetic Algorithm (MOGA) is employed to carry out the optimization using MATLAB. The technique for order of preference to by similarity to ideal solution (TOPSIS) decision-making technique has been used to find unique solutions for five different weights of exergetic efficiency and total cost. The results reveal that exergetic efficiency and total capital cost of the system are 41.76% and 223,717.6 USD, respectively, at thermo-economic optimal operating conditions.