Multi-objective Optimization of Ionic Liquid Absorption Refrigeration Cycles using Genetic Algorithm

The performance of refrigeration cycle depends not only on their configuration, but also on thermodynamic properties of working pair. Typical absorption systems use refrigerant/absorbent combinations of lithium bromide-water and water-ammonia. Because of difficulties in using these combinations, researchers proposed Ionic Liquids as novel alternative absorbent of refrigerant which can be used in absorption refrigeration cycles. In this study, the performance of the absorption refrigeration system with two different ionic liquids, thermodynamically and economically investigated and compared with the water-lithium bromide system. Multiobjective optimization using genetic algorithm is carried out for optimization of cycle. The thermodynamic properties of mixtures as the working fluid pair are predicted using Non-Random Two Liquids model. The coefficient of performance, exergetic efficiency and product cost flow rate are the parameters which were selected as objective functions. The optimal values of objective functions and design parameters were found and compared to the initial values. Among the combinations include ionic liquids, the highest coefficient of performance and exergetic efficiency and minimum product cost flow rate are obtained for the water-1-ethyl-3methylimidazolium trifluoroacetate combination.