Multi-objective optimization of a two-bed solar adsorption chiller based on exergy and economics

In this present work, a two-bed solar adsorption chiller is simulated and optimized. This system uses two working-pair candidates, namely silica gel-water and zeolite-water. Optimization using a multi-objective genetic algorithm was conducted to find out the optimum condition of the system in terms of a thermodynamic analysis and an economic point of view. Exergy destruction and total annual costs were the two objective functions examined while solar collector area, cooling water mass flow rate, hot water mass flow rate, and chilled water mass flow rate were chosen as decision variables for optimizing the procedure. The results show that the zeolite-water working pair had a lower value of exergy destruction and annual cost compared to the silica gel-water working pair, which resulted in an exergy destruction of 150,938 watts at annual cost of $216,818 USD. However, the zeolite-water working pair had a lower cooling capacity and coefficient of performance (COP) than the silica gel-water working pair.