Multi-objective optimization and exergoeconomic analysis of a novel solar desalination system with absorption cooling

This paper presents a novel design for a solar-powered desalination system utilizing a single-effect absorption refrigeration cycle with a flat-plate solar collector. The NH3-H2O working fluid pair in the refrigeration subsystem produces chilled water while the rejected heat from the condenser drives a humidification- dehumidification (HDH) subsystem for freshwater generation. This cycle has been analyzed thermodynamically and exergetically to understand its key performance parameters. Furthermore, for a detailed examination and optimization, an exergoeconomic analysis was also conducted. Design parameters for this study include the tilt angle of the solar collector, Volume fraction of nanoparticles in the CuO nanofluid, Solar collector area, Base fluid mass flow rate in the collector, Mass flow rate of the strong solution, Absorber and condenser temperatures, Mass ratio and Humidifier effectiveness. The Objective functions used to evaluate the system, performance are the Cooling effect of performance (COP), Energy performance (EP), Exergy efficiency (mu Exe), and the Total product cost rate of the system (C(center dot)p,Tot). The genetic algorithm optimization is employed to find the best system performance using two sets of three objective functions. The effectiveness of multi-objective optimization using LINMAP, TOPSIS, and Shannon Entropy methods is demonstrated. LINMAP and TOPSIS consistently achieved improvements in COP (32-42 %), exergy efficiency (33-48 %), and reduced total cost (89-90 %) compared to the base point, while Shannon Entropy offered slightly lower gains. These methods consistently identify superior system configurations, achieving significant improvements in performance while minimizing the total product cost rate.