A novel intelligent strategy-based thermodynamic modeling and analysis of solar-assisted vapor absorption refrigeration system.

Abstract

In recent times, solar energy has been utilized for refrigeration systems due to its efficiency and clean form of energy. Moreover, the evacuated tube collector (ETC)-assisted vapor absorption refrigeration system plays a significant role in the modern industrial world compared to the traditional electrical system. However, the conventional vapor absorption refrigeration system design is complex in nature and causes corrosion in the system. Therefore, in this research, novel Generalized Approximate Reasoning-Based Intelligent Control (GARIC) and Hybrid Ant Colony African Buffalo Optimization (HACABO) methods based on an ETC-linked 5-kW vapor absorption refrigeration system are proposed depending on lithium bromide-water (LiBr-H2O). Primarily, the Haryana region's solar radiation and weather parameters were taken over a year to simulate the ETC system. ETC collects the solar energy for the refrigeration cycle, and the efficiency of the ETC is estimated using the GARIC method as per the input of solar radiation, collector area, and used solar energy. Moreover, the efficiency of the ETC is optimized using the proposed HACABO method. The modified polynomial fits curved equation is utilized for performance analysis. The simulation model of the solar cooling absorption system is carried out in the MATLAB platform. The coefficient of performance (COP) rate of the absorption cycle has gained 0.82% with the help of HACABO. Compared to other recent associated models, the proposed model has maximized the COP in the finest range.