Diffusion-absorption refrigeration cycle simulations in gPROMS using SAFT-γ Mie

Abstract

Diffusion-absorption refrigeration (DAR) is a clean thermally-powered refrigeration technology that can readily be activated by low- to medium-grade renewable heat. There is an ongoing interest in identifying or designing new working fluids for performance improvement, particularly in solar applications with non-concentrating solar collectors providing heat at temperatures < 150 °C. In this work, the state-of-the-art statistical associating fluid theory (SAFT) is adopted for predicting the thermodynamic properties of suitable DAR working fluids. A first-law thermodynamic analysis is performed in the software environment gPROMS for a DAR cycle using ammonia as the refrigerant, water as the absorbent and hydrogen as the auxiliary gas. The simulation results show good agreement with experimental data generated in a prototype DAR system with a nominal cooling capacity of 100 W. In particular, at a charge pressure of 17 bar and when delivering cooling at 5 °C, the model results agree with experimental COP data to within ± 7 % over a range of heat inputs from 150 to 500 W. The maximum coefficient of performance (COP) is estimated to be 0.24 at a heat input of 250 W. The group-contribution SAFT-γ Mie equation of state is of particular interest as it offers good agreement with experimental data and provides flexibility in extending the model to test different working fluids with a high degree of fidelity. A methodology is also presented that allows the DAR thermodynamic analysis and working-fluid modelling to be integrated into a more general technology optimisation framework.