A new correlation for performance prediction of small and large capacity single-effect vapor absorption refrigeration systems

Abstract

Vapor absorption refrigeration (VAR) enables cleaner cooling by exploiting waste or renewable heat, hence avoiding the use of fossil-based electricity employed by conventional chillers. A new correlation is developed for the prediction of the coefficient of performance (COP) of single-effect VAR systems under different operating conditions, considering 27 different working fluids and 1,568 literature data points. The developed correlation incorporates for the first-time fluid parameters such as the boiling points of absorbents and refrigerants, the latent heat of vaporization of refrigerants, and the specific heat of absorbents together with the generator, condenser, absorber and evaporator temperatures. It is further applied for the first time in both small- and large-scale VAR systems, with the former validated based on results from literature and the latter based on ASPEN Plus simulation data, derived from rigorous VAR system models. The small-scale, literature results reveal that the developed COP model is applicable for all data sets with a mean absolute percentage error (MAPE) of 12.25%, for 93.78% of the data that appear within a ± 30% error range. The developed model is also applied to the simulation of large-scale VAR cycles that use ammonia-water (NH3-water) and water-lithium bromide (water-LiBr) for different cooling loads (100 TR, 1000 TR, and 10,000 TR), to evaluate its suitability for high-capacity systems. The maximum MAPE among the model-predicted and ASPEN Plus-generated data is 13.51% for the 100 TR water-LiBr system, with all data found within a ± 30% error band. The developed model can be applied to predict the COP of numerous fluids for single effect VAR cycles, paving the way for the investigation of VAR application in large scale, district cooling systems.