Use of artificial neural network in performance prediction of Solid desiccant powered Vapor compression air conditioning systems
In the present study, artificial neural network (ANN) model for a solid desiccant-vapor compression hybrid air-conditioning system is developed to predict the cooling capacity, power input and coefficient of performance (COP) of the system. This paper also describes the experimental test set up for collecting the required experimental test data. The experimental measurements are taken at steady state conditions while varying the input parameters like air stream flow rates and regeneration temperature. Most of the experimental test data (80%) are used for training the ANN model while remaining (20%) are used for the testing of ANN model. Experimental data were collected during cooling period of March to September. The outputs predicted from the ANN model have a high coefficient of correlation (R>0.988) in predicting the system performance. The results show that the ANN model can be applied successfully and can provide high accuracy and reliability for predicting the performance of the hybrid desiccant cooling systems. Keywords: Artificial neural network; Coefficient of performance; Dehumidifier effectiveness; Moisture removal rate, TRNSYS