Performance study of solar-assisted air-conditioning system provided with storage tanks using artificial neural networks

This study presents the performance of solar-assisted air-conditioning system provided with two storage tanks installed in the Solar Energy Research Center (CIESOL) building. The system consists mainly of solar collectors’ array, a hot-water driven absorption chiller, a cooling tower, two hot storage tanks, an auxiliary heater as well as two cold storage tanks. The hot storage tank circuit was further investigated. In first step, we have carried out the study about the necessity of the integration of hot water storage tanks to solar system. Subsequently, the unique Artificial Neural Network (ANN) model with the lowest number of input variables has been proposed with the main purpose to predict the coefficient of performance and the cooling capacity of the absorption chiller. The configuration 5-9-2 (5 inputs, 9 hidden and 2 output neurons) was found to be the optimal topology. The results demonstrate proper ANN’s predictions with a Root Mean Square Error (RMSE) of less than 0.70% and practically null deviation, which can be considered very satisfactory.