Modelling of steam fired double effect vapour absorption chiller using neural network

In this paper, steady state modelling of a double effect absorption chiller using steam as heat input is presented and discussed. The modelling is based on the artificial neural network (ANN) technique with 6-6-9-1 configuration. The neural network is a fully connected feed forward configuration using the back propagation learning algorithm. The model will predict the chiller performance based on the chilled water inlet and outlet temperatures, cooling water inlet and outlet temperatures and steam pressure. The network was trained with one year of experimental data and predicts the performance within ±1.2% of the actual values.