Generating hot water by solar energy and application of neural network

Abstract Solar technology already boasts a century of research and development, requires no toxic fuel and relatively little maintenance, is inexhaustible and with adequate financial support, is capable of becoming directly competitive with conventional technologies in many fields. These attributes make solar energy one of the most promising sources for many current and future energy needs. In this study, an experimental solar hot water generator, consisting of a cylindrical concentrator, an absorber, a heat exchanger, a water store, a pump and a control unit has been constructed and tested in order to establish the thermodynamic efficiency of the system. Experimental data were obtained and used to train an artificial neural network in order to implement a mapping between easily measurable features such as environmental conditions, input and output water temperatures, solar radiation and flow rate of hot water.