Fuzzy model representation of thermosyphon solar water heating system

Abstract The aim of this paper is to focus on improvement in prediction accuracy of model for thermosyphon solar water heating (SWH) system. The work employs grey-box modeling approach based on fuzzy system to predict the outlet water temperature of the said system. The prediction performance results are compared with neural network technique, which has been suggested by various researchers in the last one decade. The outlet water temperature prediction by fuzzy modeling technique is analyzed by using 3 models, one with three inputs (inlet water temperature, ambient temperature, solar irradiance), next with two inputs (inlet water temperature, solar irradiance) and last one with single input (solar irradiance/inlet water temperature). An improved prediction performance is observed with three inputs fuzzy model.

[1]  D. E. Prapas Improving the actual performance of thermosiphon solar water heaters , 1995 .

[2]  Avraham Shitzer,et al.  The natural circulation solar heater-models with linear and nonlinear temperature distributions , 1977 .

[3]  Soteris A. Kalogirou,et al.  Artificial neural networks used for the performance prediction of a thermosiphon solar water heater , 1999 .

[4]  Soteris A. Kalogirou,et al.  MODELING OF SOLAR DOMESTIC WATER HEATING SYSTEMS USING ARTIFICIAL NEURAL NETWORKS , 1999 .

[5]  Soteris A. Kalogirou,et al.  Thermosiphon solar domestic water heating systems: long-term performance prediction using artificial neural networks , 2000 .

[6]  Soteris A. Kalogirou Long-term performance prediction of forced circulation solar domestic water heating systems using artificial neural networks , 2000 .

[7]  D. J. Close,et al.  The performance of solar water heaters with natural circulation , 1962 .

[8]  E. Mizutani,et al.  Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review] , 1997, IEEE Transactions on Automatic Control.

[9]  H. P. Garg,et al.  System design in solar water heaters with natural circulation , 1968 .

[10]  H.M.S. Hussein,et al.  Transient investigation of a thermosyphon flat-plate solar collector , 1999 .

[11]  Graham Morrison,et al.  Thermosyphon circulation in solar collectors , 1980 .

[12]  Soteris A. Kalogirou,et al.  Simulation of a solar domestic water heating system using a time marching model , 2002 .

[13]  Christos N. Schizas,et al.  A comparative study of methods for estimating intercept factor of parabolic trough collectors , 1996 .

[14]  E. Pereira,et al.  Representation of a Thermosiphon System Via Neural Networks Considering Installation Parameters , 2006, 2006 IEEE International Conference on Engineering of Intelligent Systems.

[15]  K. S. Ong A finite-difference method to evaluate the thermal performance of a solar water heater , 1974 .

[16]  Afif Hasan Thermosyphon solar water heaters: effect of storage tank volume and configuration on efficiency , 1997 .

[17]  Khalid A. Joudi,et al.  Computer simulation of a two phase thermosyphon solar domestic hot water heating system , 1999 .

[18]  Graham L. Morrison,et al.  Simulation of the long term performance of thermosyphon solar water heaters , 1984 .

[19]  Graham L. Morrison,et al.  Transient response of thermosyphon solar collectors , 1980 .

[20]  Luis A. Medinelli Sanino,et al.  Modeling and identification of solar energy water heating system incorporating nonlinearities , 2007 .