Fuzzy model representation of thermosyphon solar water heating system

Solar Energy

Volumn 84, Issue 6, 2010, Pages 948-955

  Kishor, Nand ^a   Das, Mihir Kr ^b   Narain, Anirudha ^a   Prakash Ranjan, Vibhaw ^a  

^a MOTILAL NEHRU NATIONAL INSTITUTE OF TECHNOLOGY   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY BHUBANESWAR   (India)

Author keywords

Flat plate collector; Fuzzy modeling; Prediction; Solar energy; Water heating system

Indexed keywords

AMBIENT TEMPERATURES; FLAT-PLATE COLLECTOR; FUZZY MODELING; FUZZY MODELS; GREY-BOX MODELING; INLET WATER TEMPERATURES; NEURAL NETWORK TECHNIQUES; OUTLET WATER; PREDICTION ACCURACY; PREDICTION PERFORMANCE; SINGLE INPUT; SOLAR IRRADIANCES; SOLAR WATER HEATING; SOLAR WATER HEATING SYSTEMS; THERMOSYPHONS; WATER HEATING SYSTEMS; WATER TEMPERATURES;

CAPILLARY FLOW; DUST COLLECTORS; FORECASTING; FUZZY SETS; HEATING; HEATING EQUIPMENT; HOT WATER DISTRIBUTION SYSTEMS; NEURAL NETWORKS; SIPHONS; SOLAR COLLECTORS; SOLAR ENERGY; SOLAR HEATING; SOLAR RADIATION; SOLAR WATER HEATERS; TEMPERATURE;

FUZZY LOGIC;

ACCURACY ASSESSMENT; FUZZY MATHEMATICS; HEATING; MODEL TEST; NUMERICAL MODEL; PREDICTION; SOLAR POWER; WATER TEMPERATURE;

EID: 77953140332     PISSN: 0038092X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.solener.2010.03.002     Document Type: Article

References (24)

1. Bojić M., Kalogirou S.A., and Petronijević K. Simulation of a solar domestic water heating system using a time marching model. Renewable Energy 27 (2002) 441-452
2. Close D.J. The thermal performance of solar water heater with natural circulation. Solar Energy 6 (1962) 33-40
3. Fuzzy logic toolbox for use with MATLAB®, 2000. The Math Works Inc., USA.
4. Gupta C.L., and Garg H.P. System design in solar water heaters with natural circulation. Solar Energy 12 (1968) 163-182
5. Hasan A. Thermosiphon solar water heaters: effect of storage tank volume and configuration on efficiency. Energy Conversion and Management 38 (1997) 847-854
6. Hussein H.M.S., Mohamad M.A., and El-Asfouri A.S. Transient investigation of a thermosiphon flat-plate solar collector. Applied Thermal Engineering 19 (1999) 789-800
7. Jang J.-S.R., Sun C.-T., and Mizutani E. Neuro-fuzzy and soft computing: A computational approach to learning and machine intelligence (1997), Prentice Hall, Englewood Cliffs, NJ
8. Joudi K.A., and Al-Tabbakh A.A. Computer simulation of a two phase thermosiphon solar domestic hot water heating system. Energy Conversion and Management 40 (1999) 775-793
9. Kalogirou, S.A., 1996. Artificial neural networks for predicting the local concentration ratio of parabolic trough collectors, Proceedings of the International Conference EuroSun'96, Freiburg, Germany, pp. 470-475.
10. Kalogirou S.A. Long-term performance prediction of forced circulation solar domestic water heating systems using artificial neural networks. Applied Energy 66 (2000) 63-74
11. Kalogirou S.A., and Panteliou S. Thermosiphon solar domestic water heating systems: Long-term performance prediction using artificial neural networks. Solar Energy 69 (2000) 163-174
12. Kalogirou, S.A., Neocleous, C.C., Schizas, C.N., 1996a. A comparative study of methods for estimating intercept factor of parabolic trough collectors, Proceedings of the International Conference EANN'96, London, UK, pp. 5-8.
13. Kalogirou, S.A., Neocleous, C.C., Schizas, C.N., 1996b. Artificial neural networks in modeling the heat-up response of a solar steam generation plant, Proceedings of the International Conference EANN'96, London, UK, pp. 1-4.
14. Kalogirou, S.A., Neocleous, C.C., Schizas, C.N., 1997. Artificial neural networks for the estimation of the performance of a parabolic trough collector steam generation system, Proceedings of the International Conference EANN'97, Stockholm, Sweden, pp. 227-232.
15. Kalogirou S.A., Panteliou S., and Dentsoras A. Artificial neural networks used for the performance prediction of a thermosiphon solar water heater. Renewable Energy 18 (1999) 87-99
16. Kalogirou S.A., Panteliou S., and Dentsoras A. Modeling of solar domestic water heating systems using artificial neural networks. Solar Energy 65 (1999) 335-342
17. Morrison G.L., and Ranatunga D.B.J. Transient response of thermosiphon solar collectors. Solar Energy 24 (1980) 191
18. Morrison G.L., and Tran N.H. Simulation of the long term performance of thermosiphon solar water heaters. Solar Energy 33 (1984) 515-526
19. Ong K.S. A finite-difference method to evaluate the thermal performance of a solar water heater. Solar Energy 16 (1974) 137-147
20. Prapas D.E. Improving the actual performance of thermosiphon solar water heaters. Renewable Energy 6 (1995) 399-406
21. Sanino L.A.M., and Reischel R.A.R. Modeling and identification of solar energiy water heating system incorporating nonlinearities. Solar Energy 81 (2007) 570-580
22. Zárate, L.E., Pereira, E.M.D., Silva, J.P., Vimieiro, R., Pires, S., Diniz, A.S.C., 2003. Representation of a solar collector via artificial neural networks. In: Proceedings of the 3rd IASTED International Conference on Artificial Intelligence and Applications, Benalmadena, Spain, pp. 517-522.
23. Zárate, L.E., Pereira, E.M.D., Oliveira, L.A.R., Gil, V.P., Santos, T.R.A., Nogueira, B.M., Rodrigues, M.A., 2006. Representation of a thermosiphon system via neural networks considering installation parameters. In: Proceedings of the 1st IEEE International Conference on Engineering of Intelligent Systems (ICEIS), vol. 1, Islamabad, pp. 1-6.
24. Zvirin Y., Shitzer A., and Grossman G. The natural circulation solar heater-models with linear and nonlinear temperature distributions. International Journal of Heat & Mass Transfer 20 (1977) 997-999