Comparison of ANN models for estimating optimal points of crystalline silicon photovoltaic modules

IEEJ Transactions on Power and Energy

Volumn 130, Issue 7, 2010, Pages 661-669

  Syafaruddin, ^a   Karatepe, Engin ^b   Hiyama, Takashi ^a  

^a KUMAMOTO UNIVERSITY   (Japan)

^b EGE UNIVERSITY   (Turkey)

Author keywords

ANFIS; Artificial neural network; Crystalline silicon; Hill climbing; PV modules; RBF; TFFN

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ARTIFICIAL NEURAL NETWORK; COMPUTATIONAL TECHNIQUE; CRYSTALLINE SILICON PV MODULES; CRYSTALLINE SILICONS; ENERGY INDEXES; HILL CLIMBING; MAXIMUM POWER POINT; MULTI-CRYSTALLINE SILICON; NONLINEAR CHARACTERISTICS; OPERATING VOLTAGE; OPTIMAL POINTS; OPTIMIZATION PROCESS; PV MODULES; PV SYSTEM; RADIAL BASIS FUNCTION NEURAL NETWORKS; SOLAR CELL TECHNOLOGY; THIN-FILM SILICON SOLAR CELLS; WEAK POINTS;

CRYSTALLINE MATERIALS; ENERGY CONVERSION; FILM GROWTH; FUZZY INFERENCE; FUZZY SYSTEMS; OPTIMIZATION; PATTERN RECOGNITION SYSTEMS; PHOTOVOLTAIC EFFECTS; RADIAL BASIS FUNCTION NETWORKS; SEMICONDUCTING SILICON COMPOUNDS; SILICON WAFERS; SOLAR CELLS; TECHNOLOGY;

NEURAL NETWORKS;

EID: 77955548173     PISSN: 03854213     EISSN: 13488147     Source Type: Journal    
DOI: 10.1541/ieejpes.130.661     Document Type: Article

References (25)

1. A. Mellit and S.A. Kalogirou: Artificial intelligence techniques for photovoltaic applications: A review". Progress in Energy & Combustion Sci., Vol.34, No.5, pp.574-632 (2008)
2. A. Mellit, S.A. Kalogirou, L. Hontoria, and S. Shaari: "Artificial intelligence techniques for sizing photovoltaic systems: A review". Renewable & Sustainable Energy Rev., Vol.13, No.2, pp.406-419 (2009)
3. F. Giraud and Z.M. Salameh: "Analysis of the effects of a passing cloud on a grid-interactive photovoltaic system with battery storage using neural networks", IEEE Trans. Energy Conversion, Vol.14, No.4, pp.1572-1577 (1999)
4. A. Mellit, M. Benghanem, and S.A. Kalogirou: "An adaptive wavelet-network model for forecasting daily total solar-radiation", Appl. Energy, Vol.83, No.7, pp.705-722 (2006)
5. X. Sun, W. Wu, X. Li, and Q. Zhao: "A research on photovoltaic energy controlling system with maximum power point tracking", Proc. 2002 Power Conversion Conf., Vol.2, pp.822-826 (2002)
6. Syafaruddin, E. Karatepe, and T. Hiyama: "Polar coordinated fuzzy controller based real-time maximum power point control of photovoltaic system", Renewable Energy, Vol.12, No.34, pp.2597-2606 (2009)
7. Syafaruddin, E. Karatepe, and T. Hiyama: "Artificial neural network polar coordinated fuzzy controller based maximum power point tracking control under partially shaded conditions", IEE Renewable Power Generation, Vol.3, No.2, pp.239-253 (2009)
8. A. de Medeiros Torres, F.L.M. Antunes, and F.S. dos Reis: "An artificial neural network-based real time maximum power tracking controller for connecting a PV system to the grid", Proc. 1998 the 24th Annual Conf. of the IEEE on Industrial Electronics Society, Vol.1, pp.554-558 (1998)
9. Y. Narri and V. Mummadi: "Adaptive controller for PV supplied buck-boost converter", Proc. 1999 IEEE International Conf. on Power Electronics and Drive Systems, pp.789-793 (1999)
10. K. Jae-Sub, J. Byung-Jin, P. Ki-Tae, C. Chung-Hoon, and C. Dong-Hwa: "Maximum power point tracking control of PV system for DC motors drive with neural network", Proc. 2008 International Conference on Smart Manufacturing Application, pp.514-519 (2008)
11. B. Cao, L. Chang, and H. Li: "Implementation of the RBF neural network on a SOPC for maximum power point tracking", Proc. 2008 Canadian Conference on Electrical and Computer Engineering, pp.981-985 (2008)
12. A. Vamham, A.M. Al-Ibrahim, G.S. Virk, and D. Azzi: "Soft-computing model-based controllers for increased photovoltaic plant efficiencies", IEEE Trans. Energy Conversion, Vol.22, No.4, pp.873-880 (2007)
13. A. Mellit and S.A. Kalogirou: "Neuro-fuzzy based modeling for photovoltaic power supply system", Proc. 2006 the la International Power and Energy Conf. pp.88-93 (2006)
14. M.G. Villalva, J.R. Gazoli, and E.R. Filho: "Comprehensive approach to modeling and simulation of photovoltaic arrays", IEEE Trans. Power Electronics, Vol.24, No.5, pp.1198-1208 (2009)
15. D.L. King: "Photovoltaic module and array performance characterization methods for all system operating conditions", Proc. of NREL/SNL Photo-voltaics Program Review Meeting, pp.1-22 (1997)
16. D.L. King: Sandia's PV module electrical performance model, Sandia National Laboratories (2000)
17. A. Mellit, M. Menghanem, and M. Bendekhis: "Artificial neural network model for prediction solar radiation data: application for sizing stand-alone photovoltaic power system", Proc. 2005 IEEE Power Engineering Society General Meeting, Vol.1, pp.40-44 (2005) (Pubitemid 41496897)
18. A.A. Elbaset and T. Hiyama: "Fault detection and classification in transmission lines using ANFIS",IEEJTrans. PE, Vol.l29,No.7,pp.705-713 (2009)
19. K. Hyun-Soo, B.G. Morris, H. Seung-Soo, and G.S. May: "A comparison of genetic and particle swarm optimization for contact formation in high-performance silicon solar cells", Proc. 2008 IEEE International Joint Conf. on Neural Networks, pp.1531-1535 (2008)
20. Syafaruddin, E. Karatepe, and T. Hiyama: "ANN based real-time estimation of power generation of different PV module types", IEEJ Trans. Power Energy, Vol.129, No.6, pp.783-790 (2009)
21. E. Karatepe and M. Alci: "A new approach to fuzzy wavelet system modeling". Int. J. Approximate Reasoning, Vol.40, No.3, pp.302-322 (2005)
22. th IEEE Conf. on Industrial Electronics and Applications, pp.804-807 (2008)
23. S. Jain and V. Agarwal: "Comparison of the performance of maximum power point tracking schemes applied to single-stage grid-connected photovoltaic systems", IETElectric Power Applic., Vol.1, No.5, pp.753-762 (2007)
24. W. Xiao, W.G. Ounford, P.R. Palmer, and A. Capel: "Application of Centered Differentiation and Steepest Descent to Maximum Power Point Tracking", IEEE Trans. Industr. Electronics, Vol.54, No.5, pp.2539-2549 (2007)
25. K.H. Chao and C.-J. Li: "An intelligent maximum power point tracking method based on extension theory for PV systems", Expert Syst. with Applic, Vol.37, No.2, pp.1050-1055 (2010)