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Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 29912

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Study of Two MPPTs for Photovoltaic Systems Using Controllers Based in Fuzzy Logic and Sliding Mode
In this study, we proposed two techniques to track the maximum power point (MPPT) of a photovoltaic system. The first is an intelligent control technique, and the second is robust used for variable structure system. In fact the characteristics I-V and P–V of the photovoltaic generator depends on the solar irradiance and temperature. These climate changes cause the fluctuation of maximum power point; a maximum power point tracking technique (MPPT) is required to maximize the output power. For this we have adopted a control by fuzzy logic (FLC) famous for its stability and robustness. And a Siding Mode Control (SMC) widely used for variable structure system. The system comprises a photovoltaic panel (PV), a DC-DC converter, which is considered as an adaptation stage between the PV and the load. The modelling and simulation of the system is developed using MATLAB/Simulink. SMC technique provides a good tracking speed in fast changing irradiation and when the irradiation changes slowly or it is constant the panel power of FLC technique presents a much smoother signal with less fluctuations.
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[1] S. Rustemli, F. Dincer, “Modeling of Photovoltaic Panel and Examining Effects of Temperature in Matlab/Simulink”. Electronics and Electrical Engineering Elektronika ir Elektrotechnika, No 3(109) pp 35-40, 2011.
[2] M. A. Eltawil, Z. Zhao, “MPPT techniques for photovoltaic applications”. Renewable and Sustainable Energy Reviews, Vol 25, pp 793-813, 2013.
[3] T. Esram, Patrick L. Chapman, “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques”, IEEE Trans. on Energy Conversion, Vol. 22, No.2, pp 439-449, June.2007,
[4] C. Ben Salah, M. Oualia, “Comparison of fuzzy logic and neural network in maximum power point tracker for PV systems”, Electric Power Systems Research, Vol.81, no. 1, pp. 43-50, Jan. 2011.
[5] C. Chu and C. L. Chen, “Robust maximum power point tracking method for photovoltaic cells: A sliding mode control approach,” Solar Energy, vol. 83, no. 8, pp. 1370–1378, 2009.
[6] D. Vasarevicius, R. Martavicius, M. Pikutis, “Application of Artificial Neural Networks for Maximum Power Point Tracking of Photovoltaic Panels”. Elektronika ir Elektrotechnika, vol. 19, no. 10, pp. 65–68, 2012.
[7] B.C. Kok, H.H. Goh, H.G. Chua, "Optimal Power Tracker for StandAlone Photovoltaic system using Artificial Neural Network (ANN) and Particle Swarm Optimisation (PSO)", Proceedings of ICREPQ’12 Santiago de Compostela (Spain), 28-30 March, 2012.
[8] P. Takun, S. Kaitwanidvilai and C. Jettanasen, “Maximum Power Point Tracking using Fuzzy Logic Control for Photovoltaic Systems”, Proceedings of IMECS 2011, March 16 - 18, 2011, Hong Kong.
[9] N. Ould Cherchali, M.S. Boucherit, A. Morsli, L. Barazane, " Robust Controller to Extract the Maximum Power of a Photovoltaic System", Journal of Electrical and Electronics Engineering, VOL7, N01, pp. 117- 122, 2014
[10] N. Ould Cherchali, M.S. Boucherit, A. Morsli, L. Barazane, “Application of Fuzzy Robust Controller for Photovoltaic Systems”, International Renewable and Sustainable Energy Conference, March 7 9 2013, Ouarzazate, Morocco.
[11] G. Wei. Hong, K. Y. Lum, J. S. Lin “Fuzzy Grey Sliding Mode Control for Maximum Power Point Tracking of Photovoltaic Systems” proceeding of the 10th IEEE ICCA, Hangzhou, China, pp.11901195, June 12-14, 2013.
[12] E. Bianconi, J. Calvente, R. Giral, E. Mamarelis, G. Petrone, C. A. Ramos-Paja, G. Spagnuolo, M. Vitelli, “A Fast Current-Based MPPT Technique Employing Sliding Mode Control” Industrial Electronics, IEEE Transactions on , vol.60, no.3, pp.1168-1178, 2013.
[13] H. Afghoul, D. Chikouche, F. Krim, A. Beddar, “A novel implementation of MPPT sliding mode controller for PV generation systems”, proceeding of IEEE EuroCon 2013, Zagreb, Croatia, pp.789- 794,1-4 July 2013.
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