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.
[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.
[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.
@article{"International Journal of Information, Control and Computer Sciences:69981", author = "N. Ouldcherchali and M. S. Boucherit and L. Barazane and A. Morsli", title = "Study of Two MPPTs for Photovoltaic Systems Using Controllers Based in Fuzzy Logic and Sliding Mode", abstract = "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.", keywords = "Fuzzy logic controller, maximum power point,
photovoltaic system, tracker, sliding mode controller.", volume = "9", number = "5", pages = "1269-6", }