Improving Efficiency of Photovoltaic System by Using Neural Network MPPT and Predictive Control of Converter

Mahdi Heidari


This paper proposes a new method to extract maximum energy from Photovoltaic (PV) systems. The artificial neural network (ANN) is used to track the maximum power based on the irradiance level and temperature. By using this algorithm the current in which the PV operates at its maximum power is extracted. In addition to ANN, a predictive controller is used to maximize the efficiency of the boost converter. The simulation results verify the suitable performance of the proposed method and this method maximizes the photovoltaic system energy extraction.

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Photovoltaic system; MPPT; neural network; predictive controller

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A. K. Abdelsalam, A. M. Massoud, S. Ahmed, and P. N. Enjeti, "High-performance adaptive perturb and observe MPPT technique for photovoltaic-based microgrids," IEEE Transactions on Power Electronics, vol. 26, pp. 1010-1021, 2011.

S. B. Kjær, "Evaluation of the “hill climbing” and the “incremental conductance” maximum power point trackers for photovoltaic power systems," IEEE Transactions on Energy Conversion, vol. 27, pp. 922-929, 2012.

A. Safari and S. Mekhilef, "Simulation and hardware implementation of incremental conductance MPPT with direct control method using cuk converter," IEEE Transactions on Industrial Electronics, vol. 58, pp. 1154-1161, 2011.

C. Haithem and A. Sakly, "Comparison between P&O and PSO methods based MPPT algorithm for photovoltaic systems," 2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), IEEE, 2015, pp. 694-699.

R. Faraji, A. Rouholamini, HR. Naji, R. Fadaeinedjad, MR. Chavoshian, "FPGA-based real time incremental conductance maximum power point tracking controller for photovoltaic systems," IET Power Electronics, vol. 7, pp. 1294-1304, 2014.

I. Laird and D. D. Lu, "Steady state reliability of maximum power point tracking algorithms used with a thermoelectric generator," in 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013, pp. 1316-1319.

T. Esram, J. W. Kimball, P. T. Krein, P. L. Chapman, and P. Midya, "Dynamic maximum power point tracking of photovoltaic arrays using ripple correlation control," IEEE Transactions on power electronics, vol. 21, pp. 1282-1291, 2006.

V. V. Scarpa, S. Buso, and G. Spiazzi, "Low-complexity MPPT technique exploiting the PV module MPP locus characterization," IEEE transactions on industrial electronics, vol. 56, pp. 1531-1538, 2009.

X. Li, Y. Li, J.E. Seem, "Maximum Power Point Tracking for Photovoltaic System Using Adaptive Extremum Seeking Control," IEEE Transactions on Control Systems Technology, vol. 21, pp. 2315-2322, 2013.

A. Bahgat, N. Helwa, G. Ahmad, and E. El Shenawy, "Maximum power point traking controller for PV systems using neural networks," Renewable Energy, vol. 30, pp. 1257-1268, 2005.

B. Tarek, D. Said, and M. Benbouzid, "Maximum power point tracking control for photovoltaic system using adaptive neuro-fuzzy," in ANFIS"," in Eighth International Conference and Exhibition on Ecological Vehicles and Renewable Energies (EVER), Monte Carlo, 2013.

A. Gupta, P. Kumar, R. K. Pachauri, Y. K. Chauhan, "Performance analysis of neural network and fuzzy logic based MPPT techniques for solar PV systems," In Power India International Conference (PIICON), 2014 6th IEEE, pp. 1-6.

J. Li and H. Wang, "Maximum power point tracking of photovoltaic generation based on the fuzzy control method," in 2009 International Conference on Sustainable Power Generation and Supply, 2009, pp. 1-6.

J. L. Santos, F. Antunes, A. Chehab, and C. Cruz, "A maximum power point tracker for PV systems using a high performance boost converter," Solar Energy, vol. 80, pp. 772-778, 2006.

A. Kotsopoulos, J. Duarte, and M. Hendrix, "A predictive control scheme for DC voltage and AC current in grid-connected photovoltaic inverters with minimum DC link capacitance," in Industrial Electronics Society, 2001. IECON'01. The 27th Annual Conference of the IEEE, 2001, pp. 1994-1999.

M. Elshaer, A. Mohamed, and O. Mohammed, "Smart optimal control of DC-DC boost converter in PV systems," in Transmission and Distribution Conference and Exposition: Latin America (T&D-LA), 2010 IEEE/PES, 2010, pp. 403-410.

G. Walker, "Evaluating MPPT converter topologies using a MATLAB PV model," Journal of Electrical & Electronics Engineering, vol. 21, pp. 49-56, 2001.

A. Sarwar, M. Hasan, AQ. Ansari, "Five parameter modelling and simulation of solar PV cell," In Energy Economics and Environment (ICEEE), IEEE, 2015, pp. 1-5.

S. Kouro, P. Cortés, R. Vargas, U. Ammann, and J. Rodríguez, "Model predictive control—A simple and powerful method to control power converters," IEEE Transactions on Industrial Electronics, vol. 56, pp. 1826-1838, 2009.


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