Fast and Efficient Maximum Power Point Tracking Controller for Photovoltaic Modules
Adv. Sci. Technol. Eng. Syst. J. 5(6), 606–612 (2020);
DOI: 10.25046/aj050674
This paper presents an efficient Maximum Power Point Tracking (MPPT) controller for photovoltaic modules. The MPPT technique consists of a combination between backstepping controller and artificial neural network (ANN).The (ANN) has been employed to generate the optimum voltage, which corresponds to the maximum power voltage delivered by photovoltaic modules, while the backstepping controller is developed to track the generated voltage, by computing the duty cycle of the Single Ended Primary Inductor Converter (SEPIC). The control of the boost converter is based on Lyapunov stability analysis, and an integral action is added to increase system robustness. In order to prove the accuracy of the developed control a comparison between the proposed method and sliding mode was carried out. In addition the stability was evaluated under sudden variation of environmental conditions. The simulation was carried out in MATLAB software, the results shows that the proposed controller tracks the reference voltage within 25 ms, in addition the systems reacts to sudden environments change with no oscillations, which demonstrate the robustness of the proposed method.
- T. Esram, P.L. Chapman, “Comparison of photovoltaic array maximum power point tracking techniques,” IEEE Transactions on Energy Conversion, 22(2), 439–449, 2007, doi:10.1109/TEC.2006.874230.
- M.K. Dr S.R.Kapoor, “Comparison between IC and Fuzzy Logic MPPT Algorithm Based Solar PV System using Boost Converter,” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 04(06), 4927–4939, 2015, doi:10.15662/ijareeie.2015.0406007.
- J.P. Ram, T.S. Babu, N. Rajasekar, “A comprehensive review on solar PV maximum power point tracking techniques,” Renewable and Sustainable Energy Reviews, 67, 826–847, 2017, doi:10.1016/j.rser.2016.09.076.
- M. Al-Dhaifallah, A.M. Nassef, H. Rezk, K.S. Nisar, “Optimal parameter design of fractional order control based INC-MPPT for PV system,” Solar Energy, 159(June 2017), 650–664, 2018, doi:10.1016/j.solener.2017.11.040.
- O. Zebraoui, M. Bouzi, “Robust sliding mode control based MPPT for a PV/Wind hybrid energy system,” International Journal of Intelligent Engineering and Systems, 11(5), 290–300, 2018, doi:10.22266/IJIES2018.1031.27.
- O. Diouri, N. Es-Sbai, F. Errahimi, A. Gaga, C. Alaoui, “Modeling and Design of Single-Phase PV Inverter with MPPT Algorithm Applied to the Boost Converter Using Back-Stepping Control in Standalone Mode,” International Journal of Photoenergy, 2019, 2019, doi:10.1155/2019/7021578.
- S.A. Touil, N. Boudjerda, A. Boubakir, K. El Khamlichi Drissi, “A sliding mode control and artificial neural network based MPPT for a direct grid-connected photovoltaic source,” Asian Journal of Control, 21(4), 1892–1905, 2019, doi:10.1002/asjc.2007.
- W.M. Moussa, “Modeling and Performance Evaluation of a DC/DC SEPIC Converter,” Proceedings of 1995 IEEE Applied Power Electronics Conference and Exposition, 1995, 1995, doi: 10.1109/APEC.1995.469096
- D. Adar, G. Rahav, S. Ben-Yaakov, “A unified behavioral average model of SEPIC converters with coupled inductors,” Power Processing and Electronic Specialists Conference 1997, 1997,doi: 10.1109/PESC.1997.616761
- E. Durán, M. Sidrach-De-Cardona, J. Galán, J.M. Andújar, “Comparative analysis of Buck-Boost converters used to obtain I-V characteristic curves of photovoltaic modules,” PESC Record – IEEE Annual Power Electronics Specialists Conference, 2036–2042, 2008, doi:10.1109/PESC.2008.4592243.
- A.R. Kashyap, R. Ahmadi, J.W. Kimball, “Input voltage control of SEPIC for maximum power point tracking,” 2013 IEEE Power and Energy Conference at Illinois, PECI 2013, 30–35, 2013, doi:10.1109/PECI.2013.6506030..
- R.W. Erickson, D. Maksimovic, Fundamentals of Power Electronics, 2nd Edition, 2001.
- K. Chennoufi, M. Ferfra, M. Mokhlis, “An accurate modelling of PV Modules based on two-diode model,” Renewable Energy, 2020, https://doi.org/10.1016/j.renene.2020.11.085
- N. Nambiar, R.S. Palackal, K. V. Greeshma, A. Chitra, “PV fed MLI with ANN based MPPT,” 4th IEEE Sponsored International Conference on Computation of Power, Energy, Information and Communication, ICCPEIC 2015, 293–300, 2015, doi:10.1109/ICCPEIC.2015.7259478.
- S.Z. Hassan, H. Li, T. Kamal, J. Ahmad, M.H. Riaz, M. A. Khan, “Performance of Different MPPT Control Techniques for Photovoltaic Systems” in 5th International Conference on Electrical Engineering, UET Lahore, Pakistan from Feb. 15-16th, 2018, doi: 10.1109/ICEE.2018.8566713
- S.Z. Hassan, H. Li, T. Kamal, L. Khan, S. Mumtaz, “Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems” Energies, 10(3), 2017, doi: 10.3390/en10030394