Abstract
In this chapter we will deal with a comparative study between two control methods for maximum power point tracking (MPPT) algorithms in photovoltaic (PV) systems. The two MPPT controllers considered in this chapter are: the Fuzzy Logic Controller (FLC) and the Sliding Mode Controller (SMC). The MPPT controller based on the fuzzy-logic-algorithm uses directly the DC-DC converter duty cycle as a control variable and it provides a fast response and good performances against the climatic and load changes. The SMC exhibits a very fast response for tracking the maximum power point (MPP) for photovoltaic systems. The input parameters are the voltage and the current, the duty cycle is used to generate the optimal MPP under different operating conditions. Simulation results show that both algorithms can effectively perform the MPPT hence improving the efficiency of PV systems.
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References
Agorreta J. L., Reinaldos L., Gonzalez, R., Borrega M., Balda, J., & Marroyo, L. (2013). Review of maximum-power-point tracking techniques for solar-photovoltaic systems. Energy Technology, 1, 438–448.
Ammasai, G. N., Nallandula, H. A., & Krithiga, S. (2009). Fuzzy logic controller with mppt using line commutated inverter for three phase grid connected photovoltaic systems. Renewable Energy, 34, 909–915.
Bose, B. K. (2010). Global warming: Energy, environmental pollution, and the impact of power electronics. IEEE Industrial Electronics Magazine, 4, 6–17.
Femia, N., Petrone, G., Spagnuolo, G., & Vitelli, V. (2005). Optimization of perturb and observe maximum power point tracking method. IEEE Transactions on Power Electronics, 20, 963–973.
Feng, Y., Zheng, J., Yu, X., & Vu. T. N. (2009). Hybrid terminal sliding mode observer design method for a permanent magnet synchronous motor control system. IEEE Transaction on Industrial Electronics, 56, 3424–3431.
Garraoui, R., Hamed, M. B., & Sbita, L. (2013). MPPT controller for a photovoltaic power system based on fuzzy logic. 10th IEEE International Conference on International Multi-Conference on Systems, Signals and Devices (SSD), Hammamet, Tunisia.
Il-Song, K. (2007). Robust maximum power point tracker using sliding mode controller for the three-phase grid-connected photovoltaic system. Solar Energy, 81, 405–414.
Koutroulis, E., & Blaabjerg, F. (2013). Design optimization of transformer less grid-connected pv inverters including reliability. IEEE Transactions on Power Electronics, 28, 325–335.
Ran, B., & Boyce, D. E. (1996). Modeling Dynamic Transportation Network. Germany: Springer.
Rekioua, D., Lalouni, S., Rekioua, T., & Matagne, E. (2009). Fuzzy logic control of stand-alone photovoltaic system with battery storage. Journal of Power Sources, 193, 899–907.
Patcharaprakiti, N., Premrudeepreechacharn, S., & Sriuthaisiriwong, Y. (2005). Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system. Renewable Energy, 30, 1771–1788.
Young, G. O. (1964). Synthetic structure of industrial plastics. Polymers of Hexadromicon 2nd ed., J. Peters, Ed., New York: McGraw-Hill, 3, 15–64.
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Garraoui, R., Ben Hamed, M., Sbita, L. (2017). MPPT Controllers Based on Sliding-Mode Control Theory and Fuzzy Logic in Photovoltaic Power Systems: A Comparative Study. In: Derbel, N., Ghommam, J., Zhu, Q. (eds) Applications of Sliding Mode Control. Studies in Systems, Decision and Control, vol 79. Springer, Singapore. https://doi.org/10.1007/978-981-10-2374-3_12
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DOI: https://doi.org/10.1007/978-981-10-2374-3_12
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