A Comprehensive Comparison of Two Behavior MPPT Techniques, the Conventional (Incremental Conductance (INC)) and Intelligent (Fuzzy Logic Controller (FLC)) for Photovoltaic Systems

  • Aouatif Ibnelouad
  • Abdeljalil El Kari
  • Hassan Ayad
  • Mostafa Mjahed
Part of the Green Energy and Technology book series (GREEN)


This chapter presents a detailed procedure to study and discuss the behavior of different maximum power point tracking (MPPT) techniques applied to PV systems. In this work, we presented a review on the state-of-the-art of photovoltaic System, DC/DC converter and power point tracking techniques such as conventional one incremental conductance (INC) and soft computing method fuzzy logic controller (FLC) are evaluated. The simulation results obtained are developed under software MATLAB/Simulink. Both methods (INC) and (FLC) are used with a boost DC/DC converter and a load. These results show that the fuzzy logic controller is better and faster than the conventional incremental conductance (INC) technique in both dynamic response and steady state in normal operation.


MPPT PV modeling Technique INC Technique FLC Boost DC/DC converter 


  1. Abbes, H., Abid, H., Loukil, K., Toumi, A., & Abid, M. (2014). Etude comparative de cinq algorithmes de commande MPPT pour un système Photovoltaique. Revue des Energies Renouvelables, 17(3), 435–445.Google Scholar
  2. Abdelhak, B., & Boubaker, A. (2014). Contribution à l’optimisation d’une chaine de conversion d’énergie Photovoltaique. Ph.D. thesis, Universite de Constantine.Google Scholar
  3. Amarouayache, M. (2014). Contribution à l’optimisation d’une chaine de conversion d’énergie Photovoltaique. Ph.D. thesis, Constantine 1 University.Google Scholar
  4. Azab, M. (2008). A new maximum power point tracking for photovoltaic systems. World Academy of Science, Engineering and Technology. International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, 2(8).Google Scholar
  5. Carrero, C., Amador, J., & Arnaltes, S. (2007). A single procedure for helping PV designers to select silicon PV module and evaluate the loss resistances. Renewable Energy, 32(15), 2579–2589.CrossRefGoogle Scholar
  6. Eltamaly, A. M. (2010). Modeling of fuzzy logic controller for photovoltaic maximum power point tracker. In Solar Future 2010 Conference Proceedings (pp. 4–9), Istanbul, Feb 2010.Google Scholar
  7. Eltamaly, A. M., Alolah, A. I., & Abdulghany, M. Y. (2010). Digital implementation of general purpose fuzzy logic controller for photovoltaic maximum power point tracker. In Power Electronics Electrical Drives Automation and Motion (SPEEDAM), International Symposium on Digital Object Identifier (pp. 622–627).Google Scholar
  8. Gow, J. A., & Manning, C. D. (1999). Development of a photovoltaic array model for use in power-electronics simulation studies. IEE Proceedings Electric Power Applications, 146(2), 193–200.CrossRefGoogle Scholar
  9. Hyvarinen, J., & Karila, J. (2003). New analysis method for crystalline silicon cells. In Proceedings of 3rd World Conference on Photovoltaic Energy Conversion (Vol. 2, pp. 1521–1524).Google Scholar
  10. Kanji, B., (2012). Intelligent techniques for the tracking of the maximum power point of a supervised photovoltaic system. MA thesis, Lebanese University.Google Scholar
  11. Koutroulis, E., Kalaitzakis, K., & Tzitzilonis, V. (2008). Development of a FPGA-based system for real-time simulation of photovoltaic modules. Microelectronics Journal, 40(7), 1094–1102.CrossRefGoogle Scholar
  12. Moller, H. J. (1993). Semiconductors for solar cells. Norwood: Artech House.Google Scholar
  13. Naffouti, S. E. (2012). Dimensionnement et commande d’un hacheur parallèle alimenté par une source Photovoltaique. M.S. thesis, University of Burgundy, France.Google Scholar
  14. Nishioka, K., Sakitani, N., Uraoka, Y., & Fuyuki, T. (2007). Analysis of multicrystalline silicon solar cells by modified 3-diode equivalent circuit model taking leakage current through periphery into consideration. Solar Energy Materials and Solar Cells, 91(13), 1222–1227.CrossRefGoogle Scholar
  15. Rauschenbach, H. S. (1980). Solar cell array design handbook. New York: Van Nostrand Reinhold.CrossRefGoogle Scholar
  16. Rezaee Jordehi, A. (2016). Maximum power point tracking in photovoltaic (PV) systems: A review of different approaches. Renewable and Sustainable Energy Reviews, 65, 1127–1138.CrossRefGoogle Scholar
  17. Rezk, H., & Eltamaly, A. M. (2015). A comprehensive comparison of different MPPT techniques for photovoltaic systems. Solar Energy, 112, 1–11.CrossRefGoogle Scholar
  18. Reza Reisi, A., Moradi, M.H., & Jamasb, S. (2013). Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review. Renewable and Sustainable Energy Reviews 19, 433–443.CrossRefGoogle Scholar
  19. Salas, V., Olias, E., Barrado, A., & Lazaro, A. (2006). Review of the maximum power point tracking algorithms for stand-alone photovoltaic systems. Solar Energy Materials and Solar Cells, 90(11), 1555–1578.CrossRefGoogle Scholar
  20. Sedra, A. S., & Smith, K. C. (2006). Microelectronic circuits. London: Oxford University Press.Google Scholar
  21. Seyedmahmoudian, M., Horan, B., Kok Soon, T., Rahmani, R., Thango, A. M., Mekhilef S., & Stojcevskiet, A. (2016). State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems-a review. Renewable and Sustainable Energy Reviews, 64, 435–455.CrossRefGoogle Scholar
  22. Verma, D., Nema, S., Shandilya, A. M., & Dash, S. K. (2016). Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems. Renewable and Sustainable Energy Reviews, 54, 1018–1034.CrossRefGoogle Scholar
  23. Villalva, M. G., Gazoli, J. R., & Ruppert Filho, E. (2009). Comprehensive approach to modeling and simulation of photovoltaic arrays. IEEE Transactions on Power Electronics, 24(5), 1198–1208.CrossRefGoogle Scholar
  24. Xiao, W., Dunford, W. G., & Capel, A. (2004). A novel modeling method for photovoltaic cells. In Proceedings of IEEE 35th Annual Power Electronics Specialists Conference (PESC) (Vol. 3, pp. 1950–1956).Google Scholar
  25. Yi-Bo, W., Chun-Sheng, W., Hua, L., & Hong-Hua, X. (2008). Steady-state model and power flow analysis of grid-connected photovoltaic power system. In IEEE International Conference on Industrial Technology, ICIT 2008 (pp. 1–6).Google Scholar
  26. Zainudin, H. N., & Mekhilef, S. (Dec 2010). Comparison study of maximum power point tracker techniques for PV systems. In 14th Middle East Power Systems Conference, Mepcon’10, Cairo University.Google Scholar
  27. Zagroubaa, M., Bouaïchaa, M., Sellamia, A., & Ksouric, M., et al. (2010). Optimisation par les Algorithmes Genetiques et modélisation par la méthode LPV d’un systéme photovoltaique. Vème Congrès Int. sur les Energies Renouvelables et l’Environnement, 4–6 Novembre, Sousse.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Aouatif Ibnelouad
    • 1
  • Abdeljalil El Kari
    • 1
  • Hassan Ayad
    • 1
  • Mostafa Mjahed
    • 2
  1. 1.Department of Applied Physics, Laboratory of Electrical Systems and Telecommunications, Faculty of Sciences and TechnologiesCadi Ayyad UniversityMarrakechMorocco
  2. 2.Department of Mathematics and SystemsRoyal School of AeronauticsMarrakechMorocco

Personalised recommendations