Amelioration of MPPT P&O Using Fuzzy-Logic Technique for PV Pumping

  • K. NebtiEmail author
  • F. Debbabi
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 62)


This paper presents an amelioration of P&O maximum power point tracking (MPPT) technique by using fuzzy logic method, when the main goal is to extract the maximum of power to supply a pumping system in an isolated area. The role of the MPPT is to force the system for working at the maximum point for each change of the illumination or the temperature. We present in first the classical technique, by explaining how we can obtain the maximum power under a variable meteorological condition. In P&O strategy, for big value of disturbance step we can get quickly the desired point but with a large oscillation. Small value of disturbance step makes very slow system and affects the responding time. By using fuzzy logic technique the appropriate disturbance step is produced in order to obtain a fast system with an acceptable precession. The simulation of the photovoltaic pumping chain is constructed under Matlab/Simulink, when the effectiveness of the fuzzy MPPT strategy is shown by the obtained results, which makes its application for controlling solar panels very interesting.


Solar panel MPPT P&O Fuzzy logic PV pumping 


  1. 1.
    Meekhun, D., Boitier, V., Dilhac, J.M., Blin, G.: An automated and economic system for measuring of the current-voltage characteristics of photovoltaic cells and modules. In: IEEE International Conference on Sustainable Energy Technologies, Singapore (2008)Google Scholar
  2. 2.
    Bouzelata, Y., Kurt, E., Chenni, R., Altın, N.: Design and simulation of a unified power quality conditioner fed by solar energy. Int. J. Hydrog. Energy 41(29), 12485–12496 (2016)CrossRefGoogle Scholar
  3. 3.
    Madaci, B., Chenni, R., Kurt, E., Hemsas, K.E.: Design and control of a stand-alone hybrid power system. Int. J. Hydrog. Energy 41(29), 12485–12496 (2016)CrossRefGoogle Scholar
  4. 4.
    Qi, J., Zhang, Y., Chen, Y.: Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions. Renew. Energy 66, 337–345 (2014)CrossRefGoogle Scholar
  5. 5.
    Kollimalla, S.K., Mishra, M.K.: Variable perturbation size adaptive P&O MPPT algorithm for sudden changes in irradiance. IEEE Trans. Sustain. Energy 5(3), 718–728 (2014)CrossRefGoogle Scholar
  6. 6.
    Altin, N., Yildirimoglu, T.: Labview/matlab based maximum power point substitutable photovoltaic system simulator. J. Polytech. 14(4), 271–280 (2011)Google Scholar
  7. 7.
    El Basri, Y., Petibon, S., Estibals, B.: New P&O MPPT algorithm for FPGA implementation. In: IECON 2010-36th Annual Conference on IEEE Industrial Electronics Society, AZ, USA (2010)Google Scholar
  8. 8.
    Wu, X., Shen, J., Li, Y., Lee, K.Y.: Fuzzy modeling and stable model predictive tracking control of large-scale power plants. J. Process Control 24(10), 1609–1626 (2014)CrossRefGoogle Scholar
  9. 9.
    Lacrose, V., Titli, A.: Fusion and hierarchy can help fuzzy logic controller designers, fuzzy systems. In: Proceedings of the Sixth IEEE International Conference on, Barcelona, Spain (1997)Google Scholar
  10. 10.
    Labrique, F., Seguier, G., Bausier, R.: The electronic power converters. Vol 4: DC-AC Conversion, Lavoisier (1995)Google Scholar
  11. 11.
    Eskander, M.N., Zaki, A.M.: A maximum efficiency-photovoltaic-induction motor pump system. Renew. Energy Journal 10(1), 53–60 (1997)CrossRefGoogle Scholar
  12. 12.
    Chouder, A., Guijoan, F., Silvestre, S.: Simulation of fuzzy-based MPP tracker and performance comparison with perturb and observe method. Rev. Renew. Energy 11(4), 577–580 (2008)Google Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Laboratory Electrotechnique of Constantine LECConstantineAlgeria

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