Optimization of a Photovoltaic Pumping System by Applying Fuzzy Control Type-1 with Adaptive Gain

  • Samia BensmailEmail author
  • Djamila Rekioua
  • Chafiaa Serir
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 62)


In this paper a robust intelligent controller based on the theory of fuzzy logic is adopted in order to fulfil maximum power point tracking (MPPT) algorithm for a photovoltaic generator, on the one hand and to control the asynchronous motor used in the photovoltaic pumping system on the other hand. In this context, the modelization and simulation of the various constituents of the installation (photovoltaic cell, converters, asynchronous motor and pump) is done. To follow the point of maximum power, an adaptation stage equipped with an MPPT algorithm is inserted by introducing two fuzzy algorithms (classical and adaptive). In the second part we will be interested in the control of the asynchronous motor by afield oriented control (FOC, using three controllers, the simulation results obtained on Matlab/Simulink, shows the importance of the techniques implemented in particular on the efficiency, robustness and response time.


Photovoltaic PV pumping MPPT Fuzzy logic Adaptive fuzzy logic 


  1. 1.
    Bentaillah, A.: étude expérimental et de simulation des performances d’une installation PV de faible puissance. Memory of Magister in energy physics Tlemcen (1994)Google Scholar
  2. 2.
    Rekioua, D., Bensmail, S., Bettar, N.: Development of hybrid photovoltaic-fuel cellsystem for stand-alone application. Int. J. Hydrogen Energy 39, 1604–1611 (2014)CrossRefGoogle Scholar
  3. 3.
    Karbakhsh, M., Abutorabi, H., Khazaee, A.: An enhanced MPPT fuzzy control of a wind turbine equipped with permanent magnet synchronous generator. In: 2nd International Conference on Computer and Knowledge Engineering (ICCKE), October 18–19, IRAN (2012)Google Scholar
  4. 4.
    Gules, R., Pellegrin, J.D.P., Hey, H.L., Imhoff, J.: A maximum power point tracking system with parallel connection for PV stand-alone applications. IEEE Trans. Ind. Electron. 55, 2674–2683 (2008)CrossRefGoogle Scholar
  5. 5.
    Patcharaprakiti, N., Premrudeepre-echacharn, S., Sriuthaisiriwong, Y.: Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system. Renew. Energy 30, 1771–1788 (2005)CrossRefGoogle Scholar
  6. 6.
    Bensmail, S., Rekioua, D.: Optimisation d’un système de pompage photovoltaïque en utilisant la commande vectorielle basée sur la logique flou adaptative. In: Conférence ICEE 2014, October 21–23, Annaba, algeria (2014)Google Scholar
  7. 7.
    Bensmail, S., Rekioua, D., Azzi, H.: Study of hybrid photovoltaic/fuel cell system for stand-alone applications. Int. J. Hydrogen Energy 40, 13820–13826 (2015)CrossRefGoogle Scholar
  8. 8.
    Bensmail, S., Rekioua, D., Serir, C.: Energy management and optimization of a hybrid system (wind/photovoltaic) with battery storage for water pumping. In: 6th European Conference on Renewable Energy Systems, 25–27 June, Istanbul, Turkey (2018)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Samia Bensmail
    • 1
    Email author
  • Djamila Rekioua
    • 2
  • Chafiaa Serir
    • 2
  1. 1.Electrical Engineering DepartmentUniversity of BouiraBouriaAlgeria
  2. 2.Laboratory LTII, Department of Electrical EngineeringUniversity of BejaiaBéjaïaAlgeria

Personalised recommendations