Maximum Power Point Tracking of Photovoltaic System Based on Fuzzy Control to Increase There Solar Energy Efficiency

  • Ahmed HafaifaEmail author
  • Kaid Imed
  • Mouloud Guemana
  • Abudura Salam
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 7)


Recently, the growing need for energy as well as pollution from the use of fossil fuels are driving the general public to use renewable energies. In this context, solar photovoltaic energy is one of the most important sources of renewable energy, which represents a solution to our energy production problems. In addition, this energy seems the most promising, non-polluting and inexhaustible. Nevertheless, the production system of this energy is nonlinear and it varies according to the luminous intensity and the temperature. Therefore, the operating point of the photovoltaic panel does not always coincide with the point of maximum power. This work proposes a mechanism that allows the research and the pursuit of the maximum power point based on a fuzzy control of photovoltaic system. To develop an algorithm to extract the maximum energy converted by the examined photovoltaics panels.


Artificial intelligence Fuzzy control MPPT Photovoltaics Energy storage Efficiency Photovoltaic energy 


  1. 1.
    Sedaghatizadeh, N., Arjomandi, M., Kelso, R., Cazzolato, B., Ghayes, M.H.: Modelling of wind turbine wake using large eddy simulation. Renew. Energy 115, 1166–1176 (2018)CrossRefGoogle Scholar
  2. 2.
    Akour, S.N., Al-Heymari, M., Ahmed, T., Ali Khalil, K.: Experimental and theoretical investigation of micro wind turbine for low wind speed regions. Renew. Energy 116, 215–223 (2018). part ACrossRefGoogle Scholar
  3. 3.
    Menezes, E.J.N., Araújo, A.M., da Silva, N.S.B.: A review on wind turbine control and its associated methods. J. Clean. Prod. 174, 945–953 (2018)Google Scholar
  4. 4.
    Tian, W., Ozbay, A., Hui, H.: An experimental investigation on the aeromechanics and wake interferences of wind turbines sited over complex terrain. J. Wind Eng. Ind. Aerodyn. 172, 379–394 (2018)CrossRefGoogle Scholar
  5. 5.
    Mellit, A., Kalogirou, S.A.: MPPT-based artificial intelligence techniques for photovoltaic systems and its implementation into field programmable gate array chips: review of current status and future perspectives. Energy 70, 1–21 (2014)CrossRefGoogle Scholar
  6. 6.
    Tahri, A., Oozeki, T., Draou, A.: Monitoring and evaluation of photovoltaic system. Energy Proc. 42, 456–464 (2013)CrossRefGoogle Scholar
  7. 7.
    Ahadi, A., Ghadimi, N., Mirabbasi, D.: Reliability assessment for components of large scale photovoltaic systems. J. Power Sources 264, 211–219 (2014)CrossRefGoogle Scholar
  8. 8.
    Bouabdallah, A., Olivier, J.C., Bourguet, S., Machmoum, M., Schaeffer, E.: Safe sizing methodology applied to a standalone photovoltaic system. Renew. Energy 80, 266–274 (2015)CrossRefGoogle Scholar
  9. 9.
    Geurts, C., Blackmore, P.: Wind loads on stand-off photovoltaic systems on pitched roofs. J. Wind Eng. Ind. Aerodyn. 123, 239–249 (2013). Part ACrossRefGoogle Scholar
  10. 10.
    Tsuanyo, D., Azoumah, Y., Aussel, D., Neveu, P.: Modeling and optimization of batteryless hybrid PV (photovoltaic)/diesel systems for off-grid applications. Energy 86, 152–163 (2015)CrossRefGoogle Scholar
  11. 11.
    Caselli, D., Ning, D.Z.: Monolithically-integrated laterally-arrayed multiple bandgap solar cells for spectrum-splitting photovoltaic systems. Prog. Quant. Electron. 39, 24–70 (2015)CrossRefGoogle Scholar
  12. 12.
    Karakaya, E., Hidalgo, A., Nuur, C.: Motivators for adoption of photovoltaic systems at grid parity: a case study from Southern Germany. Renew. Sustain. Energy Rev. 43, 1090–1098 (2015)CrossRefGoogle Scholar
  13. 13.
    Karakaya, E., Sriwannawit, P.: Barriers to the adoption of photovoltaic systems: the state of the art. Renew. Sustain. Energy Rev. 49, 60–66 (2015)CrossRefGoogle Scholar
  14. 14.
    Shariff, F., Rahim, N.A., Hew, W.P.: Zigbee-based data acquisition system for online monitoring of grid-connected photovoltaic system. Expert Syst. Appl. 42(3), 1730–1742 (2015)CrossRefGoogle Scholar
  15. 15.
    Baig, H., Sellami, N., Mallick, T.K.: Trapping light escaping from the edges of the optical element in a concentrating photovoltaic system. Energy Convers. Manag. 90, 238–246 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Ahmed Hafaifa
    • 1
    Email author
  • Kaid Imed
    • 1
  • Mouloud Guemana
    • 2
  • Abudura Salam
    • 2
  1. 1.Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and TechnologyUniversity of DjelfaDjelfaAlgeria
  2. 2.Faculty of Science and TechnologyUniversity of MédéaMedeaAlgeria

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