International Journal of
Physical Sciences

  • Abbreviation: Int. J. Phys. Sci.
  • Language: English
  • ISSN: 1992-1950
  • DOI: 10.5897/IJPS
  • Start Year: 2006
  • Published Articles: 2529

Full Length Research Paper

A comparative study of maximum power point tracker approaches based on artificial neural network and fuzzy controllers

Moustapha Sene
  • Moustapha Sene
  • Electronics IT Telecommunications and Renewable Energy Laboratory (LEITER), Gaston Berger University, Route de Ngallele, P. O. Box 234 Saint-Louis, West Africa, Senegal.
  • Google Scholar
Fatou Ndiaye
  • Fatou Ndiaye
  • Electronics IT Telecommunications and Renewable Energy Laboratory (LEITER), Gaston Berger University, Route de Ngallele, P. O. Box 234 Saint-Louis, West Africa, Senegal.
  • Google Scholar
Marie E. Faye
  • Marie E. Faye
  • Electronics IT Telecommunications and Renewable Energy Laboratory (LEITER), Gaston Berger University, Route de Ngallele, P. O. Box 234 Saint-Louis, West Africa, Senegal.
  • Google Scholar
Saliou Diouf
  • Saliou Diouf
  • Information Processing Laboratory (LTI), Higth Polytechnic School, Cheikh Anta Diop University, P. O. Box 5085 Dakar–Fann, West Africa, Senegal.
  • Google Scholar
Amadou S. Maiga
  • Amadou S. Maiga
  • Electronics IT Telecommunications and Renewable Energy Laboratory (LEITER), Gaston Berger University, Route de Ngallele, P. O. Box 234 Saint-Louis, West Africa, Senegal.
  • Google Scholar


  •  Received: 12 November 2017
  •  Accepted: 20 December 2017
  •  Published: 16 January 2018

References

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Elgendy MA, Zahawi B, Atkinson DJ (2012). Assessment of Perturb and Observe MPPT Algorithm Implementation Techniques for PV Pumping Applications. IEEE Trans. Sustain. Energy 3(1):21-34.
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Elgharbi A, Mezghani D, Mami A (2012). A Maximum power point tracking method based on artificial neural network for a PV system. Int. J. Adv. Eng. Technol. IJAET.

 
 

Enany MA (2017). Cuckoo search–based maximum power point tracking controller for PV water pumping system. ‎J. Renew. Sustain. Energy 9:063501.
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Haskin S (2005). Neural networks: A comprehensive foundation. San Francisco Pearson Education.

 
 

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Jang JS, Anfis R (1995). Neuro-Fuzzy Modeling and Control. Proc. IEEE 83(3):378-406.
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Mastromauro RA, Liserre M, Dell'Aquila A (2012). Control Issues in Single Stage Photovoltaic Systems: MPPT, Current and Voltage Control. IEEE Trans. Ind. Inf. 8(2):241-254.
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Ndiaye F, Sène M, Beye M, Seidou Maiga A (2015). Effects of climatic conditions on a polycrystalline photovoltaic module in Niger. Int. Lett. Chem. Phys. Astron. 55:60-66.
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Reisi AR, Moradi MH, Jamasb S (2013). Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review. J. Renew. Sust. Energy Rev. 19:433-443.
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Saloux E, Teyessdou A, Sorin M (2011). Explicit model of photovoltaic panel to determine voltages and current at the maximum power point. Solar energy 85:713-722.
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Vafaei S, Rezvani A, Gandomkar M, Izadbakhsh M (2015). Enhancement of grid-connected photovoltaic system using ANFIS-GA under different circumstances. Front. Energy 9(3):322-334.
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Zou Y, Yu Y, Zhang Y, Luc J (2012). MPPT Control for PV Generation System Based on an Improved Inccond Algorithm. Elsevier, Int. Workshop Info. Electron. Eng. 105-109.
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