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FPGA based new MPPT (maximum power point tracking) method for PV (photovoltaic) array system operating partially shaded conditions

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  • Parlak, Koray Sener

Abstract

In PV (photovoltaic) systems, MPPT (maximum power point tracking) methods play highly crucial role for its own research domain. Researchers can get effective results using traditional MPPT methods which work well under uniform irradiance conditions. On the other hand mentioned methods cannot always run successfully since there is more than one local maxima in PV characteristics under partial shading conditions. Under partial shading conditions, one can meet to various approaches in the literature working accurately they can, however, reveal complex calculations or requires some of extra parameters such as datasheet values, system configuration data. Here, we propose a novel MPPT method providing GMPP (global maximum power point) for PV arrays under any environmental conditions. This method is based on sensing the current and voltage values of a capacitor connected to the output of the PV array during the charging time. Then it compares instantaneous power values to maximum power, and estimates maximum power value and corresponding voltage value. Matlab-Simulink and FPGA based test system have been utilized for verification stage of the proposed MPPT method under uniform and partially shaded conditions, and we got promising results.

Suggested Citation

  • Parlak, Koray Sener, 2014. "FPGA based new MPPT (maximum power point tracking) method for PV (photovoltaic) array system operating partially shaded conditions," Energy, Elsevier, vol. 68(C), pages 399-410.
  • Handle: RePEc:eee:energy:v:68:y:2014:i:c:p:399-410
    DOI: 10.1016/j.energy.2014.02.027
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    Cited by:

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    4. Ahmad, R. & Murtaza, Ali F. & Ahmed Sher, Hadeed & Tabrez Shami, Umar & Olalekan, Saheed, 2017. "An analytical approach to study partial shading effects on PV array supported by literature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 721-732.
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    7. Ramli, Makbul A.M. & Twaha, Ssennoga & Ishaque, Kashif & Al-Turki, Yusuf A., 2017. "A review on maximum power point tracking for photovoltaic systems with and without shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 144-159.
    8. Linares-Flores, J. & Guerrero-Castellanos, J.F. & Lescas-Hernández, R. & Hernández-Méndez, A. & Vázquez-Perales, R., 2019. "Angular speed control of an induction motor via a solar powered boost converter-voltage source inverter combination," Energy, Elsevier, vol. 166(C), pages 326-334.
    9. Dileep, G. & Singh, S.N., 2015. "Maximum power point tracking of solar photovoltaic system using modified perturbation and observation method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 109-129.
    10. Fathabadi, Hassan, 2016. "Novel highly accurate universal maximum power point tracker for maximum power extraction from hybrid fuel cell/photovoltaic/wind power generation systems," Energy, Elsevier, vol. 116(P1), pages 402-416.
    11. Fathabadi, Hassan, 2017. "Novel fast and high accuracy maximum power point tracking method for hybrid photovoltaic/fuel cell energy conversion systems," Renewable Energy, Elsevier, vol. 106(C), pages 232-242.
    12. Belhachat, Faiza & Larbes, Cherif, 2017. "Global maximum power point tracking based on ANFIS approach for PV array configurations under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 875-889.
    13. Daraban, Stefan & Petreus, Dorin & Morel, Cristina, 2014. "A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading," Energy, Elsevier, vol. 74(C), pages 374-388.
    14. Rajesh, R. & Carolin Mabel, M., 2015. "A comprehensive review of photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 231-248.

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