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An improved maximum power point tracking method for photovoltaic systems

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  • Tafticht, T.
  • Agbossou, K.
  • Doumbia, M.L.
  • Chériti, A.

Abstract

In most of the maximum power point tracking (MPPT) methods described currently in the literature, the optimal operation point of the photovoltaic (PV) systems is estimated by linear approximations. However these approximations can lead to less than optimal operating conditions and hence reduce considerably the performances of the PV system. This paper proposes a new approach to determine the maximum power point (MPP) based on measurements of the open-circuit voltage of the PV modules, and a nonlinear expression for the optimal operating voltage is developed based on this open-circuit voltage. The approach is thus a combination of the nonlinear and perturbation and observation (P&O) methods. The experimental results show that the approach improves clearly the tracking efficiency of the maximum power available at the output of the PV modules. The new method reduces the oscillations around the MPP, and increases the average efficiency of the MPPT obtained. The new MPPT method will deliver more power to any generic load or energy storage media.

Suggested Citation

  • Tafticht, T. & Agbossou, K. & Doumbia, M.L. & Chériti, A., 2008. "An improved maximum power point tracking method for photovoltaic systems," Renewable Energy, Elsevier, vol. 33(7), pages 1508-1516.
    • Handle: RePEc:eee:renene:v:33:y:2008:i:7:p:1508-1516
    DOI: 10.1016/j.renene.2007.08.015
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    Citations

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    Cited by:

    1. Rajesh, R. & Mabel, M. Carolin, 2016. "Design and real time implementation of a novel rule compressed fuzzy logic method for the determination operating point in a photo voltaic system," Energy, Elsevier, vol. 116(P1), pages 140-153.
    2. Syafaruddin, & Karatepe, Engin & Hiyama, Takashi, 2009. "Polar coordinated fuzzy controller based real-time maximum-power point control of photovoltaic system," Renewable Energy, Elsevier, vol. 34(12), pages 2597-2606.
    3. Rita H. Almeida & Isaac B. Carrêlo & Eduardo Lorenzo & Luis Narvarte & José Fernández-Ramos & Francisco Martínez-Moreno & Luis M. Carrasco, 2018. "Development and Test of Solutions to Enlarge the Power of PV Irrigation and Application to a 140 kW PV-Diesel Representative Case," Energies, MDPI, vol. 11(12), pages 1-24, December.
    4. Abu Eldahab, Yasser E. & Saad, Naggar H. & Zekry, Abdalhalim, 2014. "Enhancing the maximum power point tracking techniques for photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 505-514.
    5. Joshi, Puneet & Arora, Sudha, 2017. "Maximum power point tracking methodologies for solar PV systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1154-1177.
    6. Datta, Manoj & Senjyu, Tomonobu & Yona, Atsushi & Funabashi, Toshihisa, 2011. "A fuzzy based method for leveling output power fluctuations of photovoltaic-diesel hybrid power system," Renewable Energy, Elsevier, vol. 36(6), pages 1693-1703.
    7. Bizon, N., 2010. "On tracking robustness in adaptive extremum seeking control of the fuel cell power plants," Applied Energy, Elsevier, vol. 87(10), pages 3115-3130, October.
    8. Nubia Ilia Ponce de León Puig & Leonardo Acho & José Rodellar, 2018. "Design and Experimental Implementation of a Hysteresis Algorithm to Optimize the Maximum Power Point Extracted from a Photovoltaic System," Energies, MDPI, vol. 11(7), pages 1-24, July.
    9. Kofinas, P. & Doltsinis, S. & Dounis, A.I. & Vouros, G.A., 2017. "A reinforcement learning approach for MPPT control method of photovoltaic sources," Renewable Energy, Elsevier, vol. 108(C), pages 461-473.
    10. Ahmed Ismail M. Ali & Zuhair Muhammed Alaas & Mahmoud A. Sayed & Abdulaziz Almalaq & Anouar Farah & Mohamed A. Mohamed, 2022. "An Efficient MPPT Technique-Based Single-Stage Incremental Conductance for Integrated PV Systems Considering Flyback Central-Type PV Inverter," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
    11. Belkaid, A. & Colak, I. & Isik, O., 2016. "Photovoltaic maximum power point tracking under fast varying of solar radiation," Applied Energy, Elsevier, vol. 179(C), pages 523-530.
    12. 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.
    13. Ahmad, Riaz & Murtaza, Ali F. & Sher, Hadeed Ahmed, 2019. "Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 82-102.
    14. Houssamo, Issam & Locment, Fabrice & Sechilariu, Manuela, 2010. "Maximum power tracking for photovoltaic power system: Development and experimental comparison of two algorithms," Renewable Energy, Elsevier, vol. 35(10), pages 2381-2387.
    15. Moacyr A. G. de Brito & Victor A. Prado & Edson A. Batista & Marcos G. Alves & Carlos A. Canesin, 2021. "Design Procedure to Convert a Maximum Power Point Tracking Algorithm into a Loop Control System," Energies, MDPI, vol. 14(15), pages 1-17, July.
    16. Abu Eldahab, Yasser E. & Saad, Naggar H. & Zekry, Abdalhalim, 2017. "Enhancing the tracking techniques for the global maximum power point under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1173-1183.
    17. Rajesh, R. & Carolin Mabel, M., 2015. "A comprehensive review of photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 231-248.
    18. Li, Shuhui & Haskew, Timothy A. & Li, Dawen & Hu, Fei, 2011. "Integrating photovoltaic and power converter characteristics for energy extraction study of solar PV systems," Renewable Energy, Elsevier, vol. 36(12), pages 3238-3245.

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