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Real time estimation of photovoltaic modules characteristics and its application to maximum power point operation

Author

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  • Garrigós, Ausias
  • Blanes, José M.
  • Carrasco, José A.
  • Ejea, Juan B.

Abstract

In this paper, an approximate curve fitting method for photovoltaic modules is presented. The operation is based on solving a simple solar cell electrical model by a microcontroller in real time. Only four voltage and current coordinates are needed to obtain the solar module parameters and set its operation at maximum power in any conditions of illumination and temperature. Despite its simplicity, this method is suitable for low cost real time applications, as control loop reference generator in photovoltaic maximum power point circuits. The theory that supports the estimator together with simulations and experimental results are presented.

Suggested Citation

  • Garrigós, Ausias & Blanes, José M. & Carrasco, José A. & Ejea, Juan B., 2007. "Real time estimation of photovoltaic modules characteristics and its application to maximum power point operation," Renewable Energy, Elsevier, vol. 32(6), pages 1059-1076.
    • Handle: RePEc:eee:renene:v:32:y:2007:i:6:p:1059-1076
    DOI: 10.1016/j.renene.2006.08.004
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    Citations

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    Cited by:

    1. Heidi Kalliojärvi & Kari Lappalainen & Seppo Valkealahti, 2022. "Feasibility of Photovoltaic Module Single-Diode Model Fitting to the Current–Voltage Curves Measured in the Vicinity of the Maximum Power Point for Online Condition Monitoring Purposes," Energies, MDPI, vol. 15(23), pages 1-21, November.
    2. Danandeh, M.A. & Mousavi G., S.M., 2018. "Comparative and comprehensive review of maximum power point tracking methods for PV cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2743-2767.
    3. Toledo, F.J. & Blanes, José M., 2016. "Analytical and quasi-explicit four arbitrary point method for extraction of solar cell single-diode model parameters," Renewable Energy, Elsevier, vol. 92(C), pages 346-356.
    4. Toledo, F.J. & Blanes, José M. & Garrigós, Ausiàs & Martínez, José A., 2012. "Analytical resolution of the electrical four-parameters model of a photovoltaic module using small perturbation around the operating point," Renewable Energy, Elsevier, vol. 43(C), pages 83-89.
    5. 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.
    6. Chen, Cheng-Chuan & Chang, Hong-Chan & Kuo, Cheng-Chien & Lin, Chien-Chin, 2013. "Programmable energy source emulator for photovoltaic panels considering partial shadow effect," Energy, Elsevier, vol. 54(C), pages 174-183.
    7. Toledo, F.J. & Blanes, Jose M., 2014. "Geometric properties of the single-diode photovoltaic model and a new very simple method for parameters extraction," Renewable Energy, Elsevier, vol. 72(C), pages 125-133.
    8. 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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