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Simplified model to correct thermopile pyranometer solar radiation measurements for photovoltaic module yield estimation

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  • Lillo-Bravo, I.
  • Larrañeta, M.
  • Núñez-Ortega, E.
  • González-Galván, R.

Abstract

This article presents and evaluates the performance of a simplified model to generate 10-min global horizontal synthetic solar radiation data that would correspond to the measurements of a calibrated photovoltaic monocrystalline cell. The model, which only requires global horizontal solar radiation data measured with a thermopile pyranometer as input, is based on the characterization of the relation between the data measured with a thermopile pyranometer and a calibrated cell as a function of the sky condition and the solar elevation. We have used an extensive solar radiation database for the location of Seville (Spain) for the training of the model that has been tested in Seville and Lancaster (USA), showing satisfactory results and suggesting a global applicability with no local adaptation or calibration requirement.

Suggested Citation

  • Lillo-Bravo, I. & Larrañeta, M. & Núñez-Ortega, E. & González-Galván, R., 2020. "Simplified model to correct thermopile pyranometer solar radiation measurements for photovoltaic module yield estimation," Renewable Energy, Elsevier, vol. 146(C), pages 1486-1497.
    • Handle: RePEc:eee:renene:v:146:y:2020:i:c:p:1486-1497
    DOI: 10.1016/j.renene.2019.07.070
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    References listed on IDEAS

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    1. Lou, Siwei & Li, Danny.H.W. & Chen, Wenqiang, 2019. "Identifying overcast, partly cloudy and clear skies by illuminance fluctuations," Renewable Energy, Elsevier, vol. 138(C), pages 198-211.
    2. Polo, J. & Fernandez-Neira, W.G. & Alonso-García, M.C., 2017. "On the use of reference modules as irradiance sensor for monitoring and modelling rooftop PV systems," Renewable Energy, Elsevier, vol. 106(C), pages 186-191.
    3. Fakra, A.H. & Boyer, H. & Miranville, F. & Bigot, D., 2011. "A simple evaluation of global and diffuse luminous efficacy for all sky conditions in tropical and humid climate," Renewable Energy, Elsevier, vol. 36(1), pages 298-306.
    4. Larrañeta, M. & Reno, M.J. & Lillo-Bravo, I. & Silva-Pérez, M.A., 2017. "Identifying periods of clear sky direct normal irradiance," Renewable Energy, Elsevier, vol. 113(C), pages 756-763.
    5. Alonso-Abella, M. & Chenlo, F. & Nofuentes, G. & Torres-Ramírez, M., 2014. "Analysis of spectral effects on the energy yield of different PV (photovoltaic) technologies: The case of four specific sites," Energy, Elsevier, vol. 67(C), pages 435-443.
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