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Assessing one-minute diffuse fraction models based on worldwide climate features

Author

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  • Starke, Allan R.
  • Lemos, Leonardo F.L.
  • Barni, Cristian M.
  • Machado, Rubinei D.
  • Cardemil, José M.
  • Boland, John
  • Colle, Sergio

Abstract

Despite the variety of irradiance separation models available in the literature, there is not yet a model that performs equally well for every location worldwide. Nevertheless, separation models still represent an interesting approach when only global irradiance is measured. This work presents further developments of the recently proposed Boland-Ridley-Lauret minute model and proposes 1-min diffuse fraction models for each climate zone in the globe. To accomplish this, 1-min worldwide irradiance data from 51 the Baseline Surface Rresearch Network stations and one from Australian Bureau of Meteorology were used. The Köppen-Geiger classification was used to determine the climate zone of each station: both the simple climate classification (A, B, C, D, E) and the complete classification (Aw, Bsh, etc.). Furthermore, a robust nonlinear regression method was used to build the separation models without removing measurement outliers in advance. The climate-specific models proposed herein present better performance than other models from the literature, such as the BRL, Perez and Skartveit models (developed using hourly irradiance data) and the Engerer model (developed using minute data). Generally, the models proposed for climate zones in the complete Köppen classification presented better similitude with the measured data than the models for the simple classification, especially for stations within climate zones B and E.

Suggested Citation

  • Starke, Allan R. & Lemos, Leonardo F.L. & Barni, Cristian M. & Machado, Rubinei D. & Cardemil, José M. & Boland, John & Colle, Sergio, 2021. "Assessing one-minute diffuse fraction models based on worldwide climate features," Renewable Energy, Elsevier, vol. 177(C), pages 700-714.
  • Handle: RePEc:eee:renene:v:177:y:2021:i:c:p:700-714
    DOI: 10.1016/j.renene.2021.05.108
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    References listed on IDEAS

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    6. Ailton M. Tavares & Ricardo Conceição & Francisco M. Lopes & Hugo G. Silva, 2022. "Development of a Simple Methodology Using Meteorological Data to Evaluate Concentrating Solar Power Production Capacity," Energies, MDPI, vol. 15(20), pages 1-27, October.

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