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Assessment of solar radiation components in Brazil using the BRL model

Author

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

Abstract

Quality data regarding direct and diffuse solar irradiation is crucial for the proper design and simulation of solar systems. This information, however, is not available for the entire Brazilian territory. However, hourly measurements of global irradiation for more than seven hundred stations over the territory are available. Several mathematical models have been developed over the past few decades aiming to deliver estimations of solar irradiation components when only measurement of global irradiation is available. In order to provide reliable estimates of diffuse and direct radiation in Brazil, the recently presented Boland–Ridley–Laurent (BRL) model is adjusted to the particular features of Brazilian climate data, developing adjusted BRL models on minute and hourly bases. The model is adjusted using global, diffuse and direct solar irradiation measurements at nine stations, which are maintained by INPE in the frame of the SONDA project. The methodology for processing and analyzing the quality of the data-sets and the procedures to build the adjusted BRL model is thoroughly described. The error indicators show that the adjusted BRL model performs better or similarly to the original one, for both diffuse and DNI estimates calculated for each analyzed Brazilian station. For instance, the original BRL model diffuse fraction estimates have MeAPE errors ranging from 16% to 51%, while the adjusted BRL model gives errors from 9% to 26%. Regarding the comparison between the minute and hourly adjusted models, it can be concluded that both performed similarly, indicating that the logistic behavior of the original BRL model is well suited to make estimates in sub-hourly data sets. Based on the results, the proposed adjusted model can be used to provide reliable estimates of the distribution of direct and diffuse irradiation, and therefore, can help to properly design and reduce the risks associated to solar energy systems.

Suggested Citation

  • Lemos, Leonardo F.L. & Starke, Allan R. & Boland, John & Cardemil, José M. & Machado, Rubinei D. & Colle, Sergio, 2017. "Assessment of solar radiation components in Brazil using the BRL model," Renewable Energy, Elsevier, vol. 108(C), pages 569-580.
    • Handle: RePEc:eee:renene:v:108:y:2017:i:c:p:569-580
    DOI: 10.1016/j.renene.2017.02.077
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    References listed on IDEAS

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    1. Every, Jeremy P. & Li, Li & Dorrell, David G., 2020. "Köppen-Geiger climate classification adjustment of the BRL diffuse irradiation model for Australian locations," Renewable Energy, Elsevier, vol. 147(P1), pages 2453-2469.
    2. Nollas, Fernando M. & Salazar, German A. & Gueymard, Christian A., 2023. "Quality control procedure for 1-minute pyranometric measurements of global and shadowband-based diffuse solar irradiance," Renewable Energy, Elsevier, vol. 202(C), pages 40-55.
    3. Wang, Hong & Sun, Fubao & Wang, Tingting & Liu, Wenbin, 2018. "Estimation of daily and monthly diffuse radiation from measurements of global solar radiation a case study across China," Renewable Energy, Elsevier, vol. 126(C), pages 226-241.
    4. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparative analysis of diffuse solar radiation models based on sky-clearness index and sunshine period for humid-subtropical climatic region of India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 329-355.
    5. Rojas, Redlich García & Alvarado, Natalia & Boland, John & Escobar, Rodrigo & Castillejo-Cuberos, Armando, 2019. "Diffuse fraction estimation using the BRL model and relationship of predictors under Chilean, Costa Rican and Australian climatic conditions," Renewable Energy, Elsevier, vol. 136(C), pages 1091-1106.
    6. Moretón, R. & Lorenzo, E. & Pinto, A. & Muñoz, J. & Narvarte, L., 2017. "From broadband horizontal to effective in-plane irradiation: A review of modelling and derived uncertainty for PV yield prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 886-903.
    7. Starke, Allan R. & Lemos, Leonardo F.L. & Boland, John & Cardemil, José M. & Colle, Sergio, 2018. "Resolution of the cloud enhancement problem for one-minute diffuse radiation prediction," Renewable Energy, Elsevier, vol. 125(C), pages 472-484.
    8. Chen, Ji-Long & He, Lei & Chen, Qiao & Lv, Ming-Quan & Zhu, Hong-Lin & Wen, Zhao-Fei & Wu, Sheng-Jun, 2019. "Study of monthly mean daily diffuse and direct beam radiation estimation with MODIS atmospheric product," Renewable Energy, Elsevier, vol. 132(C), pages 221-232.
    9. 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.

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