IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v108y2017icp569-580.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148117301635
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2017.02.077?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Boland, John & Huang, Jing & Ridley, Barbara, 2013. "Decomposing global solar radiation into its direct and diffuse components," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 749-756.
    2. Kocifaj, Miroslav & Kómar, Ladislav, 2016. "Modeling diffuse irradiance under arbitrary and homogeneous skies: Comparison and validation," Applied Energy, Elsevier, vol. 166(C), pages 117-127.
    3. Martins, F.R. & Pereira, E.B. & Silva, S.A.B. & Abreu, S.L. & Colle, Sergio, 2008. "Solar energy scenarios in Brazil, Part one: Resource assessment," Energy Policy, Elsevier, vol. 36(8), pages 2843-2854, August.
    4. Martins, F.R. & Rüther, R. & Pereira, E.B. & Abreu, S.L., 2008. "Solar energy scenarios in Brazil. Part two: Photovoltaics applications," Energy Policy, Elsevier, vol. 36(8), pages 2855-2867, August.
    5. Younes, S. & Claywell, R. & Muneer, T., 2005. "Quality control of solar radiation data: Present status and proposed new approaches," Energy, Elsevier, vol. 30(9), pages 1533-1549.
    6. Ridley, Barbara & Boland, John & Lauret, Philippe, 2010. "Modelling of diffuse solar fraction with multiple predictors," Renewable Energy, Elsevier, vol. 35(2), pages 478-483.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marques Filho, Edson P. & Oliveira, Amauri P. & Vita, Willian A. & Mesquita, Francisco L.L. & Codato, Georgia & Escobedo, João F. & Cassol, Mariana & França, José Ricardo A., 2016. "Global, diffuse and direct solar radiation at the surface in the city of Rio de Janeiro: Observational characterization and empirical modeling," Renewable Energy, Elsevier, vol. 91(C), pages 64-74.
    2. 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.
    3. Liu, Peirong & Tong, Xiaojuan & Zhang, Jinsong & Meng, Ping & Li, Jun & Zhang, Jingru, 2020. "Estimation of half-hourly diffuse solar radiation over a mixed plantation in north China," Renewable Energy, Elsevier, vol. 149(C), pages 1360-1369.
    4. 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.
    5. Lou, Siwei & Li, Danny H.W. & Lam, Joseph C. & Chan, Wilco W.H., 2016. "Prediction of diffuse solar irradiance using machine learning and multivariable regression," Applied Energy, Elsevier, vol. 181(C), pages 367-374.
    6. 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.
    7. Portolan dos Santos, Ísis & Rüther, Ricardo, 2014. "Limitations in solar module azimuth and tilt angles in building integrated photovoltaics at low latitude tropical sites in Brazil," Renewable Energy, Elsevier, vol. 63(C), pages 116-124.
    8. Martins, F.R. & Abreu, S.L. & Pereira, E.B., 2012. "Scenarios for solar thermal energy applications in Brazil," Energy Policy, Elsevier, vol. 48(C), pages 640-649.
    9. Malagueta, Diego & Szklo, Alexandre & Borba, Bruno Soares Moreira Cesar & Soria, Rafael & Aragão, Raymundo & Schaeffer, Roberto & Dutra, Ricardo, 2013. "Assessing incentive policies for integrating centralized solar power generation in the Brazilian electric power system," Energy Policy, Elsevier, vol. 59(C), pages 198-212.
    10. Silva, S.B. & Severino, M.M. & de Oliveira, M.A.G., 2013. "A stand-alone hybrid photovoltaic, fuel cell and battery system: A case study of Tocantins, Brazil," Renewable Energy, Elsevier, vol. 57(C), pages 384-389.
    11. Chen, Hsing Hung & Kang, He-Yau & Lee, Amy H.I., 2010. "Strategic selection of suitable projects for hybrid solar-wind power generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 413-421, January.
    12. Jean Carlos da Silva Galdino & Marcos Aurélio Vasconcelos Freitas & Neilton Fidelis da Silva & Marcio Giannini Pereira & João Marcelo Dias Ferreira, 2020. "Creating the Path for Sustainability: Inserting Solar PV in São Francisco Transposition Project," Sustainability, MDPI, vol. 12(21), pages 1-27, October.
    13. Wang, Bingqing & Li, Yongping & Huang, Guohe & Gao, Pangpang & Liu, Jing & Wen, Yizhuo, 2023. "Development of an integrated BLSVM-MFA method for analyzing renewable power-generation potential under climate change: A case study of Xiamen," Applied Energy, Elsevier, vol. 337(C).
    14. Marcus Vinícius Coelho Vieira da Costa & Osmar Luiz Ferreira de Carvalho & Alex Gois Orlandi & Issao Hirata & Anesmar Olino de Albuquerque & Felipe Vilarinho e Silva & Renato Fontes Guimarães & Robert, 2021. "Remote Sensing for Monitoring Photovoltaic Solar Plants in Brazil Using Deep Semantic Segmentation," Energies, MDPI, vol. 14(10), pages 1-15, May.
    15. Naspolini, Helena F. & Rüther, Ricardo, 2012. "Assessing the technical and economic viability of low-cost domestic solar hot water systems (DSHWS) in low-income residential dwellings in Brazil," Renewable Energy, Elsevier, vol. 48(C), pages 92-99.
    16. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2015. "Assessment of direct normal irradiance and cloud connections using satellite data over Australia," Applied Energy, Elsevier, vol. 143(C), pages 301-311.
    17. Garlet, Taís Bisognin & Ribeiro, José Luis Duarte & de Souza Savian, Fernando & Mairesse Siluk, Julio Cezar, 2019. "Paths and barriers to the diffusion of distributed generation of photovoltaic energy in southern Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 157-169.
    18. Andrade Furtado, Gilton Carlos de & Amarante Mesquita, André Luiz & Morabito, Alessandro & Hendrick, Patrick & Hunt, Julian D., 2020. "Using hydropower waterway locks for energy storage and renewable energies integration," Applied Energy, Elsevier, vol. 275(C).
    19. 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.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:108:y:2017:i:c:p:569-580. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.