IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v190y2020ics0360544219320365.html
   My bibliography  Save this article

WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil

Author

Listed:
  • Tuchtenhagen, Patrícia
  • Carvalho, Gilvani Gomes de
  • Martins, Guilherme
  • Silva, Pollyanne Evangelista da
  • Oliveira, Cristiano Prestrelo de
  • de Melo Barbosa Andrade, Lara
  • Araújo, João Medeiros de
  • Mutti, Pedro Rodrigues
  • Lucio, Paulo Sérgio
  • Silva, Cláudio Moisés Santos e

Abstract

Offshore wind power generation is expanding in several regions of the globe but in Brazil, particularly in its southern portion, prospection studies are still scarce. Thus, the present study aims to assess wind variability and power density (PD) simulated by the Weather Research and Forecasting Model (WRF) in the Southern Brazil, focusing on the offshore region. We compared the results of the simulations with data from the Blended Sea Winds (BSW) product, who quantify wind velocity over oceans. The numerical experiment was carried out during a 5-year period, between 00UTC of January 01, 2006 until 00UTC of December 31, 2010. The domain has a total of 340 grid points in the zonal direction, 180 points in the meridional direction and 35 vertical layers with the top set at 50 hPa. We concluded that the WRF model can be used as a tool to evaluate the potential for wind power generation in the Southern Brazil region. On the other hand, the model did not perform well in simulating wind in the regions near the Brazil and Falklands Currents. This shortcoming may be corrected by coupling the WRF with an oceanic model and using parameterizations which more adequately represent turbulence in the planetary boundary layer.

Suggested Citation

  • Tuchtenhagen, Patrícia & Carvalho, Gilvani Gomes de & Martins, Guilherme & Silva, Pollyanne Evangelista da & Oliveira, Cristiano Prestrelo de & de Melo Barbosa Andrade, Lara & Araújo, João Medeiros de, 2020. "WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil," Energy, Elsevier, vol. 190(C).
    • Handle: RePEc:eee:energy:v:190:y:2020:i:c:s0360544219320365
    DOI: 10.1016/j.energy.2019.116341
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219320365
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.116341?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. Robert Vautard & Françoise Thais & Isabelle Tobin & François-Marie Bréon & Jean-Guy Devezeaux de Lavergne & Augustin Colette & Pascal Yiou & Paolo Michele Ruti, 2014. "Regional climate model simulations indicate limited climatic impacts by operational and planned European wind farms," Nature Communications, Nature, vol. 5(1), pages 1-9, May.
    2. Olaofe, Zaccheus O., 2016. "A surface-layer wind speed correction: A case-study of Darling station," Renewable Energy, Elsevier, vol. 93(C), pages 228-244.
    3. Pimenta, Felipe & Kempton, Willett & Garvine, Richard, 2008. "Combining meteorological stations and satellite data to evaluate the offshore wind power resource of Southeastern Brazil," Renewable Energy, Elsevier, vol. 33(11), pages 2375-2387.
    4. Liu, Yichao & Chen, Daoyi & Li, Sunwei & Chan, P.W., 2018. "Discerning the spatial variations in offshore wind resources along the coast of China via dynamic downscaling," Energy, Elsevier, vol. 160(C), pages 582-596.
    5. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2017. "Offshore winds and wind energy production estimates derived from ASCAT, OSCAT, numerical weather prediction models and buoys – A comparative study for the Iberian Peninsula Atlantic coast," Renewable Energy, Elsevier, vol. 102(PB), pages 433-444.
    6. Nagababu, Garlapati & Kachhwaha, Surendra Singh & Savsani, Vimal, 2017. "Estimation of technical and economic potential of offshore wind along the coast of India," Energy, Elsevier, vol. 138(C), pages 79-91.
    7. Salvação, N. & Guedes Soares, C., 2018. "Wind resource assessment offshore the Atlantic Iberian coast with the WRF model," Energy, Elsevier, vol. 145(C), pages 276-287.
    8. Pereira, Enio B. & Martins, Fernando R. & Pes, Marcelo P. & da Cruz Segundo, Eliude I. & Lyra, André de A., 2013. "The impacts of global climate changes on the wind power density in Brazil," Renewable Energy, Elsevier, vol. 49(C), pages 107-110.
    9. Mattar, Cristian & Borvarán, Dager, 2016. "Offshore wind power simulation by using WRF in the central coast of Chile," Renewable Energy, Elsevier, vol. 94(C), pages 22-31.
    10. Shoshiro Minobe & Akira Kuwano-Yoshida & Nobumasa Komori & Shang-Ping Xie & Richard Justin Small, 2008. "Influence of the Gulf Stream on the troposphere," Nature, Nature, vol. 452(7184), pages 206-209, March.
    11. Chancham, Chana & Waewsak, Jompob & Gagnon, Yves, 2017. "Offshore wind resource assessment and wind power plant optimization in the Gulf of Thailand," Energy, Elsevier, vol. 139(C), pages 706-731.
    12. Pes, Marcelo P. & Pereira, Enio B. & Marengo, Jose A. & Martins, Fernando R. & Heinemann, Detlev & Schmidt, Michael, 2017. "Climate trends on the extreme winds in Brazil," Renewable Energy, Elsevier, vol. 109(C), pages 110-120.
    13. Silva, Allan Rodrigues & Pimenta, Felipe Mendonça & Assireu, Arcilan Trevenzoli & Spyrides, Maria Helena Constantino, 2016. "Complementarity of Brazil׳s hydro and offshore wind power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 413-427.
    14. de Vries, Bert J.M. & van Vuuren, Detlef P. & Hoogwijk, Monique M., 2007. "Renewable energy sources: Their global potential for the first-half of the 21st century at a global level: An integrated approach," Energy Policy, Elsevier, vol. 35(4), pages 2590-2610, April.
    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. de Assis Tavares, Luiz Filipe & Shadman, Milad & Assad, Luiz Paulo de Freitas & Estefen, Segen F., 2022. "Influence of the WRF model and atmospheric reanalysis on the offshore wind resource potential and cost estimation: A case study for Rio de Janeiro State," Energy, Elsevier, vol. 240(C).
    2. Perini de Souza, Noele Bissoli & Sperandio Nascimento, Erick Giovani & Bandeira Santos, Alex Alisson & Moreira, Davidson Martins, 2022. "Wind mapping using the mesoscale WRF model in a tropical region of Brazil," Energy, Elsevier, vol. 240(C).
    3. Tuy, Soklin & Lee, Han Soo & Chreng, Karodine, 2022. "Integrated assessment of offshore wind power potential using Weather Research and Forecast (WRF) downscaling with Sentinel-1 satellite imagery, optimal sites, annual energy production and equivalent C," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).

    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. Tuy, Soklin & Lee, Han Soo & Chreng, Karodine, 2022. "Integrated assessment of offshore wind power potential using Weather Research and Forecast (WRF) downscaling with Sentinel-1 satellite imagery, optimal sites, annual energy production and equivalent C," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    2. de Assis Tavares, Luiz Filipe & Shadman, Milad & de Freitas Assad, Luiz Paulo & Silva, Corbiniano & Landau, Luiz & Estefen, Segen F., 2020. "Assessment of the offshore wind technical potential for the Brazilian Southeast and South regions," Energy, Elsevier, vol. 196(C).
    3. Chen, Xinping & Foley, Aoife & Zhang, Zenghai & Wang, Kaimin & O'Driscoll, Kieran, 2020. "An assessment of wind energy potential in the Beibu Gulf considering the energy demands of the Beibu Gulf Economic Rim," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    4. de Assis Tavares, Luiz Filipe & Shadman, Milad & Assad, Luiz Paulo de Freitas & Estefen, Segen F., 2022. "Influence of the WRF model and atmospheric reanalysis on the offshore wind resource potential and cost estimation: A case study for Rio de Janeiro State," Energy, Elsevier, vol. 240(C).
    5. Sward, J.A. & Ault, T.R. & Zhang, K.M., 2023. "Spatial biases revealed by LiDAR in a multiphysics WRF ensemble designed for offshore wind," Energy, Elsevier, vol. 262(PA).
    6. Rusu, Eugen & Onea, Florin, 2019. "A parallel evaluation of the wind and wave energy resources along the Latin American and European coastal environments," Renewable Energy, Elsevier, vol. 143(C), pages 1594-1607.
    7. González-Alonso de Linaje, N. & Mattar, C. & Borvarán, D., 2019. "Quantifying the wind energy potential differences using different WRF initial conditions on Mediterranean coast of Chile," Energy, Elsevier, vol. 188(C).
    8. Dong, Cong & Huang, Guohe (Gordon) & Cheng, Guanhui, 2021. "Offshore wind can power Canada," Energy, Elsevier, vol. 236(C).
    9. Salvação, N. & Guedes Soares, C., 2018. "Wind resource assessment offshore the Atlantic Iberian coast with the WRF model," Energy, Elsevier, vol. 145(C), pages 276-287.
    10. Arun Kumar, Surisetty V.V. & Nagababu, Garlapati & Kumar, Raj, 2019. "Comparative study of offshore winds and wind energy production derived from multiple scatterometers and met buoys," Energy, Elsevier, vol. 185(C), pages 599-611.
    11. Jared A. Lee & Paula Doubrawa & Lulin Xue & Andrew J. Newman & Caroline Draxl & George Scott, 2019. "Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set," Energies, MDPI, vol. 12(14), pages 1-22, July.
    12. Wang, Jianzhou & Huang, Xiaojia & Li, Qiwei & Ma, Xuejiao, 2018. "Comparison of seven methods for determining the optimal statistical distribution parameters: A case study of wind energy assessment in the large-scale wind farms of China," Energy, Elsevier, vol. 164(C), pages 432-448.
    13. Dhunny, A.Z. & Timmons, D.S. & Allam, Z. & Lollchund, M.R. & Cunden, T.S.M., 2020. "An economic assessment of near-shore wind farm development using a weather research forecast-based genetic algorithm model," Energy, Elsevier, vol. 201(C).
    14. Cheng-Dar Yue & Che-Chih Liu & Chien-Cheng Tu & Ta-Hui Lin, 2019. "Prediction of Power Generation by Offshore Wind Farms Using Multiple Data Sources," Energies, MDPI, vol. 12(4), pages 1-24, February.
    15. Herrera, Milton M. & Dyner, Isaac & Cosenz, Federico, 2019. "Assessing the effect of transmission constraints on wind power expansion in northeast Brazil," Utilities Policy, Elsevier, vol. 59(C), pages 1-1.
    16. de Jong, Pieter & Barreto, Tarssio B. & Tanajura, Clemente A.S. & Kouloukoui, Daniel & Oliveira-Esquerre, Karla P. & Kiperstok, Asher & Torres, Ednildo Andrade, 2019. "Estimating the impact of climate change on wind and solar energy in Brazil using a South American regional climate model," Renewable Energy, Elsevier, vol. 141(C), pages 390-401.
    17. Salvação, Nadia & Bentamy, Abderrahim & Guedes Soares, C., 2022. "Developing a new wind dataset by blending satellite data and WRF model wind predictions," Renewable Energy, Elsevier, vol. 198(C), pages 283-295.
    18. Erika Carvalho Nogueira & Rafael Cancella Morais & Amaro Olimpio Pereira, 2023. "Offshore Wind Power Potential in Brazil: Complementarity and Synergies," Energies, MDPI, vol. 16(16), pages 1-18, August.
    19. Cristian Mattar & Felipe Cabello-Españon & Nicolas G. Alonso-de-Linaje, 2021. "Towards a Future Scenario for Offshore Wind Energy in Chile: Breaking the Paradigm," Sustainability, MDPI, vol. 13(13), pages 1-16, June.
    20. He, J.Y. & Chan, P.W. & Li, Q.S. & Lee, C.W., 2022. "Characterizing coastal wind energy resources based on sodar and microwave radiometer observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).

    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:energy:v:190:y:2020:i:c:s0360544219320365. 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/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.