IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v94y2016icp22-31.html
   My bibliography  Save this article

Offshore wind power simulation by using WRF in the central coast of Chile

Author

Listed:
  • Mattar, Cristian
  • Borvarán, Dager

Abstract

This paper presents the first estimate of offshore wind power potential for the central coast of Chile. For this purpose, wind speed data from in-situ stations and ERA-Interim reanalysis were used to simulate wind fields at regional level by means of the Weather Research and Forecasting (WRF) model. Wind field simulations were performed at different heights (20, 30, 40 and 140 m.a.s.l.) and a spatial resolution of 3 × 3 km for the period from February 1, 2006 to January 31, 2007, which comprised the entire series of in-situ data available. The results show an RMSE and r2 of 2.2 m s−1 and 0.55 respectively for the three heights simulated as compared to in-situ data. Based on the simulated wind data, the wind power for the study area was estimated at ∼1000 W m−2 at a height of 140 m.a.s.l. For a typical wind turbine of 8 MW generator, the estimated capacity factor exceeds 40%, with an average annual generation of ∼30 GWh. Offshore wind power in Chile is an emerging renewable energy source that is as yet still under-developed, these estimates help to fill in some of the gaps in our knowledge about Chile's true renewable energy potential.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:94:y:2016:i:c:p:22-31
    DOI: 10.1016/j.renene.2016.03.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148116301896
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2016.03.005?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. Nawri, Nikolai & Petersen, Guðrún Nína & Bjornsson, Halldór & Hahmann, Andrea N. & Jónasson, Kristján & Hasager, Charlotte Bay & Clausen, Niels-Erik, 2014. "The wind energy potential of Iceland," Renewable Energy, Elsevier, vol. 69(C), pages 290-299.
    2. Rui Chang & Rong Zhu & Merete Badger & Charlotte Bay Hasager & Rongwei Zhou & Dong Ye & Xiaowei Zhang, 2014. "Applicability of Synthetic Aperture Radar Wind Retrievals on Offshore Wind Resources Assessment in Hangzhou Bay, China," Energies, MDPI, vol. 7(5), pages 1-16, May.
    3. Rodrigues, S. & Restrepo, C. & Kontos, E. & Teixeira Pinto, R. & Bauer, P., 2015. "Trends of offshore wind projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1114-1135.
    4. Sharp, Ed & Dodds, Paul & Barrett, Mark & Spataru, Catalina, 2015. "Evaluating the accuracy of CFSR reanalysis hourly wind speed forecasts for the UK, using in situ measurements and geographical information," Renewable Energy, Elsevier, vol. 77(C), pages 527-538.
    5. 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.
    6. Myhr, Anders & Bjerkseter, Catho & Ågotnes, Anders & Nygaard, Tor A., 2014. "Levelised cost of energy for offshore floating wind turbines in a life cycle perspective," Renewable Energy, Elsevier, vol. 66(C), pages 714-728.
    7. Rose, Stephen & Apt, Jay, 2015. "What can reanalysis data tell us about wind power?," Renewable Energy, Elsevier, vol. 83(C), pages 963-969.
    8. Zountouridou, E.I. & Kiokes, G.C. & Chakalis, S. & Georgilakis, P.S. & Hatziargyriou, N.D., 2015. "Offshore floating wind parks in the deep waters of Mediterranean Sea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 433-448.
    9. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Sensitivity of the WRF model wind simulation and wind energy production estimates to planetary boundary layer parameterizations for onshore and offshore areas in the Iberian Peninsula," Applied Energy, Elsevier, vol. 135(C), pages 234-246.
    10. Morales, Luis & Lang, Francisco & Mattar, Cristian, 2012. "Mesoscale wind speed simulation using CALMET model and reanalysis information: An application to wind potential," Renewable Energy, Elsevier, vol. 48(C), pages 57-71.
    11. Watts, David & Jara, Danilo, 2011. "Statistical analysis of wind energy in Chile," Renewable Energy, Elsevier, vol. 36(5), pages 1603-1613.
    12. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "WRF wind simulation and wind energy production estimates forced by different reanalyses: Comparison with observed data for Portugal," Applied Energy, Elsevier, vol. 117(C), pages 116-126.
    13. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Offshore wind energy resource simulation forced by different reanalyses: Comparison with observed data in the Iberian Peninsula," Applied Energy, Elsevier, vol. 134(C), pages 57-64.
    Full references (including those not matched with items on IDEAS)

    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. 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).
    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. 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.
    4. Santos, F. & Gómez-Gesteira, M. & deCastro, M. & Añel, J.A. & Carvalho, D. & Costoya, Xurxo & Dias, J.M., 2018. "On the accuracy of CORDEX RCMs to project future winds over the Iberian Peninsula and surrounding ocean," Applied Energy, Elsevier, vol. 228(C), pages 289-300.
    5. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    6. Alain Ulazia & Ander Nafarrate & Gabriel Ibarra-Berastegi & Jon Sáenz & Sheila Carreno-Madinabeitia, 2019. "The Consequences of Air Density Variations over Northeastern Scotland for Offshore Wind Energy Potential," Energies, MDPI, vol. 12(13), pages 1-18, July.
    7. 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).
    8. Ulazia, Alain & Saenz, Jon & Ibarra-Berastegui, Gabriel, 2016. "Sensitivity to the use of 3DVAR data assimilation in a mesoscale model for estimating offshore wind energy potential. A case study of the Iberian northern coastline," Applied Energy, Elsevier, vol. 180(C), pages 617-627.
    9. Yuan, Renyu & Ji, Wenju & Luo, Kun & Wang, Jianwen & Zhang, Sanxia & Wang, Qiang & Fan, Jianren & Ni, MingJiang & Cen, Kefa, 2017. "Coupled wind farm parameterization with a mesoscale model for simulations of an onshore wind farm," Applied Energy, Elsevier, vol. 206(C), pages 113-125.
    10. 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).
    11. Argüeso, D. & Businger, S., 2018. "Wind power characteristics of Oahu, Hawaii," Renewable Energy, Elsevier, vol. 128(PA), pages 324-336.
    12. Rose, Stephen & Apt, Jay, 2016. "Quantifying sources of uncertainty in reanalysis derived wind speed," Renewable Energy, Elsevier, vol. 94(C), pages 157-165.
    13. Ulazia, Alain & Sáenz, Jon & Ibarra-Berastegi, Gabriel & González-Rojí, Santos J. & Carreno-Madinabeitia, Sheila, 2019. "Global estimations of wind energy potential considering seasonal air density changes," Energy, Elsevier, vol. 187(C).
    14. Zappa, William & van den Broek, Machteld, 2018. "Analysing the potential of integrating wind and solar power in Europe using spatial optimisation under various scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1192-1216.
    15. 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).
    16. Nagababu, Garlapati & Kachhwaha, Surendra Singh & Naidu, Natansh K. & Savsani, Vimal, 2017. "Application of reanalysis data to estimate offshore wind potential in EEZ of India based on marine ecosystem considerations," Energy, Elsevier, vol. 118(C), pages 622-631.
    17. Gadad, Sanjeev & Deka, Paresh Chandra, 2016. "Offshore wind power resource assessment using Oceansat-2 scatterometer data at a regional scale," Applied Energy, Elsevier, vol. 176(C), pages 157-170.
    18. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2019. "Characterization of wind resource in China from a new perspective," Energy, Elsevier, vol. 167(C), pages 994-1010.
    19. César Henrique Mattos Pires & Felipe M. Pimenta & Carla A. D'Aquino & Osvaldo R. Saavedra & Xuerui Mao & Arcilan T. Assireu, 2020. "Coastal Wind Power in Southern Santa Catarina, Brazil," Energies, MDPI, vol. 13(19), pages 1-23, October.
    20. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Sensitivity of the WRF model wind simulation and wind energy production estimates to planetary boundary layer parameterizations for onshore and offshore areas in the Iberian Peninsula," Applied Energy, Elsevier, vol. 135(C), pages 234-246.

    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:94:y:2016:i:c:p:22-31. 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.