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

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  • 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
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    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. 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.
    3. 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.
    4. Rose, Stephen & Apt, Jay, 2015. "What can reanalysis data tell us about wind power?," Renewable Energy, Elsevier, vol. 83(C), pages 963-969.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Watts, David & Jara, Danilo, 2011. "Statistical analysis of wind energy in Chile," Renewable Energy, Elsevier, vol. 36(5), pages 1603-1613.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
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