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Quantifying the wind energy potential differences using different WRF initial conditions on Mediterranean coast of Chile

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  • González-Alonso de Linaje, N.
  • Mattar, C.
  • Borvarán, D.

Abstract

In this work, a comprehensive analysis of WRF initial conditions was performed to estimate the offshore wind power on the coasts of the IV region of Coquimbo, Chile. Three configurations of atmospheric physical models accounting for the planetary boundary layer and surface layer were put under consideration. In addition, sensitivity was estimated by using four physical-numerical simulations: spectral nudging, surface model, 10-days restart and definition of vertical levels. Simulations were carried out for January and July 2013. The results show that the initial condition composed of physical schemes MYNN3 – MYNN – Noah (C3) has the lowest RMSE and highest r2 with 1.748 m s−1 and 0.755 for January, and 2.512 m s−1 RMSE and 0.472 r2 for July. In the sensitivity analysis, the configuration of vertical levels (S3) has the lowest RMSE with 1.812 m s-1 and the highest r2 with 0.732. High seasonal variability between January and July 2013 and WRF initial conditions have an impact on the estimation of the wind power and technical feasibility indicators in the study area, with differences between simulated and LV data in the range of 0.01%–36.3%.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:188:y:2019:i:c:s0360544219317219
    DOI: 10.1016/j.energy.2019.116027
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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. Carvalho, D. & Rocha, A. & Santos, C. Silva & Pereira, R., 2013. "Wind resource modelling in complex terrain using different mesoscale–microscale coupling techniques," Applied Energy, Elsevier, vol. 108(C), pages 493-504.
    3. 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.
    4. Prósper, Miguel A. & Otero-Casal, Carlos & Fernández, Felipe Canoura & Miguez-Macho, Gonzalo, 2019. "Wind power forecasting for a real onshore wind farm on complex terrain using WRF high resolution simulations," Renewable Energy, Elsevier, vol. 135(C), pages 674-686.
    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. 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.
    7. 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.
    8. Celik, Ali N. & Kolhe, Mohan, 2013. "Generalized feed-forward based method for wind energy prediction," Applied Energy, Elsevier, vol. 101(C), pages 582-588.
    9. Wang, Yi-Hui & Walter, Ryan K. & White, Crow & Farr, Hayley & Ruttenberg, Benjamin I., 2019. "Assessment of surface wind datasets for estimating offshore wind energy along the Central California Coast," Renewable Energy, Elsevier, vol. 133(C), pages 343-353.
    10. Mohammadpour Penchah, Mohammadreza & Malakooti, Hossein & Satkin, Mohammad, 2017. "Evaluation of planetary boundary layer simulations for wind resource study in east of Iran," Renewable Energy, Elsevier, vol. 111(C), pages 1-10.
    11. Rose, Stephen & Apt, Jay, 2015. "What can reanalysis data tell us about wind power?," Renewable Energy, Elsevier, vol. 83(C), pages 963-969.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
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