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Offshore wind energy resource simulation forced by different reanalyses: Comparison with observed data in the Iberian Peninsula

Author

Listed:
  • Carvalho, D.
  • Rocha, A.
  • Gómez-Gesteira, M.
  • Silva Santos, C.

Abstract

Due to the increasing interest in the prospection of potential sites for the installation of offshore wind farms, it becomes important to extend the tests presented on Carvalho et al. (2014) to offshore areas. For that, the WRF model was used to conduct ocean surface wind simulations forced by different initial and boundary conditions (NCEP-R2, ERA-Interim, NCEP-CFSR, NASA-MERRA, NCEP-FNL and NCEP-GFS) aiming to assess which one of these datasets provides the most accurate ocean surface wind simulation and offshore wind energy estimates. Six near surface wind simulations were performed, each one of them forced by a different initial and boundary dataset. Results were evaluated using data collected at five buoys that measure the wind in the Iberian Peninsula region (Galician coast and Gulf of Cádiz).

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:134:y:2014:i:c:p:57-64
    DOI: 10.1016/j.apenergy.2014.08.018
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    References listed on IDEAS

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    1. 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.
    2. Gallego, C. & Pinson, P. & Madsen, H. & Costa, A. & Cuerva, A., 2011. "Influence of local wind speed and direction on wind power dynamics – Application to offshore very short-term forecasting," Applied Energy, Elsevier, vol. 88(11), pages 4087-4096.
    3. Krajacic, Goran & Duic, Neven & Carvalho, Maria da Graça, 2011. "How to achieve a 100% RES electricity supply for Portugal?," Applied Energy, Elsevier, vol. 88(2), pages 508-517, February.
    4. Snyder, Brian & Kaiser, Mark J., 2009. "A comparison of offshore wind power development in europe and the U.S.: Patterns and drivers of development," Applied Energy, Elsevier, vol. 86(10), pages 1845-1856, October.
    5. de Prada Gil, Mikel & Gomis-Bellmunt, Oriol & Sumper, Andreas, 2014. "Technical and economic assessment of offshore wind power plants based on variable frequency operation of clusters with a single power converter," Applied Energy, Elsevier, vol. 125(C), pages 218-229.
    6. Cassola, Federico & Burlando, Massimiliano, 2012. "Wind speed and wind energy forecast through Kalman filtering of Numerical Weather Prediction model output," Applied Energy, Elsevier, vol. 99(C), pages 154-166.
    7. 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.
    8. Esteban, Miguel & Leary, David, 2012. "Current developments and future prospects of offshore wind and ocean energy," Applied Energy, Elsevier, vol. 90(1), pages 128-136.
    9. Soukissian, Takvor, 2013. "Use of multi-parameter distributions for offshore wind speed modeling: The Johnson SB distribution," Applied Energy, Elsevier, vol. 111(C), pages 982-1000.
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    Keywords

    NCEP-R2; ERA-Interim; NCEP-CFSR; NCEP-FNL; GFS; Offshore winds;
    All these keywords.

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