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Spatial and temporal variability of wind energy resource and production over the North Western Mediterranean Sea: Sensitivity to air-sea interactions

Author

Listed:
  • Omrani, Hiba
  • Drobinski, Philippe
  • Arsouze, Thomas
  • Bastin, Sophie
  • Lebeaupin-Brossier, Cindy
  • Mailler, Sylvain

Abstract

This work assesses the sensitivity of the offshore wind energy density and production to SST biases and air-sea feedbacks along the French and Spanish coast in the North-Western Mediterranean. It makes use of a set of three 20-years simulations from atmosphere stand-alone and atmosphere/ocean coupled models. In this numerical experiment, the effects of SST bias and air-sea feedbacks are isolated without any interference with other sources of error and uncertainty propagation, meaning that the same model and hence the same physics are used, all other things being equal. This study shows that the effects of SST bias or air-sea feedbacks on wind energy density and production estimation can reach up to 10% and 5%, respectively. Especially, accounting for air-sea coupled processes on sub-monthly time scales weakens systematically the energy density and production by 6.5% and 2.4% with respect to the configuration where these effects are neglected. The relative variability over the 20 years of simulation does not exceed 20% so the impact of air-sea feedbacks is very robust in time in terms of wind energy density and production assessment. Uncertainties up to 6.5 and 2.5% in the evaluation of the potential in terms of wind energy density and production potential can have severe consequences on the whole industry by lowering the projects profitability. This study shows that the effects of SST bias and air-sea feedbacks usually extend vertically up to the hub-height but their magnitude depends on the stability of the atmosphere. This study concludes that reducing the SST bias at the lower boundary of numerical atmospheric models and accounting for rapid interactions and feedbacks between the ocean and the atmosphere are key to improve the reliability of offshore wind energy density and production assessment.

Suggested Citation

  • Omrani, Hiba & Drobinski, Philippe & Arsouze, Thomas & Bastin, Sophie & Lebeaupin-Brossier, Cindy & Mailler, Sylvain, 2017. "Spatial and temporal variability of wind energy resource and production over the North Western Mediterranean Sea: Sensitivity to air-sea interactions," Renewable Energy, Elsevier, vol. 101(C), pages 680-689.
    • Handle: RePEc:eee:renene:v:101:y:2017:i:c:p:680-689
    DOI: 10.1016/j.renene.2016.09.028
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    References listed on IDEAS

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    1. Al-Yahyai, Sultan & Charabi, Yassine & Gastli, Adel, 2010. "Review of the use of Numerical Weather Prediction (NWP) Models for wind energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3192-3198, December.
    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. Charabi, Yassine & Al-Yahyai, Sultan & Gastli, Adel, 2011. "Evaluation of NWP performance for wind energy resource assessment in Oman," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(3), pages 1545-1555, April.
    4. Al-Yahyai, Sultan & Charabi, Yassine & Al-Badi, Abdullah & Gastli, Adel, 2012. "Nested ensemble NWP approach for wind energy assessment," Renewable Energy, Elsevier, vol. 37(1), pages 150-160.
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    Cited by:

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    2. Eugen Rusu & Florin Onea, 2017. "Joint Evaluation of the Wave and Offshore Wind Energy Resources in the Developing Countries," Energies, MDPI, vol. 10(11), pages 1-20, November.
    3. Alexis Tantet & Marc Stéfanon & Philippe Drobinski & Jordi Badosa & Silvia Concettini & Anna Cretì & Claudia D’Ambrosio & Dimitri Thomopulos & Peter Tankov, 2019. "e 4 clim 1.0: The Energy for a Climate Integrated Model: Description and Application to Italy," Energies, MDPI, vol. 12(22), pages 1-37, November.
    4. Kazak, Jan & van Hoof, Joost & Szewranski, Szymon, 2017. "Challenges in the wind turbines location process in Central Europe – The use of spatial decision support systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 425-433.

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