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Spatial and temporal characteristics of wind and wind power off the coasts of Brittany

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  • Bentamy, Abderrahim
  • Croize-Fillon, Denis

Abstract

The main objective of this paper is to thoroughly examine the remotely sensed wind characteristics around the coasts of Brittany as well as some more specific areas. The offshore wind power potential is then assessed. To achieve this objective, information on wind speed and direction with sufficient spatial and temporal sampling under all weather conditions and during day and night is required. This study uses more than 12 years (December 1999–December 2012) of consistent remotely sensed data retrieved from the ASCAT and QuikSCAT scatterometers to estimate the conventional moments and associated wind distribution parameters. The latter are comparable to wind observations from meteorological stations. Furthermore, combining in-situ and scatterometer wind information enables an improved assessment of the spatial and temporal wind structures at specific locations of interest to be made. The wind statistical results are used to study the spatial and temporal patterns of the wind power. Although the main parameters characterizing wind power potential such as mean, variability, maximum energy, wind speed and intra-annual exhibit seasonal features, significant inter-annual variability is also depicted. Furthermore, differences are found between the wind power estimated for northern and for southern Brittany.

Suggested Citation

  • Bentamy, Abderrahim & Croize-Fillon, Denis, 2014. "Spatial and temporal characteristics of wind and wind power off the coasts of Brittany," Renewable Energy, Elsevier, vol. 66(C), pages 670-679.
    • Handle: RePEc:eee:renene:v:66:y:2014:i:c:p:670-679
    DOI: 10.1016/j.renene.2014.01.012
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    References listed on IDEAS

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    1. 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.
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    Cited by:

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    2. Daniel Ambach & Robert Garthoff, 2016. "Vorhersagen der Windgeschwindigkeit und Windenergie in Deutschland," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(1), pages 15-36, February.
    3. Daniel Ambach & Robert Garthoff, 2016. "Vorhersagen der Windgeschwindigkeit und Windenergie in Deutschland [Predictions of wind speed and wind energy in Germany]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(1), pages 15-36, February.
    4. Díaz, H. & Guedes Soares, C., 2022. "A novel multi-criteria decision-making model to evaluate floating wind farm locations," Renewable Energy, Elsevier, vol. 185(C), pages 431-454.
    5. Díaz, H. & Guedes Soares, C., 2020. "An integrated GIS approach for site selection of floating offshore wind farms in the Atlantic continental European coastline," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    6. 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).

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