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Offshore winds mapped from satellite remote sensing

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  • Charlotte Bay Hasager

Abstract

Around 2000 wind turbines in 58 offshore wind farms produce wind energy in the Northern European seas and many new wind farms are foreseen. The wind resource assessment is costly to observe using traditional meteorological masts and therefore atmospheric modeling is state of the art. However, to reduce the uncertainty on the model results on the offshore wind resource, it is necessary to compare model results with observations. Observations from ground‐based wind lidar and satellite remote sensing are the two main technologies that can provide new types of offshore wind data at relatively low cost. The advantages of microwave satellite remote sensing are (1) horizontal spatial coverage, (2) long data archives, and (3) high spatial detail both in the coastal zone and of far‐field wind farm wake. Passive microwave ocean wind speed data are available since 1987 with up to six observations per day with near‐global coverage. The data are particularly useful for investigation of long‐term wind conditions. Scatterometer ocean surface wind vectors provide a continuous series since 1999 with twice‐daily near‐global coverage. Both types of data have grid cells around 25 km. In contrast, synthetic aperture radar (SAR) wind maps can be retrieved at 1‐km grid resolution. SAR‐based wind maps have been used for wind resource assessment far offshore and in the coastal zones with good results when compared to e.g., meteorological data and mesoscale model results. High‐resolution SAR data show very long far‐field wind farm wakes. Thus wind farm wake loss is foreseen in wind farm clusters. WIREs Energy Environ 2014, 3:594–603. doi: 10.1002/wene.123 This article is categorized under: Wind Power > Science and Materials

Suggested Citation

  • Charlotte Bay Hasager, 2014. "Offshore winds mapped from satellite remote sensing," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 3(6), pages 594-603, November.
  • Handle: RePEc:bla:wireae:v:3:y:2014:i:6:p:594-603
    DOI: 10.1002/wene.123
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    References listed on IDEAS

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    1. Jiang, Dong & Zhuang, Dafang & Huang, Yaohuan & Wang, Jianhua & Fu, Jingying, 2013. "Evaluating the spatio-temporal variation of China's offshore wind resources based on remotely sensed wind field data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 142-148.
    2. Karagali, Ioanna & Badger, Merete & Hahmann, Andrea N. & Peña, Alfredo & B. Hasager, Charlotte & Sempreviva, Anna Maria, 2013. "Spatial and temporal variability of winds in the Northern European Seas," Renewable Energy, Elsevier, vol. 57(C), pages 200-210.
    3. Erik Lundtang Petersen & Ib Troen, 2012. "Wind conditions and resource assessment," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 1(2), pages 206-217, September.
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    1. Tiny Remmers & Fiona Cawkwell & Cian Desmond & Jimmy Murphy & Eirini Politi, 2019. "The Potential of Advanced Scatterometer (ASCAT) 12.5 km Coastal Observations for Offshore Wind Farm Site Selection in Irish Waters," Energies, MDPI, vol. 12(2), pages 1-16, January.
    2. Elsner, Paul & Suarez, Suzette, 2019. "Renewable energy from the high seas: Geo-spatial modelling of resource potential and legal implications for developing offshore wind projects beyond the national jurisdiction of coastal States," Energy Policy, Elsevier, vol. 128(C), pages 919-929.
    3. Tuy, Soklin & Lee, Han Soo & Chreng, Karodine, 2022. "Integrated assessment of offshore wind power potential using Weather Research and Forecast (WRF) downscaling with Sentinel-1 satellite imagery, optimal sites, annual energy production and equivalent C," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    4. Felipe M. Pimenta & Allan R. Silva & Arcilan T. Assireu & Vinicio de S. e Almeida & Osvaldo R. Saavedra, 2019. "Brazil Offshore Wind Resources and Atmospheric Surface Layer Stability," Energies, MDPI, vol. 12(21), pages 1-21, November.
    5. Elsner, Paul, 2019. "Continental-scale assessment of the African offshore wind energy potential: Spatial analysis of an under-appreciated renewable energy resource," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 394-407.

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