Using SAR for Characterization of Offshore Wind Farm Wakes and Coastal Wind Speed Gradients

Charlotte Bay Hasager, Tobias Torben Ahsbahs, Merete Badger, Kurt Schaldemose Hansen, Patrick Volker

    Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review


    Offshore wind farms influence the atmosphere downwind for considerable distances and SAR has been used to demonstrate this effect in earlier studies. SAR has also been used to characterize winds in the coastal zone influenced by the proximity to the land. The novelty of the present study — focusing on the Anholt wind farm in the Kattegat Strait between Denmark and Sweden — is the interplay between the wind farm wake effect and a strong horizontal wind speed gradient from the coastline and further offshore. The wind farm was constructed after the Envisat ASAR mission ended and prior to the Sentinel-1 mission.

    The study is based on the SAR wind archive available at . The SAR data are processed at DTU using CMOD5.N and wind directions from the Climate Forecast System Reanalysis (CFSR) from 2002 to 2010 and the Global Forecasting System (GFS) from 2011 to 2017. The pixel size is 500 m.

    The offshore winds observed by Envisat are compared to Weather and Research and Forecasting (WRF) model results. More specifically, the variation in wind speed along the first (western) row of wind turbines (stretching 20 km from north to south located closest to the Danish coastline) for winds coming from 265° (±15°) show good agreement between SAR and WRF. The wind speed variation along this row of turbines is also assessed based on the Supervisory Control And Data Acquisition (SCADA) data from the wind turbines kindly provided by Ørsted and Partners. The data are 10 minute values from January 2013 to June 2015. Interestingly, the average variation in wind speed along the western row for winds coming from 265° (±15°) show around 1 m/s higher winds at the northernmost turbines compared to the southernmost turbines. This difference is most likely caused by the varying distance to the coast. The fetch is up to 50 km in the north and down to 16 km in the south. Wind speeds relative to the center turbine from SAR and SCADA agree within 0.1% while WRF over-predicts around 1% as compared to SCADA. All data sets quantify a significant coastal wind speed variation.

    The comparison of winds from SAR and SCADA (extrapolated from 81.6 m hub-height with logarithmic profile to 10 m) in non-waked and waked conditions give results of R2 of 0.97 with RMSE of 1.80 and 1.70 m/s and bias -0.12 and -0.52 m/s, respectively.

    An investigation of the wind farm wake effects is completed using the Envisat data versus the Sentinel-1 data to provide the difference between free-stream and wind farm wake conditions. Various horizontal transects aligned with the wind direction and perpendicular to the wind direction are analysed. The uncertainty of the average wind speed is also assessed and significant variations are mapped (Ahsbahs et al. in review, Wind Energy Science).

    The conclusions are that SAR enables quantification of spatial horizontal wind speed gradients and wind farm wakes. The large SAR wind archive can be used to explore complex cases providing a measurement independent of modelling results.

    Original languageEnglish
    Publication date2018
    Publication statusPublished - 2018
    EventSeasar2018 - advance in SAR oceanography - Frascati, Italy
    Duration: 7 May 201810 May 2018


    ConferenceSeasar2018 - advance in SAR oceanography


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