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A new methodology for offshore wind speed assessment integrating Sentinel-1, ERA-Interim and in-situ measurement

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  • Nezhad, M. Majidi
  • Neshat, M.
  • Heydari, A.
  • Razmjoo, A.
  • Piras, G.
  • Garcia, D. Astiaso

Abstract

Offshore Wind (OW) speed assessment is a key aspect for the development of new wind farms at sea. Satellites can be used to globally obtain ocean and sea distribution, compensating limited in-situ measurements. In this study, a new methodology to estimate the wind’s speed potential is here proposed. Preliminary, Sentinel-1 (S-1) images have been analyzed by means of the Sentinel Application Platform (SNAP) software, extrapolating wind speed data for each cell pixel size of a testing area. Then GIS (Geographic Information System) software has been used to map wind data and find the best pixel location comparing these data with in-situ data. Furthermore, wind speed has been analyzed using the ERA-Interim reanalysis dataset for areas within 11 km and 40 km from the Lillgrund OW farm in the Baltic Sea to better understand wind regimes. Finally, wind speed parameters obtained by S-1 in Sea Surface Water (SSW) with the 10 m standard high have been compared with wind speed recorded by Supervisory Control and Data Acquisition (SCADA) systems of two turbine using wind profile formula. Obtained results show the comparison accuracy of wind speed assessment for each center of the pixels by S-1 satellite images and in-situ (SCADA) measurements. Data actually depends on the distance between the selected center pixel and the location of the turbines. The obtained wind speed differences (0.26 m/s - RMSE = 1.38 and 0.92 m/s - RMSE = 1.82) pinpointed the direct effect of the distance between the selected pixel center and the in-situ measurements location in the S-1 imagery for wind speed potential assessment. Obtained results proved an improvement of the OW assessment accuracy using multiple satellite observations, demonstrating that SAR wind maps can support OW speed sites assessment by introducing observations in different phases of an OW farm project.

Suggested Citation

  • Nezhad, M. Majidi & Neshat, M. & Heydari, A. & Razmjoo, A. & Piras, G. & Garcia, D. Astiaso, 2021. "A new methodology for offshore wind speed assessment integrating Sentinel-1, ERA-Interim and in-situ measurement," Renewable Energy, Elsevier, vol. 172(C), pages 1301-1313.
    • Handle: RePEc:eee:renene:v:172:y:2021:i:c:p:1301-1313
    DOI: 10.1016/j.renene.2021.03.026
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    Cited by:

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    2. Liang Cui & Ye Xu & Ling Xu & Guohe Huang, 2021. "Wind Farm Location Special Optimization Based on Grid GIS and Choquet Fuzzy Integral Method in Dalian City, China," Energies, MDPI, vol. 14(9), pages 1-13, April.
    3. Majidi Nezhad, M. & Heydari, A. & Pirshayan, E. & Groppi, D. & Astiaso Garcia, D., 2021. "A novel forecasting model for wind speed assessment using sentinel family satellites images and machine learning method," Renewable Energy, Elsevier, vol. 179(C), pages 2198-2211.

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