Measuring the wind resource with SAR satellites

Context

  • Co-financing of a study by the Centre National d’Etudes Spatiales, The French Space Agency, to develop a method for calculating producible energy from SAR data and atmospheric models using Machine Learning techniques.

Challenge

  • Calculate the producible energy at the height of the turbines.

CLS Innovative Solution: Machine Learning

Setting up an industrial partnership

  • This contract has benefited from the partnership we have created with ATMOSKY, a specialist in atmospheric forecasting.
  • The contribution of atmospheric turbulence data is crucial for a fine forecast of the wind resource at the height of the turbines (100 to 200 meters).

Update: METEODYN, the CLS subsidiary specialized in wind assessment, is now our partner for all wind offshore projects.

An original combination of 3 different techniques to calculate the wind at the surface and aloft

  • SAR: for the measurement of surface winds from water roughness.
  • WRF: a high-resolution atmospheric model to extrapolate the wind aloft.
  • Machine Learning, learning of SAR wind calculation functions to refine results through systematic error correction.
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Wind Observation - SAR images

Benefits for the Wind Industry

  • Spatialized: information spanning the entire wind field.
  • A classification of the winds over 18 years of satellite measurements.
  • A better estimate of the energy produced over the life cycle of the wind farm.