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.
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.
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.