A key pillar of ECOWIND is bridging the gap between remote sensing technology and real-time turbine control. Your focus will be the development of a predictive capability that allows turbines to react to the wind before it hits the blades.
Using upstream LiDAR measurements (taken several rotor diameters ahead), you will develop a wind field forecasting method, leveraging principles like Taylor’s Frozen Turbulence Hypothesis, to estimate incoming turbulent flow. You will then assess the method’s validity under real atmospheric conditions using a combination of LiDAR data and Large Eddy Simulation (LES) results.