The space-time structure of turbulence for lidar-assisted wind turbine control

Lidar-assisted windturbinecontrol has been proven to be beneficial for turbine load reduction. It relies on the preview of incoming turbulence provided by anacellelidar, which allows the turbine controller to react to the flow disturbances before their impact on the turbine. When assessing its benefits, previous studies mainly use the standard turbulence parameters suggested by the IEC 61400-1 standard and assume Taylor's frozen hypothesis. Based onatmospheric turbulenceobservations, the parameters of the Mann spectral turbulence model differ significantly from the values recommended in the standard, and they vary, e.g., with atmospheric stability. Also, turbulence evolution from upstream to therotor positionconflicts with the frozen turbulence hypothesis, and its effect on the preview quality by a nacelle lidar still needs quantification. This work presents a simple method to extend the Mann model to account for thetemporal evolutionof turbulence using a space-time spectral velocity tensor. Under various atmospheric stability conditions, we derive the space-time tensor parameters and evaluate the space-time tensor using data from a five-beam lidar and a meteorological mast, we found good agreement between the space-time tensor and the measurement data. In addition, a numerical method for simulating a four-dimensional (4D) space-timevelocity fieldbased on the space-time tensor is presented. In the end, we analyze the importance of including the temporal evolution of turbulence for assessing lidar wind preview quality.