The TurbSim stochastic inflow turbulence code was developed to provide a numerical simulation of a full-field flow that contains coherent turbulence structures that reflect the proper spatiotemporal turbulent velocity field relationships seen in instabilities associated with nocturnal boundary layer flows. This report provides a user's guide for the TurbSim code.

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Light Detection and Ranging (LIDAR) systems are able to measure the speed of incoming wind before it interacts with a wind turbine rotor. These preview wind measurements can be used in feedforward control systems designed to reduce turbine loads. However, the degree to which such preview-based control techniques can reduce loads by reacting to turbulence depends on how accurate the incoming wind field can be measured. This study examines the accuracy of different measurement scenarios that rely on coherent continuouswave Doppler LIDAR systems to determine their applicability to feedforward control. In particular, the impacts of measurement range and angular offset from the wind direction are studied for various wind conditions. A realistic case involving a scanning LIDAR unit mounted in the spinner of a wind turbine is studied in depth, with emphasis on choices for scan radius and preview distance. The effects of turbulence parameters on measurement accuracy are studied as well.wind velocity wavenumber (m −1 ) r scan radius for spinning LIDAR RMS root mean square σ u standard deviation of u component of wind velocity TI turbulence intensity θ LIDAR measurement anglē u mean u wind speed u * friction velocity U * D average friction velocity over rotor disk φ angle between laser and wind velocity vector ψ angle in the rotor plane ω rotational rate of spinning LIDAR * This work was supported in part by the US National Renewable Energy Laboratory. Additional industrial support is also greatly appreciated. The authors also thank Alan Wright, Fiona Dunne, and Jason Laks for discussions on desired characteristics of wind speed measurement devices that can enable preview-based control methods for wind turbines.

Light detection and ranging (LIDAR) systems are able to measure the speed of incoming wind before it reaches a wind turbine rotor. These preview wind measurements can be used in feedforward control systems designed to reduce turbine structural loads. However, the degree to which such preview-based control techniques can reduce loads by reacting to turbulence depends on how accurately the incoming wind field can be measured. This study examines the accuracy of different measurement scenarios that rely on coherent continuous-wave or pulsed Doppler LIDAR systems, in terms of root-mean-square measurement error, to determine their applicability to feedforward control. In particular, the impacts of measurement range, angular offset of the LIDAR beam from the wind direction, and measurement noise are studied for various wind conditions. A realistic simulation case involving a scanning LIDAR unit mounted in the spinner of a MW-scale wind turbine is studied in depth, with emphasis on preview distances that provide minimum measurement error for a specific scan radius. Measurement error is analyzed for LIDAR-based estimates of point wind speeds at the rotor as well as spanwise averaged blade effective wind speeds. The impact of turbulence structures with high coherent turbulent kinetic energy on measurement error is discussed as well.

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