Numerous previous works have shown that vertical shear in wind speed and wind direction exist in the atmospheric boundary layer. In this work, meteorological forcing mechanisms, such as the Ekman spiral, thermal wind, and inertial oscillation, are discussed as likely drivers of such shears in the statically stable environment. Since the inertial oscillation, the Ekman spiral, and statically stable conditions are independent of geography, potentially significant magnitudes of speed and direction shear are hypothesized to occur to some extent at any inland site in the world. The frequency of occurrence of non-trivial magnitudes of speed and direction shear are analyzed from observation platforms in Lubbock, Texas and Goodland, Indiana. On average, the correlation between speed and direction shear magnitudes and static atmospheric stability are found to be very high. Moreover, large magnitude speed and direction shears are observed in conditions with relatively high hub-height wind speeds. The effects of speed and direction shear on wind turbine power performance are tested by incorporating a simple steady direction shear profile into the fatigue analysis structures and turbulence simulation code from the National Renewable Energy Laboratory. In general, the effect on turbine power production varies with the magnitude of speed and direction shear across the turbine rotor, with the majority of simulated conditions exhibiting power loss relative to a zero shear baseline. When coupled with observational data, the observed power gain is calculated to be as great as 0.5% and depletion as great as 3% relative to a no shear baseline. The average annual power change at Lubbock is estimated to be −0.5%.

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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.

An experimental study of the spatial wind structure in the vicinity of a wind turbine by a NOAA coherent Doppler lidar has been conducted. It was found that a working wind turbine generates a wake with the maximum velocity deficit varying from 27% to 74% and with the longitudinal dimension varying from 120 up to 1180 m, depending on the wind strength and atmospheric turbulence. It is shown that, at high wind speeds, the twofold increase of the turbulent energy dissipation rate (from 0.0066 to 0.013 m2 s−3) leads, on average, to halving of the longitudinal dimension of the wind turbine wake (from 680 to 340 m).

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.