Defining optimal scanning geometries for scanning lidars for wind energy applications remains an active field of research. This paper evaluates uncertainties associated with arc scan geometries and presents recommendations regarding optimal configurations in the atmospheric boundary layer. The analysis is based on arc scan data from a Doppler wind lidar with one elevation angle and seven azimuth angles spanning 30° and focuses on an estimation of 10-min mean wind speed and direction. When flow is horizontally uniform, this approach can provide accurate wind measurements required for wind resource assessments in part because of its high resampling rate. Retrieved wind velocities at a single range gate exhibit good correlation to data from a sonic anemometer on a nearby meteorological tower, and vertical profiles of horizontal wind speed, though derived from range gates located on a conical surface, match those measured by mast-mounted cup anemometers. Uncertainties in the retrieved wind velocity are related to high turbulent wind fluctuation and an inhomogeneous horizontal wind field. The radial velocity variance is found to be a robust measure of the uncertainty of the retrieved wind speed because of its relationship to turbulence properties. It is further shown that the standard error of wind speed estimates can be minimized by increasing the azimuthal range beyond 30° and using five to seven azimuth angles.

The 3D wind and turbulence characteristics of the atmospheric boundary layer experiment (3D Wind) was conducted to evaluate innovative remote sensing and in situ platforms for measurements of wind and turbulence regimes. The experiment is part of a planned series that focuses on quantifying wind and turbulence characteristics at the scales of modern wind turbines and wind farms and was conducted in northern Indiana in May 2012. 3D Wind had the following specific objectives: (i) intercomparison experiments evaluating wind speed profiles across the wind turbine rotor plane from traditional cup anemometers and wind vanes on a meteorological mast and from a tethered balloon, sonic anemometers (mast mounted and on an unmanned aerial vehicle), three vertical-pointing (continuous wave) lidars and a pulsed scanning lidar, and (ii) integrate these measurements and output from 3-km-resolution (over the inner domain) simulations with the Weather Research and Forecasting Model to develop a detailed depiction of the a... The 3D wind and turbulence characteristics of the atmospheric boundary layer experiment (3D Wind) was conducted to evaluate innovative remote sensing and in situ platforms for measurements of wind and turbulence regimes. The experiment is part of a planned series that focuses on quantifying wind and turbulence characteristics at the scales of modern wind turbines and wind farms and was conducted in northern Indiana in May 2012. 3D Wind had the following specific objectives: (i) intercomparison experiments evaluating wind speed profiles across the wind turbine rotor plane from traditional cup anemometers and wind vanes on a meteorological mast and from a tethered balloon, sonic anemometers (mast mounted and on an unmanned aerial vehicle), three vertical-pointing (continuous wave) lidars and a pulsed scanning lidar, and (ii) integrate these measurements and output from 3-km-resolution (over the inner domain) simulations with the Weather Research and Forecasting Model to develop a detailed depiction of the a...

Doppler lidars are frequently operated in a mode referred to as arc scans, wherein the lidar beam scans across a sector with a fixed elevation angle and the resulting measurements are used to derive an estimate of the n minute horizontal mean wind velocity (speed and direction). Previous studies have shown that the uncertainty in the measured wind speed originates from turbulent wind fluctuations and depends on the scan geometry (the arc span and the arc orientation). This paper is designed to provide guidance on optimal scan geometries for two key applications in the wind energy industry: wind turbine power performance analysis and annual energy production prediction. We present a quantitative analysis of the retrieved wind speed uncertainty derived using a theoretical model with the assumption of isotropic and frozen turbulence, and observations from three sites that are onshore with flat terrain, onshore with complex terrain and offshore, respectively. The results from both the theoretical model and observations show that the uncertainty is scaled with the turbulence intensity such that the relative standard error on the 10 min mean wind speed is about 30 % of the turbulence intensity. The uncertainty in both retrieved wind speeds and derived wind energy production estimates can be reduced by aligning lidar beams with the dominant wind direction, increasing the arc span and lowering the number of beams per arc scan. Large arc spans should be used at sites with high turbulence intensity and/or large wind direction variation.