Boundary Layer, Urban Meteorology and Land-Surface Processes

Optimizing Lidar Scanning Strategies for Wind Energy Turbulence Measurements

Jennifer Newman
OU School of Meteorology

06 March 2015, 3:00 PM

National Weather Center, Room 5600
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK

Lidars have recently emerged as a valuable tool for wind resource assessment. Unlike cup anemometers on a traditional meteorological tower, which have fixed measurement heights and are limited by the tower height, lidars can measure wind speeds across an entire turbine rotor disk and can be easily deployed at different locations around a wind farm to examine spatial variability of the wind resource. The ability of lidars to accurately measure mean wind speeds has already been well-documented in the literature. However, several questions remain regarding the measurement of turbulence with lidars. Turbulence has profound effects on the amount of power produced by a turbine and can also impact loads on the turbine blades. Thus, lidars must be able to accurately measure turbulence in order to be seen as a viable alternative to meteorological towers.

Most lidar scanning strategies were designed to measure mean wind speeds, not turbulence, and the scanning strategy used by the lidar can actually induce errors in the lidar-measured turbulence. Lidars that use a scanning circle to deduce the three-dimensional wind field require the assumption that the flow is horizontally homogeneous across the lidar scanning circle; when this assumption is invalid, errors are induced in the turbulence components. In addition, lidar measurements from these techniques are affected by variance contamination, which occurs when measurements from different beam positions are combined to calculate the variance of the different velocity components.

In order to improve variance estimates by lidars, two new techniques were evaluated: 1) multi-lidar scanning strategies, which eliminate the use of a scanning circle and 2) the six-beam scanning strategy, which was designed to mitigate variance contamination. Multi-lidar scanning strategies were evaluated at the Southern Great Plains Atmospheric Radiation Measurement site with three research-grade scanning lidars, while the six-beam strategy and two commonly used lidar scanning strategies were evaluated at the Boulder Atmospheric Observatory, which featured a heavily instrumented 300-m tower. Results indicate that the majority of variance errors occur under unstable conditions, when the lower boundary layer is horizontally heterogeneous and variance contamination can overcome the effects of volume averaging. Methods to improve variance estimation under unstable conditions are discussed and evaluated using co-located lidar and sonic anemometer data. In addition, the performance of the two new techniques under different stability conditions is discussed.

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