Quantifying error of remote sensing observations of wind turbine wakes using computational fluid dynamics

Abstract:

Wind-profiling lidars are now regularly used in wind energy for wind resource assessment, inflow characterization, and wake measurements. Lidar wind profilers exploit the Doppler shift of laser light backscattered from particulates carried by the wind to measure a line-of-sight (LOS) velocity. The Doppler Beam Swinging (DBS) technique, used by many commercial systems, considers measurements of this LOS velocity in multiple radial directions in order to estimate horizontal and vertical winds. The method relies on the assumption of homogeneous flow across the region sampled by the beams. Use of such a system in inhomogeneous flow, such as wind turbine wakes or complex terrain, will result in error which may or may not be significant.

To quantify the error expected from such violation of the assumption of horizontal homogeneity, we simulate inhomogeneous flow in the atmospheric boundary layer, notably stably-stratified flow past a wind turbine using large-eddy simulation. This slightly stable case results in 15 degrees of wind direction change across the turbine rotor disk. The resulting flow-field is sampled in the same fashion that a lidar samples the atmosphere with the DBS approach, enabling quantification of the error in the DBS observations. The observations from the instruments located upwind have small error, which is further ameliorated with time-averaging. However, the downwind observations, particularly within the first two rotor diameters downwind from the wind turbine, suffer from errors due to the heterogeneity of the wind turbine wake. Errors in the stream-wise component of the flow are generally small, less than 0.5 m s^-1. Errors in the cross-stream and vertical velocity components are much larger: cross-stream component errors are on the order of 1.0 m s^-1, while errors in the vertical velocity exceed the actual values of the vertical velocity. DBS-based assessments of wake wind speed deficits based on the stream-wise velocity can be relied upon even within the near wake within 0.5 m s^-1, but cross-stream and vertical velocity estimates in the near wake are compromised. Measurements of inhomogeneous flow such as wind turbine wakes are susceptible to these errors, and interpretations of field observations should account for this uncertainty.