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Title: Quantifying error of lidar and sodar Doppler beam swinging measurements of wind turbine wakes using computational fluid dynamics

Journal Article · · Atmospheric Measurement Techniques (Online)
 [1];  [2];  [2]; ORCiD logo [2]
  1. Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)

Wind-profiling lidars are now regularly used in boundary-layer meteorology and in applications such as wind energy and air quality. 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. Using such a system in inhomogeneous flow, such as wind turbine wakes or complex terrain, will result in errors. To quantify the errors 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, with a mean wind speed of 6.5 m s-1 at the turbine hub-height of 80 m. This slightly stable case results in 15° 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, including the lidar range weighting function, enabling quantification of the error in the DBS observations. The observations from the instruments located upwind have small errors, which are 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 approach 30% of the hub-height inflow wind speed close to the rotor disk. Errors in the cross-stream and vertical velocity components are also significant: cross-stream component errors are on the order of 15% of the hub-height inflow wind speed (1.0 m s−1) and errors in the vertical velocity measurement exceed the actual vertical velocity. By three rotor diameters downwind, DBS-based assessments of wake wind speed deficits based on the stream-wise velocity can be relied on even within the near wake within 1.0 s-1 (or 15% of the hub-height inflow wind speed), and the cross-stream velocity error is reduced to 8% while vertical velocity estimates are compromised. Furthermore, measurements of inhomogeneous flow such as wind turbine wakes are susceptible to these errors, and interpretations of field observations should account for this uncertainty.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1220606
Report Number(s):
NREL/JA-5000-62369
Journal Information:
Atmospheric Measurement Techniques (Online), Vol. 8, Issue 2; ISSN 1867-8548
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 63 works
Citation information provided by
Web of Science

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Cited By (30)

Testing and validation of multi-lidar scanning strategies for wind energy applications: Testing and validation of multi-lidar scanning strategies for wind energy applications journal March 2016
Field investigation on the influence of yaw misalignment on the propagation of wind turbine wakes journal June 2018
Observing and Simulating Wind-Turbine Wakes During the Evening Transition journal May 2017
A Numerical Study of Wind-Turbine Wakes for Three Atmospheric Stability Conditions journal May 2017
Investigating wind turbine impacts on near-wake flow using profiling lidar data and large-eddy simulations with an actuator disk model journal July 2015
Implementation of a generalized actuator line model for wind turbine parameterization in the Weather Research and Forecasting model journal November 2017
Wind turbine wake characterization in complex terrain via integrated Doppler lidar data from the Perdigão experiment journal June 2018
Modeling of the atmospheric boundary layer under stability stratification for wind turbine wake production journal October 2019
An Analytical Model for the Effect of Vertical Wind Veer on Wind Turbine Wakes journal July 2018
Low-Frequency Wind Energy Variability in the Continental Contiguous United States journal December 2019
Using a Virtual Lidar Approach to Assess the Accuracy of the Volumetric Reconstruction of a Wind Turbine Wake journal May 2018
Characterization of Wind Turbine Wakes with Nacelle-Mounted Doppler LiDARs and Model Validation in the Presence of Wind Veer journal September 2019
Wind Turbine Wake Characterization from Temporally Disjunct 3-D Measurements journal November 2016
Characterization of Turbulence in Wind Turbine Wakes under Different Stability Conditions from Static Doppler LiDAR Measurements journal March 2017
Assessment of virtual towers performed with scanning wind lidars and Ka-band radars during the XPIA experiment journal January 2017
Validating precision estimates in horizontal wind measurements from a Doppler lidar journal January 2017
Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign journal January 2017
Three-dimensional structure of wind turbine wakes as measured by scanning lidar journal January 2017
Evaluation of turbulence measurement techniques from a single Doppler lidar journal January 2017
Evaluation of three lidar scanning strategies for turbulence measurements journal January 2016
Wind turbine power production and annual energy production depend on atmospheric stability and turbulence journal January 2016
An error reduction algorithm to improve lidar turbulence estimates for wind energy journal January 2017
Atmospheric turbulence affects wind turbine nacelle transfer functions posted_content December 2016
Do wind turbines pose roll hazards to light aircraft? journal January 2018
The effect of wind direction shear on turbine performance in a wind farm in central Iowa journal January 2020
Lidar-based wake tracking for closed-loop wind farm control journal September 2016
Evaluation of three lidar scanning strategies for turbulence measurements journal January 2015
Atmospheric turbulence affects wind turbine nacelle transfer functions journal January 2017
Lidar-based wake tracking for closed-loop wind farm control journal January 2017
Reconstruction of turbulent flow fields from lidar measurements based on large-eddy simulation text January 2020