The Effect of Wind-Turbine Wakes on Summertime US Midwest Atmospheric Wind Profiles as Observed with Ground-Based Doppler Lidar

Abstract

We examine the influence of a modern multi-megawatt wind turbine on wind and turbulence profiles three rotor diameters (D) downwind of the turbine. Light detection and ranging (lidar) wind-profile observations were collected during summer 2011 in an operating wind farm in central Iowa at 20-m vertical intervals from 40 to 220 m above the surface. After a calibration period during which two lidars were operated next to each other, one lidar was located approximately 2D directly south of a wind turbine; the other lidar was moved approximately 3D north of the same wind turbine. Data from the two lidars during southerly flow conditions enabled the simultaneous capture of inflow and wake conditions. The inflow wind and turbulence profiles exhibit strong variability with atmospheric stability: daytime profiles are well-mixed with little shear and strong turbulence, while nighttime profiles exhibit minimal turbulence and considerable shear across the rotor disk region and above. Consistent with the observations available from other studies and with wind-tunnel and large-eddy simulation studies, measurable reductions in wake wind-speeds occur at heights spanning the wind turbine rotor (43-117 m), and turbulent quantities increase in the wake. In generalizing these results as a function of inflow wind speed, we find the wind-speed deficit in the wake is largest at hub height or just above, and the maximum deficit occurs when wind speeds are below the rated speed for the turbine. Similarly, the maximum enhancement of turbulence kinetic energy and turbulence intensity occurs at hub height, although observations at the top of the rotor disk do not allow assessment of turbulence in that region. The wind shear below turbine hub height (quantified here with the power-law coefficient) is found to be a useful parameter to identify whether a downwind lidar observes turbine wake or free-flow conditions. These field observations provide data for validating turbine-wake models and wind-tunnel observations, and for guiding assessments of the impacts of wakes on surface turbulent fluxes or surface temperatures downwind of turbines.

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

“…Note that in Fig. 7c, the lidar derives TKE using 2 min variances, which is intrinsically different from the modelled TKE, as discussed in Kumer et al (2016) and Rhodes and Lundquist (2013). Hence, readers should focus 00:00 12:00 00:00 12:00 00:00 12:00 00:00 12:00 00:00…”

“…This campaign was a component of the larger CWEX project, which explored the interactions of wind turbines with crops, surface fluxes, and near-surface flows in different atmospheric stability regimes in flat terrain (Rajewski et al, 2013). Research facilitated by the CWEX projects include diurnal changes in observed turbine wakes (Rhodes and Lundquist, 2013), turbine interactions with moisture and carbon dioxide fluxes , LES modelling of turbine wakes in changing stability regimes , nocturnal low-level jet (LLJ) occurrences (Vanderwende et al, 2015), diurnal changes of the microclimate near wind turbines (Rajewski et al, 2016), multiple-wake interactions (Bodini et al, 2017), the evolution of turbine wakes during the evening transition (Lee and Lundquist, 2017), and coupled mesoscalemicroscale modelling (Muñoz-Esparza et al, 2017).…”

“…In CWEX-11, wind-turbine wake measurements at a different location in this wind farm were collected with these instruments (Rhodes and Lundquist, 2013), and the errors in the WC lidar measurements due to inhomogeneous flow were explored by Bingöl et al (2009) and Lundquist et al (2015). The WINDCUBE 200S scanning lidar (green square in Fig.…”

Observing and Simulating Wind-Turbine Wakes During the Evening Transition

“…To explore wake behaviour, the Crop/Wind Energy EXperiment 2011 (CWEX-11) collected wind observations in a 200-turbine wind farm in central Iowa from June to August 2011 (Rajewski et al 2013(Rajewski et al , 2014Rhodes and Lundquist , while the flux towers collected 20-Hz measurements of near-surface wind speed and direction, the surface heat flux Q H , virtual temperature, and water vapour density at 4.5 m a.g.l. Since the prevailing wind direction at the site is southerly, the instruments were located directly north (250 m, about 3D) and south (164 m, about 2D) of a row of east-west oriented turbines (Fig.…”

Estimate of Boundary-Layer Depth Over Beijing, China, Using Doppler Lidar Data During SURF-2015

“…Satellite-based lidar has the potential to provide wind measurements in regions not sampled by radiosondes or tracking of clouds or other features (Baker et al 1995;Devara et al 2015). With improvements in high-energy pulsed lasers, advanced lidars with low-noise detectors and high optical quality telescopes have been evaluated for wind measurements at ranges up to 10 km, and with low aerosol/cloud droplet concentrations (e.g., Frehlich et al 1994;Rhodes and Lundquist 2013;Devara et al 2015). Compared to radiosondes or aircraft, the Doppler lidar has the advantage of superior spatial and temporal resolutions (Devara 1989;Singh and Kavaya 2004).…”