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.
Highlights
A global transition to renewable energy sources is possible due to abundant renewable resources and technology (Jacobson and Delucchi 2011)
In excess of 4,000 10-min time periods are available for analysis; more than 600 time periods (6,000 min) meet the criteria based on wind speed, wind direction, and precipitation for a wind-turbine wake detected by the lidar
Where U is the mean horizontal wind speed (Stull 1988) at the level at which the velocities are observed. (Note that some investigators focusing on wind-tunnel studies, such as Chamorro and Porté-Agel (2009), normalize turbulence intensity with hub-height wind speed rather than the wind speed at the altitude of the measurement.) In the wind energy industry, turbulence intensity is usually calculated over a 10-min period, it is likely that other averaging times are more appropriate for capturing all the energetic length scales of turbulent fluctuations (Mahrt 1998)
Summary
A global transition to renewable energy sources is possible due to abundant renewable resources and technology (Jacobson and Delucchi 2011). Turbulent wakes affect the energy production of turbines located downwind of other turbines (Barthelmie et al 2007, among others) It is not yet known whether wind-turbine wakes have a beneficial or detrimental impact on crop growth (Rajewski et al 2013) primarily due to the lack of detailed observations of the atmosphere and of the surface exchanges of heat, momentum, moisture, and carbon dioxide upwind and downwind of operational turbines. Measuring mean and turbulence values of the flow under neutral conditions, they found signatures of turbine wakes at distances up to 20D downwind in the wind tunnel. They found the wake momentum deficit to be axially symmetric while wake-driven turbulence characteristics were concentrated above hub height.
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