Wake measurements behind a large horizontal axis wind turbine generator

Baker, Robert W.; Walker, S.N.

doi:10.1016/0038-092x(84)90110-5

Cited by 42 publications

(21 citation statements)

References 1 publication

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“…Hence, the local velocity relative to the rotating blade (V rel ) and the angle of attack α = ϕ − γ can be computed. Then, the resulting force is obtained using Equation 6. It should be mentioned that in the model based on blade-element theory, the lift and drag coefficients are obtained from the tabulated airfoil data.…”

Section: B Wind-turbine Parameterizationmentioning

confidence: 99%

Influence of atmospheric stability on wind-turbine wakes: A large-eddy simulation study

2015

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In this study, large-eddy simulation is combined with a turbine model to investigate the influence of atmospheric thermal stability on wind-turbine wakes. The simulation results show that atmospheric stability has a significant effect on the spatial distribution of the mean velocity deficit and turbulence statistics in the wake region as well as the wake meandering characteristics downwind of the turbine. In particular, the enhanced turbulence level associated with positive buoyancy under the convective condition leads to a relatively larger flow entrainment and, thus, a faster wake recovery. For the particular cases considered in this study, the growth rate of the wake is about 2.4 times larger for the convective case than for the stable one. Consistent with this result, for a given distance downwind of the turbine, wake meandering is also stronger under the convective condition compared with the neutral and stable cases. It is also shown that, for all the stability cases, the growth rate of the wake and wake meandering in the vertical direction are smaller compared with the ones in the lateral direction. This is mainly related to the different turbulence levels of the incoming wind in the different directions, together with the anisotropy imposed by the presence of the ground. It is also found that the wake velocity deficit is well characterized by a modified version of a recently proposed analytical model that is based on mass and momentum conservation and the assumption of a self-similar Gaussian distribution of the velocity deficit. Specifically, using a two-dimensional elliptical (instead of axisymmetric) Gaussian distribution allows to account for the different lateral and vertical growth rates, particularly in the convective case where the non-axisymmetry of the wake is stronger. Detailed analysis of the resolved turbulent kinetic energy budget in the wake reveals also that thermal stratification considerably affects the magnitude and spatial distribution of the turbulence production, dissipation and transport terms.

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Section: B Wind-turbine Parameterizationmentioning

confidence: 99%

Influence of atmospheric stability on wind-turbine wakes: A large-eddy simulation study

2015

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“…Results illustrate the relevance of accounting for the atmospheric stratification, showing major differences in power output, wake recovery, and turbulence intensity within the wind farm. For example, Baker and Walker (1984) found that the wake deficit behind a 2.5-MW wind turbine decreased by 10 % in a flow with higher turbulence levels, indicating that in the CBL, the wake recovers more rapidly. These results are consistent with Iungo and Porté-Agel (2014) who used wind-lidar measurements.…”

Section: Introductionmentioning

confidence: 99%

Perturbations to the Spatial and Temporal Characteristics of the Diurnally-Varying Atmospheric Boundary Layer Due to an Extensive Wind Farm

Sharma

Parlange

Calaf

2016

Boundary-Layer Meteorol

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The effect of extensive terrestrial wind farms on the spatio-temporal structure of the diurnally-evolving atmospheric boundary layer is explored. High-resolution largeeddy simulations of a realistic diurnal cycle with an embedded wind farm are performed. Simulations are forced by a constant geostrophic velocity with time-varying surface boundary conditions derived from a selected period of the CASES-99 field campaign. Through analysis of the bulk statistics of the flow as a function of height and time, it is shown that extensive wind farms shift the inertial oscillations and the associated nocturnal low-level jet vertically upwards by approximately 200 m; cause a three times stronger stratification between the surface and the rotor-disk region, and as a consequence, delay the formation and growth of the convective boundary layer (CBL) by approximately 2 h. These perturbations are shown to have a direct impact on the potential power output of an extensive wind farm with the displacement of the low-level jet causing lower power output during the night as compared to the day. The low-power regime at night is shown to persist for almost 2 h beyond the morning transition due to the reduced growth of the CBL. It is shown that the wind farm induces a deeper entrainment region with greater entrainment fluxes. Finally, it is found that the diurnally-averaged effective roughness length for wind farms is much lower than the reference value computed theoretically for neutral conditions.

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“…Previous observational campaigns on turbines observe that downwind of a turbine there is a discernible wake region characterized by reduced horizontal wind speed and increased turbulence (Baker and Walker 1984;Hogström et al 1988;Magnusson and Smedman 1994;Käsler et al 2010;Trujillo et al 2011;Iungo et al 2013;Smalikho et al 2013). Chamorro and Porté-Agel (2010) used a wind tunnel to determine the effects of a model wind turbine on fluid flow.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, towers pose logistical problems due to the high measurement heights required to sample turbine wakes. Tethered kites and remotely piloted vehicles outfitted with onboard hotwire anemometers (Baker and Walker 1984;Hogström et al 1988;Frehlich et al 2003;Kocer et al 2011) observe details of turbulence within wakes at multiple locations on the scale of seconds to minutes without the flow disruption of towers. Remote sensing technology, including acoustic, microwave, and laser systems, have the ability to observe turbine wakes at multiple locations.…”

Section: Introductionmentioning

confidence: 99%

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

Rhodes

Lundquist

2013

Boundary-Layer Meteorol

104

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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.

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Wake measurements behind a large horizontal axis wind turbine generator

Cited by 42 publications

References 1 publication

Influence of atmospheric stability on wind-turbine wakes: A large-eddy simulation study

Influence of atmospheric stability on wind-turbine wakes: A large-eddy simulation study

Perturbations to the Spatial and Temporal Characteristics of the Diurnally-Varying Atmospheric Boundary Layer Due to an Extensive Wind Farm

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

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