An experimental and numerical study of the atmospheric stability impact on wind turbine wakes

In this paper, the impact of atmospheric stability on a wind turbine wake is studied experimentally and numerically. The experimental approach is based on full‐scale (nacelle based) pulsed lidar measurements of the wake flow field of a stall‐regulated 500 kW turbine at the DTU Wind Energy, Risø campus test site. Wake measurements are averaged within a mean wind speed bin of 1 m s^?1 and classified according to atmospheric stability using three different metrics: the Obukhov length, the Bulk–Richardson number and the Froude number. Three test cases are subsequently defined covering various atmospheric conditions. Simulations are carried out using large eddy simulation and actuator disk rotor modeling. The turbulence properties of the incoming wind are adapted to the thermal stratification using a newly developed spectral tensor model that includes buoyancy effects. Discrepancies are discussed, as basis for future model development and improvement. Finally, the impact of atmospheric stability on large‐scale and small‐scale wake flow characteristics is presently investigated. Copyright © 2015 John Wiley & Sons, Ltd.     

Upwind preview to a horizontal axis wind turbine: a wind tunnel and field‐scale study

Data collected at the Eolos wind research facility and in the Saint Anthony Falls Laboratory atmospheric boundary layer wind tunnel are used to study the impact of turbulent inflow conditions on the performance of a horizontal axis wind turbine on flat terrain. The Eolos test facility comprises a 2.5MW Clipper Liberty C96 wind turbine, a meteorological tower and a WindCube LiDAR wind profiler. A second set of experiments was completed using particle image velocimetry upwind and in a wake of a miniature turbine in the wind tunnel to complement LiDAR measurements near the Eolos turbine. Joint statistics, most notably temporal cross‐correlations between wind velocity at different heights and turbine performance, are presented and compared at both the laboratory and field scales. The work (i) confirms that the turbine exerts a blockage effect on the mean flow and (ii) suggests a key, specific elevation, above hub height, where the incoming velocity signal is statistically most relevant to turbine operation and control. Wind tunnel measurements confirm such indication and suggest that hub height velocity measurements are optimal for wind preview and/or as input for active control strategies in aligned turbine configurations. Copyright © 2015 John Wiley & Sons, Ltd.     

Observations of wind turbine wakes and surface roughness effects on wind flow variability

Wind data collected at nine meteorological towers at the Goodnoe Hills MOD-2 wind turbine site were analyzed to characterize the wind flow over the site both in the absence and presence of wind turbine wakes. Free-flow characteristics examined were the variability of wind speed and turbulence intensity across the site as a function of wind direction and surface roughness. The nine towers' data revealed that scattered areas of trees upwind of the site caused pronounced variations in the wind flow over the site. At two towers that were frequently downwind of an extensive grove of trees, up to 30% reductions in wind speed and a factor of 2 to 3 increase in turbulence intensity were measured. A substantial increase in the magnitude of the wind gusts, as well as a considerable decrease in the mean wind speed, was observed when a tower was downwind of the trees.Wind turbine wake characteristics analyzed included the average velocity deficits, wake turbulence, wake width, wake trajectory, vertical profile of the wake, and the stratification of wake properties as a function of the ambient wind speed and turbulence intensity. The wind turbine rotor disk spanned a height of 15 m to 107 m. The nine towers' data permitted a detailed analysis of the wake behavior at a height of 32 m at various downwind distances from 2 to 10 rotor diameters (D). The relationship between velocity deficit and downwind distance was surprisingly linear, with average maximum deficits ranging from 34% at 2 D to 7% at 10 D. Largest deficits were at low wind speeds and low turbulence intensities. Average wake widths were 2.8 D at a downwind distance of 10 D. Implications for turbine spacing are that, for a wind farm with a 10-D row separation, array losses would be significantly greater for a 2-D than a 3-D spacing because of incremental effects caused by overlapping wakes. Other interesting wake properties observed were the wake turbulence (which was greatest along the flanks of the wake). the vertical variation of deficits (which were greater below hub height than above), and the trajectory of the wake (which was essentially straight).     

Wind tunnel investigation on the effect of the turbine tower on wind turbines wake symmetry

In wind farms, the wake of the upstream turbines becomes the inflow for the downstream machines. Ideally, the turbine wake is a stable vortex system. In reality, because of factors like background turbulence, mean flow shear, and tower‐wake interaction, the wake velocity deficit is not symmetric and is displaced away from its mean position. The irregular velocity profile leads to a decreased efficiency and increased blade stress levels for the downstream turbines. The object of this work is the experimental investigation of the effect of the wind turbine tower on the symmetry and displacement of the wake velocity deficit induced by one and two in‐line model wind turbines (,D= 0.9 m). The results of the experiments, performed in the closed‐loop wind tunnel of the Norwegian University of Science and Technology in Trondheim (Norway), showed that the wake of the single turbine expanded more in the horizontal direction (side‐wall normal) than in the vertical (floor normal) direction and that the center of the wake vortex had a tendency to move toward the wind tunnel floor as it was advected downstream from the rotor. The wake of the turbine tandem showed a similar behavior, with a larger degree of non‐symmetry. The analysis of the cross‐stream velocity profiles revealed that the non‐symmetries were caused by a different cross‐stream momentum transport in the top‐tip and bottom‐tip region, induced by the turbine tower wake. In fact, when a second additional turbine tower, mirroring the original one, was installed above the turbine nacelle, the wake recovered its symmetric structure. Copyright © 2017 John Wiley & Sons, Ltd.     

A spinner‐integrated wind lidar for enhanced wind turbine control

A field test with a continuous wave wind lidar (ZephIR) installed in the rotating spinner of a wind turbine for unimpeded preview measurements of the upwind approaching wind conditions is described. The experimental setup with the wind lidar on the tip of the rotating spinner of a large 80 m rotor diameter, 59 m hub height 2.3 MW wind turbine (Vestas NM80), located at Tjæreborg Enge in western Denmark is presented. Preview wind data at two selected upwind measurement distances, acquired during two measurement periods of different wind speed and atmospheric stability conditions, are analyzed. The lidar‐measured speed, shear and direction of the wind field previewed in front of the turbine are compared with reference measurements from an adjacent met mast and also with the speed and direction measurements on top of the nacelle behind the rotor plane used by the wind turbine itself. Yaw alignment of the wind turbine based on the spinner lidar measurements is compared with wind direction measurements from both the nearby reference met mast and the turbine's own yaw alignment wind vane. Furthermore, the ability to detect vertical wind shear and vertical direction veer in the inflow, through the analysis of the spinner lidar data, is investigated. Finally, the potential for enhancing turbine control and performance based on wind lidar preview measurements in combination with feed‐forward enabled turbine controllers is discussed. Copyright © 2012 John Wiley & Sons, Ltd.     

Reynolds number dependence of turbulence statistics in the wake of wind turbines

A wind tunnel experiment has been performed to quantify the Reynolds number dependence of turbulence statistics in the wake of a model wind turbine. A wind turbine was placed in a boundary layer flow developed over a smooth surface under thermally neutral conditions. Experiments considered Reynolds numbers on the basis of the turbine rotor diameter and the velocity at hub height, ranging from Re = 1.66 × 10⁴ to 1.73 × 10⁵. Results suggest that main flow statistics (mean velocity, turbulence intensity, kinematic shear stress and velocity skewness) become independent of Reynolds number starting from Re ≈ 9.3 × 10⁴. In general, stronger Reynolds number dependence was observed in the near wake region where the flow is strongly affected by the aerodynamics of the wind turbine blades. In contrast, in the far wake region, where the boundary layer flow starts to modulate the dynamics of the wake, main statistics showed weak Reynolds dependence. These results will allow us to extrapolate wind tunnel and computational fluid dynamic simulations, which often are conducted at lower Reynolds numbers, to full‐scale conditions. In particular, these findings motivates us to improve existing parameterizations for wind turbine wakes (e.g. velocity deficit, wake expansion, turbulence intensity) under neutral conditions and the predictive capabilities of atmospheric large eddy simulation models. Copyright © 2011 John Wiley & Sons, Ltd.     

Characterizing the response of a wind turbine model under complex inflow conditions

A horizontal axis wind turbine model was tested in a closed‐circuit wind tunnel under various inflow conditions. Separate experiments placed the test turbine (i) in the wake of a three‐dimensional, sinusoidal hill, (ii) in the wake of another turbine and (iii) in the turbulent boundary layer, as a reference case. Simultaneous high‐frequency measurements of the turbine output voltage, rotor angular velocity along with streamwise and wall normal velocity components were collected at various locations through the turbine's miniature direct‐current (DC) generator, a high‐resolution laser tachometer and cross‐wire anemometer, respectively. Validation trials were conducted first in order to characterize the test turbine's output and response to the baseline turbulent boundary layer. Analysis was performed by comparing the cross‐wire anemometry measurements of the incoming flow with the turbine voltage output to investigate the unsteady rotor kinematics under different flow perturbations. Using spectral, auto‐correlation and cross‐correlation methods, it was found that the flow structures developing downwind of the hill leave a stronger signature on the fluctuations and spectrum of the rotor angular velocity, as compared with those flow structures filtered or deflected by placing a turbine upwind. In summary, we show that the effects on downwind turbines of complex terrain and multi‐turbine arrangements are consistent with the induced modifications by the hill or turbine on the large scale structures in the incoming flow. Copyright © 2014 John Wiley & Sons, Ltd.     

Validation of the dynamic wake meander model for loads and power production in the Egmond aan Zee wind farm

This paper investigates wake effects on load and power production by using the dynamic wake meander (DWM) model implemented in the aeroelastic code HAWC2. The instationary wind farm flow characteristics are modeled by treating the wind turbine wakes as passive tracers transported downstream using a meandering process driven by the low frequent cross‐wind turbulence components. The model complex is validated by comparing simulated and measured loads for the Dutch Egmond aan Zee wind farm consisting of 36 Vestas V90 turbine located outside the coast of the Netherlands. Loads and production are compared for two distinct wind directions—a free wind situation from the dominating southwest and a full wake situation from northwest, where the observed turbine is operating in wake from five turbines in a row with 7D spacing. The measurements have a very high quality, allowing for detailed comparison of both fatigue and min–mean–max loads for blade root flap, tower yaw and tower bottom bending moments, respectively. Since the observed turbine is located deep inside a row of turbines, a new method on how to handle multiple wakes interaction is proposed. The agreement between measurements and simulations is excellent regarding power production in both free and wake sector, and a very good agreement is seen for the load comparisons too. This enables the conclusion that wake meandering, caused by large scale ambient turbulence, is indeed an important contribution to wake loading in wind farms. Copyright © 2012 John Wiley & Sons, Ltd.     

Analysis of light detection and ranging wind speed measurements for wind turbine control

Light detection and ranging (LIDAR) systems are able to measure the speed of incoming wind before it reaches a wind turbine rotor. These preview wind measurements can be used in feedforward control systems designed to reduce turbine structural loads. However, the degree to which such preview‐based control techniques can reduce loads by reacting to turbulence depends on how accurately the incoming wind field can be measured. This study examines the accuracy of different measurement scenarios that rely on coherent continuous‐wave or pulsed Doppler LIDAR systems, in terms of root‐mean‐square measurement error, to determine their applicability to feedforward control. In particular, the impacts of measurement range, angular offset of the LIDAR beam from the wind direction, and measurement noise are studied for various wind conditions. A realistic simulation case involving a scanning LIDAR unit mounted in the spinner of a MW‐scale wind turbine is studied in depth, with emphasis on preview distances that provide minimum measurement error for a specific scan radius. Measurement error is analyzed for LIDAR‐based estimates of point wind speeds at the rotor as well as spanwise averaged blade effective wind speeds. The impact of turbulence structures with high coherent turbulent kinetic energy on measurement error is discussed as well. Copyright © 2013 John Wiley & Sons, Ltd.     

Another engineering wake model variant for horizontal axis wind turbines

An engineering model is presented for predicting the performance of a single turbine located in an incoming turbulent, sheared, wind velocity field. The approach used is a variant of the well‐known and documented Ainslie eddy viscosity approach as also employed in the Direct Wake Meandering model. It incorporates a new and simple means of representing the rotor's loading profile, initializing the calculations, simplifying the wakes' shear layer mixing model and accounting for wind shear effects. Additionally, two figures of merit are employed for assessing the reliability of all data used and predictions provided. The first, a wake momentum‐flux/thrust parameter, is used for quantitatively assessing the accuracy and utility of both measured and/or computational wake data. The second, a rotor swept area wake‐averaged velocity, is employed as a single quantitative measure of a turbine's impact on its downstream neighbor. Through detailed comparisons with three independent state‐of‐the‐art Computational Fluid Dynamic generated datasets and a field‐measured dataset, the current model is shown to be accurate for turbine rated power levels from 100 kW to 2.3 MW, wind speeds of 6 to 22 m s^?1 (corresponding to turbine thrust coefficient levels of 0.14 to 0.8) and free‐stream turbulence levels from 0% to 16%. Copyright © 2015 John Wiley & Sons, Ltd.     

Wake meandering effects on floating wind turbines

As more floating farms are being developed, the wake interaction between multiple floating wind turbines (FWTs) is becoming increasingly relevant. FWTs have long natural periods in certain degrees of freedom, and the large‐scale movement of the wake, known as wake meandering, occurs at very low frequencies. In this study, we use FAST.Farm to simulate a two‐turbine case with three different FWT concepts: a semisubmersible (semi), a spar, and a tension leg platform (TLP), separated by eight rotor diameters in the wind direction. Since wake meandering varies depending on the environmental conditions, three different wind speeds (for all three concepts) as well as two different turbulence levels (for the semi) are considered. For the below‐rated wind speed, when wake meandering was most extreme, yaw motion standard deviations for the downstream semi were approximately 40% greater in high turbulence and over 100% greater in low turbulence when compared with the upstream semi. The low yaw natural frequency (0.01 Hz) of the semi was excited by meandering, while quasi‐static responses resulted in approximately 20% increases in yaw motion standard deviations for the spar and TLP. Differences in fatigue loading between the upstream and downstream turbines for the mooring line tension and tower base fore‐aft bending moment mostly depended on the velocity deficit and were not directly affected by meandering. However, wake meandering did affect fatigue loading related to the tower top yaw moment and the blade root out‐of‐plane moment.     

A pragmatic approach to wind farm simulations using the dynamic wake meandering model

This paper presents a computationally efficient method for using the dynamic wake meandering model to conduct simulations of wind farm power production. The method is based on creating a database, which contains the time and rotor‐averaged wake effect at any point downstream of a wake‐emitting turbine operating in arbitrary ambient conditions and at an arbitrary degree of wake influence. This database is later used as a look‐up table at runtime to estimate the operating conditions at all turbines in the wind farm, thus eliminating the need to run the dynamic wake meandering model at runtime. By using the proposed method, the time required to conduct wind farm simulations is reduced by three orders of magnitude compared with running the standalone dynamic wake meandering model at runtime. As a result, the wind farm production dynamics for a farm of 100 turbines at 10,000 different sets of ambient conditions run on a normal laptop in 1 h. The method is validated against full scale measurements from the Smøla and OWEZ wind farms, and fair agreement is achieved. Copyright © 2014 John Wiley & Sons, Ltd.     

Performance and wake of a Savonius vertical‐axis wind turbine under different incoming conditions

In this study, the performance, drag, and horizontal midplane wake characteristics of a vertical‐axis Savonius wind turbine are investigated experimentally. The turbine is drag driven and has a helical configuration, with the top rotated 180° relative to the bottom. Both performance and wake measurements were conducted in four different inflow conditions, using Reynolds numbers of Re_D≈1.6×10⁵ and Re_D≈2.7×10⁵ and turbulence intensities of 0.6% and 5.7%. The efficiency of the turbine was found to be highly dependent on the Reynolds number of the incoming flow. In the high Reynolds number flow case, the efficiency was shown to be considerably higher, compared with the lower Reynolds number case. Increasing the incoming turbulence intensity was found to mitigate the Reynolds number effects. The drag of the turbine was shown to be independent of the turbine's rotational speed over the range tested, and it was slightly lower when the inflow turbulence was increased. The wake was captured for the described inflow conditions in both optimal and suboptimal operating conditions by varying the rotational speed of the turbine. The wake was found to be asymmetrical and deflected to the side where the blade moves opposite to the wind. The largest region of high turbulent kinetic energy was on the side where the blade is moving in the same direction as the wind. Based on the findings from the wake measurements, some recommendations on where to place supplementary turbines are made.     

LiDAR measurements for an onshore wind farm: Wake variability for different incoming wind speeds and atmospheric stability regimes

Wind measurements were performed with the UTD mobile LiDAR station for an onshore wind farm located in Texas with the aim of characterizing evolution of wind‐turbine wakes for different hub‐height wind speeds and regimes of the static atmospheric stability. The wind velocity field was measured by means of a scanning Doppler wind LiDAR, while atmospheric boundary layer and turbine parameters were monitored through a met‐tower and SCADA, respectively. The wake measurements are clustered and their ensemble statistics retrieved as functions of the hub‐height wind speed and the atmospheric stability regime, which is characterized either with the Bulk Richardson number or wind turbulence intensity at hub height. The cluster analysis of the LiDAR measurements has singled out that the turbine thrust coefficient is the main parameter driving the variability of the velocity deficit in the near wake. In contrast, atmospheric stability has negligible influence on the near‐wake velocity field, while it affects noticeably the far‐wake evolution and recovery. A secondary effect on wake‐recovery rate is observed as a function of the rotor thrust coefficient. For higher thrust coefficients, the enhanced wake‐generated turbulence fosters wake recovery. A semi‐empirical model is formulated to predict the maximum wake velocity deficit as a function of the downstream distance using the rotor thrust coefficient and the incoming turbulence intensity at hub height as input. The cluster analysis of the LiDAR measurements and the ensemble statistics calculated through the Barnes scheme have enabled to generate a valuable dataset for development and assessment of wind farm models.     

Parabolic RANS solver for low‐computational‐cost simulations of wind turbine wakes

A numerical framework for simulations of wake interactions associated with a wind turbine column is presented. A Reynolds‐averaged Navier‐Stokes (RANS) solver is developed for axisymmetric wake flows using parabolic and boundary‐layer approximations to reduce computational cost while capturing the essential wake physics. Turbulence effects on downstream evolution of the time‐averaged wake velocity field are taken into account through Boussinesq hypothesis and a mixing length model, which is only a function of the streamwise location. The calibration of the turbulence closure model is performed through wake turbulence statistics obtained from large‐eddy simulations of wind turbine wakes. This strategy ensures capturing the proper wake mixing level for a given incoming turbulence and turbine operating condition and, thus, accurately estimating the wake velocity field. The power capture from turbines is mimicked as a forcing in the RANS equations through the actuator disk model with rotation. The RANS simulations of the wake velocity field associated with an isolated 5‐MW NREL wind turbine operating with different tip speed ratios and turbulence intensity of the incoming wind agree well with the analogous velocity data obtained through high‐fidelity large‐eddy simulations. Furthermore, different cases of columns of wind turbines operating with different tip speed ratios and downstream spacing are also simulated with great accuracy. Therefore, the proposed RANS solver is a powerful tool for simulations of wind turbine wakes tailored for optimization problems, where a good trade‐off between accuracy and low‐computational cost is desirable.     

On atmospheric stability in the dynamic wake meandering model

The present study investigates a new approach for capturing the effects of atmospheric stability on wind turbine wake evolution and wake meandering by using the dynamic wake meandering model. The most notable impact of atmospheric stability on the wind is the changes in length and velocity scales of the atmospheric turbulence. The length and velocity scales in the turbulence are largely responsible for the way in which wind turbine wakes meander as they convect downstream. The hypothesis of the present work is that appropriate turbulence scales can be extracted from the oncoming atmospheric turbulence spectra and applied to the dynamic wake meandering model to capture the correct wake meandering behaviour. The ambient turbulence in all stability classes is generated using the Mann turbulence model, where the effects of non‐neutral atmospheric stability are approximated by the selection of input parameters. In order to isolate the effect of atmospheric stability, simulations of neutral and unstable atmospheric boundary layers using large‐eddy simulation are performed at the same streamwise turbulence intensity level. The turbulence intensity is kept constant by calibrating the surface roughness in the computational domain. The changes in the turbulent length scales due to the various atmospheric stability states impact the wake meandering characteristics and thus the power generation by the individual turbines. The proposed method is compared with results from both large‐eddy simulation coupled with an actuator line model and field measurements, where generally good agreement is found with respect to the velocity, turbulence intensity and power predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

Light detection and ranging measurements of wake dynamics. Part II: two‐dimensional scanning

A nacelle‐mounted lidar system pointing downstream has been used to measure wind turbine wake dynamics. The new measurement and data analysis techniques allow estimation of quasi‐instantaneous wind fields in planes perpendicular to the rotor axis. A newly developed wake tracking procedure delivers the instantaneous transversal wake position which is quantitatively compared with the prediction of the Dynamic Wake Meandering model. The results, shown for two 10‐min time series, suggest that the conjecture of the wake behaving as a passive tracer is a fair approximation; this corroborates and expands the results of one‐dimensional measurements already presented in the first part of this paper. Consequently, it is now possible to separate the deterministic and turbulent parts of the wake wind field, thus enabling capturing the wake in the meandering frame of reference. The results correspond, qualitatively and to some extent quantitatively, to the expectations from CFD simulations which are compared in the paper. Copyright © 2010 John Wiley & Sons, Ltd.     

Synthetic atmospheric turbulence and wind shear in large eddy simulations of wind turbine wakes

A method of generating a synthetic ambient wind field in neutral atmosphere is described and verified for modelling the effect of wind shear and turbulence on a wind turbine wake using the flow solver EllipSys3D. The method uses distributed volume forces to represent turbulent fluctuations, superimposed on top of a mean deterministic shear layer consistent with that used in the IEC standard for wind turbine load calculations. First, the method is evaluated by running a series of large‐eddy simulations in an empty domain, where the imposed turbulence and wind shear is allowed to reach a fully developed stage in the domain. The performance of the method is verified by comparing the turbulence intensity and spectral distribution of the turbulent energy to the spectral distribution of turbulence generated by the IEC suggested Mann model. Second, the synthetic turbulence and wind shear is used as input for simulations with a wind turbine, represented by an actuator line model, to evaluate the development of turbulence in a wind turbine wake. The resulting turbulence intensity and spectral distribution, as well as the meandering of the wake, are compared to field data. Overall, the performance of the synthetic methods is found to be adequate to model atmospheric turbulence, and the wake flow results of the model are in good agreement with field data. An investigation is also carried out to estimate the wake transport velocity, used to model wake meandering in lower‐order models. The conclusion is that the appropriate transport velocity of the wake lies somewhere between the centre velocity of the wake deficit and the free stream velocity. Copyright © 2013 John Wiley & Sons, Ltd.     

Near wake flow analysis of a vertical axis wind turbine by stereoscopic particle image velocimetry

The development of the near wake of a vertical axis wind turbine is investigated by stereoscopic particle image velocimetry. The experiments are conducted in an open-jet wind tunnel on an H-shaped rotor, operated at a tip speed ratio of 4.5 and at an average chord-based Reynolds number of 1.7 × 10⁵. Phase-locked measurements are acquired at the turbine mid span in order to study the horizontal wake dynamics at the symmetry plane. Results show the evolution of the vorticity shed by the blade, how it organizes in large scale vortical structures at the edges of the wake and the resulting asymmetric induction field in the wake. The evolution of the blade tip vortices and the 3D wake geometry are detailed by a second set of measurements acquired at several vertical planes aligned with the free stream. The dynamics of the system of tip vortices, their vertical motion and interactions are discussed and related to the geometry and the recovery of the wind turbine wake. The experimental data are made publicly available for research purposes.