Wake Characteristics Of Wind Turbine Research Articles

Effect of the tip speed ratio on the wake characteristics of wind turbines using LBM‐LES

AbstractIn this paper, the wake characteristics of Zell 2000 wind turbine under different tip velocity ratios are studied by using the lattice Boltzmann method and large eddy simulation. The adaptive mesh refinement method is performed to capture the fine flow structure and wake characteristics development. In this paper, we mainly focus on the effect of the tip speed ratio on the flow structure and unsteady characteristics of wind turbine wake. The three‐dimensional flow vorticity structures, the section vorticity diagram, the pressure fluctuation of wake and the lift coefficient of wind turbine wake are utilized to explore the effect of the tip speed ratio on the unsteady physics mechanism of wind turbine wake. With the increase of the tip speed ratio, the distance between two adjacent vortex rings along the axial direction gradually decreases, as the position of the broken vortex circles gradually approaches the center of the blade, separated vortexes are rapidly generated, and the coherent structure appears closer to the wind turbine. A relationship is established between the tip speed ratios and the positions of the broken vortex circles. It is further found that the dominant frequency amplitude gradually increases with the increase of tip speed ratio and the pressure amplitude spectra of vortex increases with the decrease of the distance between the wake and the center of the blade axis. The above series of studies can provide significant physical insight into deep understanding the influence of the tip speed ratio on the wake characteristics of wind turbines.

A reduced order modeling-based machine learning approach for wind turbine wake flow estimation from sparse sensor measurements

A comprehensive understanding of wind turbine wake characteristics is vital, particularly in the context of expanding large offshore wind farms. Existing wake measurement techniques provide only spatially sparse wake measurement data, limiting their utility in precise wind turbine design and control. This paper introduces a data-driven approach that combines proper orthogonal decomposition (POD) with machine learning (ML) techniques, designing a Reduced Order Modeling-based Wake Flow Estimation (ROM-WFE) framework. This framework establishes a nonlinear mapping between sensor measurements and low-dimensional POD coefficients. Two distinct sensor placements, wall-mounted and wake-mounted, are investigated for real measurement scenarios. The results highlight the effectiveness of the proposed wake flow estimation method in reconstructing a complete flow field from exceptionally sparse sensor data, with both wall-mounted and wake-mounted strategies, exhibiting promising results with maximum relative errors of 6.37% and 4.51%, respectively. From the reliability assessments considering various configurations of POD modes and sensor numbers, the ROM-WFE framework demonstrates its capability to estimate wake flow effectively, offering a cost-effective tool for practical applications. Furthermore, the framework maintains accuracy even with high-noise and low-frequency data, demonstrating robustness and generalization. This method significantly contributes to wind turbine wake prediction controller design, promising accurate and robust wake flow field estimation, potentially revolutionizing active wake control and enhancing wind farm operational efficiency.

Aerodynamic performance analysis of a floating wind turbine with coupled blade rotation and surge motion

The unsteady aerodynamic characteristics and interference effects of a floating wind turbine are significantly influenced by the six-degree-of-freedom (6DoF) motions. In this paper, the computational fluid dynamics (CFD) method using the overset grid technique and the improved delayed detached eddy simulation (IDDES) model was adopted to investigate the effects of harmonic enforced surge motions on the aerodynamic performance and wake characteristics of wind turbines. The aerodynamic load coefficients including the constant term, damping coefficients (surge velocity-induced), and additional mass coefficients (surge acceleration-induced), were fitted by using the least squares method at different surge frequencies and surge amplitudes. The blade pressure distributions and wake characteristics were analysed in detail. The Ω ~ R of the third-generation vortex identification method was applied to visualize vortex evolution. The numerical results are evaluated against the data obtained by wind tunnel experiments, indicating an acceptable relative error of 3.45 % for the power coefficient, C p , at the rated tip speed ratio (TSR). The higher frequency and greater amplitude surge motions lead to more dramatic fluctuations for the power coefficient than the axial load coefficient. The neglect of the additional mass coefficient only results in an acceptable error. Furthermore, the mean damping coefficient is on average approximately 3.5 times the mean constant term coefficient for C p , approximately 1.5 times for C z . In terms of the blade pressure distributions and wake characteristics, a higher comprehensive induced velocity, V c , is induced to expand the wider high-pressure area and shrink the low-pressure area at the pressure surface. Meanwhile, toroidal vortex ropes were induced by surge motion. Besides, the surge motion at high frequency and greater amplitude positively impacts enhancing wake deficit recovery.

Influence of turbulent coherent structures on the performance and wake of a wind turbine

Wind energy in the atmospheric boundary layer serves as the primary source for energy absorption and structural load on wind turbines. However, the impact of turbulent coherent structures on the aerodynamic performance and wake characteristics of wind turbines has not been comprehensively evaluated. In this study, the proper orthogonal decomposition (POD) method is employed to assess the influence of turbulent coherent structures of varying scales on the aerodynamic performance and wake characteristics of wind turbines in the neutral atmospheric boundary layer. The results show that turbulent coherent structures are the main factor that determines the wind velocity fluctuation, aerodynamic performance and wake characteristics of wind turbine in the atmospheric boundary layer. When considering the 13th or lower order POD mode, the wind velocity fluctuation increases with the increase of energy content (more POD modes) of the turbulent coherent structures. When considering the first 19 POD modes, the dynamic loads and power of wind turbine fluctuate with high frequencies, the thrust fluctuates in an amplitude range between 2.4 % and 13.9 % around the mean value, and the power fluctuates from 4.5 % to 28.6 % of the mean value. When considering the first 40 POD modes, the average power generation of the wind turbine increases by 26 % compared to the case with no turbulent structures considered. The study of turbine wake shows that turbulent coherent structures can expand the wind turbine wake approximately to a width of 2.5D and a height of 3D (D is the diameter of the wind turbine), offset the wake approximately to 2D, and move forward the position of the wake vortex beginning to dissipation approximately to 7D behind the wind turbine. In addition, turbulent coherent structures can accelerate the wake velocity recovery by increasing the momentum exchange between the atmospheric boundary layer and wind turbine wake.

Numerical investigation of wind turbine wake characteristics using a coupled CFD-CSD method considering blade and tower flexibility

With the increase in wind turbine sizes, careful investigation into wind turbine wake effect is crucial for operational safety. This study proposes a two-way fluid-structure interaction (FSI) model combining large eddy simulation (LES) and computational structural dynamics (CSD) to investigate wind turbine wake characteristics. Examining the effect of blade and tower flexibility and inflow conditions, the study reveals negligible influence of blade and tower flexibility on mean velocity deficit under both inflow conditions. However, they significantly impact turbulence intensity under uniform inflow condition. The tower motion produces a maximum increase of approximately 45% while the blade flap-wise motion has the second-largest impact, increasing the maximum turbulence intensity by approximately 33% when compared with the fully rigid case. Additionally, the study quantitatively examines wake vortex inclination based on the inclination angle of the second-circle wake vortex structure. Finally, the study concludes that the streamline near the blade tip follows the blade surface, while the flow separation occurs near the blade root, generating two vortices on the suction side. As the tower motion is considered, the larger vortex exhibits alternate vortex shedding while the smaller vortex remains stable in both uniform and turbulent winds.

Optimal combined wake and active power control of large‐scale wind farm considering available power

AbstractThe high‐order nonlinear complex characteristics of traditional static wake model (SWM) restrict the fast optimization of wake effect. Therefore, this paper introduces a dynamic wake model (DWM) to describe the time‐varying wake characteristics of wind turbines (WTs) with low computational cost. The traditional SWM is linearized to derive the wake wind speed sensitivity coefficients, which represents the sensitivity of wake wind speed deficit with respect to the active power reference. Considering the natural propagation characteristics of wake effect, a wake delay function is added to realize the future wind speed prediction of different locations of the wind farm. And a joint control strategy of wake and active power based on model predictive control (MPC) is proposed to optimize the power contribution of each WT to minimize wake effects, and maximize total available power. Thus, the increased available power is able to satisfy the power demand from Transmission System Operator (TSO) for ancillary services and enhance power support capability. The control performance of the proposed control strategy is evaluated by simulations under constant and varying incoming wind speed.

Super-resolution reconstruction framework of wind turbine wake: Design and application

Complete and clear global wind turbine wake data is very important for the study of wind turbine wake characteristics in increasingly large offshore wind farms. Existing wake measurement techniques can only obtain local high-resolution (HR) wake flow field, or sacrifice accuracy to obtain larger measurement area, which is insufficient for accurate modeling of wake effect. To overcome this challenge, this paper proposes a novel super-resolution (SR) reconstruction approach that can reconstruct the global HR wake flow field from low-resolution (LR) wake flow field measurement data effectively. The proposed approach utilizes a deep learning framework called down-sampled skip-connection and multi-scale network. The performance of the SR approach is evaluated by enhancing the resolution of the wake flow field at different scale factors, and its potential application is demonstrated by assessing the prediction accuracy of three typical wake models. The results indicate that the resolution of the global wind turbine wake can be improved by 16 times using the SR model, and the reconstructed global SR wake flow fields are consistent with the ground truth in terms of both the spatial distribution and the temporal variation. By comparing the prediction results of three different wake models with the LR or SR wake data, it is shown that the SR flow reconstruction method can be applied to more accurately evaluate the wake model prediction performance, which has the potential to improve wake models. Overall, this study presents an innovative solution to the problem of incomplete and inaccurate wake flow measurement in the wind energy industry, which could reduce the workload of experimental measurements and the cost burden of accurate measuring equipment for engineering applications.

Proposal of fully-coupled actuated disk model for wind turbine operation modeling in turbulent flow field due to complex topography

The wind speed and direction of flow fields in the time and space domains are complicated owing to topographic relief, and it is not yet known how time-varying incoming wind speed and automatic windward effect interact with the wake characteristics of wind turbines. To address this, semi-coupled ADM-SR model (SR model) and a fully coupled ADM-DR model (DR model) are proposed in this study. The wakes of wind turbines located at various locations on the slant ridge were then compared. The wake velocity deficit of the wind turbines using the SR and DR models were found to be up to 40% and 20% upstream of the ridge, respectively, with large variations. Downstream, the wind turbine wakes of both models were similar. The DR model with the automatic windward orientation caused the wind turbine actuator disk to rotate by 9.24° and 7.40° perpendicular to the tangential direction of the streamline, and the accuracy of the control procedure was verified. Furthermore, the lower the turbulence intensity, the greater the difference between the predictions of the two models, and the power prediction value of the DR model was approximately 80% higher than that of the SR model.

Experimental investigation on wake characteristics of wind turbine and a new two-dimensional wake model

Wind tunnel experiments are performed to investigate the wake characteristics of a model wind turbine using Particle Image Velocimetry (PIV) and Hot-wire velocimetry. Results show that the velocity deficit at the hub height is the largest, and the stratification of the velocity shear layer at the blade tip is obvious. The instantaneous turbulence kinetic energy (TKE) level is much larger than the mean TKE, especially downstream of the blade tip. In the x/dT=4 position of the wake region, the mean TKE increased by two times due to the blade tip disturbance. The Reynolds stresses also increase and the instantaneous value is the highest along the blade’s tip. A thin vortex band appears at the root and tip of the blade, the vortex core expands and diffuses with the development of the wake along the downstream direction. The two-dimensional distributions of velocity spectra fΦu reveal that the velocity fluctuation at x/dT=2 location is small and that at x/dT=4 position is the largest. Based on Jensen’s wake model, a new theoretical wake model is proposed to predict the velocity distribution in the wind turbine wake. The calculated results of the wake model are in good agreement with the experimental data.

Experimental study of turbulence intensity on the wake characteristics of a horizontal-axis wind turbine

ABSTRACT A time-resolved particle image velocity (TR-PIV) system was used to test the wake flow of a small horizontal-axis wind turbine at tip speed ratios (TSRs) in the range of 4–6 under uniform inflow and turbulent inflow in order to study the impact of turbulence intensity on wind turbine wake characteristics. The impact of incoming turbulence on the wake structure of a wind turbine and its mechanism was examined by comparing and analyzing the turbulence properties of the wake flow, including velocity field, vortex structure, additional turbulence intensity, and energy distribution coefficient. It was found that tip vortex structure remained intact in the range of 9 R under uniform inflow, and the longitudinal distribution of turbulent intensity had double peaks, indicating that it was in the near wake zone. Under turbulent inflow, the three vortex systems could not be distinguished at the position of 5 R, and the longitudinal distribution of turbulent intensity did not have peaks, the wake vortex system was broken and the wake transitioned to the far wake zone. With the increase in the turbulence intensity and tip speed ratio, the contribution of the longitudinal component of turbulence intensity to the turbulent kinetic energy increases, which is also the reason for the rapid wake recovery. Additionally, the recovery of the wake velocity was sped up in the range of 3 R and gradually decreased after 3 R.

Thrust-matched optimization of blades for the reduced-scale wind tunnel tests of wind turbine wakes

This study proposes a thrust-matched optimization methodology of wind turbine blades to accurately reproduce the wind turbine wake characteristics in the reduced-scale wind tunnel experiment. The scaled models with scale ratio of 1:250 for two wind turbines (5 MW and 2 MW) from the industrial community are produced by the proposed optimization methodology for validation purposes. In addition, the wake characteristics of the scaled wind turbine model are experimentally measured and discussed against the analytical wake model. The results show that the wake from the experiment is consistent with that predicted by the wake model, verifying the rationality and feasibility of the proposed optimization method. Also, the effects of upstream turbulence on the wind turbine wakes and the declining wake center in the vertical direction could be satisfactorily reproduced and revealed in the wind tunnel tests.

A study on measuring wind turbine wake based on UAV anemometry system

Unmanned aerial vehicle (UAV) wind measurement is a newly developed wind measurement method that can improve the efficiency of conventional wind measurements. A method for measuring the wake characteristics of wind turbines based on UAV is proposed. The research results show that when the downstream distance was 1D, the wake wind speed and turbulence intensity at the hub height are about 60–70% and 130–150% of the incoming flow, respectively. When the downstream distance was 10D, the wake wind speed and turbulence intensity at the hub height gradually recovered to about 90% and 110% of the incoming flow, respectively, and the wake width in the area was about 2.5 times the diameter of the turbine. The wind speed measured by UAV was in good agreement with that predicted by the AV model and the 3DJG model, indicating that the Gaussian-shape curve could better describe the wake wind speed distribution. The UAV anemometry system provides a new research approach for wind turbine wake wind field measurement and the assessment of in-service wind farm resources. Moreover, the results from this study provide a reference for the determination of wind turbine wake, generation power prediction, and structure design.

Large eddy simulation for the effects of ground roughness and atmospheric stratification on the wake characteristics of wind turbines mounted on complex terrains

The wake characteristics of wind turbine mounted on complex terrains are of great significance in wind energy utilization. The ground roughness and atmospheric stratification are two key factors for this issue and their coupling effect has not been fully studied before. In this research, the wake distributions of wind turbine mounted on two typical complex terrains and a real complex terrain are investigated using large eddy simulations and actuator disk model with rotation. The ground roughness and atmospheric stratification are simulated by adding source term in the governing equations of fluid dynamics to generated temperature gradient and vegetation canopy. It is found that the effects of ground roughness and atmospheric stratification on the wake of wind turbine are superimposed or counteracted depending on the shape of complex terrain. The presence of atmospheric stratification reduces the power of wind turbine drastically by more than 40% and the rough ground causes a small decrease in the power of wind turbine on typical complex terrains. For the multiple wind turbines on a real terrain with rough ground, the influence of atmospheric stratification on the wake characteristics and power production of each wind turbine strongly affected by the micrositing of wind turbines. The usual practice in industry of multiplying the oncoming wind profile by the turbine power curve overestimates the power production of wind turbines on complex terrains with atmospheric stratification by up to 670% compared with the numerical results.

Experimental Investigation on Wake Characteristics of Wind Turbine and a New Two-Dimensional Wake Model

Experimental Investigation on Wake Characteristics of Wind Turbine and a New Two-Dimensional Wake Model

Effects of continuously changing inlet wind direction on near-to-far wake characteristics behind wind turbines over flat terrain

The wake characteristics of a utility-scale wind turbine under realistic atmospheric boundary layer conditions are affected by the continuously changing wind direction arriving at the wind turbine. In the present study, the effects of continuous changes in the incoming wind direction were studied for a wind turbine on flat terrain, with the objective of understanding the wake characteristics of the wind turbine. Thus, understanding the effects of continuously changing incoming wind direction on the wake characteristics of wind turbines over flat terrain is important in the design of wind farm layouts, including in the design of offshore wind power plants. For this purpose, a computational fluid dynamics (CFD) approach using large-eddy simulations (LES) was adopted in the present study. An in-house LES-solver based on the actuator line (AL) aerodynamics technique was constructed in order to successfully capture the wake structure behind the wind turbine. First, experimental investigations on both a blade-only wind turbine scale model and a full 3D wind turbine scale model (isolated wind turbine) were conducted for a fixed inlet wind condition, the latter including the nacelle and the tower. Through a detailed comparison of the wind tunnel experimental and numerical results, the prediction accuracy of the in-house LES-solver was verified and validated for fixed inlet wind conditions. On the basis of the validation results obtained, and using the full 3D wind turbine scale model, the effects of the continuously changing inlet wind conditions on the wake characteristics in the near- and far-wake regions were numerically investigated. In addition, the effects of the wind turbine nacelle and tower on the wake characteristics were also investigated. The numerical results show that the most significant impact of the effects of the continuously changing wind direction was the rapid recovery of the mean velocity deficits in the wind turbine wake region. Further, at the x = 10D position (D is the rotor diameter) downstream of the wind turbine, the non-dimensional streamwise mean velocity was 0.93, which nearly matches the approaching flow speed, under an optimal tip speed ratio of 4.0, compared to the fixed wind direction scenario.

Effects of Inflow Shear on Wake Characteristics of Wind-Turbines over Flat Terrain

The scope of the present study was to understand the wake characteristics of wind-turbines under various inflow shears. First, in order to verify the prediction accuracy of the in-house large-eddy simulation (LES) solver, called RIAM-COMPACT, based on a Cartesian staggered grid, we conducted a wind-tunnel experiment using a wind-turbine scale model and compared the numerical and experimental results. The total number of grid points in the computational domain was about 235 million. Parallel computation based on a hybrid LES/actuator line (AL) model approach was performed with a new SX-Aurora TSUBASA vector supercomputer. The comparison between wind-tunnel experiment and high-resolution LES results showed that the AL model implemented in the in-house LES solver in this study could accurately reproduce both performances of the wind-turbine scale model and flow characteristics in the wake region. Next, with the LES solver developed in-house, flow past the entire wind-turbine, including the nacelle and the tower, was simulated for a tip-speed ratio (TSR) of 4, the optimal TSR. Three types of inflow shear, N = 4, N = 10, and uniform flow, were set at the inflow boundary. In these calculations, the calculation domain in the streamwise direction was very long, 30.0 D (D being the wind-turbine rotor diameter) from the center of the wind-turbine hub. Long-term integration of t = 0 to 400 R/Uin was performed. Various turbulence statistics were calculated at t = 200 to 400 R/Uin. Here, R is the wind-turbine rotor radius, and Uin is the wind speed at the hub-center height. On the basis of the obtained results, we numerically investigated the effects of inflow shear on the wake characteristics of wind-turbines over a flat terrain. Focusing on the center of the wind-turbine hub, all results showed almost the same behavior regardless of the difference in the three types of inflow shear.

Effect of different atmospheric boundary layers on the wake characteristics of NREL phase VI wind turbine

Abstract In this study, the interaction of horizontal axis wind turbine (HAWT) with neutrally stratified atmospheric boundary layer (ABL) and its wake characteristics are investigated. Important wake characteristics of wind turbine such as velocity deficit and turbulence level are analyzed. For this purpose, Unsteady Reynolds-Averaged Navier-Stokes (URANS) using k-e turbulence closure models are performed using commercial Computational Fluid Dynamics (CFD) software called ANSYS FLUENT. Full rotor CFD simulations of the NREL Phase VI wind turbine by virtually placing on a flat surface with different aerodynamic roughness lengths are performed. Discussions on effective modelling of horizontal homogeneity for the undisturbed ABL is included. The influence of inflow ABL's turbulence level in the wake velocity recovery and the ground effect on the wake turbulence intensity (TI) is analyzed. In addition, comparison of rotor aerodynamics of wind turbine in different terrains is performed using pressure coefficient distributions. Finally, the necessity of inclusion of TI recovery in addition to velocity recovery in the wake for the wind farm alignment is discussed.

An experimental investigation on the aeromechanics and wake interferences of wind turbines sited over complex terrain

An experimental study was conducted to investigate the aeromechanics and wake interferences of wind turbines sited on two-dimensional hills with different slopes. First, detailed flow field measurements were correlated with dynamic wind load measurements to reveal the effect of topography on the performance of an individual wind turbine sited at different locations on hilly terrains. Compared to a flat surface, wind turbines sited on a hilltop not only generate more power due to the speed-up effect but also experience reduced fatigue loads due to the decreased level of the turbulence on a hilltop. It was also found that a wind turbine located downstream of a steep hill has a greater likelihood of experiencing extreme wind loads compared to one on a gentle hill. Second, wind turbine wake characteristics and their effects on the dynamic wind loads of downstream wind turbines were also assessed. The effect of an upstream turbine wake on the wind turbine sited on a hilltop was found to be much less significant compared to a wind turbine on a flat surface. In addition, while the wake of an upstream turbine sited on hilltop has a significant influence on the dynamic wind loads of a downstream turbine sited behind a gentle hill, the effect of an upstream turbine wake on a downstream turbine placed behind a steep hill was found to be almost negligible. The quantitative measurement results of the present study not only provide a database for the validation of wake models and numerical simulations but can also be used to optimize the layout of wind turbines sited on complex terrain for higher power yield and better durability.

Offshore Wind Turbine Wake characteristics using Scanning Doppler Lidar

Within an offshore wind park, wind flow characteristics are quite complex and govern both the energy production and the structural wind turbine response. An experimental study focussed on assessing the spatial variability of winds near the German offshore wind energy platform FINO1 was conducted using multiple remote sensing devices. This study focuses on measuring the wind turbine wake characteristics, such as velocity deficit, the extent (length and width) of the wake and wake meandering under various atmospheric conditions using the data collected from a single scanning Doppler Lidar for several months in 2016. A new algorithm based on using a Gaussian model to measure the downwind wake characteristics is developed. The wind turbine downwind wake deficits compared well to previous models at far-wake regions, while at near-wake regions the models deviated due to different instruments & methodologies used in measuring the wake characteristics. It was also observed that the length of the Alpha Ventus wind turbine wake varied from 3 to 15 times the Rotor Diameter (RD), and the maximum velocity deficit varied from 55% to 75% of the free-stream wind speed, depending on mean wind speed and atmospheric stability. Detailed analysis of the Alpha Ventus wind turbine wake characteristics is presented.

Investigation of wake effects on a Horizontal Axis Wind Turbine in field experiments (Part I: Horizontal axis direction)

In order to investigate the effects of turbulence intensity and wind shear on the wind turbine wake characteristics, this paper presented the wind velocity distribution of Horizontal Axis Wind Turbine (HAWT) in the horizontal axis direction by field experiments. The test wind turbine had a generator capacity of 30 kW, a rotor diameter of 10.0 m and a hub height of 13.4 m. The reference wind velocity was measured with an ultrasonic anemometer. In the upstream wind measurement mast, the three-cup type anemometers and arrowhead type wind vane were installed. An ultrasonic current meter (SAT-550) which was mounted on the after-stream measuring device equipped which was used for the measurement of the wake at multiple points. Furthermore, the experimental condition of the wake measurement was set at the different inflow velocities and the tip speed ratios. As a result, the maximum velocity deficit in the wake was reduced with the increase of the turbulence intensity. Moreover, as the wind shear index increased, the maximum velocity deficit in the wake was increased. The maximum deficit amount of the non-dimensional wind velocity ratio UNR in the wake increased with the increase of the tip speed ratio.