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.     

Investigation of wind turbine wake superposition models using Reynolds‐averaged Navier‐Stokes simulations

It is well accepted that the wakes created by upstream turbines significantly impact on the power production and fatigue loading of downstream turbines and that this phenomenon affects wind farm performance. Improving the understanding of wake effects and overall efficiency is critical for the optimisation of layout and operation of increasingly large wind farms. In the present work, the NREL 5‐MW reference turbine was simulated using blade element embedded Reynolds‐averaged Navier‐Stokes computations in sheared onset flow at three spatial configurations of two turbines at and above rated flow speed to evaluate the effects of wakes on turbine performance and subsequent wake development. Wake recovery downstream of the rearward turbine was enhanced due to the increased turbulence intensity in the wake, although in cases where the downstream turbine was laterally offset from the upstream turbine this resulted in relatively slower recovery. Three widely used wake superposition models were evaluated and compared with the simulated flow‐field data. It was found that when the freestream hub‐height flow speed was at the rated flow speed, the best performing wake superposition model varied depending according to the turbine array layout. However, above rated flow speed where the wake recovery distance is reduced, it was found that linear superposition of single turbine velocity deficits was the best performing model for all three spatial layouts studied.     

Improving farm efficiency of interacting vertical‐axis wind turbines through wake deflection using pitched struts

This work presents a numerical study of the obtained performance and the resulting flow field between two interacting large scale vertical‐axis wind turbines (VAWTs), under the influence of a deflected wake through the struts pitching of the upwind turbine. The configuration consists of two VAWTs aligned in the direction of the incoming flow in which a wide range of fixed struts pitching angles in the upwind turbine have been investigated. The main goal is to evaluate the influence of the wake deflection on the turbines performance while they are operating at their optimal tip speed ratio (TSR), and to reproduce the most relevant phenomena involved in the flow pattern of the interacting wake. Arrangements with cross‐stream offsets have also been tested for quantifying the contribution of this modification into the overall performance. For this purpose, an actuator line model (ALM) has been implemented using the open‐source CFD library OpenFOAM in order to solve the governing equations and to calculate the resulting flow. The Large eddy simulation (LES) approach is considered to reproduce the turbulence flow effects. A preliminary study to identify the optimal TSR of the interacting downwind turbine has been investigated.     

Investigation of wake interaction using full‐scale lidar measurements and large eddy simulation

In this paper, wake interaction resulting from two stall regulated turbines aligned with the incoming wind is studied experimentally and numerically. The experimental work is based on a full‐scale remote sensing campaign involving three nacelle mounted scanning lidars. A thorough analysis and interpretation of the measurements is performed to overcome either the lack of or the poor calibration of relevant turbine operational sensors, as well as other uncertainties inherent in resolving wakes from full‐scale experiments. The numerical work is based on the in‐house EllipSys3D computational fluid dynamics flow solver, using large eddy simulation and fully turbulent inflow. The rotors are modelled using the actuator disc technique. A mutual validation of the computational fluid dynamics model with the measurements is conducted for a selected dataset, where wake interaction occurs. This validation is based on a comparison between wake deficit, wake generated turbulence, turbine power production and thrust force. An excellent agreement between measurement and simulation is seen in both the fixed and the meandering frame of reference. Copyright © 2015 John Wiley & Sons, Ltd.     

Wind turbine performance in shear flow and in the wake of another turbine through high fidelity numerical simulations with moving mesh technique

We present numerical simulations of two horizontal axis wind turbines, one operating under the wake of the other, under an incoming sheared velocity profile. We use a moving mesh technique to represent the rotation of the turbine blades and solve the unsteady Reynolds averaged Navier–Stokes equations with a shear stress transport k ? ω turbulence model. Temporal evolution of the lift and drag coefficients of the front turbine show a phase shift in the periodic cycle due to the non‐uniform incoming free stream velocity. Comparisons of the lift and drag coefficients for the back turbine with the unperturbed behaviour of the front demonstrate the complex non‐linear interactions of the blades with the wake, with a significant decrease in overall performance and two peaks at specific points in the cycle associated with local angle of attack modification in the wake. The vorticity field in the near wake shows tilting of the vortex lines in the wake due to the shear and a faster diffusion of the tip vortical signature compared with the uniform free stream velocity case. Observations of the wake–wake interaction show good agreement with recent studies that use different methodologies. Copyright © 2012 John Wiley & Sons, Ltd.     

Large‐eddy simulations of wind‐farm wake characteristics associated with a low‐level jet

In this study, we performed a suite of flow simulations for a 12‐wind‐turbine array with varying inflow conditions and lateral spacings, and compared the impacts of the flow on velocity deficit and wake recovery. We imposed both laminar inflow and turbulent inflows, which contain turbulence for the Ekman layer and a low‐level jet (LLJ) in the stable boundary layer. To solve the flow through the wind turbines and their wakes, we used a large‐eddy simulation technique with an actuator‐line method. We compared the time series for the velocity deficit at the first and rear columns to observe the temporal change in velocity deficit for the entire wind farm. The velocity deficit at the first column for LLJ inflow was similar to that for laminar inflow. However, the magnitude of velocity deficit at the rear columns for the case with LLJ inflow was 11.9% greater because of strong wake recovery, which was enhanced by the vertical flux of kinetic energy associated with the LLJ. To observe the spatial transition and characteristics of wake recovery, we performed statistical analyses of the velocity at different locations for both the laminar and LLJ inflows. These studies indicated that strong wake recovery was present, and a kurtosis analysis showed that the probability density function for the streamwise velocity followed a Gaussian distribution. In a quadrant analysis of the Reynolds stress, we found that the ejection and sweep motions for the LLJ inflow case were greater than those for the laminar inflow case.     

Blade‐resolved simulations of a model wind turbine: effect of temporal convergence

Simulations of a model wind turbine at various tip‐speed‐ratios were carried out using Tenasi, a node‐centered, finite volume unstructured flow solver. The simulations included the tunnel walls, tower, nacelle, hub and the blades. The effect of temporal convergence on the predicted thrust and power coefficients is evaluated and guidelines for best practices are established. The results presented here are for tip‐speed‐ratios of 3, 6 and 10, with 6 being the design point. All simulations were carried out at a freestream velocity of 10 m s^?1 with an incoming boundary layer present and the wind turbine RPM was varied to achieve the desired tip‐speed‐ratio. The performance of three turbulence models is evaluated. The models include a one‐equation model (Spalart–Allmaras), a two‐equation model (Menter SST) and the DES version of the Menter SST. Turbine performance as well as wake data at various locations is compared to experiment. All the turbulence models performed well in terms of predicting power and thrust coefficients. The DES model was significantly better than the other two turbulence models for predicting the mean and fluctuating components of the velocity in the wake. Copyright © 2015 John Wiley & Sons, Ltd.     

Simulation and wake analysis of a single vertical axis wind turbine

Because of several design advantages and operational characteristics, particularly in offshore farms, vertical axis wind turbines (VAWTs) are being reconsidered as a complementary technology to horizontal axial turbines. However, considerable gaps remain in our understanding of VAWT performance since cross‐flow rotor configurations have been significantly less studied than axial turbines. This study examines the wakes of VAWTs and how their evolution is influenced by turbine design parameters. An actuator line model is implemented in an atmospheric boundary layer large eddy simulation code, with offline coupling to a high‐resolution blade‐scale unsteady Reynolds‐averaged Navier–Stokes model. The large eddy simulation captures the turbine‐to‐farm scale dynamics, while the unsteady Reynolds‐averaged Navier–Stokes captures the blade‐to‐turbine scale flow. The simulation results are found to be in good agreement with three existing experimental datasets. Subsequently, a parametric study of the flow over an isolated VAWT, carried out by varying solidities, height‐to‐diameter aspect ratios and tip speed ratios, is conducted. The analyses of the wake area and velocity and power deficits yield an improved understanding of the downstream evolution of VAWT wakes, which in turn enables a more informed selection of turbine designs for wind farms. Copyright © 2016 John Wiley & Sons, Ltd.     

Large eddy simulation of dynamically controlled wind turbines in an offshore environment

Accurate modelling of transient wind turbine wakes is an important component in the siting of turbines within wind farms because of wake structures that affect downwind turbine performance and loading. Many current industry tools for modelling these effects are limited to empirically derived predictions. A technique is described for coupling transient wind modelling with an aero‐elastic simulation to dynamically model both turbine operation and wake structures. The important feature of this approach is a turbine model in a flow simulation, which actively responds to transient wind events through the inclusion of controller actions such as blade pitching and regulation of generator torque. The coupled nature of the aero‐elastic/flow simulation also allows recording of load and control data, which permits the analysis of turbine interaction in multiple turbine systems. An aero‐elastic turbine simulation code and a large eddy simulation (LES) solver using an actuator disc model were adapted for this work. Coupling of the codes was implemented with the use of a software framework to transfer data between simulations in a synchronous manner. A computationally efficient simulation was developed with the ability to model turbines exhibiting standard baseline control operating in an offshore environment. Single and multiple wind turbine instances were modelled in a transient flow domain to investigate wake structures and wake interaction effects. Blade loading data were analysed to quantify the increased fluctuating loads on downwind turbines. The results demonstrate the successful implementation of the coupled simulation and quantify the effect of the dynamic‐turbine model. Copyright © 2012 John Wiley & Sons, Ltd.     

A numerical study of tilt‐based wake steering using a hybrid free‐wake method

This study investigates the potential of using tilt‐based wake steering to alleviate wake shielding problems experienced by downwind turbines. Numerical simulations of turbine wakes have been conducted using a hybrid free‐wake analysis combining vortex lattice method (VLM) and an innovative free‐wake model called constant circulation contour method (CCCM). Simulation results indicate tilting a horizontal axis wind turbine's shaft upward causes its wake to ascend, carrying energy‐depleted air upward and pumping more energetic replacement air into downstream turbines, thereby having the potential to recover downstream turbine power generation. Wake cross section vorticity and velocity distributions reveal that the wake upward transport is caused by the formation of near‐wake streamwise vorticity components, and furthermore, the wake velocity deficit is weakened because of the skewed wake structure. Beyond the single turbine wake simulation, an inline two‐turbine case is performed as an assessment of the wake steering influence on the two‐turbine system and as an exploratory work of simulating turbine‐wake interactions using the hybrid free‐wake model. Individual and total turbine powers are calculated. A comparison between different tilting angles suggests turbine power enhancement may be achieved by tilting the upstream turbine and steering its wakes away from the downstream turbine.     

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.     

The flow upstream of a row of aligned wind turbine rotors and its effect on power production

A row of wind turbine rotors with a mutual spacing of three diameters is simulated using both Reynolds averaged Navier‐Stokes (RANS) simulations and a simple inviscid vortex model. The angle between the incoming wind and the line connecting the turbines is varied between 45 and 90 degrees. The simulations show that the power production of the turbines deviate significantly compared with a corresponding isolated turbine even though there is no direct wake‐turbine interaction at the considered wind directions. Nevertheless, both models indicate marked alterations in the upstream flow, which directly link to the turbines' power adjustments. Thus, turbines which are placed laterally relative to the prevailing wind (as seen at various test sites) have, at least numerically, a mutual effect on each other. Therefore, they might not necessarily produce the same power as a stand‐alone turbine. Copyright © 2016 John Wiley & Sons, Ltd.     

Self‐similarity and turbulence characteristics of wind turbine wakes via large‐eddy simulation

Mean and turbulent properties of the wake generated by a single wind turbine are studied in this paper with a new large eddy simulation (LES) code, the wind turbine and turbulence simulator (WiTTS hereafter). WiTTS uses a scale‐dependent Lagrangian dynamical model of the sub‐grid shear stress and actuator lines to simulate the effects of the rotating blades. WiTTS is first tested by simulating neutral boundary layers without and with a wind turbine and then used to study the common assumptions of self‐similarity and axisymmetry of the wake under neutral conditions for a variety of wind speeds and turbine properties. We find that the wind velocity deficit generally remains self similarity to a Gaussian distribution in the horizontal. In the vertical, the Gaussian self‐similarity is still valid in the upper part of the wake, but it breaks down in the region of the wake close to the ground. The horizontal expansion of the wake is always faster and greater than the vertical expansion under neutral stability due to wind shear and impact with the ground. Two modifications to existing equations for the mean velocity deficit and the maximum added turbulence intensity are proposed and successfully tested. The anisotropic wake expansion is taken into account in the modified model of the mean velocity deficit. Turbulent kinetic energy (TKE) budgets show that production and advection exceed dissipation and turbulent transport. The nacelle causes significant increase of every term in the TKE budget in the near wake. In conclusion, WiTTS performs satisfactorily in the rotor region of wind turbine wakes under neutral stability. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

Simulation comparison of wake mitigation control strategies for a two‐turbine case

Wind turbines arranged in a wind plant impact each other through their wakes. Wind plant control is an active research field that attempts to improve wind plant performance by coordinating control of individual turbines to take into account these turbine–wake interactions. In this paper, high‐fidelity simulations of a two‐turbine fully waked scenario are used to investigate several wake mitigation strategies, including modification of yaw and tilt angles of an upstream turbine to induce wake skew, as well as repositioning of the downstream turbine. The simulation results are compared through change relative to a baseline operation in terms of overall power capture and loading on the upstream and downstream turbine. Results demonstrated improved power production for all methods. Analysis of control options, including individual pitch control, shows potential to minimize the increase of, or even reduce, turbine loads.Copyright © 2014 John Wiley & Sons, Ltd.     

Large‐eddy simulation of turbulent flow past wind turbines/farms: the Virtual Wind Simulator (VWiS)

A large‐eddy simulation framework, dubbed as the Virtual Wind Simulator (VWiS), for simulating turbulent flow over wind turbines and wind farms in complex terrain is developed and validated. The wind turbines are parameterized using the actuator line model. The complex terrain is represented by the curvilinear immersed boundary method. The predictive capability of the present method is evaluated by simulating two available wind tunnel experimental cases: the flow over a stand‐alone turbine and an aligned wind turbine array. Systematic grid refinement studies are carried out, for both single turbine and multi‐turbine array cases, and the accuracy of the computed results is assessed through detailed comparisons with wind tunnel experiments. The model is further applied to simulate the flow over an operational utility‐scale wind farm. The inflow velocities for this case are interpolated from a mesoscale simulation using a Weather Research and Forecasting (WRF) model with and without adding synthetic turbulence to the WRF‐computed velocity fields. Improvements on power predictions are obtained when synthetic turbulence is added at the inlet. Finally the VWiS is applied to simulate a yet undeveloped wind farm at a complex terrain site where wind resource measurements have already been obtained. Good agreement with field measurements is obtained in terms of the time‐averaged streamwise velocity profiles. To demonstrate the ability of the model to simulate the interactions of terrain‐induced turbulence with wind turbines, eight hypothetical turbines are placed in this area. The computed extracted power underscores the significant effect of site‐specific topography on turbine performance. Copyright © 2014 John Wiley & Sons, Ltd.     

Impact of different forest densities on atmospheric boundary‐layer development and wind‐turbine wake

The aim of this work is to investigate the atmospheric boundary‐layer (ABL) flow and the wind turbine wake over forests with varying leaf area densities (LAD). The forest LAD profile used in this study is based on a real forest site, Ryningsnäs, located in Sweden. The reference turbine used to model the wake is a well‐documented 5‐MW turbine, which is implemented in the simulations using an actuator line model (ALM). All simulations are carried out with openFOAM using the Reynolds averaged Navier‐Stokes (RANS) approach. Twelve forest cases with leaf area index (LAI) ranging from 0.42 to 8.5 are considered. Results show that the mean velocity decreases with increasing LAI within the forest canopy, but increases with LAI above the hub height. Meanwhile, the turbulent kinetic energy (TKE) varies nonmonotonically with forest density. The TKE increases with forest density and reaches to its maximum at an average LAI of 1.70, afterwards, it decreases gradually as the density increases. It is also observed that the forest density has a clear role in the wake development and recovery. Comparisons between no‐forest and forest cases show that the forest characteristics help in damping the added turbulence from the turbine. As a consequence, the forest with the highest upstream turbulence has the shortest wake downstream of the turbine.     

Two improvements to the dynamic wake meandering model: including the effects of atmospheric shear on wake turbulence and incorporating turbulence build‐up in a row of wind turbines

The dynamic wake meandering (DWM) model is an engineering wake model designed to physically model the wake deficit evolution and the unsteady meandering that occurs in wind turbine wakes. The present study aims at improving two features of the model:

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An improved k‐ ϵ model applied to a wind turbine wake in atmospheric turbulence

An improved k‐ ? turbulence model is developed and applied to a single wind turbine wake in a neutral atmospheric boundary layer using a Reynolds averaged Navier–Stokes solver. The proposed model includes a flow‐dependent C_μ that is sensitive to high velocity gradients, e.g., at the edge of a wind turbine wake. The modified k‐ ? model is compared with the original k‐ ? eddy viscosity model, Large‐Eddy Simulations and field measurements using eight test cases. The comparison shows that the velocity wake deficits, predicted by the proposed model are much closer to the ones calculated by the Large‐Eddy Simulation and those observed in the measurements, than predicted by the original k‐ ? model. Copyright © 2014 John Wiley & Sons, Ltd.     

Evaluation of the effects of turbulence model enhancements on wind turbine wake predictions

The modelling of wind turbine wakes is investigated in this paper using a Navier–Stokes solver employing the k–ω turbulence model appropriately modified for atmospheric flows. It is common knowledge that even single‐wind turbine wake predictions with computational fluid dynamic methods underestimate the near wake deficit, directly contributing to the overestimation of the power of the downstream turbines. For a single‐wind turbine, alternative modelling enhancements under neutral and stable atmospheric conditions are tested in this paper to account for and eventually correct the turbulence overestimation that is responsible for the faster flow recovery that appears in the numerical predictions. Their effect on the power predictions is evaluated with comparison with existing wake measurements. A second issue addressed in this paper concerns multi‐wake predictions in wind farms, where the estimation of the reference wind speed that is required for the thrust calculation of a turbine located in the wake(s) of other turbines is not obvious. This is overcome by utilizing an induction factor‐based concept: According to it, the definition of the induction factor and its relationship with the thrust coefficient are employed to provide an average wind speed value across the rotor disk for the estimation of the axial force. Application is made on the case of five wind turbines in a row. Copyright © 2010 John Wiley & Sons, Ltd.