The k‐ϵ‐fP model applied to wind farms

The recently developed k‐?‐f_P eddy‐viscosity model is applied to one on‐shore and two off‐shore wind farms. The results are compared with power measurements and results of the standard k‐? eddy‐viscosity model. In addition, the wind direction uncertainty of the measurements is used to correct the model results with a Gaussian filter. The standard k‐? eddy‐viscosity model underpredicts the power deficit of the first downstream wind turbines, whereas the k‐?‐f_P eddy‐viscosity model shows a good agreement with the measurements. However, the difference in the power deficit predicted by the turbulence models becomes smaller for wind turbines that are located further downstream. Moreover, the difference between the capability of the turbulence models to estimate the wind farm efficiency reduces with increasing wind farm size and wind turbine spacing. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

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.     

Model‐based receding horizon control of wind farms for secondary frequency regulation

In this study, we propose the use of model‐based receding horizon control to enable a wind farm to provide secondary frequency regulation for a power grid. The controller is built by first proposing a time‐varying one‐dimensional wake model, which is validated against large eddy simulations of a wind farm at startup. This wake model is then used as a plant model for a closed‐loop receding horizon controller that uses wind speed measurements at each turbine as feedback. The control method is tested in large eddy simulations with actuator disk wind turbine models representing an 84‐turbine wind farm that aims to track sample frequency regulation reference signals spanning 40 min time intervals. This type of control generally requires wind turbines to reduce their power set points or curtail wind power output (derate the power output) by the same amount as the maximum upward variation in power level required by the reference signal. However, our control approach provides good tracking performance in the test system considered with only a 4% derate for a regulation signal with an 8% maximum upward variation. This performance improvement has the potential to reduce the opportunity cost associated with lost revenue in the bulk power market that is typically associated with providing frequency regulation services. Copyright © 2017 John Wiley & Sons, Ltd.     

Large‐eddy simulations of the Lillgrund wind farm

The power production of the Lillgrund wind farm is determined numerically using large‐eddy simulations and compared with measurements. In order to simulate realistic atmospheric conditions, pre‐generated turbulence and wind shear are imposed in the computational domain. The atmospheric conditions are determined from data extracted from a met mast, which was erected prior to the establishment of the farm. In order to allocate most of the computational power to the simulations of the wake flow, the turbines are modeled using an actuator disc method where the discs are imposed in the computational domain as body forces which for every time step are calculated from tabulated airfoil data. A study of the influence of imposed upstream ambient turbulence is performed and shows that higher levels of turbulence results in slightly increased total power production and that it is of great importance to include ambient turbulence in the simulations. By introducing ambient atmospheric turbulence, the simulations compare very well with measurements at the studied inflow angles. A final study aiming at increasing the farm production by curtailing the power output of the front row turbines and thus letting more kinetic energy pass downstream is performed. The results, however, show that manipulating only the front row turbines has no positive effect on the farm production, and therefore, more complex curtailment strategies are needed to be tested. Copyright © 2014 John Wiley & Sons, Ltd.     

Benefits of collocating vertical‐axis and horizontal‐axis wind turbines in large wind farms

In this study, we address the benefits of a vertically staggered (VS) wind farm, in which vertical‐axis and horizontal‐axis wind turbines are collocated in a large wind farm. The case study consists of 20 small vertical‐axis turbines added around each large horizontal‐axis turbine. Large‐eddy simulation is used to compare power extraction and flow properties of the VS wind farm versus a traditional wind farm with only large turbines. The VS wind farm produces up to 32% more power than the traditional one, and the power extracted by the large turbines alone is increased by 10%, caused by faster wake recovery from enhanced turbulence due to the presence of the small turbines. A theoretical analysis based on a top‐down model is performed and compared with the large‐eddy simulation. The analysis suggests a nonlinear increase of total power extraction with increase of the loading of smaller turbines, with weak sensitivity to various parameters, such as size, and type aspect ratio, and thrust coefficient of the vertical‐axis turbines. We conclude that vertical staggering can be an effective way to increase energy production in existing wind farms. Copyright © 2016 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.     

Computational Fluid Dynamics model of stratified atmospheric boundary‐layer flow

For wind resource assessment, the wind industry is increasingly relying on computational fluid dynamics models of the neutrally stratified surface‐layer. So far, physical processes that are important to the whole atmospheric boundary‐layer, such as the Coriolis effect, buoyancy forces and heat transport, are mostly ignored. In order to decrease the uncertainty of wind resource assessment, the present work focuses on atmospheric flows that include stability and Coriolis effects. The influence of these effects on the whole atmospheric boundary‐layer are examined using a Reynolds‐averaged Navier–Stokes k‐ ε model. To validate the model implementations, results are compared against measurements from several large‐scale field campaigns, wind tunnel experiments, and previous simulations and are shown to significantly improve the predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

Horizontal axis wind turbine systems: optimization using genetic algorithms

A method for the optimization of a grid‐connected wind turbine system is presented. The behaviour of the system components is coupled in a non‐linear way, and optimization must take into account technical and economical aspects of the complete system design. The annual electrical energy cost is estimated using a cost model for the wind turbine rotor, nacelle and tower and an energy output model based on the performance envelopes of the power coefficient of the rotor, C_P, on the Weibull parameters k and c and on the power law coefficient α of the wind profile. In this study the site is defined with these three parameters and the extreme wind speed V_max. The model parameters vary within a range of possible values. Other elements of the project (foundation, grid connection, financing cost, etc.) are taken into account through coefficients. The optimal values of the parameters are determined using genetic algorithms, which appear to be efficient for such a problem. These optimal values were found to be very different for a Mediterranean site and a northern European site using our numerical model. Optimal wind turbines at the Mediterranean sites considered in this article have an excellent profitability compared with reference northern European wind turbines. Most of the existing wind turbines appear to be well designed for northern European sites but not for Mediterranean sites. Copyright © 2001 John Wiley & Sons, Ltd.     

Testing of self‐similarity and helical symmetry in vortex generator flow simulations

Vortex generators (VGs) are used increasingly by the wind turbine industry as flow control devices to improve rotor blade performance. According to experimental observations, the vortices generated by VGs have previously been observed to be self‐similar for both the axial (u_z) and azimuthal (u_θ) velocity components. Furthermore, the measured vortices have been observed to obey the criteria for helical symmetry. These are powerful results, as it reduces the highly complex 3‐D flow to merely four parameters and therefore significantly facilitates the modeling of this type of flow, which in a larger perspective can assist in parametric studies to increase the total power output of wind turbines. In this study, corresponding computer simulations using Reynolds‐averaged Navier–Stokes equations have been carried out and compared with the experimental observations. The main objective is to investigate how well the simulations can reproduce these aspects of the physics of the flow, i.e., investigate if the same analytical model can be applied and therefore significantly facilitate the modeling of this type of flow, which in a larger perspective can assist in parametric studies to increase the total power output of wind turbines. This is especially interesting since these types of flows are notoriously difficult for the turbulence models to predict correctly. Using this model, parametric studies can be significantly reduced, and moreover, reliable simulations can substantially reduce the costs of the parametric studies themselves. Copyright © 2015 John Wiley & Sons, Ltd.     

A study on the prediction of aerofoil trailing‐edge noise for wind‐turbine applications

This paper presents a comparative study between the so‐called BPM and TNO models for the prediction of aerofoil trailing‐edge noise with particular emphasis on wind‐turbine applications (the BPM model is named after Brooks, Pope and Marcolini who first proposed the model, and the TNO model is named after the TNO institute of Applied Physics where it was first proposed). In this work, two enhanced versions of the BPM model are proposed, and their performances are compared against two recent anisotropic TNO models that require more detailed boundary‐layer information than the BPM‐based models. The two current enhanced models are denoted as BPMM‐PVII and BPMM‐BLkω, where the former uses a panel method with viscous‐inviscid interaction implemented (PVII) for boundary‐layer calculations, the latter estimates the boundary‐layer (BL) properties using a two‐dimensional k‐ω turbulence model (kω), and BPMM stands for BPM‐Modified. By comparing the predicted sound spectra with existing measurement data for seven different aerofoils tested in the current study, it is shown that the BPMM‐PVII model exhibits superior results to those by the other models for most cases despite the simplicity without considering anisotropy. The BPMM‐PVII model is then combined with Prandtl's nonlinear lifting‐line theory to calculate and investigate three‐dimensional rotor noise characteristics of an NREL UAE Phase‐VI wind turbine (NREL UAE stand for the National Renewable Energy Laboratory Unsteady Aerodynamic Experiment). It is demonstrated that the current approach may provide an efficient solution for the prediction of rotor aerodynamics and noise facilitating industrial design and development for low‐noise wind turbines. Copyright © 2016 John Wiley & Sons, Ltd.     

Time‐adaptive wind turbine model for an LES framework

Most large‐eddy simulation studies related to wind energy have been carried out either by using a fixed pressure gradient to ensure that mean wind direction is perpendicular to the wind turbine rotor disk or by forcing the flow with a geostrophic wind and timely readjusting the turbines' orientation. This has not allowed for the study of wind farm characteristics with a time‐varying wind vector. In this paper, a new time‐adaptive wind turbine model for the large‐eddy simulation framework is introduced. The new algorithm enables the wind turbines to dynamically realign with the incoming wind vector and self‐adjust the yaw orientation with the incoming wind vector similar to real wind turbines. The performance of the new model is tested first with a neutrally stratified atmospheric flow forced with a time‐varying geostrophic wind vector. A posteriori, the new model is used to further explore the interaction between a synthetic time‐changing thermal atmospheric boundary layer and an embedded wind farm. Results show that there is significant potential power to be harvested during the unstable time periods at the cost of designing wind turbines capable of adapting to the enhanced variance of these periods. Stable periods provide less power but are more constant over time with an enhanced lateral shear induced by an increased change in wind direction with height. Copyright © 2015 John Wiley & Sons, Ltd.     

One‐way mesoscale‐microscale coupling for simulating a wind farm in North Texas: Assessment against SCADA and LiDAR data

One‐way nested mesoscale to microscale simulations of an onshore wind farm have been performed nesting the Weather Research and Forecasting (WRF) model and our in‐house high‐resolution large‐eddy simulation code (UTD‐WF). Each simulation contains five nested WRF domains, with the largest domain spanning the north Texas Panhandle region with a 4 km resolution, while the highest resolution (50 m) nest simulates microscale wind fluctuations and turbine wakes within a single wind farm. The finest WRF domain in turn drives the UTD‐WF LES higher‐resolution domain for a subset of six turbines at a resolution of ～5 m. The wind speed, direction, and boundary layer profiles from WRF are compared against measurements obtained with a met‐tower and a scanning Doppler wind LiDAR located within the wind farm. Additionally, power production obtained from WRF and UTD‐WF are assessed against supervisory control and data acquisition (SCADA) system data. Numerical results agree well with the experimental measurements of the wind speed, direction, and power production of the turbines. UTD‐WF high‐resolution domain improves significantly the agreement of the turbulence intensity at the turbines location compared with that of WRF. Velocity spectra have been computed to assess how the nesting allows resolving a wide range of scales at a reasonable computational cost. A domain sensitivity analysis has been performed. Velocity spectra indicate that placing the inlet too close to the first row of turbines results in an unrealistic peak of energy at the rotational frequency of the turbines. Spectra of the power production of a single turbine and of the cumulative power of the array have been compared with analytical models.     

Modifications to Reynolds-averaged Navier–Stokes turbulence models for the wind flow over buildings

The standard k–ε turbulence model is well known to perform poorly in the stagnation regions in front of buildings where it over-predicts the turbulent kinetic energy, k. It is less well known that this error is compounded by an excess decay of the turbulence over and behind a building so that k is eventually under-estimated in the building wake. A new formulation of the eddy viscosity in the standard k–ε turbulence model was developed and compared with previous modifications designed for stagnation regions. The new formulation provides more accurate values of k and it showed similar results for streamwise mean velocity predicted by the shear stress transport turbulence model. A blend between the new model and the standard eddy viscosity model provides the best overall prediction of the mean velocities and turbulence.     

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.     

Aerodynamic simulations of offshore floating wind turbine in platform‐induced pitching motion

Forfloating offshore wind turbines, rotors are under coupled motions of rotating and platform‐induced motions because of hydrodynamics impacts. Notably, the coupled motion of platform pitching and rotor rotating induces unsteadiness and nonlinear aerodynamics in turbine operations; thus having a strong effect on the rotor performances including thrust and power generation. The present work aims at developing a computational fluid dynamics model for simulations of rotor under floating platform induced motions. The rotor motion is realized using arbitrary mesh interface, and wind flows are modelled by incompressible Navier‐Stokes flow solver appended by the k  ? ω shear stress transport turbulence model to resolve turbulence quantities. In order to investigate the fully coupled motion of floating wind turbine, the six degree of freedom solid body motion solver is extended to couple with multiple motions, especially for the motion of rotor coupled with the prescribed surge‐heave‐pitch motion of floating platform. The detailed methodology of multiple motion coupling is also described and discussed in this work. Both steady and unsteady simulations of offshore floating wind turbine are considered in the present work. The steady aerodynamic simulation of offshore floating wind turbine is implemented by the multiple reference frames approach and for the transient simulation, the rotor motion is realized using arbitrary mesh interface. A rigorous benchmark of the present numerical model is performed by comparing to the reported literatures. The detailed elemental thrust and power comparisons of wind turbine are carried out by comparing with the results from FAST developed by National Renewable Energy Laboratory and various existing numerical data with good agreement. The proposed approach is then applied for simulations of National Renewable Energy Laboratory 5MW turbine in coupled platform motion at various wind speeds under a typical load case scenario. Transient effect of flows over turbines rotor is captured with good prediction of turbine performance as compared with existing data from FAST. Copyright © 2016 John Wiley & Sons, Ltd.     

On the application of the Jensen wake model using a turbulence‐dependent wake decay coefficient: the Sexbierum case

We present a methodology to process wind turbine wake simulations, which are closely related to the nature of wake observations and the processing of these to generate the so‐called wake cases. The method involves averaging a large number of wake simulations over a range of wind directions and partly accounts for the uncertainty in the wind direction assuming that the same follows a Gaussian distribution. Simulations of the single and double wake measurements at the Sexbierum onshore wind farm are performed using a fast engineering wind farm wake model based on the Jensen wake model, a linearized computational fluid dynamics wake model by Fuga and a nonlinear computational fluid dynamics wake model that solves the Reynolds‐averaged Navier–Stokes equations with a modified k‐ε turbulence model. The best agreement between models and measurements is found using the Jensen‐based wake model with the suggested post‐processing. We show that the wake decay coefficient of the Jensen wake model must be decreased from the commonly used onshore value of 0.075 to 0.038, when applied to the Sexbierum cases, as wake decay is related to the height, roughness and atmospheric stability and, thus, to turbulence intensity. Based on surface layer relations and assumptions between turbulence intensity and atmospheric stability, we find that at Sexbierum, the atmosphere was probably close to stable, although the stability was not observed. We support these assumptions using detailed meteorological observations from the Høvsøre site in Denmark, which is topographically similar to the Sexbierum region. © 2015 The Authors. Wind Energy published by John Wiley & Sons Ltd.     

Partially-Averaged Navier–Stokes method with modified k–ε model for cavitating flow around a marine propeller in a non-uniform wake

Unsteady cavitating turbulent flow simulations need to be responsible for both cavitation and turbulence modeling issues. The Partially-Averaged Navier–Stokes (PANS) computational model developed from the RANS method and the k–ε turbulence model are used to model turbulent cavitating flow with a mass transfer cavitation model in the present paper. An objective of this study is to pursue more accurate estimates of unsteady cavitating flows with large-scale fluctuations at a reasonable cost. Firstly, the unsteady cavitating flow simulations over a NACA66-mod hydrofoil are performed using the PANS method with various values of the resolution control parameters (f_k = 1 ～ 0.2, f_ε = 1) to evaluate the numerical methods based on experimental data. The comparison with the experiments show that the numerical analysis with a f_k = 0.2 can predict the cavity evolution and shedding frequency fairly well. Then, cavitating flow around a marine propeller in non-uniform wake was simulated by PANS method. The calculations show that large cavity volume pulsation as the blade passes through the wake region is resolved better by the PANS method with f_k = 0.2 than by the RANS method with the k–ε or k–ω SST turbulence models. This can be contributed to the fact that a smaller f_k give larger cavity volume pulsations leading to increased cavity volume accelerations and larger pressure fluctuations above the propeller, while a larger f_k overestimates the turbulent viscosity along the rear part of the cavity. Finally, it is confirmed from the simulation by the PANS method with f_k = 0.2 that the whole process of cavitating flow evolution around the propeller in non-uniform wake can be very well reproduced including cavitation inception, sheet cavitation and tip vortex cavitation observed experimentally.     

Exploring the benefits of vertically staggered wind farms: Understanding the power generation mechanisms of turbines operating at different scales

Wind farms are known to modulate large scale structures in and around the wake regions of the turbines. The potential benefits of placing small hub height, small rotor turbines in between the large turbines in a wind farm to take advantage of such modulated large‐scale eddies are explored using large eddy simulation (LES). The study has been carried out in an infinite wind farm framework invoking an asymptotic limit, and the wind turbines are modeled using an actuator line model. The vertically staggered wind turbine arrangements that are studied in the present work consist of rows of large wind turbines, with rows of smaller wind turbines (ie, smaller rotor size and shorter hub height) placed in between the rows of large turbines. The influence of the hub height of the small turbines, in particular, how it affects the interactions between the large and small turbines and consequently their power, along with the multiscale dynamics involved, has been assessed in the current study. It was found that, in the multiscale layouts, the small turbines at lower hub heights operate more efficiently than their homogeneous single‐scale counterparts. In contrast, the small turbines with higher hub heights incur a loss of power compared with the corresponding single‐scale arrangements.