Application of a LES technique to characterize the wake deflection of a wind turbine in yaw

When a wind turbine works in yaw, the wake intensity and the power production of the turbine become slightly smaller and a deflection of the wake is induced. Therefore, a good understanding of this effect would allow an active control of the yaw angle of upstream turbines to steer the wake away from downstream machines, reducing its effect on them. In wind farms where interaction between turbines is significant, it is of interest to maximize the power output from the wind farm as a whole and to reduce fatigue loads on downstream turbines due to the increase of turbulence intensity in wakes. A large eddy simulation model with particular wind boundary conditions has been used recently to simulate and characterize the turbulence generated by the presence of a wind turbine and its evolution downstream the machine. The simplified turbine is placed within an environment in which relevant flow properties like wind speed profile, turbulence intensity and the anisotropy of turbulence are found to be similar to the ones of the neutral atmosphere. In this work, the model is used to characterize the wake deflection for a range of yaw angles and thrust coefficients of the turbine. The results are compared with experimental data obtained by other authors with a particle image velocimetry technique from wind tunnel experiments. Also, a comparison with simple analytical correlations is carried out. Copyright © 2009 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.     

Effect of winds in a mountain pass on turbine performance

Mountain passes are potentially advantageous sites for the deployment of wind turbines because of road links and electrical transmission infrastructure. However, relatively little is known about wind characteristics and turbine response in these environments. Using hub height wind data from a mountain pass in Switzerland, this paper discusses the causes of the observed pass winds and how a generic wind turbine might perform in those conditions. During 3 months of winter measurements, the winds in the pass showed signatures of forcing by regional pressure gradients rather than local cooling or heating. Turbulence intensity was often less than 10%, and the magnitude of the wind shear power law exponent was less than 0.1. To understand the impact of pass winds on a wind turbine, we simulated a Wind Partnership for Advanced Component Technologies 1.5 MW wind turbine using the Fatigue, Aerodynamics, Structures, and Turbulence (FAST) aeroelastic simulator , forced by artificial wind fields of varying turbulence intensity and shear generated by the turbulence simulator TurbSim. We used the turbine simulation data to train a regression model that is used to predict the turbine response to the pass wind time series. Results showed that depending on long‐term wind characteristics, wind turbines in the pass may perform differently than predicted using a power curve derived from test measurements at another location. This method of generating site‐specific energy capture predictions could be combined with long‐term wind resource data and specific turbine models to better predict the energy production and turbine loads at this, or any other site. Copyright © 2013 John Wiley & Sons, Ltd.     

Variable‐sized wind turbines are a possibility for wind farm optimization

The potential benefits associated with harnessing available momentum and reducing turbulence levels in a wind farm composed of wind turbines of alternating size are investigated through wind tunnel experiments. A variable size turbine array composed of 3 by 8 model wind turbines is placed in a boundary layer flow developed over both a smooth and rough surfaces under neutrally stratified thermal conditions. Cross‐wire anemometry is used to capture high resolution and simultaneous measurements of the streamwise and vertical velocity components at various locations along the central plane of the wind farm. A laser tachometer is employed to obtain the instantaneous angular velocity of various turbines. The results suggest that wind turbine size heterogeneity in a wind farm introduces distinctive flow interactions not possible in its homogeneous counterpart. In particular, reduced levels of turbulence around the wind turbine rotors may have positive effects on turbulent loading. The turbines also appear to perform quite uniformly along the entire wind farm, whereas surface roughness impacts the velocity recovery and the spectral content of the turbulent flow within the wind farm. Copyright © 2013 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.     

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.     

Wake impacts on downstream wind turbine performance and yaw alignment

Aerodynamic wake interaction between commercial scale wind turbines can be a significant source of power losses and increased fatigue loads across a wind farm. Significant research has been dedicated to the study of wind turbine wakes and wake model development. This paper profiles influential wake regions for an onshore wind farm using 6 months of recorded SCADA (supervisory control and data acquisition) data. An average wind velocity deficit of over 30% was observed corresponding to power coefficient losses of 0.2 in the wake region. Wind speed fluctuations are also quantified for an array of turbines, inferring an increase in turbulence within the wake region. A study of yaw data within the array showed turbine nacelle misalignment under a range of downstream wake angles, indicating a characteristic of wind turbine behaviour not generally considered in wake studies. The turbines yaw independently in order to capture the increased wind speeds present due to the lateral influx of turbulent wind, contrary to many experimental and simulation methods found in the literature. Improvements are suggested for wind farm control strategies that may improve farm‐wide power output. Additionally, possible causes for wind farm wake model overestimation of wake losses are proposed.Copyright © 2012 John Wiley & Sons, Ltd.     

The helix approach: Using dynamic individual pitch control to enhance wake mixing in wind farms

Wind farm control using dynamic concepts is a research topic that is receiving an increasing amount of interest. The main concept of this approach is that dynamic variations of the wind turbine control settings lead to higher wake turbulence, and subsequently faster wake recovery due to increased mixing. As a result, downstream turbines experience higher wind speeds, thus increasing their energy capture. In dynamic induction control (DIC), the magnitude of the thrust force of an upstream turbine is varied. Although very effective, this approach also leads to increased power and thrust variations, negatively impacting energy quality and fatigue loading. In this paper, a novel approach for the dynamic control of wind turbines in a wind farm is proposed: using individual pitch control, the fixed‐frame tilt and yaw moments on the turbine are varied, thus dynamically manipulating the wake. This strategy is named the helix approach because the resulting wake has a helical shape. Large eddy simulations of a two‐turbine wind farm show that this approach leads to enhanced wake mixing with minimal power and thrust variations.     

Evaluation of different wind fields for the investigation of the dynamic response of offshore wind turbines

As the size of offshore wind turbines increases, a realistic representation of the spatiotemporal distribution of the incident wind field becomes crucial for modeling the dynamic response of the turbine. The International Electrotechnical Commission (IEC) standard for wind turbine design recommends two turbulence models for simulations of the incident wind field, the Mann spectral tensor model, and the Kaimal spectral and exponential coherence model. In particular, for floating wind turbines, these standard models are challenged by more sophisticated ones. The characteristics of the wind field depend on the stability conditions of the atmosphere, which neither of the standard turbulence models account for. The spatial and temporal distribution of the turbulence, represented by coherence, is not modeled consistently by the two standard models. In this study, the Mann spectral tensor model and the Kaimal spectral and exponential coherence model are compared with wind fields constructed from offshore measurements and obtained from large‐eddy simulations. Cross sections and durations relevant for offshore wind turbine design are considered. Coherent structures from the different simulators are studied across various stability conditions and wind speeds through coherence and proper orthogonal decomposition mode plots. As expected, the standard models represent neutral stratification better than they do stable and unstable. Depending upon the method used for generating the wind field, significant differences in the spatial and temporal distribution of coherence are found. Consequently, the computed structural design loads on a wind turbine are expected to vary significantly depending upon the employed turbulence model. The knowledge gained in this study will be used in future studies to quantify the effect of various turbulence models on the dynamic response of large offshore wind turbines.     

Effects of spatial and temporal resolution of the turbulent inflow on wind turbine performance estimation

The effects of spatial and temporal resolution of wind inflows generated using large eddy simulations (LES) on the scales of turbulence present in the wind inflow, and the resulting changes in wind turbine performance were investigated for neutral atmospheric boundary layer conditions. Wind inflows with four different spatial resolutions and five different temporal resolutions were used to produce different turbine responses. An aero‐elastic code assessed the dynamic response of two wind turbines to the different inflows. Auto‐spectral density functions (ASDF) of turbine responses, such as blade deflection and bending moment, that are representative of the turbine response were used to assess the effect of the inflow. The results indicated that, as additional turbulence scales were resolved, the wind turbines showed a similar increased response that was evident in both the ASDF and variance of the different wind turbine performance parameters. As a result, the amount to which turbulence is resolved in the inflow, particularly using tools such as LES, will be important to consider when using these inflows for wind turbine design and performance prediction. Copyright © 2015 John Wiley & Sons, Ltd.     

An experimental investigation on the effect of individual turbine control on wind farm dynamics

Individual wind turbines in a wind farm typically operate to maximize their performance with no consideration of the impact of wake effects on downstream turbines. There is potential to increase power and reduce structural loads within a wind farm by properly coordinating the turbines. To effectively design and analyze coordinated wind turbine controllers requires control‐oriented turbine wake models of sufficient accuracy. This paper focuses on constructing such a model from experiments. The experiments were conducted to better understand the wake interaction and impact on voltage production in a three‐turbine array. The upstream turbine operating condition was modulated in time, and the dynamic impact on the downstream turbine was recorded through the voltage output time signal. The flow dynamics observed in the experiments were used to improve a static wake model often used in the literature for wind farm control. These experiments were performed in the atmospheric boundary layer wind tunnel at the Saint Anthony Falls Laboratory at the University of Minnesota using particle image velocimetry for flow field analysis and turbine voltage modulation to capture the physical evolution in addition to the dynamics of turbine wake interactions. Copyright © 2015 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.     

Modelling and measurements of power losses and turbulence intensity in wind turbine wakes at Middelgrunden offshore wind farm

Understanding of power losses and turbulence increase due to wind turbine wake interactions in large offshore wind farms is crucial to optimizing wind farm design. Power losses and turbulence increase due to wakes are quantified based on observations from Middelgrunden and state‐of‐the‐art models. Observed power losses due solely to wakes are approximately 10% on average. These are relatively high for a single line of wind turbines due in part to the close spacing of the wind farm. The wind farm model Wind Analysis and Application Program (WAsP) is shown to capture wake losses despite operating beyond its specifications for turbine spacing. The paper describes two methods of estimating turbulence intensity: one based on the mean and standard deviation (SD) of wind speed from the nacelle anemometer, the other from mean power output and its SD. Observations from the nacelle anemometer indicate turbulence intensity which is around 9% higher in absolute terms than those derived from the power measurements. For comparison, turbulence intensity is also derived from wind speed and SD from a meteorological mast at the same site prior to wind farm construction. Despite differences in the measurement height and period, overall agreement is better between the turbulence intensity derived from power measurements and the meteorological mast than with those derived from data from the nacelle anemometers. The turbulence in wind farm model indicates turbulence increase of the order 20% in absolute terms for flow directly along the row which is in good agreement with the observations. Copyright © 2007 John Wiley & Sons, Ltd.     

Prediction of flicker produced by wind turbines

Electrical flicker is a measure of voltage variations which may cause disturbances to consumers. Flicker is caused by both generators and loads connected to the network. This paper discusses the various issues which affect electrical flicker from wind turbines, and describes the development of a software tool capable of predicting, at the design stage, the flicker which would be produced by a wind turbine, or by a wind farm of similar turbines, on a particular network. The paper describes the modelling of the physical dynamics of the wind turbine and the turbulence in the wind which drives it, the electrical dynamics of the generator, and the network itself with various types of embedded consumer loads. Measurements carried out on two different 1 MW wind turbines have been used to validate the models. Copyright © 1998 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.     

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.     

Evaluation of wind farm efficiency and wind turbine wakes at the Nysted offshore wind farm

Here, we quantify relationships between wind farm efficiency and wind speed, direction, turbulence and atmospheric stability using power output from the large offshore wind farm at Nysted in Denmark. Wake losses are, as expected, most strongly related to wind speed variations through the turbine thrust coefficient; with direction, atmospheric stability and turbulence as important second order effects. While the wind farm efficiency is highly dependent on the distribution of wind speeds and wind direction, it is shown that the impact of turbine spacing on wake losses and turbine efficiency can be quantified, albeit with relatively large uncertainty due to stochastic effects in the data. There is evidence of the ‘deep array effect’ in that wake losses in the centre of the wind farm are under‐estimated by the wind farm model WAsP, although overall efficiency of the wind farm is well predicted due to compensating edge effects. Copyright © 2010 John Wiley & Sons, Ltd.     

Validation of the standalone implementation of the dynamic wake meandering model for power production

This paper presents validation for using the standalone implementation of the dynamic wake meandering (DWM) model to conduct numerical simulations of power production of rows of wind turbines. The standalone DWM model is an alternative formulation of the conventional DWM model that does not require information exchange with an aeroelastic code. As a consequence, the standalone DWM model has significantly shorter computational times and lower demands on the user environment. The drawback of the standalone DWM model is that it does not have the capability to predict turbine loads. Instead, it should be seen as an alternative for simulating the power production of a wind farm. The main advantage of the standalone DWM model is the ability to capture the key physics for wake dynamics such as the turbine specific induction, the build‐up of wake turbulence and wake deficit in the wind farm, and the effect of ambient turbulence intensity and atmospheric stability. The predicted power production of the standalone DWM model is compared with that of full scale measurements from Horns Rev, Lillgrund, Nysted and Weingermeer wind farms. Overall, the difference between the models predictions and the reference data is on the order of 5%. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

新型双风轮风力机气动特性的三维流场数值模拟

基于Simplic算法,采用SST κ-ω湍流模型,利用Fluent6．3数值模拟软件对新型的小型双风轮风力机的气动特性进行了三维流场研究,并与同规格单风轮风力机的三维流场进行了比较．结果表明：与单风轮风力机相比,随着后风轮叶片数目的增加,新型双风轮风力机的湍流强度变大,风力机运行的稳定性在一定程度上有所降低;当后风轮的叶片数目合理时,后风轮对前风轮的影响较小,且可以有效地捕捉到前风轮的漏风,使得新型双风轮风力机的风轮在获得较大迎风面积的同时可以保持较高的转速,进而能够高效地实现风能的两级利用,明显提高发电功率和增大风能利用系数．