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.     

Wind turbine partial wake merging description and quantification

Individual turbine location within a wind plant defines the flow characterisitcs experienced by a given turbine. Irregular turbine arrays and inflow misalignment can reduce plant efficiency by producing highly asymmetric wakes with enhanced downstream longevity. Changes in wake dynamics as a result of turbine position were quantified in a wind tunnel experiment. Scale model turbines with a rotor diameter of 20 cm and a hub height of 24 cm were placed in symmetric, asymmetric, and rotated configurations. Simultaneous hub height velocity measurements were recorded at 11 spanwise locations for three distances downstream of the turbine array under two inflow conditions. Wake interactions are described in terms of the time‐average streamwise velocity and turbulence intensity as well as the displacement, momentum, and energy thicknesses. The effects of wake merging on power generation are quantified, and the two‐point correlation is used to examine symmetry in the mean velocity between wakes. The results indicate that both asymmetric and rotated wind plant arrangements can produce long‐lasting wakes. At shallow angles, rotated configurations compound the effects of asymmetric arrangements and greatly increase downstream wake persistence.     

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.     

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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The flow in the induction and entrance regions of lab-scale wind farms

With the increasing demand for wind energy, it is important to be able to understand and predict the available wind resources. To that end, the present wind tunnel study addresses the flow in the induction and entrance region of wind farms through particle image velocimetry, with focus on differences between actuator disks and two-bladed rotating wind turbine models. Both staggered and aligned farm layouts are examined for three different incoming wind directions. For each layout, 69 disks or turbines are used, and the field of view ranges from 12 rotor diameters upstream of the farms to 8 diameters downstream of the first row. The results show that the induction, or blockage effect, is higher for the disks, even though the thrust (or drag) coefficient is the same. In contrast, the wake is stronger downstream of the turbines. The orientation and layout of the farm do not have a major impact on the results. Modal decomposition of the flow shows that the flow structure similarity between the disk and turbines improves downstream of the second row of wake generating objects, indicating that the substitution of wind turbines by actuator disks is more appropriate for wind farms than for the investigation of single wakes.     

Blockage effects in wind farms

An experimental study of wind farm blockage has been performed to quantify the velocity decrease that the first row of a wind farm experiences due to the presence of the other turbines downstream. The general perception has been that turbines downstream of the first row are only influenced by the wakes from upstream turbines without any upstream effect. In the present study, an attempt is made to demonstrate the existence of a two‐way coupling between individual turbines and turbines in the wind farm. Several staggered layouts were tested in the wind tunnel experiments by changing the spacing between rows, spacing between turbines in the rows, and the amount of wind turbines involved. The experiments focused on turbines located in the center of the first row as well as the two turbines located in the row edges, usually believed to experience a speedup. The present results show that no speedup is present and that all the turbines in the first row are subjected to a reduced wind speed. This phenomenon has been considered to be due to “global blockage.” An empirical correlation formula between spacing, number of rows, and velocity decrease is proposed to quantify such effect for the center turbine as well as for the turbines at the edges.     

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 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.     

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.     

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.     

Numerical investigation of wind turbine wake development in directionally sheared inflow

Turbines in wind farms are subject to complex mutual aerodynamic interactions, which in detail depend upon the characteristics of the atmospheric boundary layer. Our two objectives with this paper were to investigate the impact of directionally sheared inflow on the wake development behind a single wind turbine and to analyse the impact of the wakes on the energy yield and loading of a downstream turbine, which is exposed to partial and full wake conditions. We performed simulations with a framework based on a coupled approach of large‐eddy simulation and an actuator line representation of an aeroelastic turbine model. Our results show that directionally sheared inflow leads to a non‐symmetrical wake development, which transfers to distinct differences in the energy yield and loading of downstream turbines of equal lateral offsets in opposite direction. Therefore, the assumption of wakes being axisymmetrical could lead to notable deviations in the prediction of wake behaviour and their impact on downstream turbines for atmospheric inflow conditions, which include directional shear. Copyright © 2016 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.     

格尼襟翼垂直轴风力机风场研究

为研究垂直轴风力机风场中机组气动性能受格尼襟翼的影响,采用TSST湍流模型对直线翼垂直轴风力机进行数值模拟研究.结果表明:风场上游风力机组尖速比越大,机组间流体加速效果越显著,使风力机组气动性能高于单风力机;在中低尖速比时,格尼襟翼可有效提升单个风力机气动效率,在尖速比较高时,提升效果并不明显;在风力机组中安装格尼襟翼...     

Quantification of power losses due to wind turbine wake interactions through SCADA,meteorological and wind LiDAR data

Power production of an onshore wind farm is investigated through supervisory control and data acquisition data, while the wind field is monitored through scanning light detection and ranging measurements and meteorological data acquired from a met‐tower located in proximity to the turbine array. The power production of each turbine is analysed as functions of the operating region of the power curve, wind direction and atmospheric stability. Five different methods are used to estimate the potential wind power as a function of time, enabling an estimation of power losses connected with wake interactions. The most robust method from a statistical standpoint is that based on the evaluation of a reference wind velocity at hub height and experimental mean power curves calculated for each turbine and different atmospheric stability regimes. The synergistic analysis of these various datasets shows that power losses are significant for wind velocities higher than cut‐in wind speed and lower than rated wind speed of the turbines. Furthermore, power losses are larger under stable atmospheric conditions than for convective regimes, which is a consequence of the stability‐driven variability in wake evolution. Light detection and ranging measurements confirm that wind turbine wakes recover faster under convective regimes, thus alleviating detrimental effects due to wake interactions. For the wind farm under examination, power loss due to wake shadowing effects is estimated to be about 4% and 2% of the total power production when operating under stable and convective conditions, respectively. However, cases with power losses about 60‐80% of the potential power are systematically observed for specific wind turbines and wind directions. Copyright © 2017 John Wiley & Sons, Ltd.     

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.     

Near and far field flow disturbances induced by model hydrokinetic turbine: ADV and ADP comparison

Wake flows downstream of hydrokinetic turbines are characterized by hub and tip vortices, a velocity deficit and an increase in turbulence intensity. Velocity and turbulence recovery in the wakes of individual turbines constrains the density of turbines in an array and limits the amount of energy that can be produced by a turbine farm. However, few hydrokinetic turbine flow recovery studies have been conducted, especially on the far-field flow characteristics. Nor have studies evaluated the accuracy of acoustic Doppler profiler measurements in the wakes of turbines. The present study examines vertical profiles of mean velocity and turbulence, as well as longitudinal profiles of velocity deficit and turbulence levels measured at the symmetry plane of a model three-blade axial flow turbine in a large open channel flow. Mean velocity and turbulence statistics are measured using an acoustic Doppler velocimeter (ADV) and a pulse coherent acoustic Doppler profiler (ADP). ADV and corrected-ADP derived values of mean velocity, turbulence intensity and root-mean-square velocity constitute a well-documented data set that can be used to validate numerical models simulating the effects of hydrokinetic turbine arrays. We found that 80% of the flow recovery occurred about ten diameters downstream from the rotor plane, which suggests that practical values for longitudinal spacing of turbines should be between ten and fifteen diameters. Significant errors observed in mean velocity and turbulence statistics derived from ADP measurements in the near wake region raise concerns on the use of these instruments for such measurements in lab and field studies. Although the cause of some of the errors requires further investigation, we show that errors in turbulence intensity can be successfully corrected with supplemental ADV measurements.     

Effect of tower and nacelle on the flow past a wind turbine

Large eddy simulations (LES) of the flow past a wind turbine with and without tower and nacelle have been performed at 2 tip speed ratios (TSR, ), λ=3 and 6, where the latter corresponds to design conditions. The turbine model is placed in a virtual wind tunnel to reproduce the “Blind test 1” experiment performed at the Norwegian University of Science and Technology (NTNU) closed‐loop wind tunnel. The wind turbine was modeled using the actuator line model for the rotor blades and the immersed boundary method for the tower and nacelle. The aim of the paper is to highlight the impact of tower and nacelle on the turbine wake. Therefore, a second set of simulations with the rotating blades only (neglecting the tower and nacelle) has been performed as reference. Present results are compared with the experimental measurements made at NTNU and numerical simulations available in the literature. The tower and nacelle not only produce a velocity deficit in the wake but they also affect the turbulent kinetic energy and the fluxes. The wake of the tower interacts with that generated by the turbine blades promoting the breakdown of the tip vortex and increasing the mean kinetic energy flux into the wake. When tower and nacelle are modeled in the numerical simulations, results improve significantly both in the near wake and in the far wake.     

Optimization of turbine design in wind farms with multiple hub heights,using exact analytic gradients and structural constraints

Wind farms are generally designed with turbines of all the same hub height. If wind farms were designed with turbines of different hub heights, wake interference between turbines could be reduced, lowering the cost of energy (COE). This paper demonstrates a method to optimize onshore wind farms with two different hub heights using exact, analytic gradients. Gradient‐based optimization with exact gradients scales well with large problems and is preferable in this application over gradient‐free methods. Our model consisted of the following: a version of the FLOw Redirection and Induction in Steady‐State wake model that accommodated three‐dimensional wakes and calculated annual energy production, a wind farm cost model, and a tower structural model, which provided constraints during optimization. Structural constraints were important to keep tower heights realistic and account for additional mass required from taller towers and higher wind speeds. We optimized several wind farms with tower height, diameter, and shell thickness as coupled design variables. Our results indicate that wind farms with small rotors, low wind shear, and closely spaced turbines can benefit from having two different hub heights. A nine‐by‐nine grid wind farm with 70‐meter rotor diameters and a wind shear exponent of 0.08 realized a 4.9% reduction in COE by using two different tower sizes. If the turbine spacing was reduced to 3 diameters, the reduction in COE decreased further to 11.2%. Allowing for more than two different turbine heights is only slightly more beneficial than two heights and is likely not worth the added complexity.     

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.