Time-Averaged Wind Turbine Wake Flow Field Prediction Using Autoencoder Convolutional Neural Networks

A convolutional neural network (CNN) autoencoder model has been developed to generate 3D realizations of time-averaged velocity in the wake of the wind turbines at the Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility. Large-eddy simulations (LES) of the SWiFT site are conducted using an actuator surface model to simulate the turbine structures to produce training and validation datasets of the CNN. The simulations are validated using the SpinnerLidar measurements of turbine wakes at the SWiFT site and the instantaneous and time-averaged velocity fields from the training LES are used to train the CNN. The trained CNN is then applied to predict 3D realizations of time-averaged velocity in the wake of the SWiFT turbines under flow conditions different than those for which the CNN was trained. LES results for the validation cases are used to evaluate the performance of the CNN predictions. Comparing the validation LES results and CNN predictions, we show that the developed CNN autoencoder model holds great potential for predicting time-averaged flow fields and the power production of wind turbines while being several orders of magnitude computationally more efficient than LES.

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Analytical model for the power–yaw sensitivity of wind turbines operating in full wake

Wind Energy Science ◽

10.5194/wes-5-427-2020 ◽

2020 ◽

Vol 5 (1) ◽

pp. 427-437 ◽

Cited By ~ 2

Author(s):

Jaime Liew ◽

Albert M. Urbán ◽

Søren Juhl Andersen

Keyword(s):

Wind Turbines ◽

Wind Farm ◽

Power Production ◽

Wake Flow ◽

High Fidelity ◽

Combined Effects ◽

Wind Farm Optimization ◽

Computational Fluid Dynamics Simulations ◽

Dynamics Simulations ◽

Blade Element

Abstract. Wind turbines are designed to align themselves with the incoming wind direction. However, turbines often experience unintentional yaw misalignment, which can significantly reduce the power production. The unintentional yaw misalignment increases for turbines operating in the wake of upstream turbines. Here, the combined effects of wakes and yaw misalignment are investigated, with a focus on the resulting reduction in power production. A model is developed, which considers the trajectory of each turbine blade element as it passes through the wake inflow in order to determine a power–yaw loss exponent. The simple model is verified using the HAWC2 aeroelastic code, where wake flow fields have been generated using both medium- and high-fidelity computational fluid dynamics simulations. It is demonstrated that the spatial variation in the incoming wind field, due to the presence of wakes, plays a significant role in the power loss due to yaw misalignment. Results show that disregarding these effects on the power–yaw loss exponent can yield a 3.5 % overestimation in the power production of a turbine misaligned by 30∘. The presented analysis and model is relevant to low-fidelity wind farm optimization tools, which aim to capture the combined effects of wakes and yaw misalignment as well as the uncertainty on power output.

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Do Wind Turbines Pose Roll Hazards to Light Aircraft?

10.5194/wes-2018-42 ◽

2018 ◽

Author(s):

Jessica M. Tomaszewski ◽

Julie K. Lundquist ◽

Matthew J. Churchfield ◽

Patrick J. Moriarty

Keyword(s):

Wind Turbines ◽

Wind Farm ◽

The United States ◽

General Aviation ◽

Open Spaces ◽

Increased Risk ◽

Large Eddy ◽

Utility Scale ◽

Turbine Wake ◽

Small Aircraft

Abstract. Wind energy accounted for 5.6 % of all electricity generation in the United States in 2016. Much of this development has occurred in rural locations, where open spaces favorable for harnessing wind also serve general aviation airports. As such, nearly 40 % of all U.S. wind turbines exist within 10 km of a small airport. Wind turbines generate electricity by extracting momentum from the atmosphere, creating downwind wakes characterized by wind-speed deficits and increased turbulence. Recently, the concern that turbine wakes pose hazards for small aircraft has been used to limit wind farm development. Herein, we assess roll hazards to small aircraft using large-eddy simulations of a utility-scale turbine wake. Wind-generated rolling moments on hypothetical aircraft transecting the wake in stably and neutrally stratified conditions are calculated. In both cases, only 0.001 % of rolling moments experienced by hypothetical aircraft during down-wake and cross-wake transects lead to an increased risk of rolling.

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Near wake analysis of actuator line method immersed in turbulent flow using large-eddy simulations

10.5194/wes-2018-9 ◽

2018 ◽

Author(s):

Jörn Nathan ◽

Christian Masson ◽

Louis Dufresne

Keyword(s):

Wind Farm ◽

Isotropic Turbulence ◽

Large Eddy Simulations ◽

Energy Output ◽

Flow Conditions ◽

Wind Tunnel Experiments ◽

Near Wake ◽

Large Eddy ◽

Distribution Kernel ◽

Global Indicator

Abstract. The interaction between wind turbines through their wakes is an important aspect of the conception and operation of a wind farm. Wakes are characterized by an elevated turbulence level and a noticable velocity deficit which causes a decrease in energy output and fatigue on downstream turbines. In order to gain a better understanding of this phenomenon this works uses large-eddy simulations together with an actuator line model and different ambient turbulences imposed as boundary conditions. This is achieved by using the SOWFA framework from NREL (USA) which is first validated against another popular CFD framework for wind energy, EllipSys3D, and then verified against the experimental results from the MEXICO and NEW MEXICO wind tunnel experiments. By using the predicted torque as a global indicator, the optimal width of the distribution kernel for the actuator line is determined for different grid resolutions. Then the rotor is immersed in homogeneous isotropic turbulence and a shear layer turbulence with different turbulence intensities, allowing to determine how far downstream the effect of the distinct blades is discernible. This can be used as an indicator for the extents of the near wake for different flow conditions

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Analytical model for the power-yaw sensitivity of wind turbines operating in full wake

10.5194/wes-2019-65 ◽

2019 ◽

Cited By ~ 1

Author(s):

Jaime Liew ◽

Albert M. Urbán ◽

Søren Juhl Andersen

Keyword(s):

Wind Turbines ◽

Wind Field ◽

Wind Farm ◽

Power Production ◽

Loss Coefficient ◽

Wake Flow ◽

Wind Farm Optimization ◽

Wake Effects ◽

Computational Fluid Dynamics Simulations ◽

Dynamics Simulations

Abstract. Wind turbines are designed to align themselves with the incoming wind direction. However, turbines often experience unintentional yaw misalignment, which can significantly reduce the power production. The unintentional yaw misalignment increase for turbines operating in wake of upstream turbines. Here, the combined effects of wakes and yaw misalignment are investigated with the resulting reduction in power production. A model is developed, which considers the trajectory of each turbine blade element as it passes through the waked wind field in order to determine a power-yaw loss coefficient. The simple model is verified using the HAWC2 aeroelastic code, where wake flow fields have been generated using both medium and high-fidelity computational fluid dynamics simulations. It is demonstrated that the spatial variation of the incoming wind field, due to the presence of wake(s), plays a significant role in the power loss due to yaw misalignment. Results show that disregarding these effects on the power-yaw loss coefficient can yield a 3.5 % overestimation in the power production of a turbine misaligned by 30°. The presented analysis and model is relevant to low-fidelity wind farm optimization tools, which aim to capture the effects of wake effects and yaw misalignment as well as uncertainty on power output.

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Large Eddy Simuation of an Onshore Wind Farm with the Actuator Line Model Including Wind Turbine’s Control Below and Above Rated Wind Speed

Energies ◽

10.3390/en12183508 ◽

2019 ◽

Vol 12 (18) ◽

pp. 3508 ◽

Cited By ~ 5

Author(s):

Andrés Guggeri ◽

Martín Draper

Keyword(s):

Wind Speed ◽

Wind Turbines ◽

Wind Farm ◽

Fluid Dynamic ◽

Power Production ◽

Model Framework ◽

Line Model ◽

Onshore Wind ◽

Large Eddy ◽

Actuator Line Model

As the size of wind turbines increases and their hub heights become higher, which partially explains the vertiginous increase of wind power worldwide in the last decade, the interaction of wind turbines with the atmospheric boundary layer (ABL) and between each other is becoming more complex. There are different approaches to model and compute the aerodynamic loads, and hence the power production, on wind turbines subject to ABL inflow conditions ranging from the classical Blade Element Momentum (BEM) method to Computational Fluid Dynamic (CFD) approaches. Also, modern multi-MW wind turbines have a torque controller and a collective pitch controller to manage power output, particularly in maximizing power production or when it is required to down-regulate their production. In this work the results of a validated numerical method, based on a Large Eddy Simulation-Actuator Line Model framework, was applied to simulate a real 7.7 MNW onshore wind farm on Uruguay under different wind conditions, and hence operational situations are shown with the aim to assess the capability of this approach to model actual wind farm dynamics. A description of the implementation of these controllers in the CFD solver Caffa3d, presenting the methodology applied to obtain the controller parameters, is included. For validation, the simulation results were compared with 1 Hz data obtained from the Supervisory Control and Data Acquisition System of the wind farm, focusing on the temporal evolution of the following variables: Wind velocity, rotor angular speed, pitch angle, and electric power. In addition to this, simulations applying active power control at the wind turbine level are presented under different de-rate signals, both constant and time-varying, and were subject to different wind speed profiles and wind directions where there was interaction between wind turbines and their wakes.

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An Investigation of Wind Farm Power Production for Various Atmospheric Boundary Layer Heights

Journal of Energy Resources Technology ◽

10.1115/1.4037311 ◽

2017 ◽

Vol 139 (5) ◽

Cited By ~ 4

Author(s):

A. Al Sam ◽

R. Szasz ◽

J. Revstedt

Keyword(s):

Boundary Layer ◽

Atmospheric Boundary Layer ◽

Wind Shear ◽

Wind Farm ◽

Power Production ◽

Large Eddy Simulations ◽

Power Coefficient ◽

Higher Power ◽

Large Eddy ◽

Aerodynamic Roughness

The dependency of the atmospheric boundary layer (ABL) characteristics on the ABL’s height is investigated by using large eddy simulations (LES). The impacts of ABL’s height on the wind turbine (WT) power production are also investigated by simulating two subsequent wind turbines using the actuator line method (ALM). The results show that, for the same driving pressure forces and aerodynamic roughness height, the wind velocity is higher at deeper ABL, while the wind shear and the wind veer are not affected by the depth. Moreover, the turbulence intensity, kinetic energy, and kinematic shear stress increase with the ABL’s height. Higher power production and power coefficient are obtained from turbines operating at deeper ABL.

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Optimal control of energy extraction in wind-farm boundary layers

Journal of Fluid Mechanics ◽

10.1017/jfm.2015.70 ◽

2015 ◽

Vol 768 ◽

pp. 5-50 ◽

Cited By ~ 91

Author(s):

Jay P. Goit ◽

Johan Meyers

Keyword(s):

Boundary Layer ◽

Optimal Control ◽

Boundary Layers ◽

Wind Turbines ◽

Wind Farm ◽

Large Eddy Simulations ◽

Energy Extraction ◽

Reynolds Stresses ◽

Turbulent Dissipation ◽

Large Eddy

In very large wind farms, the vertical interaction with the atmospheric boundary layer plays an important role, i.e. the total energy extraction is governed by the vertical transport of kinetic energy from higher regions in the boundary layer towards the turbine level. In the current study, we investigate optimal control of wind-farm boundary layers, considering the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the flow field and the vertical energy transport. To this end, we use large-eddy simulations of a fully developed pressure-driven wind-farm boundary layer in a receding-horizon optimal control framework. For the optimization of the wind-turbine controls, a conjugate-gradient optimization method is used in combination with adjoint large-eddy simulations for the determination of the gradients of the cost functional. In a first control study, wind-farm energy extraction is optimized in an aligned wind farm. Results are accumulated over one hour of operation. We find that the energy extraction is increased by 16 % compared to the uncontrolled reference. This is directly related to an increase of the vertical fluxes of energy towards the wind turbines, and vertical shear stresses increase considerably. A further analysis, decomposing the total stresses into dispersive and Reynolds stresses, shows that the dispersive stresses increase drastically, and that the Reynolds stresses decrease on average, but increase in the wake region, leading to better wake recovery. We further observe also that turbulent dissipation levels in the boundary layer increase, and overall the outer layer of the boundary layer enters into a transient decelerating regime, while the inner layer and the turbine region attain a new statistically steady equilibrium within approximately one wind-farm through-flow time. Two additional optimal control cases study penalization of turbulent dissipation. For the current wind-farm geometry, it is found that the ratio between wind-farm energy extraction and turbulent boundary-layer dissipation remains roughly around 70 %, but can be slightly increased by a few per cent by penalizing the dissipation in the optimization objective. For a pressure-driven boundary layer in equilibrium, we estimate that such a shift can lead to an increase in wind-farm energy extraction of 6 %.

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Large Eddy Simulations of Curled Wakes from Tilted Wind Turbines

SSRN Electronic Journal ◽

10.2139/ssrn.3875189 ◽

2021 ◽

Author(s):

Hannah M. Johlas ◽

David P. Schmidt ◽

Matthew A. Lackner

Keyword(s):

Wind Turbines ◽

Large Eddy Simulations ◽

Large Eddy

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Investigation on hydrodynamic forces leading to coarse particle entrainment using Large-Eddy Simulations

10.5194/egusphere-egu21-13221 ◽

2021 ◽

Author(s):

Gaston Latessa ◽

Angela Busse ◽

Manousos Valyrakis

Keyword(s):

Experimental Data ◽

Flow Field ◽

Large Scale ◽

Large Eddy Simulations ◽

Flow Conditions ◽

Mean Flow ◽

Protection Measures ◽

Practical Applications ◽

Particle Entrainment ◽

Large Eddy

The prediction of particle motion in a fluid flow environment presents several challenges from the quantification of the forces exerted by the fluid onto the solids -normally with fluctuating behaviour due to turbulence- and the definition of the potential particle entrainment from these actions. An accurate description of these phenomena has many practical applications in local scour definition and to the design of protection measures.In the present work, the actions of different flow conditions on sediment particles is investigated with the aim to translate these effects into particle entrainment identification through analytical solid dynamic equations.Large Eddy Simulations (LES) are an increasingly practical tool that provide an accurate representation of both the mean flow field and the large-scale turbulent fluctuations. For the present case, the forces exerted by the flow are integrated over the surface of a stationary particle in the streamwise (drag) and vertical (lift) directions, together with the torques around the particle&#8217;s centre of mass. These forces are validated against experimental data under the same bed and flow conditions.The forces are then compared against threshold values, obtained through theoretical equations of simple motions such as rolling without sliding. Thus, the frequency of entrainment is related to the different flow conditions in good agreement with results from experimental sediment entrainment research.A thorough monitoring of the velocity flow field on several locations is carried out to determine the relationships between velocity time series at several locations around the particle and the forces acting on its surface. These results a relevant to determine ideal locations for flow investigation both in numerical and physical experiments.Through numerical experiments, a large number of flow conditions were simulated obtaining a full set of actions over a fixed particle sitting on a smooth bed. These actions were translated into potential particle entrainment events and validated against experimental data. Future work will present the coupling of these LES models with Discrete Element Method (DEM) models to verify the entrainment phenomena entirely from a numerical perspective.

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