Large-Eddy Simulations of Two In-Line Turbines in a Wind Tunnel with Different Inflow Conditions

Ciri, Umberto; Petrolo, Giovandomenico; Salvetti, Maria Vittoria; Leonardi, Stefano

doi:10.3390/en10060821

Cited by 31 publications

(25 citation statements)

References 48 publications

(62 reference statements)

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“…The turbine tower and nacelle are directly simulated using the immersed boundary method . UTD‐WF has been previously validated against measurements from wind tunnel experiments on model wind turbines …”

Section: Methodsmentioning

confidence: 99%

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Effect of the turbine scale on yaw control

2018

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Yaw misalignment between the incoming wind and the rotor of a turbine causes a lateral displacement of the wake. This effect can be exploited to avoid or mitigate wake interactions in wind farms, so that power losses are minimized. We performed large‐eddy simulations to evaluate yaw control for a three‐turbine wind farm. We used two different turbine models to assess how the size of the turbine rotor affects the farm efficiency and the effectiveness of the control strategy. A utility‐scale wind turbine with rotor diameter of 126 m is compared with a scaled research wind turbine with rotor diameter of 27 m. In both cases, a model‐free algorithm is used to determine the turbine yaw set point, which maximizes total power production. The algorithm is the nested extremum‐seeking control (NESC), which allows for the coordinated optimization of the wind turbine operating points. The results achieved with NESC are validated by computing a static performance map for different yaw angles. NESC converges to optimal operating conditions, which are in good agreement with the static map benchmark. Numerical results show that a larger rotor diameter induces larger wake deflection, thus achieving higher power improvements. From the analysis of the turbine structural loads, an increase in damage equivalent load is observed for both the yawed turbine and the waked one. Present results suggest that there is a cost‐effective trade‐off between performance and loads for large turbines.

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Section: Methodsmentioning

confidence: 99%

“…20 UTD-WF has been previously validated against measurements from wind tunnel experiments on model wind turbines. 21,22 The rotational speed of the turbine, Ω, is determined by the angular momentum balance:…”

Section: Methodsmentioning

confidence: 99%

Effect of the turbine scale on yaw control

2018

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“…The viscous terms are treated implicitly while the nonlinear ones are treated explicitly. For the subgrid scale stress tensor, Smagorinsky closure is employed with

C_{S} = 0.09

based on previous works …”

Section: Methodsmentioning

confidence: 99%

“…For subgrid stress tensor, the Smagorinsky model, with Van Driest damping near the walls, is employed with a constant of

C_{s} = 0.09

. This value has been chosen based on previous works . All the quantities in the present work are made dimensionless by using the chord length (

c

), the fluid density (

ρ

), and the freestream velocity (

U_{\infty}

).…”

Section: Validation and Main Wake Featuresmentioning

confidence: 99%

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Appraisal and calibration of the actuator line model for the prediction of turbulent separated wakes

et al. 2020

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The aim of this study is to further investigate the accuracy and the reliability of the actuator line model (ALM) predictions for turbulent separated wakes. Large eddy simulations (LES) of the flow around a NACA0009 airfoil are performed mimicking the geometry with the immersed boundary method. Results are validated against experiments and used to assess the accuracy of the ALM predictions for the same airfoil, with different values of the spreading parameter and of the reference velocity and for two values of the angle of attack. It is found that the ALM setup recently derived from linearized inviscid analysis leads to accurate results for the lower angle of attack, while at the higher one for which a significant separation of the boundary layer occurs, the ALM requires a different set of model parameters. This calls for a systematic investigation of the sensitivity to the ALM parameters for separated flows, which is carried out herein through a stochastic approach allowing continuous response surfaces to be obtained in the parameter space. The ALM parameters are calibrated against the results obtained with the immersed boundaries. With the calibrated model parameters, the ALM gives good predictions of the velocity and turbulent kinetic energy in the far wake. Finally, the proposed model parameters are used to predict the flow past a different geometry, a flat plate, at high angle of attack.The accuracy of the prediction of the far wake is again good, showing the robustness of the identified setup. KEYWORDS actuator line model, generalized Polynomial Chaos expansion, stochastic sensitivity analysis, turbulent wake 1In the actuator line model (ALM), the force is distributed in a small region centered into the line representing the blade position. The spreading kernel is typically a Gaussian function of the distance from the actuator line position. The standard deviation of the Gaussian kernel, , determines the width of the spreading. The ALM is known to represent more accurately the wake flow features than similar models, like the actuator disk or the rotating actuator disk, which have lower computational cost. [3][4][5] However, the flow obtained with the ALM strongly depends on the spreading parameter ( ). There are no definitive guidelines to set this input parameter. For numerical stability, it is suggested that the spreading parameter be at least twice the grid spacing, in order to avoid singularities due to a pointwise force. 6 This was confirmed by Martínez et al. 3 who investigated the sensitivity to the spreading to grid-spacing ratio as well as to the grid resolution for a fixed spreading value. Shives and Crawford suggested 7 that the spreading parameter should be related to the local chord length ( ∕c ≃ 1∕8-1∕4) and thus vary along the radial direction for a common wind turbine blade geometry. An analogous approach was also pursued by Jha et al. 8 and Jha and Schmitz 9 defining an equivalent elliptic blade planform.Recently, Martìnez et al 10 carried out analytical computations using the linearized Eu...

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

et al. 2020

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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.

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Large-Eddy Simulations of Two In-Line Turbines in a Wind Tunnel with Different Inflow Conditions

Cited by 31 publications

References 48 publications

Effect of the turbine scale on yaw control

Effect of the turbine scale on yaw control

Appraisal and calibration of the actuator line model for the prediction of turbulent separated wakes

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

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