The Effect of Free-Atmosphere Stratification on Boundary-Layer Flow and Power Output from Very Large Wind Farms

Abkar, Mahdi; Porté‐Agel, Fernando

doi:10.3390/en6052338

Cited by 119 publications

(132 citation statements)

References 42 publications

Supporting

Mentioning

120

Contrasting

Order By: Relevance

“…On the simulation side, this is similar to many neutral wind farm simulation studies, such as, e.g., [20,21]. Note that wind farm performance is strongly influenced by stratification in the boundary layer and the atmosphere aloft (see, e.g., [22][23][24]), and these conditions can be potentially very interesting for an optimal control study. However, this is not in the scope of the current work.…”

Section: Introductionsupporting

confidence: 68%

Optimal Coordinated Control of Power Extraction in LES of a Wind Farm with Entrance Effects

2016

View full text Add to dashboard Cite

Abstract:We investigate the use of optimal coordinated control techniques in large eddy simulations of wind farm boundary layer interaction with the aim of increasing the total energy extraction in wind farms. The individual wind turbines are considered as flow actuators, and their energy extraction is dynamically regulated in time, so as to optimally influence the flow field. We extend earlier work on wind farm optimal control in the fully-developed regime (Goit and Meyers 2015, J. Fluid Mech. 768, 5-50) to a 'finite' wind farm case, in which entrance effects play an important role. For the optimal control, a receding horizon framework is employed in which turbine thrust coefficients are optimized in time and per turbine. Optimization is performed with a conjugate gradient method, where gradients of the cost functional are obtained using adjoint large eddy simulations. Overall, the energy extraction is increased 7% by the optimal control. This increase in energy extraction is related to faster wake recovery throughout the farm. For the first row of turbines, the optimal control increases turbulence levels and Reynolds stresses in the wake, leading to better wake mixing and an inflow velocity for the second row that is significantly higher than in the uncontrolled case. For downstream rows, the optimal control mainly enhances the sideways mean transport of momentum. This is different from earlier observations by Goit and Meyers (2015) in the fully-developed regime, where mainly vertical transport was enhanced.

show abstract

Section: Introductionsupporting

confidence: 68%

Optimal Coordinated Control of Power Extraction in LES of a Wind Farm with Entrance Effects

2016

View full text Add to dashboard Cite

show abstract

“…The LES framework utilized in this study, which has been employed in previous wind-energy research studies (e.g., [17][18][19][20][21]), is based upon the filtered incompressible Navier-Stokes equations, including the Coriolis and buoyancy effects, and the filtered transport equation for the potential temperature,…”

Section: Les Governing Equationsmentioning

confidence: 99%

An Analytical Model for the Effect of Vertical Wind Veer on Wind Turbine Wakes

2018

Self Cite

View full text Add to dashboard Cite

Abstract:In this study, an analytical wake model for predicting the mean velocity field downstream of a wind turbine under veering incoming wind is systematically derived and validated. The new model, which is an extended version of the one introduced by Bastankhah and Porté-Agel, is based upon the application of mass conservation and momentum theorem and considering a skewed Gaussian distribution for the wake velocity deficit. Particularly, using a skewed (instead of axisymmetric) Gaussian shape allows accounting for the lateral shear in the incoming wind induced by the Coriolis force. This analytical wake model requires only the wake expansion rate as an input parameter to predict the mean wake flow downstream. The performance of the proposed model is assessed using the large-eddy simulation (LES) data of a full-scale wind turbine wake under the stably stratified condition. The results show that the proposed model is capable of predicting the skewed structure of the wake downwind of the turbine, and its prediction for the wake velocity deficit is in good agreement with the high-fidelity simulation data.

show abstract

“…For that reason, analytical modeling of wind farms has been and continues to be an important topic of research in the field of wind energy. Analytical wind farm models can be divided into two main types: Kinematic models (e.g., [5,6]) and distributed roughness models (e.g., [7][8][9]). Kinematic models consider each turbine wake individually and apply superposition principles to address the interaction of neighboring wakes.…”

Section: Introductionmentioning

confidence: 99%

Analytical Modeling of Wind Farms: A New Approach for Power Prediction

2016

Self Cite

View full text Add to dashboard Cite

Wind farm power production is known to be strongly affected by turbine wake effects. The purpose of this study is to develop and test a new analytical model for the prediction of wind turbine wakes and the associated power losses in wind farms. The new model is an extension of the one recently proposed by Bastankhah and Porté-Agel for the wake of stand-alone wind turbines. It satisfies the conservation of mass and momentum and assumes a self-similar Gaussian shape of the velocity deficit. The local wake growth rate is estimated based on the local streamwise turbulence intensity. Superposition of velocity deficits is used to model the interaction of the multiple wakes. Furthermore, the power production from the wind turbines is calculated using the power curve. The performance of the new analytical wind farm model is validated against power measurements and large-eddy simulation (LES) data from the Horns Rev wind farm for a wide range of wind directions, corresponding to a variety of full-wake and partial-wake conditions. A reasonable agreement is found between the proposed analytical model, LES data, and power measurements. Compared with a commonly used wind farm wake model, the new model shows a significant improvement in the prediction of wind farm power.

show abstract

The Effect of Free-Atmosphere Stratification on Boundary-Layer Flow and Power Output from Very Large Wind Farms

Cited by 119 publications

References 42 publications

Optimal Coordinated Control of Power Extraction in LES of a Wind Farm with Entrance Effects

Optimal Coordinated Control of Power Extraction in LES of a Wind Farm with Entrance Effects

An Analytical Model for the Effect of Vertical Wind Veer on Wind Turbine Wakes

Analytical Modeling of Wind Farms: A New Approach for Power Prediction

Contact Info

Product

Resources

About