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In wind farm design, accurately predicting the wake turbulence level is crucial for turbine power and load evaluation. However, a knowledge gap still exists on the characteristics of wake turbulence, meanwhile there has been little work on the development of related engineering models. In view of this, firstly, one-dimensional analytical models that can estimate the wake width and maximum wake turbulence level at any streamwise positions are proposed and validated. Based on these, a highly simple three-dimensional cosine shape (3D-COTI) model is proposed for estimating the wake turbulence intensity in an effective way. Moreover, by taking into account the wind shear and ground effects, this proposed model is capable of describing the anisotropic property of the 3-D wake field. Afterwards, model evaluations are performed through several test cases consisting various types of turbines operating under a wide range of inflow conditions. Overall, the proposed model shows a good agreement with the measurements about the spatial distribution of turbulence enhancement within the wake flow. Because of its good accuracy, simplicity and universality, the present model has potential for large-scale wind farm applications. [ABSTRACT FROM AUTHOR]

The power generated by a wind turbine largely depends on the properties of wind resource. In this work, wind characteristics in different regimes occurring throughout the idealized diurnal cycle and its impact on wind turbine's power performance are investigated systematically by means of large-eddy simulation (LES), and blade element momentum method (BEM), respectively. Through a precursor simulation of the atmospheric boundary layer (ABL) over a homogenous surface throughout a day, it is found that the resulting shapes of wind profiles (including wind speed, wind direction and turbulence level) vary significantly at different time periods, induced by distinct stabilities of the atmosphere. The simulated wind field data are then applied to a NREL 5 MW wind turbine for its power evaluation. Due to variabilities in wind shear and turbulence, the equivalent (disk-averaged) wind speed is introduced for power prediction. It is found that the magnitude and fluctuation of turbine's diurnal power are closely related to the atmospheric stability. In general, the average power production is higher under convective conditions during the day than under stable conditions at night, with a difference approaching 24.4%. This indicates that wind energy resource assessment will close to reality and benefit from increased accuracy if atmospheric stability impacts are considered for turbine's power predictions. Image 1 • Explore the spatio-temporal structure of the diurnally-evolving ABL by LES method. • Induced by distinct ABL regimes, wind profiles vary significantly throughout a day. • Study the diurnal variation of wind turbine's instantaneous power performance. • Nearly 24.4% greater amount of power is produced during the day than at night. • Taking ABL stability into account would give a more meaningful power efficiency. [ABSTRACT FROM AUTHOR]

Most existing analytical wake models have been designed to represent the velocity distribution of the far wake region behind a wind turbine, but fail to reproduce the trend of the near wake. In order to meet the demand for both near and far wake velocity predictions, a concise three-dimensional dual-cosine shape (3D-COU) model is proposed. Moreover, by taking into account the wind shear and ground effects in the vertical direction, this model is capable of describing the anisotropic property of the 3-D wake field and is much closer to the reality. The proposed model is then calibrated and validated through a series of test cases, including different scales of turbines that are operating under a wide range of inflow conditions, and meanwhile the reference data resource is diverse. Overall, the results demonstrate that the 3D-COU model can accurately predict the variations of the wake velocity in both the vertical and horizontal directions throughout the whole wake region. Given its good accuracy, simplicity and applicability, this model provides the potential to effectively address practical problems in wind energy projects. [ABSTRACT FROM AUTHOR]

The improved analytical wake model named as 2D_k Jensen model (which was proposed to overcome some shortcomes in the classical Jensen wake model) is applied and validated in this work for wind turbine multi-wake predictions. Different from the original Jensen model, this newly developed 2D_k Jensen model uses a cosine shape instead of the top-hat shape for the velocity deficit in the wake, and the wake decay rate as a variable that is related to the ambient turbulence as well as the rotor generated turbulence. Coupled with four different multi-wake combination models, the 2D_k Jensen model is assessed through (1) simulating two wakes interaction under full wake and partial wake conditions and (2) predicting the power production in the Horns Rev wind farm for different wake sectors around two different wind directions. Through comparisons with field measurements, results from Large Eddy Simulations (LES) as well as results from other commercial codes, it is found that the predictions obtained with the 2D_k Jensen model exhibit good to excellent agreements with experimental and LES data. [ABSTRACT FROM AUTHOR]