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Wake effects increase the fatigue loads on wind turbines in operation. However, the wake flow is considerably different from the traditional boundary layer flow, and poses many challenges in determining the fatigue loads on wind turbines operating in a wake. Therefore, in the present study, the actuator‐line model was adopted to numerically simulate the wake flow and an in‐house code named AOWT, which is based on a generalized coordinate method, was developed for analyzing the dynamics of wind turbines under an arbitrary distribution of the turbulent flow field varying in time and space. Using the numerically modeled instantaneous wake flow fields and AOWT, the dynamic response of a wind turbine, located at specified positions in both tandem and staggered arrangements in a wake, was examined, and the fatigue loads were determined. Furthermore, to determine the major contributions to the fatigue loads, the loads induced by the spatial variation of the mean flow fields were predicted. To the best of the authors' knowledge, no such analysis has been conducted thus far. Importantly, it was found that in the near‐wake region, the mean flow field had a significant influence on the fatigue loads, especially in the staggered layout. However, there is no analytical wake model available in the literature capable of predicting the near‐wake mean flow fields. Therefore, in this study, a near‐wake model was proposed, which yielded satisfactory predictions of the mean velocities in the near‐wake region. [ABSTRACT FROM AUTHOR]

The downwind rotor configuration provides a structural advantage compared with an upwind design. However, tower shadow has long been a concern for downwind systems. The tower shadow negatively affects the blade by introducing a load impulse during the wake passage. An aerodynamic fairing could shroud the tower reducing the wake. However, there is no clear consensus on the importance of a tower shadow for utility‐scale wind turbines. Simulations were conducted in FAST to determine the general parameters that influence the importance of the tower shadow effect for the differently sized wind turbines. The lock number of the blade was a significant driving quantity. Lower lock numbers (typical of small‐scale wind turbines) lead to greater relative fatigue damage from tower shadow effects. It was determined that a fairing is very helpful for small‐scale wind turbines operating in a low‐turbulence environment (such as a subscale wind tunnel test). However, the tower shadow increased the damage equivalent loading on an extreme scale blade by less than 5% in a turbulent environment. These results indicate that the cost of a tower fairing is likely unnecessary for utility‐scale wind turbines in operation. [ABSTRACT FROM AUTHOR]

In order to study the effect of vertical staggering in large wind farms, large eddy simulations (LES) of large wind farms with a regular turbine layout aligned with the given wind direction were conducted. In the simulations, we varied the hub heights of consecutive downstream rows to create vertically staggered wind farms. We analysed the effect of streamwise and spanwise turbine spacing, the wind farm layout, the turbine rotor diameter, and hub height difference between consecutive downstream turbine rows on the average power output. We find that vertical staggering significantly increases the power production in the entrance region of large wind farms and is more effective when the streamwise turbine spacing and turbine diameter are smaller. Surprisingly, vertical staggering does not significantly improve the power production in the fully developed regime of the wind farm. The reason is that the downward vertical kinetic energy flux, which brings high velocity fluid from above the wind farm towards the hub height plane, does not increase due to vertical staggering. Thus, the shorter wind turbines are effectively sheltered from the atmospheric flow above the wind farm that supplies the energy, which limits the benefit of vertical staggering. In some cases, a vertically staggered wind farm even produced less power than the corresponding non vertically staggered reference wind farm. In such cases, the production of shorter turbines is significantly negatively impacted while the production of the taller turbine is only increased marginally. [ABSTRACT FROM AUTHOR]

Understanding the detailed dynamics of wind turbine wakes is critical to predicting the performance and maximizing the efficiency of wind farms. This knowledge requires atmospheric data at a high spatial and temporal resolution, which are not easily obtained from direct measurements. Therefore, research is often based on numerical models, which vary in fidelity and computational cost. The simplest models produce axisymmetric wakes and are only valid beyond the near wake. Higher-fidelity results can be obtained by solving the filtered Navier-Stokes equations at a resolution that is sufficient to resolve the relevant turbulence scales. This work addresses the gap between these two extremes by proposing a stochastic model that produces an unsteady asymmetric wake. The model is developed based on a large-eddy simulation (LES) of an offshore wind farm. Because there are several ways of characterizing wakes, the first part of this work explores different approaches to defining global wake characteristics. From these, a model is developed that captures essential features of a LES-generated wake at a small fraction of the cost. The synthetic wake successfully reproduces the mean characteristics of the original LES wake, including its area and stretching patterns, and statistics of the mean azimuthal radius. The mean and standard deviation of the wake width and height are also reproduced. This preliminary study focuses on reproducing the wake shape, while future work will incorporate velocity deficit and meandering, as well as different stability scenarios. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We describe a generalization of the coupled wake boundary layer (CWBL) model for wind farms that can be used to evaluate the performance of wind farms under arbitrary wind inflow directions, whereas the original CWBL model (Stevens et al., J. Renewable and Sustainable Energy 7, 023115 (2015)) focused on aligned or staggered wind farms. The generalized CWBL approach combines an analytical Jensen wake model with a 'top-down' boundary layer model coupled through an iterative determination of the wake expansion coefficient and an effective wake coverage area for which the velocity at hub-height obtained using both models converges in the 'deep-array' portion (fully developed region) of the wind farm. The approach accounts for the effect of the wind direction by enforcing the coupling for each wind direction. Here, we present detailed comparisons of model predictions with large eddy simulation results and field measurements for the Horns Rev and Nysted wind farms operating over a wide range of wind inflow directions. Our results demonstrate that two-way coupling between the Jensen wake model, and a 'top-down' model enables the generalized CWBL model to predict the 'deep-array' performance of a wind farm better than the Jensen wake model alone. The results also show that the new generalization allows us to study a much larger class of wind farms than the original CWBL model, which increases the utility of the approach for wind farm designers. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We present a methodology to process wind turbine wake simulations, which are closely related to the nature of wake observations and the processing of these to generate the so-called wake cases. The method involves averaging a large number of wake simulations over a range of wind directions and partly accounts for the uncertainty in the wind direction assuming that the same follows a Gaussian distribution. Simulations of the single and double wake measurements at the Sexbierum onshore wind farm are performed using a fast engineering wind farm wake model based on the Jensen wake model, a linearized computational fluid dynamics wake model by Fuga and a nonlinear computational fluid dynamics wake model that solves the Reynolds-averaged Navier-Stokes equations with a modified k- ε turbulence model. The best agreement between models and measurements is found using the Jensen-based wake model with the suggested post-processing. We show that the wake decay coefficient of the Jensen wake model must be decreased from the commonly used onshore value of 0.075 to 0.038, when applied to the Sexbierum cases, as wake decay is related to the height, roughness and atmospheric stability and, thus, to turbulence intensity. Based on surface layer relations and assumptions between turbulence intensity and atmospheric stability, we find that at Sexbierum, the atmosphere was probably close to stable, although the stability was not observed. We support these assumptions using detailed meteorological observations from the Høvsøre site in Denmark, which is topographically similar to the Sexbierum region. © 2015 The Authors. Wind Energy published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

An engineering model is presented for predicting the performance of a single turbine located in an incoming turbulent, sheared, wind velocity field. The approach used is a variant of the well-known and documented Ainslie eddy viscosity approach as also employed in the Direct Wake Meandering model. It incorporates a new and simple means of representing the rotor's loading profile, initializing the calculations, simplifying the wakes' shear layer mixing model and accounting for wind shear effects. Additionally, two figures of merit are employed for assessing the reliability of all data used and predictions provided. The first, a wake momentum-flux/thrust parameter, is used for quantitatively assessing the accuracy and utility of both measured and/or computational wake data. The second, a rotor swept area wake-averaged velocity, is employed as a single quantitative measure of a turbine's impact on its downstream neighbor. Through detailed comparisons with three independent state-of-the-art Computational Fluid Dynamic generated datasets and a field-measured dataset, the current model is shown to be accurate for turbine rated power levels from 100 kW to 2.3 MW, wind speeds of 6 to 22 m s−1 (corresponding to turbine thrust coefficient levels of 0.14 to 0.8) and free-stream turbulence levels from 0% to 16%. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Mean and turbulent properties of the wake generated by a single wind turbine are studied in this paper with a new large eddy simulation (LES) code, the wind turbine and turbulence simulator (WiTTS hereafter). WiTTS uses a scale-dependent Lagrangian dynamical model of the sub-grid shear stress and actuator lines to simulate the effects of the rotating blades. WiTTS is first tested by simulating neutral boundary layers without and with a wind turbine and then used to study the common assumptions of self-similarity and axisymmetry of the wake under neutral conditions for a variety of wind speeds and turbine properties. We find that the wind velocity deficit generally remains self similarity to a Gaussian distribution in the horizontal. In the vertical, the Gaussian self-similarity is still valid in the upper part of the wake, but it breaks down in the region of the wake close to the ground. The horizontal expansion of the wake is always faster and greater than the vertical expansion under neutral stability due to wind shear and impact with the ground. Two modifications to existing equations for the mean velocity deficit and the maximum added turbulence intensity are proposed and successfully tested. The anisotropic wake expansion is taken into account in the modified model of the mean velocity deficit. Turbulent kinetic energy (TKE) budgets show that production and advection exceed dissipation and turbulent transport. The nacelle causes significant increase of every term in the TKE budget in the near wake. In conclusion, WiTTS performs satisfactorily in the rotor region of wind turbine wakes under neutral stability. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]