scholarly journals Turbulence and entrainment length scales in large wind farms

Author(s):  
Søren J. Andersen ◽  
Jens N. Sørensen ◽  
Robert F. Mikkelsen

A number of large wind farms are modelled using large eddy simulations to elucidate the entrainment process. A reference simulation without turbines and three farm simulations with different degrees of imposed atmospheric turbulence are presented. The entrainment process is assessed using proper orthogonal decomposition, which is employed to detect the largest and most energetic coherent turbulent structures. The dominant length scales responsible for the entrainment process are shown to grow further into the wind farm, but to be limited in extent by the streamwise turbine spacing, which could be taken into account when developing farm layouts. The self-organized motion or large coherent structures also yield high correlations between the power productions of consecutive turbines, which can be exploited through dynamic farm control. This article is part of the themed issue ‘Wind energy in complex terrains’.

2021 ◽  
Author(s):  
Oliver Maas ◽  
Siegfried Raasch

Abstract. Germany’s expansion target for offshore wind power capacity of 40 GW by the year 2040 can only be reached if large portions of the Exclusive Economic Zone in the German Bight are equipped with wind farms. Because these wind farm clusters will be much larger than existing wind farms, it is unknown how they affect the boundary layer flow and how much power they will produce. The objective of this large-eddy-simulation study is to investigate the wake properties and the power output of very large potential wind farms in the German Bight for different turbine spacings, stabilities and boundary layer heights. The results show that very large wind farms cause flow effects that small wind farms do not. These effects include, but are not limited to, inversion layer displacement, counterclockwise flow deflection inside the boundary layer and clockwise flow deflection above the boundary layer. Wakes of very large wind farms are longer for shallower boundary layers and smaller turbine spacings, reaching values of more than 100 km. The wake in terms of turbulence intensity is approximately 20 km long, where longer wakes occur for convective boundary layers and shorter wakes for stable boundary layers. Very large wind farms in a shallow, stable boundary layer can excite gravity waves in the overlying free atmosphere, resulting in significant flow blockage. The power output of very large wind farms is higher for thicker boundary layers, because thick boundary layers contain more kinetic energy than thin boundary layers. The power density of the energy input by the geostrophic pressure gradient limits the power output of very large wind farms. Because this power density is very low (approximately 2 W m−2), the installed power density of very large wind farms should be small to achieve a good wind farm efficiency.


Author(s):  
Tanmoy Chatterjee ◽  
Yulia Peet

Wind Turbine Array Boundary Layer (WTABL) is a relatively simple, yet useful theoretical conceptualization to study very large wind farms in atmospheric boundary layer (ABL). In the current paper, we perform a high-fidelity LES investigation of a 3 × 3 wind turbine array in a WTABL framework, with a main focus on extending the work beyond the simple analytical model and providing a rigorous fundamental understanding of the dynamic behaviour of length scales, their scaling laws and the anisotropic structure of the energy containing eddies responsible for power generation from the wind turbines. This is accomplished by studying the components of energy and shear-stress spectra in the flow. This knowledge can potentially provide an efficient way to control the wind farm power output as well as serve as a stepping stone to design efficient low order numerical models for predicting farm power and dynamics at reduced computational expense.


2021 ◽  
Author(s):  
Gregor Giebel ◽  
Tuhfe Göçmen ◽  
Jakob Mann ◽  
Anna Maria Sempreviva ◽  
Haakon Lund ◽  
...  

<p>TRAIN<sup>2</sup>WIND is a PhD TRAINing school analysing enTRAINment in offshore WIND farms with computer models and experiments. By its very nature, a wind turbine extracts energy from the wind, which is replenished from the wind field on the sides and above due to the ambient turbulence. However, offshore the turbulence is lower, and wind farms are typically larger than onshore, therefore the wind can only be replenished from above in a process called entrainment. Train<sup>2</sup>Wind will investigate the entrainment process using advanced high-resolution computer modelling and wind tunnel models together with measurements of the wind field above, in and downstream of large wind farms, using lidars, radars, satellites and Unmanned Aerial Systems.</p><p>Besides the natural science package, one humanities PhD student at the University of Copenhagen will investigate the collaboration between the researchers from a social science and collaboration tools perspective.</p><p>The main work is done during the education of 18 fellows, where 13 embark on a PhD, while the other ones are employed for one year. The students will work with high-fidelity numerical simulations, lidars, unmanned aerial systems, wind tunnels and satellite data in order to understand entrainment of new momentum in very large wind farms. This changes the atmospheric boundary layer over a very extended wind farm, which becomes a wind turbine array boundary layer. The resulting change in wind resource is the main object of interest. The main planned activity is an experimental campaign at a major cluster of wind farms, probably in the North Sea. Another activity revolves around vertical axis turbines and their significantly different wake pattern, a potential mitigation measure.</p><p>So far we recruited the fellows and started with the simulations and the development of the hardware. We intend to employ a vertical take-off and landing model plane with a wing span of about 2m, which would allow to start and land from a helicopter pad offshore, and after the vertical start enjoy the advantage of a winged plane and its much larger range and endurance. Another instrument is a hexacopter mounted with a sonic anemometer, which allows to sample in a single point much akin a conventional met mast, but at any given point in or above a large wind farm. Lidar usage and development is part of the project as well, with a floating lidar in Bergen University and long-range lidars at DTU.</p><p>There are three numerical codes used in Train<sup>2</sup>Wind: Ellipsys3D, a Large Eddy Simulation (LES) high-fidelity code from DTU, WIRE-LES, another LES code from EPFL, and the Weather Research and Forecasting model run at DTU.</p><p>The outcome of the project is more knowledge of the entrainment process, and a guidance on how close to position clusters of wind farms in order not to exhaust the wind resource. The talk will give an overview of the project, highlighting the challenges.</p>


Author(s):  
Puyi Yang ◽  
Hamidreza Najafi

Abstract The accuracy of analytical wake models applied in wind farm layout optimization (WFLO) problems plays a vital role in the present era that the high-fidelity methods such as LES and RANS are still not able to handle an optimization problem for large wind farms. Based on a verity of analytical wake models developed in the past decades, FLOw Redirection and Induction in Steady State (FLORIS) has been published as a tool integrated several widely used wake models and the expansions for them. This paper compares four wake models selected from FLORIS by applying three classical WFLO scenarios. The results illustrate that the Jensen wake model is the fastest one but the defect of underestimation of velocity deficit is obvious. The Multi Zone model needs to be applied additional tunning on the parameters inside the model to fit specific wind turbines. The Gaussian-Curl wake model as an advanced expansion of the Gaussian wake model does not perform an observable improvement in the current study that the yaw control is not included. The default Gaussian wake model is recommended to be used in the WFLO projects which implemented under the FLROIS framework and has similar wind conditions with the present work.


2018 ◽  
Vol 42 (6) ◽  
pp. 547-560 ◽  
Author(s):  
Fa Wang ◽  
Mario Garcia-Sanz

The power generation of a wind farm depends on the efficiency of the individual wind turbines of the farm. In large wind farms, wind turbines usually affect each other aerodynamically at some specific wind directions. Previous studies suggest that a way to maximize the power generation of these wind farms is to reduce the generation of the first rows wind turbines to allow the next rows to generate more power (coordinated case). Yet, other studies indicate that the maximum generation of the wind farm is reached when every wind turbine works at its individual maximum power coefficient CPmax (individual case). This article studies this paradigm and proposes a practical method to evaluate when the wind farm needs to be controlled according to the individual or the coordinated case. The discussion is based on basic principles, numerical computations, and wind tunnel experiments.


Author(s):  
Takafumi Nishino ◽  
William Hunter

A new theoretical method is presented for future multi-scale aerodynamic optimization of very large wind farms. The new method combines a recent two-scale coupled momentum analysis of ideal wind turbine arrays with the classical blade-element-momentum (BEM) theory for turbine rotor design, making it possible to explore some potentially important relationships between the design of rotors and their performance in a very large wind farm. The details of the original two-scale momentum model are described first, followed by the new coupling procedure with the classical BEM theory and some example solutions. The example solutions, obtained using a simplified but still realistic NREL S809 aerofoil performance curve, illustrate how the aerodynamically optimal rotor design may change depending on the farm density. It is also shown that the peak power of the rotors designed optimally for a given farm (i.e. ‘tuned' rotors) could be noticeably higher than that of the rotors designed for a different farm (i.e. ‘untuned' rotors) even if the blade pitch angle is allowed to be adjusted optimally during the operation. The results presented are for ideal very large wind farms and a possible future extension of the present work for real large wind farms is also discussed briefly.


Wind Energy ◽  
2020 ◽  
Vol 23 (2) ◽  
pp. 423-431
Author(s):  
John Stephen Haywood ◽  
Adrian Sescu ◽  
Kevin Allan Adkins

2013 ◽  
Vol 715 ◽  
pp. 335-358 ◽  
Author(s):  
Johan Meyers ◽  
Charles Meneveau

AbstractAs a generalization of the mass–flux based classical stream tube, the concept of momentum and energy transport tubes is discussed as a flow visualization tool. These transport tubes have the property that no fluxes of momentum or energy exist over their respective tube mantles. As an example application using data from large eddy simulation, such tubes are visualized for the mean-flow structure of turbulent flow in large wind farms, in fully developed wind-turbine-array boundary layers. The three-dimensional organization of energy transport tubes changes considerably when turbine spacings are varied, enabling the visualization of the path taken by the kinetic energy flux that is ultimately available at any given turbine within the array.


2016 ◽  
Vol 33 (3) ◽  
pp. 481-501 ◽  
Author(s):  
Niranjan S. Ghaisas ◽  
Cristina L. Archer

AbstractLayout studies are critical in designing large wind farms, since wake effects can lead to significant reductions in power generation. Optimizing wind farm layout using computational fluid dynamics is practically unfeasible today because of their enormous computational requirements. Simple statistical models, based on geometric quantities associated with the wind farm layout, are therefore attractive because they are less demanding computationally. Results of large-eddy simulations of the Lillgrund (Sweden) offshore wind farm are used here to calibrate such geometry-based models. Several geometric quantities (e.g., blockage ratio, defined as the fraction of the swept area of a wind turbine that is blocked by upstream turbines) and their linear combinations are found to correlate very well (correlation coefficient of ~0.95) with the power generated by the turbines. Linear models based on these geometric quantities are accurate at predicting the farm-averaged power and are therefore used here to study layout effects in large wind farms. The layout parameters that are considered include angle between rows and columns, angle between incoming wind and columns (orientation), turbine spacings, and staggering of alternate rows. Each can impact wind power production positively or negatively, and their interplay is complex. The orientation angle is the most critical parameter influencing wake losses, as small changes in it can cause sharp variations in power. In general, for a prevailing wind direction, the orientation angle should be small (7.5°–20°) but not zero; staggering and spacing are beneficial; and nonorthogonal layouts may outperform orthogonal ones. This study demonstrates the utility of simple, inexpensive, and reasonably accurate geometry-based models to identify general principles governing optimal wind farm layout.


2020 ◽  
Author(s):  
Yu-Ting Wu ◽  
Yu-Hsiang Tsao

<p>A large-eddy simulation (LES) model, coupled with a dynamic actuator-disk model, is used to investigate the turbine power production and the turbine wake distribution in large wind farms where the streamwise turbine spacing of 7, 9, 12, 15, and 18 rotor diameters are considered. Two incoming flow conditions, three wind turbine arrangements, as well as the five turbine spacings are involved in this study, which leads to a total of 30 LES wind farm scenarios. The two incoming flow conditions have the same mean velocity of 9 m s<sup>-1</sup> but different turbulence intensity levels (i.e., 7% and 11%) at the hub height level. The considered turbine arrangements are the perfectly-aligned, laterally-staggered, and vertically-staggered layouts. The simulated results show that the turbine power production has a significant improvement by increasing the streamwise turbine spacing. With increasing the streamwise turbine spacing from 7 to 18 rotor diameters, the overall averaged power outputs are raised by about 27% in the staggered wind farms and about 38% in the aligned wind farms. The wind farm scenarios with the turbine spacing of 12d or greater in a large wind farm can lead to an increasing trend in the power production from the downstream turbines in the high-turbulence inflow condition, or also avoids the degradation of the power output on the turbines with the low-turbulence inflow condition. The flow adjustment above the wind farm results in the generation of the internal boundary layer (IBL), which grows up vertically along with the wake-wise direction. The growth of the IBL is found to be affected by the changes in the inflow condition and the turbine spacing. The IBL depth above the wind farms is found to be influenced by the turbine spacing, whereas the IBL depth in the downstream wake region of the wind farms shows a rapid increase under the high-turbulence inflow condition.</p>


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