scholarly journals Distinct Turbulent Regions in the Wake of a Wind Turbine and Their Inflow-Dependent Locations: The Creation of a Wake Map

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5392
Author(s):  
Ingrid Neunaber ◽  
Michael Hölling ◽  
Richard J. A. M. Stevens ◽  
Gerard Schepers ◽  
Joachim Peinke

Wind turbines are usually clustered in wind farms which causes the downstream turbines to operate in the turbulent wakes of upstream turbines. As turbulence is directly related to increased fatigue loads, knowledge of the turbulence in the wake and its evolution are important. Therefore, the main objective of this study is a comprehensive exploration of the turbulence evolution in the wind turbine’s wake to identify characteristic turbulence regions. For this, we present an experimental study of three model wind turbine wake scenarios that were scanned with hot-wire anemometry with a very high downstream resolution. The model wind turbine was exposed to three inflows: laminar inflow as a reference case, a central wind turbine wake, and half of the wake of an upstream turbine. A detailed turbulence analysis reveals four downstream turbulence regions by means of the mean velocity, variance, turbulence intensity, energy spectra, integral and Taylor length scales, and the Castaing parameter that indicates the intermittency, or gustiness, of turbulence. In addition, a wake core with features of homogeneous isotropic turbulence and a ring of high intermittency surrounding the wake can be identified. The results are important for turbulence modeling in wakes and optimization of wind farm wake control.

2019 ◽  
Vol 869 ◽  
pp. 1-26 ◽  
Author(s):  
Daniel Foti ◽  
Xiaolei Yang ◽  
Lian Shen ◽  
Fotis Sotiropoulos

Wake meandering, a phenomenon of large-scale lateral oscillation of the wake, has significant effects on the velocity deficit and turbulence intensities in wind turbine wakes. Previous studies of a single turbine (Kang et al., J. Fluid. Mech., vol. 774, 2014, pp. 374–403; Foti et al., Phys. Rev. Fluids, vol. 1 (4), 2016, 044407) have shown that the turbine nacelle induces large-scale coherent structures in the near field that can have a significant effect on wake meandering. However, whether nacelle-induced coherent structures at the turbine scale impact the emergent turbine wake dynamics at the wind farm scale is still an open question of both fundamental and practical significance. We take on this question by carrying out large-eddy simulation of atmospheric turbulent flow over the Horns Rev wind farm using actuator surface parameterisations of the turbines without and with the turbine nacelle taken into account. While the computed mean turbine power output and the mean velocity field away from the nacelle wake are similar for both cases, considerable differences are found in the turbine power fluctuations and turbulence intensities. Furthermore, wake meandering amplitude and area defined by wake meanders, which indicates the turbine wake unsteadiness, are larger for the simulations with the turbine nacelle. The wake influenced area computed from the velocity deficit profiles, which describes the spanwise extent of the turbine wakes, and the spanwise growth rate, on the other hand, are smaller for some rows in the simulation with the nacelle model. Our work shows that incorporating the nacelle model in wind farm scale simulations is critical for accurate predictions of quantities that affect the wind farm levelised cost of energy, such as the dynamics of wake meandering and the dynamic loads on downwind turbines.


2021 ◽  
Author(s):  
Ingrid Neunaber ◽  
Joachim Peinke ◽  
Martin Obligado

Abstract. Within the energy transition, more and more wind turbines are clustered in big wind farms, often offshore. Therefore, an optimal positioning of the wind turbines is crucial to optimize both the annual power production and the maintenance time. Good knowledge of the wind turbine wake and the turbulence within is thus important. However, although wind turbine wakes have been subject to various studies, they are still not fully understood. One possibility to improve the comprehension is to look into the modeling of bluff body wakes. These wakes have been the subject of intensive study for decades, and by means of the scaling behavior of the centerline mean velocity deficit, the nature of the turbulence inside a wake can be classified. In this paper, we introduce the models for equilibrium and non-equilibrium turbulence from classical wake theory as introduced by A. Townsend and W. George, and we test whether the requirements are fulfilled in the wake of a wind turbine. Finally, we apply the theory to characterize the wind turbine wake, and we compare the results to the Jensen and the Bastankhah-Porté-Agel model. We find that the insight into the classical bluff body wake can be used to further improve the wind turbine wake models. Particularly, the classical bluff body wake models perform better than the wind turbine wake models due to the presence of a virtual origin in the scalings, and we demonstrate the possibility of improving the wind turbine wake models by implementing this parameter. We also see how the dissipation changes across the wake which is important to model wakes within wind farms correctly.


Author(s):  
Alexander Štrbac ◽  
Tanja Martini ◽  
Daniel H. Greiwe ◽  
Frauke Hoffmann ◽  
Michael Jones

AbstractThe use of offshore wind farms in Europe to provide a sustainable alternative energy source is now considered normal. Particularly in the North Sea, a large number of wind farms exist with a significant distance from the coast. This is becoming standard practice as larger areas are required to support operations. Efficient transport and monitoring of these wind farms can only be conducted using helicopters. As wind turbines continue to grow in size, there is a need to continuously update operational requirements for these helicopters, to ensure safe operations. This study assesses German regulations for flight corridors within offshore wind farms. A semi-empirical wind turbine wake model is used to generate velocity data for the research flight simulator AVES. The reference offshore wind turbine NREL 5 MW has been used and scaled to represent wind turbine of different sizes. This paper reports result from a simulation study concerning vortex wake encounter during offshore operations. The results have been obtained through piloted simulation for a transport case through a wind farm. Both subjective and objective measures are used to assess the severity of vortex wake encounters.


2014 ◽  
Vol 31 (7) ◽  
pp. 1529-1539 ◽  
Author(s):  
Matthew L. Aitken ◽  
Julie K. Lundquist

Abstract To facilitate the optimization of turbine spacing at modern wind farms, computational simulations of wake effects must be validated through comparison with full-scale field measurements of wakes from utility-scale turbines operating in the real atmosphere. Scanning remote sensors are particularly well suited for this objective, as they can sample wind fields over large areas at high temporal and spatial resolutions. Although ground-based systems are useful, the vantage point from the nacelle is favorable in that scans can more consistently transect the central part of the wake. To the best of the authors’ knowledge, the work described here represents the first analysis in the published literature of a utility-scale wind turbine wake using nacelle-based long-range scanning lidar. The results presented are of a field experiment conducted in the fall of 2011 at a wind farm in the western United States, quantifying wake attributes such as the velocity deficit, centerline location, and wake width. Notable findings include a high average velocity deficit, decreasing from 60% at a downwind distance x of 1.8 rotor diameters (D) to 40% at x = 6D, resulting from a low average wind speed and therefore a high average turbine thrust coefficient. Moreover, the wake width was measured to expand from 1.5D at x = 1.8D to 2.5D at x = 6D. Both the wake growth rate and the amplitude of wake meandering were observed to be greater for high ambient turbulence intensity and daytime conditions as compared to low turbulence and nocturnal conditions.


2016 ◽  
Author(s):  
Amy Stidworthy ◽  
David Carruthers

Abstract. A new model, FLOWSTAR-Energy, has been developed for the practical calculation of wind farm energy production. It includes a semi-analytic model for airflow over complex surfaces (FLOWSTAR) and a wind turbine wake model that simulates wake-wake interaction by exploiting some similarities between the decay of a wind turbine wake and the dispersion of plume of passive gas emitted from an elevated source. Additional turbulence due to the wind shear at the wake edge is included and the assumption is made that wind turbines are only affected by wakes from upstream wind turbines. The model takes account of the structure of the atmospheric boundary layer, which means that the effect of atmospheric stability is included. A marine boundary layer scheme is also included to enable offshore as well as onshore sites to be modelled. FLOWSTAR-Energy has been used to model three different wind farms and the predicted energy output compared with measured data. Maps of wind speed and turbulence have also been calculated for two of the wind farms. The Tjaæreborg wind farm is an onshore site consisting of a single 2 MW wind turbine, the NoordZee offshore wind farm consists of 36 V90 VESTAS 3 MW turbines and the Nysted offshore wind farm consists of 72 Bonus 2.3 MW turbines. The NoordZee and Nysted measurement datasets include stability distribution data, which was included in the modelling. Of the two offshore wind farm datasets, the Noordzee dataset focuses on a single 5-degree wind direction sector and therefore only represents a limited number of measurements (1,284); whereas the Nysted dataset captures data for seven 5-degree wind direction sectors and represents a larger number of measurements (84,363). The best agreement between modelled and measured data was obtained with the Nysted dataset, with high correlation (0.98 or above) and low normalised mean square error (0.007 or below) for all three flow cases. The results from Tjæreborg show that the model replicates the Gaussian shape of the wake deficit two turbine diameters downstream of the turbine, but the lack of stability information in this dataset makes it difficult to draw conclusions about model performance. One of the key strengths of FLOWSTAR-Energy is its ability to model the effects of complex terrain on the airflow. However, although the airflow model has been previously compared extensively with flow data, it has so far not been used in detail to predict energy yields from wind farms in complex terrain. This will be the subject of a further validation study for FLOWSTAR-Energy.


2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Alireza Arabgolarcheh ◽  
Sahar Jannesarahmadi ◽  
Ernesto Benini ◽  
Luca Menegozzo

Over recent years, considerable attention has been devoted to the optimization of energy production in wind farms, where yaw angles can play a significant role. In order to quantify and maximize such potential power, the simulation of wakes is vital. In the present study, an actuator line model code was implemented in the OpenFOAM flow solver. A tip treatment was applied to involve the tip effect induced by the pressure equalization from the suction and pressure sides. The Leishman–Beddoes dynamic stall (LB-DS) model modified by Sheng et al. was employed to consider the dynamic stall phenomenon. The developed ALM-CFD solver was validated for the NREL Phase VI wind turbine reference case. The solver was then used in simulating the yawed wind turbine, and power variation was compared with UBEM and CFD. Overall, according to the obtained data, the coupled solver compared well with CFD. There was an improvement in terms of prediction of the phase delay that is due to the dynamic stall. However, there was still negligible overestimation in deep stall conditions. Based on the obtained results, it is suggested that the reduction of power output follows a cosine to the power of X function of the yaw angle. In terms of visualizing wake, the results demonstrated that the current ALM code was satisfying enough to simulate skewed wake and vortices trajectory. The effect of advancing and retreating blade was captured. It was found that yaw led to the concentration of the induced velocity downstream, resulting in a lower velocity deficit on a broader area, which is essential for wind farm optimization.


2021 ◽  
Author(s):  
Ravi Kumar ◽  
Ojing Siram ◽  
Niranjan Sahoo ◽  
Ujjwal K. Saha

Abstract Knowledge of wind energy harvesting is an ever-growing process, and to meet the enormous energy demand, wind farms shall have a significant role. An efficient wind farm is required to have an in-depth knowledge of turbine wake characteristics. This article presents an experimental investigation of the wake expansion process defined by the transition of wake from near to far wake regimes. The study has been performed on models horizontal axis wind turbine (HAWT) composed of NACA 0012 profile, keeping the ratio of root chord to tip chord length is 5:2. A constant temperature hot-wire anemometer (HWA) has been used to examine the rotor’s fluctuating flow field. The subsequent time-averaged normalizes velocity deficit, and vortex shedding frequency are used for the flow characteristics. Time-averaged velocity deficit measurement suggests a drop in upstream velocity by 20–30% within the vicinity of rotor tip downstream of the rotor plane. The study shows that flow recovery is initiating from the near wake regime around 1.08R. Further, the spectral findings indicates the low frequency dominance within 4R (R being the rotor radius), and the Strouhal number falls close to 0.23. The present wind tunnel study on wake characteristics throws significant insight into further enhancing the WT wake modeling.


2018 ◽  
Vol 140 (3) ◽  
Author(s):  
Enrico G. A. Antonini ◽  
David A. Romero ◽  
Cristina H. Amon

Computational fluid dynamics (CFD) simulations of wind turbine wakes are strongly influenced by the choice of the turbulence model used to close the Reynolds-averaged Navier-Stokes (RANS) equations. A wrong choice can lead to incorrect predictions of the velocity field characterizing the wind turbine wake and, consequently, to an incorrect power estimation for wind turbines operating downstream. This study aims to investigate the influence of different turbulence models, namely the k–ε, k–ω, SSTk–ω, and Reynolds stress models (RSM), on the results of CFD wind turbine simulations. Their influence was evaluated by comparing the CFD results with the publicly available experimental measurements of the velocity field and turbulence quantities from the Sexbierum and Nibe wind farms. Consistent turbulence model constants were proposed for atmospheric boundary layer (ABL) and wake flows according to previous literature and appropriate experimental observations, and modifications of the derived turbulence model constants were also investigated in order to improve agreement with experimental data. The results showed that the simulations using the k–ε and k–ω turbulence models consistently overestimated the velocity and turbulence quantities in the wind turbine wakes, whereas the simulations using the shear-stress transport (SST) k–ω and RSMs could accurately match the experimental data. Results also showed that the predictions from the k–ε and k–ω turbulence models could be improved by using the modified set of turbulence coefficients.


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