scholarly journals Comparison of Different Driving Modes for the Wind Turbine Wake in Wind Tunnels

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1915
Author(s):  
Bingzheng Dou ◽  
Zhanpei Yang ◽  
Michele Guala ◽  
Timing Qu ◽  
Liping Lei ◽  
...  
Keyword(s):  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Farm ◽  
Relevant Information ◽  
Operating Conditions ◽  
Wind Tunnels ◽  
Driving Mode ◽  
Significant Difference ◽  
The Mean ◽  
Turbine Wake

The wake of upstream wind turbine is known to affect the operation of downstream turbines and the overall efficiency of the wind farm. Wind tunnel experiments provide relevant information for understanding and modeling the wake and its dependency on the turbine operating conditions. There are always two main driving modes to operate turbines in a wake experiment: (1) the turbine rotor is driven and controlled by a motor, defined active driving mode; (2) the rotor is driven by the incoming wind and subject to a drag torque, defined passive driving mode. The effect of the varying driving mode on the turbine wake is explored in this study. The mean wake velocities, turbulence intensities, skewness and kurtosis of the velocity time-series estimated from hot-wire anemometry data, were obtained at various downstream locations, in a uniform incoming flow wind tunnel and in an atmospheric boundary layer wind tunnel. The results show that there is not a significant difference in the mean wake velocity between these two driving modes. An acceptable agreement is observed in the comparison of wake turbulence intensity and higher-order statistics in the two wind tunnels.

scholarly journals Wake behavior and control: comparison of LES simulations and wind tunnel measurements

2019 ◽  
Vol 4 (1) ◽  
pp. 71-88 ◽  
Author(s):  
Jiangang Wang ◽  
Chengyu Wang ◽  
Filippo Campagnolo ◽  
Carlo L. Bottasso
Keyword(s):  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Farm ◽  
Operating Conditions ◽  
Test Cases ◽  
Near Wake ◽  
Large Eddy ◽  
Control Comparison ◽  
High Turbulence ◽  
And Control

Abstract. This paper applies a large-eddy actuator line approach to the simulation of wind turbine wakes. In addition to normal operating conditions, a specific focus of the paper is on wake manipulation, which is performed here by derating, yaw misalignment and cyclic pitching of the blades. With the purpose of clarifying the ability of LES methods to represent conditions that are relevant for wind farm control, numerical simulations are compared to experimental observations obtained in a boundary layer wind tunnel with scaled wind turbine models. Results indicate a good overall matching of simulations with experiments. Low-turbulence test cases appear to be more challenging than moderate- and high-turbulence ones due to the need for denser grids to limit numerical diffusion and accurately resolve tip-shed vortices in the near-wake region.

scholarly journals Documenting Wind Speed and Power Deficits behind a Utility-Scale Wind Turbine

2013 ◽  
Vol 52 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Brian D. Hirth ◽  
John L. Schroeder
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Large Variability ◽  
Cost Of Energy ◽  
The Mean ◽  
Utility Scale ◽  
Turbine Wake

AbstractHigh-spatial-and-temporal-resolution radial velocity measurements surrounding a single utility-scale wind turbine were collected using the Texas Tech University Ka-band mobile research radars. The measurements were synthesized to construct the first known dual-Doppler analyses of the mean structure and variability of a single turbine wake. The observations revealed a wake length that subjectively exceeded 20 rotor diameters, which far exceeds the typically employed turbine spacing of 7–10 rotor diameters. The mean horizontal wind speed deficits found within the turbine wake region relative to the free streamflow were related to potential reductions in the available power for a downwind turbine. Mean wind speed reductions of 17.4% (14.8%) were found at 7 (10) rotor diameters downwind, corresponding to a potential power output reduction of 43.6% (38.2%). The wind speed deficits found within the wake also exhibit large variability over short time intervals; this variability would have an appreciable impact on the inflow of a downstream turbine. The full understanding and application of these newly collected data have the potential to alter current wind-farm design and layout practices and to affect the cost of energy.

Comparison of Wind Tunnel Airfoil Performance Data With Wind Turbine Blade Data

1992 ◽  
Vol 114 (2) ◽  
pp. 119-124 ◽  
Author(s):  
C. P. Butterfield ◽  
George Scott ◽  
Walt Musial
Keyword(s):  
Wind Tunnel ◽  
Wind Turbine ◽  
Peak Power ◽  
Unsteady Aerodynamics ◽  
Leading Edge ◽  
Operating Conditions ◽  
Performance Data ◽  
Horizontal Axis Wind Turbine ◽  
Force Coefficients ◽  
Basic Fluid

Horizontal axis wind turbine (HAWT) performance is usually predicted by using wind tunnel airfoil performance data in a blade element momentum theory analysis. This analysis assumes that the rotating blade airfoils will perform as they do in the wind tunnel. However, when stall-regulated HAWT performance is measured in full-scale operation, it is common to find that peak power levels are significantly greater than those predicted. Pitch-controlled rotors experience predictable peak power levels because they do not rely on stall to regulate peak power. This has led to empirical corrections to the stall predictions. Viterna and Corrigan (1981) proposed the most popular version of this correction. But very little insight has been gained into the basic cause of this discrepancy. The National Renewable Energy Laboratory (NREL), funded by the DOE, has conducted the first phase of an experiment which is focused on understanding the basic fluid mechanics of HAWT aerodynamics. Results to date have shown that unsteady aerodynamics exist during all operating conditions and dynamic stall can exist for high yaw angle operation. Stall hysteresis occurs for even small yaw angles and delayed stall is a very persistent reality in all operating conditions. Delayed stall is indicated by a leading edge suction peak which remains attached through angles of attack (AOA) up to 30 degrees. Wind tunnel results show this peak separating from the leading edge at 18 deg AOA. The effect of this anomaly is to raise normal force coefficients and tangent force coefficients for high AOA. Increased tangent forces will directly affect HAWT performance in high wind speed operation. This report describes pressure distribution data resulting from both wind tunnel and HAWT tests. A method of bins is used to average the HAWT data which is compared to the wind tunnel data. The analysis technique and the test set-up for each test are described.

scholarly journals Utility-Scale Wind Turbine Wake Characterization Using Nacelle-Based Long-Range Scanning Lidar

2014 ◽  
Vol 31 (7) ◽  
pp. 1529-1539 ◽  
Author(s):  
Matthew L. Aitken ◽  
Julie K. Lundquist
Keyword(s):  
Wind Turbine ◽  
Long Range ◽  
Wind Farm ◽  
Thrust Coefficient ◽  
Velocity Deficit ◽  
Scanning Lidar ◽  
Range Scanning ◽  
Utility Scale ◽  
Turbine Wake ◽  
Wind Turbine Wake

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.

Effect of wind turbine nacelle on turbine wake dynamics in large wind farms

2019 ◽  
Vol 869 ◽  
pp. 1-26 ◽  
Author(s):  
Daniel Foti ◽  
Xiaolei Yang ◽  
Lian Shen ◽  
Fotis Sotiropoulos
Keyword(s):  
Wind Turbine ◽  
Coherent Structures ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Practical Significance ◽  
Mean Velocity ◽  
Velocity Deficit ◽  
Farm Scale ◽  
Turbine Wake

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.

scholarly journals Wind Turbine Wake Modeling in Accelerating Wind Field: A Preliminary Study on a Two-Dimensional Hill

Fluids ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 153 ◽  
Author(s):  
Omar M. A. M. Ibrahim ◽  
Shigeo Yoshida ◽  
Masahiro Hamasaki ◽  
Ao Takada
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Field ◽  
Complex Terrain ◽  
Wind Farm ◽  
Wind Tunnel Test ◽  
Two Dimensional ◽  
Preliminary Study ◽  
Wake Model

Complex terrain can influence wind turbine wakes and wind speed profiles in a wind farm. Consequently, predicting the performance of wind turbines and energy production over complex terrain is more difficult than it is over flat terrain. In this preliminary study, an engineering wake model, that considers acceleration on a two-dimensional hill, was developed based on the momentum theory. The model consists of the wake width and wake wind speed. The equation to calculate the rotor thrust, which is calculated by the wake wind speed profiles, was also formulated. Then, a wind-tunnel test was performed in simple flow conditions in order to investigate wake development over a two-dimensional hill. After this the wake model was compared with the wind-tunnel test, and the results obtained by using the new wake model were close to the wind-tunnel test results. Using the new wake model, it was possible to estimate the wake shrinkage in an accelerating two-dimensional wind field.

scholarly journals Linear stability analysis of wind turbine wakes performed on wind tunnel measurements

2013 ◽  
Vol 737 ◽  
pp. 499-526 ◽  
Author(s):  
G. V. Iungo ◽  
F. Viola ◽  
S. Camarri ◽  
F. Porté-Agel ◽  
F. Gallaire
Keyword(s):  
Stability Analysis ◽  
Wind Tunnel ◽  
Wind Turbine ◽  
Linear Stability ◽  
Linear Stability Analysis ◽  
Rotational Velocity ◽  
Base Flow ◽  
Wind Tunnel Measurements ◽  
Turbine Wake ◽  
Wind Turbine Wake

AbstractWind tunnel measurements were performed for the wake produced by a three-bladed wind turbine immersed in uniform flow. These tests show the presence of a vorticity structure in the near-wake region mainly oriented along the streamwise direction, which is denoted as the hub vortex. The hub vortex is characterized by oscillations with frequencies lower than that connected to the rotational velocity of the rotor, which previous works have ascribed to wake meandering. This phenomenon consists of transversal oscillations of the wind turbine wake, which might be excited by the vortex shedding from the rotor disc acting as a bluff body. In this work, temporal and spatial linear stability analyses of a wind turbine wake are performed on a base flow obtained with time-averaged wind tunnel velocity measurements. This study shows that the low-frequency spectral component detected experimentally matches the most amplified frequency of the counter-winding single-helix mode downstream of the wind turbine. Then, simultaneous hot-wire measurements confirm the presence of a helicoidal unstable mode of the hub vortex with a streamwise wavenumber roughly equal to that predicted from the linear stability analysis.

scholarly journals FLOWSTAR-Energy: a high resolution wind farm wake model

2016 ◽  
Author(s):  
Amy Stidworthy ◽  
David Carruthers
Keyword(s):  
Boundary Layer ◽  
Wind Turbine ◽  
Complex Terrain ◽  
Wind Farm ◽  
Wind Farms ◽  
Measured Data ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Wake Model ◽  
Turbine Wake

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.

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