scholarly journals Field measurements of wake meandering at a utility-scale wind turbine with nacelle-mounted Doppler LiDARs

2021 ◽  
Author(s):  
Peter Andreas Brugger ◽  
Corey D. Markfort ◽  
Fernando Porté-Agel
Keyword(s):  
Wind Turbine ◽  
Turbulence Intensity ◽  
Wind Farm ◽  
Maximum Velocity ◽  
Field Measurements ◽  
Lateral Velocity ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Downstream Distance ◽  
Utility Scale

Abstract. Wake meandering is a low-frequency oscillation of the entire wind turbine wake that can contribute to power and load fluctuations of downstream turbines in wind farms. Field measurements of two Doppler LiDARs mounted on the nacelle of a utility-scale wind turbine were used to investigate relationships between the inflow and the wake meandering as well as the effect of wake meandering on the temporally averaged wake. A correlation analysis showed a linear relationship between the instantaneous wake position and the lateral velocity that degraded with the evolution of the turbulent wind field during the time of downstream advection. A low-pass filter proportional to the advection time delay is recommended to remove small scales that become decorrelated even for distances within the typical spacing of wind turbine rows in a wind farm. The results also showed that the velocity at which wake meandering is transported downstream was slower than the inflow wind speed, but faster than the velocity at the wake center. This indicates that the modelling assumption of the wake as an passive scalar should be revised in the context of the downstream advection. Further, the strength of wake meandering increased linearly with the turbulence intensity of the lateral velocity and with the downstream distance. Wake meandering reduced the maximum velocity deficit of the temporally averaged wake and increased its width. Both effects scaled with the wake meandering strength. Lastly, we found that the fraction of the wake turbulence intensity that was caused by wake meandering decreased with downstream distance contrary to the wake meandering strength.

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.

High-fidelity simulations and field measurements for characterizing wind fields in a utility-scale wind farm

2021 ◽  
Vol 281 ◽  
pp. 116115
Author(s):  
Xiaolei Yang ◽  
Christopher Milliren ◽  
Matt Kistner ◽  
Christopher Hogg ◽  
Jeff Marr ◽  
...  
Keyword(s):  
Wind Farm ◽  
Field Measurements ◽  
High Fidelity ◽  
Wind Fields ◽  
High Fidelity Simulations ◽  
Utility Scale

Research on the Met Mast Siting Used in Post Assessment of Mountain Wind Farm

2014 ◽  
Vol 953-954 ◽  
pp. 443-447
Author(s):  
Jia Yuan Yang ◽  
Yu Mo Woo ◽  
Ke Sheng ◽  
Yu Hui Tang
Keyword(s):  
Wind Turbine ◽  
Turbulence Intensity ◽  
Wind Farm ◽  
Southern China ◽  
Average Level ◽  
Speed Up ◽  
Relationship Of ◽  
Post Assessment

Abstract. For a mountain wind farm in southern China, the paper used CFD software, METEODYN WT, to simulate the wind in all directions to assess their speed-up factor, turbulence intensity, inflow angle and horizontal deviation caused by the terrain. The turbulence intensity, the horizontal deviation and the inflow angle in the met-mast position should be low or small, and the speed-up factor should be able to represent the average level of all the wind turbine sites. The positional relationship of the wind turbine and met-mast is reference to IEC61400-12-1. The paper provided two optional areas.

Turbulence Estimation Using Fast-Response Thermistors Attached to a Free-Fall Vertical Microstructure Profiler

2016 ◽  
Vol 33 (10) ◽  
pp. 2065-2078 ◽  
Author(s):  
Yasutaka Goto ◽  
Ichiro Yasuda ◽  
Maki Nagasawa
Keyword(s):  
Temperature Gradient ◽  
Frequency Response ◽  
Turbulence Intensity ◽  
Free Fall ◽  
Fast Response ◽  
Double Pole ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Wide Range ◽  
Low Pass

AbstractEstimation of turbulence intensity with a fast-response thermistor is examined by comparing the energy dissipation rate from a Fastip Probe, model 07 (FP07), thermistor with from a shear probe, both of which are attached to a free-fall microstructure profiler with the fall rate of 0.6–0.7 m s−1. Temperature gradient spectra corrected with previously introduced frequency response functions represented by a single-pole low-pass filter yields with a bias that strongly depends on turbulence intensity. Meanwhile, the correction with the form of a double-pole low-pass filter derives less bias than of single-pole low-pass filter. The rate is compatible with when the double-pole correction with the time constant of 3 × 10−3 s is applied, and 68% of data are within a factor of 2.8 of in the wide range of = 10−10–3 × 10−7 W kg−1. The rate is still compatible with even in the anisotropy range, where the buoyancy Reynolds number is 20–100. Turbulence estimation from the fast-response thermistor is thus confirmed to be valid in this range by applying the appropriate correction to temperature gradient spectra. Measurements with fast-response thermistors, which have not been common because of their poor frequency response, are less sensitive to the vibration of profilers than those with shear probes. Hence, measurements could be available when a fast-response thermistor is attached to a CTD frame or a float, which extends the possibility of obtaining much more turbulence data in deep and wide oceans.

scholarly journals Numerical Study of Nacelle Wind Speed Characteristics of a Horizontal Axis Wind Turbine under Time-Varying Flow

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3993 ◽  
Author(s):  
Xiaodong Wang ◽  
Yunong Liu ◽  
Luyao Wang ◽  
Lin Ding ◽  
Hui Hu
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Horizontal Axis ◽  
Wake Flow ◽  
Horizontal Axis Wind Turbine ◽  
Inlet Flow ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Speed Condition ◽  
Simulation Results

Nacelle wind speed transfer function (NTF) is usually used for power prediction and operational control of a horizontal axis wind turbine. Nacelle wind speed exhibits high instability as it is influenced by both incoming flow and near wake of a wind turbine rotor. Enhanced understanding of the nacelle wind speed characteristics is critical for improving the accuracy of NTF. This paper presents Reynolds-averaged Navier–Stokes (RANS) simulation results obtained for a multi-megawatt wind turbine under both stable and dynamic incoming flows. The dynamic inlet wind speed varies in the form of simplified sinusoidal and superposed sinusoidal functions. The simulation results are analyzed in time and frequency domains. For a stable inlet flow, the variation of nacelle wind speed is mainly influenced by the blade rotation. The influence of wake flow shows high frequency characteristics. The results with stable inlet flow show that the reduction of the nacelle wind speed with respect to the inlet wind speed is overestimated for low wind speed condition, and underestimated for high wind speed condition. Under time-varing inflow conditions, for the time scale and fluctuation amplitude subject to the International Electrotechnical Commission (IEC) standard, the nacelle wind speed is mainly influenced by the dynamic inflow. The variation of inflow can be recovered by choosing a suitable low pass filter. The work in this paper demonstrates the potential for building accurate NTF based on Computational Fluid Dynamics (CFD) simulations and signal analysis.

Modelling and measurements of power losses and turbulence intensity in wind turbine wakes at Middelgrunden offshore wind farm

Wind Energy ◽  
2007 ◽  
Vol 10 (6) ◽  
pp. 517-528 ◽  
Author(s):  
R. J. Barthelmie ◽  
S. T. Frandsen ◽  
M. N. Nielsen ◽  
S. C. Pryor ◽  
P.-E. Rethore ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Turbulence Intensity ◽  
Wind Farm ◽  
Offshore Wind ◽  
Power Losses ◽  
Offshore Wind Farm

scholarly journals Power curve and wake analyses of the Vestas multi-rotor demonstrator

2019 ◽  
Author(s):  
Maarten Paul van der Laan ◽  
Søren Juhl Anderson ◽  
Néstor Ramos García ◽  
Nikolas Angelou ◽  
Georg Raimund Pirrung ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Wind Turbine ◽  
Wind Farm ◽  
Field Measurements ◽  
Power Curve ◽  
Power Performance ◽  
Near Wake ◽  
Wind Speeds ◽  
Wake Turbulence ◽  
Far Wake

Abstract. Numerical simulations of the Vestas multi-rotor demonstrator (4R-V29) are compared with field measurements of power performance and remote sensing measurements of the wake deficit by a short-range WindScanner lidar system. The simulations predict a gain of 0–2 % in power due to the rotor interaction, for wind speeds below rated. The power curve measurements also show that the rotor interaction increases the power performance below rated by 1.8 ± 0.2 %, which can result in a 1.5 ± 0.2 % increase in the annual energy production. The wake measurements and numerical simulations show four distinct wake deficits in the near wake, which merge into a single wake structure further downstream. Numerical simulations show that the wake recovery distance of a simplified 4R-V29 wind turbine is 1.03–1.44 Deq shorter than for an equivalent single-rotor wind turbine with a rotor diameter Deq. In addition, the numerical simulations show that the added wake turbulence of the simplified 4R-V29 wind turbine is lower in the far wake compared to the equivalent single-rotor wind turbine. The faster wake recovery and lower far-wake turbulence of such a multi-rotor wind turbine has the potential to reduce the wind turbine spacing within a wind farm while providing the same production.

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.

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