scholarly journals Lidar measurements of yawed wind turbine wakes: characterisation and validation of analytical models

2020 ◽  
Author(s):  
Peter Brugger ◽  
Mithu Debnath ◽  
Andrew Scholbrock ◽  
Paul Fleming ◽  
Patrick Moriarty ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Cross Sections ◽  
Wake Flow ◽  
Analytical Models ◽  
Power Coefficient ◽  
Doppler Lidar ◽  
Wind Turbine Control ◽  
Lidar Measurements ◽  
Set Up ◽  
Yaw Angle

Abstract. Wake measurements of a scanning Doppler lidar mounted on the nacelle of a yawed full-scale wind turbine are used for the characterization of the wake flow and the validation of analytical wake models. Inflow scanning Doppler lidars, a meteorological mast and the data of the wind turbine control system complemented the set-up. Results showed an increase of the wake deflection with the yaw angle that agreed with two of the three compared models. For yawed cases, the predicted power of a waked downwind turbine estimated by the two previously successful models had an error of 17 % and 24 % compared to the SCADA data and 12 % and 13 % compared to the power estimated from the Doppler lidar measurements. Shortcomings of the method to compute the power coefficient in an inhomogeneous wind field are likely the reason for disagreement between estimates using the Doppler lidar data versus SCADA data. Further, it was found that some wake steering cases were detrimental to the power output due to errors of the inflow wind direction perceived by the yawed wind turbine and the wake steering design implemented. Lastly, it was observed that the spanwise cross-section of the wake is strongly affected by wind veer, masking the kidney-shaped wake cross-sections observed from wind-tunnel experiments and numerical simulations.

scholarly journals Lidar measurements of yawed-wind-turbine wakes: characterization and validation of analytical models

2020 ◽  
Vol 5 (4) ◽  
pp. 1253-1272
Author(s):  
Peter Brugger ◽  
Mithu Debnath ◽  
Andrew Scholbrock ◽  
Paul Fleming ◽  
Patrick Moriarty ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Cross Sections ◽  
Wake Flow ◽  
Analytical Models ◽  
Power Coefficient ◽  
Doppler Lidar ◽  
Scada System ◽  
Lidar Measurements ◽  
Set Up ◽  
Yaw Angle

Abstract. Wake measurements of a scanning Doppler lidar mounted on the nacelle of a full-scale wind turbine during a wake-steering experiment were used for the characterization of the wake flow, the evaluation of the wake-steering set-up, and the validation of analytical wake models. Inflow-scanning Doppler lidars, a meteorological mast, and the supervisory control and data acquisition (SCADA) system of the wind turbine complemented the set-up. Results from the wake-scanning Doppler lidar showed an increase in the wake deflection with the yaw angle and that the wake deflection was not in all cases beneficial for the power output of a downstream turbine due to a bias of the inflow wind direction perceived by the yawed wind turbine and the wake-steering design implemented. Both observations could be reproduced with an analytical model that was initialized with the inflow measurements. Error propagation from the inflow measurements that were used as model input and the power coefficient of a waked wind turbine contributed significantly to the model uncertainty. Lastly, the span-wise cross section of the wake was strongly affected by wind veer, masking the effects of the yawed wind turbine on the wake cross sections.

scholarly journals Reconstruction of Three-Dimensional Dynamic Wind-Turbine Wake Wind Fields with Volumetric Long-Range Wind Doppler LiDAR Measurements

2019 ◽  
Vol 11 (22) ◽  
pp. 2665 ◽  
Author(s):  
Beck ◽  
Kühn
Keyword(s):  
Wind Turbine ◽  
Long Range ◽  
Wind Field ◽  
Three Dimensional ◽  
Wake Flow ◽  
Wind Fields ◽  
Wake Field ◽  
Eddy Simulation ◽  
Lidar Measurements ◽  
Set Up

This paper presents a method for reconstructing the wake wind field of a wind turbine based on planar light detection and ranging (LiDAR) scans crossing the wake transversally in the vertical and horizontal directions. Volumetric measurements enable the study of wake characteristics in these two directions. Due to a lack of highly resolved wind speed measurements as reference data, we evaluate the reconstruction in a synthetic environment and determine the reconstruction errors. The wake flow of a multi-megawatt wind turbine is calculated within a 10-min large-eddy simulation (LES) for high-thrust loading conditions. We apply a numerical LiDAR simulator to this wake wind field to achieve realistic one-dimensional velocity data. We perform a nacelle-based set-up with combined plan position indicator and range height indicator scans with eight scanning velocities each. We temporally up-sample the synthetic LiDAR data with a weighted combination of forward- and backward-oriented space–time conversion to retrospectively extract high-resolution wake characteristic dynamics. These dynamics are used to create a dynamic volumetric wake deficit. Finally, we reconstruct the dynamic wake wind field in three spatial dimensions by superposing an ambient wind field with the dynamic volumetric wake deficit. These results demonstrate the feasibility of wake field reconstruction using long-range LiDAR measurements.

Small Horizontal Axis Wind Turbine: Analytical Blade Design and Comparison With RANS-Prediction and First Experimental Data

2013 ◽  
Author(s):  
Tom Gerhard ◽  
Michael Sturm ◽  
Thomas H. Carolus
Keyword(s):  
Experimental Data ◽  
Flow Field ◽  
Wind Turbine ◽  
Horizontal Axis ◽  
Analytical Models ◽  
Power Coefficient ◽  
Analysis Tool ◽  
Computational Domain ◽  
Horizontal Axis Wind Turbine ◽  
Data Set

State-of-the-art wind turbine performance prediction is mainly based on semi-analytical models, incorporating blade element momentum (BEM) analysis and empirical models. Full numerical simulation methods can yield the performance of a wind turbine without empirical assumptions. Inherent difficulties are the large computational domain required to capture all effects of the unbounded ambient flow field and the fact that the boundary layer on the blade may be transitional. A modified turbine design method in terms of the velocity triangles, Euler’s turbine equation and BEM is developed. Lift and drag coefficients are obtained from XFOIL, an open source 2D design and analysis tool for subcritical airfoils. A 3 m diameter horizontal axis wind turbine rotor was designed and manufactured. The flow field is predicted by means of a Reynolds-averaged Navier-Stokes simulation. Two turbulence models were utilized: (i) a standard k-ω-SST model, (ii) a laminar/turbulent transition model. The manufactured turbine is placed on the rooftop of the University of Siegen. Three wind anemometers and wind direction sensors are arranged around the turbine. The torque is derived from electric power and the rotational speed via a calibrated grid-connected generator. The agreement between the analytically and CFD-predicted kinematic quantities up- and downstream of the rotor disc is quite satisfactory. However, the blade section drag to lift ratio and hence the power coefficient vary with the turbulence model chosen. Moreover, the experimentally determined power coefficient is considerably lower as predicted by all methods. However, this conclusion is somewhat preliminary since the existing experimental data set needs to be extended.

scholarly journals An Induction Motor Based Wind Turbine Emulator

2014 ◽  
Vol 51 (2) ◽  
pp. 11-21 ◽  
Author(s):  
A. Sokolovs ◽  
L. Grigans ◽  
E. Kamolins ◽  
J. Voitkans
Keyword(s):  
Wind Turbine ◽  
Induction Motor ◽  
Frequency Converter ◽  
Real Life ◽  
Power Coefficient ◽  
Small Scale ◽  
Ac Drive ◽  
Set Up ◽  
Ac Induction Motor ◽  
Good Agreement

Abstract The authors present a small-scale wind turbine emulator based on the AC drive system and discuss the methods for power coefficient calculation. In the work, the experimental set-up consisting of an AC induction motor, a frequency converter, a synchronous permanent magnet generator, a DC-DC boost converter and DC load was simulated and tested using real-life equipment. The experimentally obtained wind turbine power and torque diagrams using the emulator are in a good agreement with the theoretical ones.

Aerodynamic Characteristics of Horizontal Axis Wind Turbine With Archimedes Spiral Blade

2013 ◽  
Author(s):  
Kyung Chun Kim ◽  
Yoon Kee Kim ◽  
Ho Seong Ji ◽  
Jook Ho Beak ◽  
Rinus Mieremet
Keyword(s):  
Steady State ◽  
Wind Turbine ◽  
Cfd Simulation ◽  
Aerodynamic Characteristics ◽  
Wake Flow ◽  
Power Coefficient ◽  
Horizontal Axis Wind Turbine ◽  
Mean Velocity ◽  
Archimedes Spiral ◽  
Spiral Blade

To investigate the aerodynamic characteristics of an Archimedes spiral wind turbine for urban-usage, both experimental and numerical studies were carried out. The Archimedes spiral blade was designed to produce wind power using drag and lift forces on the blade together. Instantaneous velocity fields were measured by two-dimensional PIV method in the near field of the blade. Mean velocity profiles were compared to those predicted by the steady state and unsteady state CFD simulation. It was found that the interaction between the wake flow at the rotor downstream and the induced velocity due to the tip vortices were strongly affected by the wind speed and resulting rotational speed of the blade. PIV measurements revealed the presence of dominant vertical structures at downstream the hub and near the blade tip. Unsteady CFD simulation results agreed well with those of PIV experiments than the steady state analysis. The power coefficient (Cp) obtained by CFD simulation demonstrated that the new type of wind turbine produced about 0.25, relatively high value compared to other types of urban-usage wind turbine.

Effect of Flow Inclination on Wind Turbine Performance

2012 ◽  
Vol 134 (12) ◽  
Author(s):  
Christina Tsalicoglou ◽  
Sarah Barber ◽  
Ndaona Chokani ◽  
Reza S. Abhari
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Complex Terrain ◽  
Wake Flow ◽  
Test Facility ◽  
Power Coefficient ◽  
Incoming Flow ◽  
Turbine Performance ◽  
The Impact ◽  
Blade Element

This work examines the effect of flow inclination on the performance of a stand-alone wind turbine and of wind turbines operating in the wakes of upstream turbines. The experimental portion of this work, which includes performance and flowfield measurements, is conducted in the ETH dynamically-scaled wind turbine test facility, with a wind turbine model that can be inclined relative to the incoming flow. The performance of the wind turbine is measured with an in-line torquemeter, and a 5-hole steady-state probe is used to detail the inflow and wake flow of the turbine. Measurements show that over a range of tip-speed ratios of 4–7.5, the power coefficient of a wind turbine with an incoming flow of 15 deg inclination decreases on average by 7% relative to the power coefficient of a wind turbine with a noninclined incoming flow. Flowfield measurements show that the wake of a turbine with an inclined incoming flow is deflected; the deflection angle is approximately 6 deg for an incoming flow with 15 deg inclination. The measured wake profiles are used as inflow profiles for a blade element momentum code in order to quantify the impact of flow inclination on the performance of downstream wind turbines. In comparison to the case without inclination in the incoming flow, the combined power output of two aligned turbines with incoming inclined flow decreases by 1%, showing that flow inclination in complex terrain does not significantly reduce the energy production.

scholarly journals Field Measurements of Wind Turbine Wakes with Lidars

2013 ◽  
Vol 30 (2) ◽  
pp. 274-287 ◽  
Author(s):  
Giacomo Valerio Iungo ◽  
Yu-Ting Wu ◽  
Fernando Porté-Agel
Keyword(s):  
Wind Turbine ◽  
Symmetry Plane ◽  
Field Measurements ◽  
Wake Flow ◽  
Laser Beams ◽  
Measured Velocity ◽  
Wake Turbulence ◽  
Lidar Measurements ◽  
Dimensional Measurements ◽  
Wind Lidar

AbstractField measurements of the wake flow produced from a 2-MW Enercon E-70 wind turbine were performed using three scanning Doppler wind lidars. A GPS-based technique was used to determine the position of the wind turbine and the wind lidar locations, as well as the direction of the laser beams. The lidars used in this study are characterized by a high spatial resolution of 18 m, which allows the detailed characterization of the wind turbine wake. Two-dimensional measurements of wind speed were carried out by scanning a single lidar over the vertical symmetry plane of the wake. The mean axial velocity field was then retrieved by averaging 2D scans performed consecutively. To investigate wake turbulence, single lidar measurements were performed by staring the laser beam at fixed directions and using the maximum sampling frequency. From these tests, peaks in the velocity variance are detected within the wake in correspondence of the turbine top tip height; this enhanced turbulence could represent a source of dangerous fatigue loads for downstream turbines. The spectral density of the measured velocity fluctuations shows a clear inertial-range scaling behavior. Then, simultaneous measurements with two lidars were performed in order to characterize both the axial and the vertical velocity components. For this setup, the two velocity components were retrieved only for measurement points for which the two laser beams crossed nearly at a right angle. Statistics were computed over the sample set for both velocity components, and they showed strong flow fluctuations in the near-wake region at turbine top tip height, with a turbulence intensity of about 30%.

scholarly journals Measurement procedures for characterization of wind turbine wakes with scanning Doppler wind LiDARs

2013 ◽  
Vol 10 (1) ◽  
pp. 71-75 ◽  
Author(s):  
G. V. Iungo ◽  
F. Porté-Agel
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Wake Flow ◽  
Lidar Measurement ◽  
Wake Turbulence ◽  
Main Challenge ◽  
Measuring Techniques ◽  
The Mean ◽  
Yaw Angle

Abstract. The wake flow produced from an Enercon E-70 wind turbine is investigated through three scanning Doppler wind LiDARs. One LiDAR is deployed upwind to characterize the incoming wind, while the other two LiDARs are located downstream to carry out wake measurements. The main challenge in performing measurements of wind turbine wakes is represented by the varying wind conditions, and by the consequent adjustments of the turbine yaw angle needed to maximize power production. Consequently, taking into account possible variations of the relative position between the LiDAR measurement volume and wake location, different measuring techniques were carried out in order to perform 2-D and 3-D characterizations of the mean wake velocity field. However, larger measurement volumes and higher spatial resolution require longer sampling periods; thus, to investigate wake turbulence tests were also performed by staring the LiDAR laser beam over fixed directions and with the maximum sampling frequency. The characterization of the wake recovery along the downwind direction is performed. Moreover, wake turbulence peaks are detected at turbine top-tip height, which can represent increased fatigue loads for downstream wind turbines within a wind farm.

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