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 Wind Turbine Wake Characterization for Improvement of the Ainslie Eddy Viscosity Wake Model

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2823 ◽  
Author(s):  
Hyungyu Kim ◽  
Kwansu Kim ◽  
Carlo Bottasso ◽  
Filippo Campagnolo ◽  
Insu Paek
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Eddy Viscosity ◽  
Wind Tunnel Test ◽  
Original Model ◽  
Test Results ◽  
Wake Model ◽  
Turbine Model

This paper presents a modified version of the Ainslie eddy viscosity wake model and its accuracy by comparing it with selected exiting wake models and wind tunnel test results. The wind tunnel test was performed using a 1.9 m rotor diameter wind turbine model operating at a tip speed ratio similar to that of modern megawatt wind turbines. The control algorithms for blade pitch and generator torque used for below and above rated wind speed regions similar to those for multi-MW wind turbines were applied to the scaled wind turbine model. In order to characterize the influence of the wind turbine operating conditions on the wake, the wind turbine model was tested in both below and above rated wind speed regions at which the thrust coefficients of the rotor varied. The correction of the Ainslie eddy viscosity wake model was made by modifying the empirical equation of the original model using the wind tunnel test results with the Nelder-Mead simplex method for function minimization. The wake prediction accuracy of the modified wake model in terms of wind speed deficit was found to be improved by up to 6% compared to that of the original model. Comparisons with other existing wake models are also made in detail.

scholarly journals Wake and Turbulence Analysis for Wind Turbine Layouts in an Island

2018 ◽  
Vol 64 ◽  
pp. 06010
Author(s):  
Bachhal Amrender Singh ◽  
Vogstad Klaus ◽  
Lal Kolhe Mohan ◽  
Chougule Abhijit ◽  
Beyer Hans George
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Wind Farm ◽  
Full Length Paper ◽  
Turbulence Analysis ◽  
Wake Model ◽  
Wind Resources

There is a big wind energy potential in supplying the power in an island and most of the islands are off-grid. Due to the limited area in island(s), there is need to find appropriate layout / location for wind turbines suited to the local wind conditions. In this paper, we have considered the wind resources data of an island in Trøndelag region of the Northern Norway, situated on the coastal line. The wind resources data of this island have been analysed for wake losses and turbulence on wind turbines for determining appropriate locations of wind turbines in this island. These analyses are very important for understanding the fatigue and mechanical stress on the wind turbines. In this work, semi empirical wake model has been used for wake losses analysis with wind speed and turbine spacings. The Jensen wake model used for the wake loss analysis due to its high degree of accuracy and the Frandsen model for characterizing the turbulent loading. The variations of the losses in the wind energy production of the down-wind turbine relative to the up-wind turbine and, the down-stream turbulence have been analysed for various turbine distances. The special emphasis has been taken for the case of wind turbine spacing, leading to the turbulence conditions for satisfying the IEC 61400-1 conditions to find the wind turbine layout in this island. The energy production of down-wind turbines has been decreased from 2 to 20% due to the lower wind speeds as they are located behind up-wind turbine, resulting in decreasing the overall energy production of the wind farm. Also, the higher wake losses have contributed to the effective turbulence, which has reduced the overall energy production from the wind farm. In this case study, the required distance for wind turbines have been changed to 6 rotor diameters for increasing the energy gain. From the results, it has been estimated that the marginal change in wake losses by moving the down-stream wind turbine by one rotor diameter distance has been in the range of 0.5 to 1% only and it is insignificant. In the full-length paper, the wake effects with wind speed variations and the wind turbine locations will be reported for reducing the wake losses on the down-stream wind turbine. The Frandsen model has been used for analysing turbulence loading on the down-stream wind turbine as per IEC 61400-1 criteria. In larger wind farms, the high turbulence from the up-stream wind turbines increases the fatigues on the turbines of the wind farm. In this work, we have used the effective turbulence criteria at a certain distance between up-stream and down-stream turbines for minimizing the fatigue load level. The sensitivity analysis on wake and turbulence analysis will be reported in the full-length paper. Results from this work will be useful for finding wind farm layouts in an island for utilizing effectively the wind energy resources and electrification using wind power plants.

Experimental and Numerical Investigation of Inflow Turbulence on the Performance of Wind Turbine Airfoils

2013 ◽  
Author(s):  
O. Eisele ◽  
G. Pechlivanoglou ◽  
C. N. Nayeri ◽  
C. O. Paschereit
Keyword(s):  
Wind Tunnel ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Wind Tunnel Test ◽  
Wind Turbine Blade ◽  
Two Dimensional ◽  
Airfoil Surface ◽  
Wind Tunnel Measurements ◽  
Inflow Turbulence ◽  
The Impact

Wind turbine blade design is currently based on the combination of a plurality of airfoil sections along the rotorblade span. The two-dimensional airfoil characteristics are usually measured with wind tunnel experiments or computed by means of numerical simulation codes. The general airfoil input for the calculation of the rotorblade power characteristics as well as the subsequent aerodynamic and aeroelastic loads are based on these two-dimensional airfoil characteristics. In this paper, the effects of inflow turbulence and wind tunnel test measurement deviations are investigated and discussed, to allow considerations of such effects in the rotorblade design process. The results of CFD simulations with various turbulence models are utilized in combination with wind tunnel measurements in order to assess the impact of such discrepancies. It seems that turbulence, airfoil surface roughness and early transition effects are able to contribute significantly to the uncertainty and scattering of measurements. Various wind tunnel facilities generate different performance characteristic curves, while grid-generated turbulence is generally not included in the wind tunnel measurements during airfoil characterization. Furthermore the correlation of grid-generated wind tunnel turbulence with the atmospheric turbulence time and length scales is not easily achieved. All the aforementioned uncertainties can increase the performance scattering of current wind turbine blade designs as well as the generated aeroelastic loads. A brief assessment of the effect of such uncertainties on wind turbine performance is given at the last part of this work by means of BEM simulations on a wind turbine blade.

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.

scholarly journals Experimental and Numerical Analysis of a Seawall’s Effect on Wind Turbine Performance

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3877 ◽  
Author(s):  
Hyun-Goo Kim ◽  
Wan-Ho Jeon
Keyword(s):  
Numerical Analysis ◽  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Turbine ◽  
Flow Separation ◽  
Wind Farm ◽  
Wind Tunnel Experiment ◽  
Scale Model ◽  
Wind Flow ◽  
Cfd Analysis

For the purposes of this study, a wind tunnel experiment and a numerical analysis during ebb and high tides were conducted to determine the positive and negative effects of wind flow influenced by a seawall structure on the performance of wind turbines installed along a coastal seawall. The comparison of the wind flow field between a wind tunnel experiment performed with a 1/100 scale model and a computational fluid dynamics (CFD) analysis confirmed that the MP k-turbulence model estimated flow separation on the leeside of the seawall the most accurately. The CFD analysis verified that wind speed-up occurred due to the virtual hill effect caused by the seawall’s windward slope and the recirculation zone of its rear face, which created a positive effect by mitigating wind shear while increasing the mean wind speed in the wind turbine’s rotor plane. In contrast, the turbulence effect of flow separation on the seawall’s leeside was limited to the area below the wind turbine rotor, and had no negative effect. The use of the CFD verified with the comparison with the wind tunnel experiment was extended to the full-scale seawall, and the results of the analysis based on the wind turbine Supervisory Control and Data Acquisition (SCADA) data of a wind farm confirmed that the seawall effect was equivalent to a 1.5% increase in power generation as a result of a mitigation of the wind profile.

scholarly journals Dynamic Stall Model for Tower Shadow Effects on Downwind Turbines and Its Scale Effects

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5237
Author(s):  
Shigeo Yoshida
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Scale Effects ◽  
Wind Tunnel Test ◽  
Dynamic Stall ◽  
Test Model ◽  
Wind Speed Profile ◽  
Empirical Parameter ◽  
Wake Model ◽  
Tower Shadow

A dynamic stall model for tower shadow effects is developed for downwind turbines. Although Munduate’s model shows good agreement with a 1.0 m wind tunnel test model, two problems exist: (1) it does not express load increase before the entrance of the tower wake, and (2) it uses the empirical tower wake model to determine the wind speed profile behind the tower. The present research solves these problems by combining Moriarty’s tower wake model and the entrance condition of the tower wake. Moriarty’s model does not require any empirical parameter other than tower drag coefficient and it expresses positive wind speed around the tower also. Positive wind speed change is also allowed as the tower wake entrance condition in addition to the negative change observed in the previous model. It demonstrates better agreement with a wind tunnel test and contributes to the accuracy of the fatigue load, as it expresses a slight increase in load around the entrance of the tower wake. Furthermore, the scale effects are also evaluated; lift deviation becomes smaller as the scale increases, i.e., lower rotor speed.

scholarly journals Comparison of Wake Model Simulations with Offshore Wind Turbine Wake Profiles Measured by Sodar

2006 ◽  
Vol 23 (7) ◽  
pp. 888-901 ◽  
Author(s):  
R. J. Barthelmie ◽  
G. C. Larsen ◽  
S. T. Frandsen ◽  
L. Folkerts ◽  
K. Rados ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Offshore Wind ◽  
Superior Performance ◽  
Offshore Wind Turbine ◽  
Wide Range ◽  
Wake Model ◽  
Method Of Evaluation ◽  
Turbine Wake

Abstract This paper gives an evaluation of most of the commonly used models for predicting wind speed decrease (wake) downstream of a wind turbine. The evaluation is based on six experiments where free-stream and wake wind speed profiles were measured using a ship-mounted sodar at a small offshore wind farm. The experiments were conducted at varying distances between 1.7 and 7.4 rotor diameters downstream of the wind turbine. Evaluation of the models compares the predicted and observed velocity deficits at hub height. A new method of evaluation based on determining the cumulative momentum deficit over the profiles is described. Despite the apparent simplicity of the experiments, the models give a wide range of predictions. Overall, it is not possible to establish any of the models as having individually superior performance with respect to the measurements.

Drone-Based Experimental Investigation of Three-Dimensional Flow Structure of a Multi-Megawatt Wind Turbine in Complex Terrain

2015 ◽  
Vol 137 (5) ◽  
Author(s):  
B. Subramanian ◽  
N. Chokani ◽  
R. S. Abhari
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Direction ◽  
Complex Terrain ◽  
Wind Farm ◽  
Three Dimensional ◽  
Energy Yield ◽  
Near Wake ◽  
Tip Vortices

The aerodynamic characteristics of wakes in complex terrain have a profound impact on the energy yield of wind farms and on the fatigue loads on wind turbines in the wind farm. In order to detail the spatial variations of the wind speed, wind direction, and turbulent kinetic energy (TKE) in the near-wake, comprehensive drone-based measurements at a multi-megawatt (MW) wind turbine that is located in complex terrain have been conducted. A short-time Fourier transform (STFT)-based analysis method is used to derive time-localized TKE along the drone's trajectory. In upstream and in the near-wake, the vertical profiles of wind speed, wind direction, and TKE are detailed. There is an increase in the TKE from upstream to downstream of the wind turbine, and whereas, the characteristic microscale length scales increase with increasing height above the ground upstream of the turbine, in the near-wake the microscale lengths are of constant, smaller magnitude. The first-ever measurements of the pressure field across a multi-MW wind turbines rotor plane and of the tip vortices in the near-wake are also reported. It is shown that the pitch between subsequent tip vortices, which are shed from the wind turbines blades, increases in the near-wake as the wake evolves. These details of the near-wake can have an important effect on the subsequent evolution of the wake and must be incorporated into the three-dimensional (3D) field wake models that are currently under intensive development.

scholarly journals Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2319
Author(s):  
Hyun-Goo Kim ◽  
Jin-Young Kim
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Free Stream ◽  
Turbine Blades ◽  
Wind Farms ◽  
Lidar Measurement ◽  
Wind Turbine Blades ◽  
Wake Effect

This study analyzed the performance decline of wind turbine with age using the SCADA (Supervisory Control And Data Acquisition) data and the short-term in situ LiDAR (Light Detection and Ranging) measurements taken at the Shinan wind farm located on the coast of Bigeumdo Island in the southwestern sea of South Korea. Existing methods have generally attempted to estimate performance aging through long-term trend analysis of a normalized capacity factor in which wind speed variability is calibrated. However, this study proposes a new method using SCADA data for wind farms whose total operation period is short (less than a decade). That is, the trend of power output deficit between predicted and actual power generation was analyzed in order to estimate performance aging, wherein a theoretically predicted level of power generation was calculated by substituting a free stream wind speed projecting to a wind turbine into its power curve. To calibrate a distorted wind speed measurement in a nacelle anemometer caused by the wake effect resulting from the rotation of wind-turbine blades and the shape of the nacelle, the free stream wind speed was measured using LiDAR remote sensing as the reference data; and the nacelle transfer function, which converts nacelle wind speed into free stream wind speed, was derived. A four-year analysis of the Shinan wind farm showed that the rate of performance aging of the wind turbines was estimated to be −0.52%p/year.

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