Bulletin of the American Physical Society
64th Annual Meeting of the APS Division of Fluid Dynamics
Volume 56, Number 18
Sunday–Tuesday, November 20–22, 2011; Baltimore, Maryland
Session G27: Focus Session: Wind Energy Fluid Dynamics III |
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Chair: Jonathan Naughton, University of Wyoming Room: Ballroom I |
Monday, November 21, 2011 8:00AM - 8:13AM |
G27.00001: Atmospheric turbulence and its relevance for wind energy related research Michael H\"olling, Allan Morales, Matthias W\"achter, Joachim Peinke Positioned in the highly turbulent atmospheric boundary layer, wind turbines experience extreme wind conditions. By using the mean wind speed and the turbulence intensity on a ten minute basis to describe these turbulent wind fields, information about the chronology of the wind time series gets averaged out. Detailed knowledge about the wind field's behavior in time and their statistics can e.g. help to better estimate wind induced loads on wind turbines. We present a method to estimate the statistics of the fluctuations and more importantly the extreme fluctuations based on the ten minute averaged values of the turbulent intensity. In addition we present the effect of turbulent wind velocities on the lift coefficient of a FX 79-W-151A airfoil. Square grids and a fractal grid have been used to create turbulent flows with different turbulence intensities and increment statistics. Even though the turbulent intensity of the wind field generated by the fractal grid is smaller than of the wind field generated by the square grid, the results show a higher standard deviation in the measured lift coefficients. These increased fluctuations are a direct result from the generated atmospheric-like wind field with intermittent increment statistics on a wider range of scales created by the fractal grid. [Preview Abstract] |
Monday, November 21, 2011 8:13AM - 8:26AM |
G27.00002: Effect of the Ekman Layer on the Effective Roughness Length of Large Scale Wind Farms Jay Prakash Goit, Joris Codd\'e, Hans Robeers, Johan Meyers Large scale wind farms induce additional surface drag increasing the effective surface roughness (\textit{z}$_{0,hi} $) experienced by upper atmospheric boundary layer (ABL). In a previous study, Calaf \textit{et al.} [1] obtain \textit{z}$_ {0,hi}$ for wind farms when they are situated within the inner layer of the boundary layer, such that outer-layer dynamics, e.g., the effect of Coriolis forces induced by the Earth's rotation, may be neglected. However, for shallow ABLs where the wind-farm is not entirely situated in the inner layer, the effect of Coriolis forces may become important. In the present work, Large Eddy Simulations (LES) are used to addresses the effect of Coriolis forces on the evaluation of \textit{z}$_ {0,hi}$ for a very large wind farm. Results are compared with existing models for \textit{z}$_{0,hi}$ [1, 2]. We find that the models for \textit{z}$_{0,hi}$ agree well with the roughness obtained from the LES when wind turbines are well inside the inner region of the ABL. However, when the turbine height is more than $20\%$ of the ABL, the model's predicted roughness height gets less accurate. This difference can be attributed to the influence of Coriolis Forces .\\[4pt] [1] Calaf M. \textit{et al.} Phys Fluids, \textbf{22}, 015110, 2010.\\[0pt] [2] Frandsen S. \textit{et al.} Wind Energy, \textbf{9}, 39-53, 2006. [Preview Abstract] |
Monday, November 21, 2011 8:26AM - 8:39AM |
G27.00003: Statistical unfolding of atmospheric turbulence Allan Morales, Patrick Millan, Joachim Peinke Intermittent statistics, higher probability of extreme events in comparison to Gaussian statistics, is one of the trademarks of homogeneous isotropic turbulence (HIT). In the atmosphere, wind speed increments' probability density functions (PDFs) remain intermittent for a broader range of temporal and spatial scales. Moreover, wind speed fluctuations from the mean are intermittent for wind time series, which is not the case for HIT. In this work we revisit some features behind HIT with a free stream experiment and compare the results with those coming from atmospheric time series. We validate the idea that, within the inertial range, intermittency is coming from the randomness of the energy transfer rate. With a formulation, due to Castaing, based on Kolmogorov 62 (K62) we model increments' PDFs for packages of HIT in the atmosphere. With this knowledge and the observation that in the atmosphere not only the mean wind speed is non-stationary but also the turbulent kinetic energy, we are able to clearly identify two sources of intermittency in wind. We build a general model for modeling atmospheric turbulence statistics. Our model encapsulates mesoscale fluctuations, whereas high frequency turbulence can be treated and modeled with the full machinery developed in laboratory turbulence, in our case K62. We elaborate in the implications and utility of this work for Wind Energy. [Preview Abstract] |
Monday, November 21, 2011 8:39AM - 8:52AM |
G27.00004: Development of a Wind Turbine Array Boundary Layer Under Thermally Stratified Conditions Elizabeth Camp, Zachary Wilson, Dominic Delucia, Ra\'{u}l Bayo\'{a}n Cal Efforts have intensified in studying wind energy from a fluid mechanics and turbulence standpoint. Here, a wind turbine boundary layer is studied experimentally under stratified conditions. In this wind tunnel experiment, the mean velocities and turbulent quantities within a 3 by 3 scale-model wind turbine array are investigated. Cases for unstable and neutral boundary layer flows are described. These flows are modified upstream of the turbine array in order to emulate the atmospheric turbulent boundary layer using an active grid, strakes, thermally controlled floor panels, and roughness elements. All reported measured quantities are obtained through dual simultaneous stereo Particle Image Velocimetry systems which are made along the entire streamwise length of the array in order to chart the development of the flow. [Preview Abstract] |
Monday, November 21, 2011 8:52AM - 9:05AM |
G27.00005: Identification of Flow Structures in a Stratified Wind Turbine Array Boundary Layer Matt Melius, Zachary Wilson, Elizabeth Camp, Ra\'{u}l Bayo\'{a}n Cal Turbulent structures contained within a thermally stratified flow field as they convect through a wind turbine array are identified using instantaneous velocity fields obtained $\emph{via}$ particle image velocimetry (PIV). The experiment is conducted by placing a 3 by 3 scaled model wind turbine array in the test section of a wind tunnel. Using an active grid, strakes, and a thermally controlled tunnel floor, the conditions of a stratified atmospheric turbulent boundary layer are reproduced. Neutral and unstable conditions are compared. Vortical structures are captured both upstream and in the wake of the center turbine in the last row. The behaviors of the structures and how these evolve downstream are analyzed and compared to statistical quantities of the flow. Understanding these structures can prove important in determining the overall behavior of the flow and impact of the wind turbine array on the local environment. [Preview Abstract] |
Monday, November 21, 2011 9:05AM - 9:18AM |
G27.00006: Influences of Atmospheric Stability State on Wind Turbine Aerodynamic Loadings Ganesh Vijayakumar, Adam Lavely, James Brasseur, Eric Paterson, Michael Kinzel Wind turbine power and loadings are influenced by the structure of atmospheric turbulence and thus on the stability state of the atmosphere. Statistical differences in loadings with atmospheric stability could impact controls, blade design, etc. Large-eddy simulation (LES) of the neutral and moderately convective atmospheric boundary layer (NBL, MCBL) are used as inflow to the NREL FAST advanced blade-element momentum theory code to predict wind turbine rotor power, sectional lift and drag, blade bending moments and shaft torque. Using horizontal homogeneity, we combine time and ensemble averages to obtain converged statistics equivalent to ``infinite'' time averages over a single turbine. The MCBL required longer effective time periods to obtain converged statistics than the NBL. Variances and correlation coefficients among wind velocities, turbine power and blade loadings were higher in the MCBL than the NBL. We conclude that the stability state of the ABL strongly influences wind turbine performance. Supported by NSF and DOE. [Preview Abstract] |
Monday, November 21, 2011 9:18AM - 9:31AM |
G27.00007: Inherent Variability in Short-time Wind Turbine Statistics from Turbulence Structure in the Atmospheric Surface Layer Adam Lavely, Ganesh Vijayakumar, James Brasseur, Eric Paterson, Michael Kinzel Using large-eddy simulation (LES) of the neutral and moderately convective atmospheric boundary layers (NBL, MCBL), we analyze the impact of coherent turbulence structure of the atmospheric surface layer on the short-time statistics that are commonly collected from wind turbines. The incoming winds are conditionally sampled with a filtering and thresholding algorithm into high/low horizontal and vertical velocity fluctuation coherent events. The time scales of these events are $\sim$5 - 20 blade rotations and are roughly twice as long in the MCBL as the NBL. Horizontal velocity events are associated with greater variability in rotor power, lift and blade-bending moment than vertical velocity events. The variability in the industry standard 10 minute average for rotor power, sectional lift and wind velocity had a standard deviation of $\sim$~5\% relative to the ``infinite time'' statistics for the NBL and $\sim$10\% for the MCBL. We conclude that turbulence structure associated with atmospheric stability state contributes considerable, quantifiable, variability to wind turbine statistics. Supported by NSF and DOE. [Preview Abstract] |
Monday, November 21, 2011 9:31AM - 9:44AM |
G27.00008: Spatial and Temporal Scale Dependence of Atmospheric Boundary Layer Turbulence Cheryl Klipp Turbulence affects wind turbine performance, often in ways that are not well understood. A better understanding of the atmospheric turbulence may help in understanding effects on the turbines. Analysis of atmospheric boundary layer turbulence needs to account for different scales of motion since turbulence occurs over a wide range of scales from dissipation scales to very large scale motion on the order of tens of kilometers. Using sonic anemometer data from the 60m tower from the CASES99 field experiment near Leon, KS, the variances and covariances are expressed as sums of the variances and covariances due to motions at a range of temporal scales through the use of a multiresolution decomposition. The temporal scales are converted to spatial scales by multiplying by the mean wind value. Turbulent kinetic energy (TKE) has the most energy in scales of motion about 600m at a location 50m agl. This peak is broad; the width at half max covers a range of turbulence scales from 20m to 2500m (1.5 sec - 3.5 min). Individual variances show peak energies at different scales; the vertical variance having peak energy at smaller scales than the TKE peak scales, and streamwise variances having peak energy at larger scales. Analysis of all three covariances shows that the assumption of 2D flow is not a good approximation for the 50m agl. [Preview Abstract] |
Monday, November 21, 2011 9:44AM - 9:57AM |
G27.00009: Estimating Wind Turbine Inflow Using Sparse Wind Data Raj Rai, Jonathan Naughton An accurate spatially and temporally resolved estimation of the wind inflow under various atmospheric boundary layer stability conditions is useful for several applications relevant to wind turbines. Estimations of a wind inflow plane in a neutrally stable boundary layer using sparse data (temporally resolved but spatially sparse, and spatially resolved but temporally sparse) has shown good agreement with the original data provided by a Large Eddy Simulation. A complementary Proper Orthogonal Decomposition-Linear Stochastic Estimation (POD-LSE) approach has been used for the estimation in which the POD identifies the energetic modes of the flow that are then used in estimating the time dependent flow-field using LSE. The applicability of such an approach is considered by simulating the estimation of the wind inflow using data collected in the field. Modern remote measurement approaches, such as Lidar (Light detection and ranging), can sample the wind at the multiple locations, but cannot sufficiently resolve the inflow in space in time that is required for many wind turbine applications. Since inflow estimations using the POD-LSE approach can simultaneously provide spatial and temporal behavior, the use of the approach with field data for better understanding the characteristics of the wind inflow at a particular site under different atmospheric conditions is demonstrated. [Preview Abstract] |
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