An official website of the United States government
As turbines continue to grow in hub height and rotor diameter and wind farms grow larger, consideration of stratified atmospheric boundary layer (ABL) processes in wind power models becomes increasingly important. Atmospheric stratification can considerably alter the boundary layer structure and flow characteristics through buoyant forcing. Variations in buoyancy, and corresponding ABL stability, in both space and time impact ABL wind speed shear, wind direction shear, boundary layer height, turbulence kinetic energy, and turbulence intensity. In addition, the presence of stratification will result in a direct buoyant forcing within the wake region. These ABL mechanisms affect turbine power production, the momentum and kinetic energy deficit wakes generated by turbines, and the turbulent mixing and kinetic energy entrainment in wind farms. Presently, state-of-practice engineering models of mean wake momentum utilize highly empirical turbulence models that do not explicitly account for ABL stability. Models also often neglect the interaction between the wake momentum deficit and the turbulence kinetic energy added by the wake, which depends on stratification. In this work, we develop a turbulence model that models the wake-added turbulence kinetic energy, and we couple it with a wake model based on the parabolized Reynolds-averaged Navier–Stokes equations. Comparing the model predictions to large eddy simulations across stabilities (Obukhov lengths) and surface roughness lengths, we find lower prediction error in both power production and the wake velocity field across the ABL conditions and error metrics investigated.
more »
« less
Momentum deficit and wake-added turbulence kinetic energy budgets in the stratified atmospheric boundary layer
To achieve decarbonization targets, wind turbines are growing in hub height and rotor diameter, and they are being deployed in new locations with diverse atmospheric conditions not previously seen, such as offshore. Physics-based analytical wake models commonly used for design and control of wind farms simplify atmospheric boundary layer (ABL) and wake physics to achieve computational efficiency. This is accomplished primarily through a simplified model form that neglects certain flow processes, such as atmospheric stability, and through the parametrization of ABL and wake turbulence through a wake spreading rate. In this study, we systematically analyze the physical mechanisms that govern momentum and turbulence within a wind turbine wake in the stratified ABL. We use large-eddy simulation and analysis of the streamwise momentum deficit and wake-added turbulence kinetic energy (TKE) budgets to study wind turbine wakes under neutral and stable conditions. To parse the turbulence in the wake from the turbulent, incident ABL flow, we decompose the flow into the base ABL flow and the deficit flow produced by the presence of a turbine. We then analyze the decomposed flow field budgets to study the effects of changing stability on the streamwise momentum deficit and wake-added TKE. The results demonstrate that stability changes the relative balance of turbulence and advection for both the streamwise momentum deficit and wake-added TKE primarily through the nonlinear interactions of the base flow with the deficit flow. The stable cases are most affected by increased shear and veer in the base flow and the neutral case is most affected by the increased ambient turbulence intensity. These differences in the base flow that arise from stratification are relatively more important than the buoyancy forcing terms in the wake-added TKE budget. The wake-added TKE depends on the ABL stability. An existing wake-added TKE model that neglects the effects of ABL stability yields error compared to large-eddy simulation, with errors that are higher in stable conditions than neutral. These results motivate future research to develop fast-running models of wake-added TKE that account for stability effects. Published by the American Physical Society2024
more »
« less
- Award ID(s):
- 2226053
- PAR ID:
- 10558408
- Publisher / Repository:
- APS Physical Review Journals
- Date Published:
- Journal Name:
- Physical Review Fluids
- Volume:
- 9
- Issue:
- 11
- ISSN:
- 2469-990X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Reliable characterization of wind turbine wakes in the presence of Atmospheric Boundary Layer (ABL) flows is crucial to accurately predict wind farm performance. Wind veering in the ABL shears the wake in the lateral direction, and wind veer strength depends on the thermal stability of the ABL. Analytical wake modeling approaches must capture these ABL effects to ensure correct prediction of the wake structure under varied atmospheric conditions. To this end, a new physics-based analytical wake model is developed in this study that is capable of predicting the shape of wakes influenced by wind veer and thermal stratification effects. This model combines a novel ABL wind field model with the Gaussian wake model. The new ABL wind model is capable of predicting both the streamwise and spanwise velocity components in conventionally neutral (CNBL) and stable (SBL) ABL flows. The analytical expressions for both of these horizontal velocity components adhere to Monin-Obukhov Similarity Theory (MOST) in the surface layer, while capturing wind veering in the outer layer of the ABL. Incorporating this ABL model with the Gaussian wake model predicts laterally deflected wake shapes in a fully predictive and self-consistent fashion for a wide range of atmospheric conditions. The results also demonstrate that the enhanced wake model gives improved predictions relative to Large Eddy Simulations of power losses due to wake interactions under strongly stably stratified atmospheric conditions, where wind veer effects are dominant.more » « less
-
Analytical wake models provide a computationally efficient means to predict velocity distributions in wind turbine wakes in the atmospheric boundary layer (ABL). Most existing models are developed for neutral atmospheric conditions and correspondingly neglect the effects of buoyancy and Coriolis forces that lead to veer, i.e., changes in the wind direction with height. Both veer and changes in thermal stratification lead to lateral shearing of the wake behind a wind turbine, which affects the power output of downstream turbines. Here we develop an analytical engineering wake model for a wind turbine in yaw in ABL flows including Coriolis and thermal stratification effects. The model combines the new analytical representation of ABL vertical structure based on coupling Ekman and surface layer descriptions developed in Narasimhan et al. [Boundary Layer Meteorol. 190, 16 (2024)] with the vortex sheet-based wake model for yawed turbines proposed in Bastankhah et al. [J. Fluid Mech. 933, A2 (2022)], as well as a new method to predict the wake expansion rate based on the Townsend-Perry logarithmic scaling of streamwise velocity variance. The proposed wake model's predictions show good agreement with large-eddy simulation results, capturing the effects of wind veer and yawing, including the curled and sheared wake structures across various states of the ABL, ranging from neutrally to strongly stably stratified atmospheric conditions. The model significantly improves power loss predictions from wake interactions, especially in strongly stably stratified conditions where wind veer effects dominate.more » « less
-
Wind turbines operate in the atmospheric boundary layer (ABL), where Coriolis effects are present. As wind turbines with larger rotor diameters are deployed, the wake structures that they create in the ABL also increase in length. Contemporary utility-scale wind turbines operate at rotor diameter-based Rossby numbers, the non-dimensional ratio between inertial and Coriolis forces, of$$\mathcal {O}(100)$$where Coriolis effects become increasingly relevant. Coriolis forces provide a direct forcing on the wake, but also affect the ABL base flow, which indirectly influences wake evolution. These effects may constructively or destructively interfere because both the magnitude and sign of the direct and indirect Coriolis effects depend on the Rossby number, turbulence and buoyancy effects in the ABL. Using large eddy simulations, we investigate wake evolution over a wide range of Rossby numbers relevant to offshore wind turbines. Through an analysis of the streamwise and lateral momentum budgets, we show that Coriolis effects have a small impact on the wake recovery rate, but Coriolis effects induce significant wake deflections which can be parsed into two regimes. For high Rossby numbers (weak Coriolis forcing), wakes deflect clockwise in the northern hemisphere. By contrast, for low Rossby numbers (strong Coriolis forcing), wakes deflect anti-clockwise. Decreasing the Rossby number results in increasingly anti-clockwise wake deflections. The transition point between clockwise and anti-clockwise deflection depends on the direct Coriolis forcing, pressure gradients and turbulent fluxes in the wake. At a Rossby number of 125, Coriolis deflections are comparable to wake deflections induced by$${\sim} 20^{\circ }$$of yaw misalignment.more » « less
-
Light detection and ranging (LiDAR) measurements of isolated wakes generated by wind turbines installed at an onshore wind farm are leveraged to characterize the variability of the wake mean velocity and turbulence intensity during typical operations, which encompass a breadth of atmospheric stability regimes and rotor thrust coefficients. The LiDAR measurements are clustered through the k-means algorithm, which enables identifying the most representative realizations of wind turbine wakes while avoiding the imposition of thresholds for the various wind and turbine parameters. Considering the large number of LiDAR samples collected to probe the wake velocity field, the dimensionality of the experimental dataset is reduced by projecting the LiDAR data on an intelligently truncated basis obtained with the proper orthogonal decomposition (POD). The coefficients of only five physics-informed POD modes are then injected in the k-means algorithm for clustering the LiDAR dataset. The analysis of the clustered LiDAR data and the associated supervisory control and data acquisition and meteorological data enables the study of the variability of the wake velocity deficit, wake extent, and wake-added turbulence intensity for different thrust coefficients of the turbine rotor and regimes of atmospheric stability. Furthermore, the cluster analysis of the LiDAR data allows for the identification of systematic off-design operations with a certain yaw misalignment of the turbine rotor with the mean wind direction.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1103/PhysRevFluids.9.114607
