scholarly journals Evaluation of the the wind farm wake parametrization with large-eddy simulations of wakes in WRF

2021 ◽  
Author(s):  
Alfredo Peña ◽  
Jeffrey Mirocha
Keyword(s):  
Boundary Layer ◽  
Wind Farm ◽  
Wrf Model ◽  
Wind Farms ◽  
Large Eddy Simulations ◽  
Disk Model ◽  
Mesoscale Models ◽  
Boundary Layer Height ◽  
Wind Speeds ◽  
Large Eddy

<p>Mesoscale models, such as the Weather Research and Forecasting (WRF) model, are now commonly used to predict wind resources, and in recent years their outputs are being used as inputs to wake models for the prediction of the production of wind farms. Also, wind farm parametrizations have been implemented in the mesoscale models but their accuracy to reproduce wind speeds and turbulent kinetic energy fields within and around wind farms is yet unknown. This is partly because they have been evaluated against wind farm power measurements directly and, generally, a lack of high-quality observations of the wind field around large wind farms. Here, we evaluate the in-built wind farm parametrization of the WRF model, the so-called Fitch scheme that works together with the MYNN2 planetary boundary layer (PBL) scheme against large-eddy simulations (LES) of wakes using a generalized actuator disk model, which was also implemented within the same WRF version. After setting both types of simulations as similar as possible so that the inflow conditions are nearly identical, preliminary results show that the velocity deficits can differ up to 50% within the same area (determined by the resolution of the mesoscale run) where the turbine is placed. In contrast, within that same area, the turbine-generated TKE is nearly identical in both simulations. We also prepare an analysis of the sensitivity of the results to the inflow wind conditions, horizontal grid resolution of both the LES and the PBL run, number of turbines within the mesoscale grid cells, surface roughness, inversion strength, and boundary-layer height.</p>

scholarly journals Mountain waves can impact wind power generation

2021 ◽  
Vol 6 (1) ◽  
pp. 45-60
Author(s):  
Caroline Draxl ◽  
Rochelle P. Worsnop ◽  
Geng Xia ◽  
Yelena Pichugina ◽  
Duli Chand ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Power Output ◽  
Wind Farm ◽  
Wrf Model ◽  
Wind Farms ◽  
The United States ◽  
Mountain Wave ◽  
Mountain Waves ◽  
Improvement Project ◽  
Wind Speeds

Abstract. Mountains can modify the weather downstream of the terrain. In particular, when stably stratified air ascends a mountain barrier, buoyancy perturbations develop. These perturbations can trigger mountain waves downstream of the mountains that can reach deep into the atmospheric boundary layer where wind turbines operate. Several such cases of mountain waves occurred during the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River basin in the lee of the Cascade Range bounding the states of Washington and Oregon in the Pacific Northwest of the United States. Signals from the mountain waves appear in boundary layer sodar and lidar observations as well as in nacelle wind speeds and power observations from wind plants. Weather Research and Forecasting (WRF) model simulations also produce mountain waves and are compared to satellite, lidar, and sodar observations. Simulated mountain wave wavelengths and wave propagation speeds (group velocities) are analyzed using the fast Fourier transform. We found that not all mountain waves exhibit the same speed and conclude that the speed of propagation, magnitudes of wind speeds, or wavelengths are important parameters for forecasters to recognize the risk for mountain waves and associated large drops or surges in power. When analyzing wind farm power output and nacelle wind speeds, we found that even small oscillations in wind speed caused by mountain waves can induce oscillations between full-rated power of a wind farm and half of the power output, depending on the position of the mountain wave's crests and troughs. For the wind plant analyzed in this paper, mountain-wave-induced fluctuations translate to approximately 11 % of the total wind farm output being influenced by mountain waves. Oscillations in measured wind speeds agree well with WRF simulations in timing and magnitude. We conclude that mountain waves can impact wind turbine and wind farm power output and, therefore, should be considered in complex terrain when designing, building, and forecasting for wind farms.

scholarly journals The Aerodynamics of the Curled Wake: A Simplified Model in View of Flow Control

2018 ◽  
Author(s):  
Luis A. Martínez-Tossas ◽  
Jennifer Annoni ◽  
Paul A. Fleming ◽  
Matthew J. Churchfield
Keyword(s):  
Boundary Layer ◽  
Steady State ◽  
Wind Farm ◽  
Stokes Equations ◽  
Large Eddy Simulations ◽  
Simplified Model ◽  
Navier Stokes ◽  
Navier Stokes Equations ◽  
Actuator Disk ◽  
Large Eddy

Abstract. When a wind turbine is yawed, the shape of the wake changes and a curled wake profile is generated. The curled wake has drawn a lot of interest because of its aerodynamic complexity and applicability to wind farm controls. The main mechanism for the creation of the curled wake has been identified in the literature as a collection of vortices that are shed from the rotor plane when the turbine is yawed. This work extends that idea by using aerodynamic concepts to develop a control-oriented model for the curled wake based on approximations to the Navier-Stokes equations. The model is tested and compared to large-eddy simulations using actuator disk and line models. The model is able to capture the curling mechanism for a turbine under uniform inflow and in the case of a neutral atmospheric boundary layer. The model is then tested inside the FLOw Redirection and Induction in Steady State framework and provides excellent agreement with power predictions for cases with two and three turbines in a row.

scholarly journals Recovery processes in coastal wind farms under sea-breeze conditions

2021 ◽  
Vol 56 ◽  
pp. 129-139
Author(s):  
Tanvi Gupta ◽  
Somnath Baidya Roy
Keyword(s):  
Wind Farm ◽  
Wrf Model ◽  
Wind Farms ◽  
Sea Breeze ◽  
Offshore Wind ◽  
Dominant Factor ◽  
Offshore Wind Farms ◽  
Sea Breezes ◽  
Wind Speeds ◽  
Recovery Processes

Abstract. With the rapid growth in offshore wind energy, it is important to understand the dynamics of offshore wind farms. Most of the offshore wind farms are currently installed in coastal regions where they are often affected by sea-breezes. In this work, we quantitatively study the recovery processes for coastal wind farms under sea-breeze conditions. We use a modified Borne's method to identify sea breeze days off the west coast of India in the Arabian Sea. For the identified sea breeze days, we simulate a hypothetical wind farm covering 50×50 km2 area using the Weather Research and Forecasting (WRF) model driven by realistic initial and boundary conditions. We use three wind farm layouts with the turbines spaced 0.5, 1, and 2 km apart. The results show an interesting power generation pattern with a peak at the upwind edge and another peak at the downwind edge due to sea breeze. Wind farms affect the circulation patterns, but the effects of these modifications are very weak compared to the sea breezes. Vertical recovery is the dominant factor with more than half of the momentum extracted by wind turbines being replenished by vertical turbulent mixing. However, horizontal recovery can also play a strong role for sparsely packed wind farms. Horizontal recovery is stronger at the edges where the wind speeds are higher whereas vertical recovery is stronger in the interior of the wind farms. This is one of the first studies to examine replenishment processes in offshore wind farms under sea breeze conditions. It can play an important role in advancing our understanding wind farm-atmospheric boundary layer interactions.

Two Corrections for Turbulent Kinetic Energy Generated by Wind Farms in the WRF Model

2020 ◽  
Vol 148 (12) ◽  
pp. 4823-4835
Author(s):  
Cristina L. Archer ◽  
Sicheng Wu ◽  
Yulong Ma ◽  
Pedro A. Jiménez
Keyword(s):  
Wind Speed ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Wind Farm ◽  
Atmospheric Stability ◽  
Wrf Model ◽  
Wind Farms ◽  
Near Surface ◽  
Large Eddy ◽  
The Way

AbstractAs wind farms grow in number and size worldwide, it is important that their potential impacts on the environment are studied and understood. The Fitch parameterization implemented in the Weather Research and Forecasting (WRF) Model since version 3.3 is a widely used tool today to study such impacts. We identified two important issues related to the way the added turbulent kinetic energy (TKE) generated by a wind farm is treated in the WRF Model with the Fitch parameterization. The first issue is a simple “bug” in the WRF code, and the second issue is the excessive value of a coefficient, called CTKE, that relates TKE to the turbine electromechanical losses. These two issues directly affect the way that a wind farm wake evolves, and they impact properties like near-surface temperature and wind speed at the wind farm as well as behind it in the wake. We provide a bug fix and a revised value of CTKE that is one-quarter of the original value. This 0.25 correction factor is empirical; future studies should examine its dependence on parameters such as atmospheric stability, grid resolution, and wind farm layout. We present the results obtained with the Fitch parameterization in the WRF Model for a single turbine with and without the bug fix and the corrected CTKE and compare them with high-fidelity large-eddy simulations. These two issues have not been discovered before because they interact with one another in such a way that their combined effect is a somewhat realistic vertical TKE profile at the wind farm and a realistic wind speed deficit in the wake. All WRF simulations that used the Fitch wind farm parameterization are affected, and their conclusions may need to be revisited.

scholarly journals Wake properties and power output of very large wind farms for different meteorological conditions and turbine spacings: A large-eddy simulation case study for the German Bight

2021 ◽  
Author(s):  
Oliver Maas ◽  
Siegfried Raasch
Keyword(s):  
Boundary Layer ◽  
Power Density ◽  
Boundary Layers ◽  
Power Output ◽  
German Bight ◽  
Wind Farm ◽  
Wind Farms ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Large Wind

Abstract. Germany’s expansion target for offshore wind power capacity of 40 GW by the year 2040 can only be reached if large portions of the Exclusive Economic Zone in the German Bight are equipped with wind farms. Because these wind farm clusters will be much larger than existing wind farms, it is unknown how they affect the boundary layer flow and how much power they will produce. The objective of this large-eddy-simulation study is to investigate the wake properties and the power output of very large potential wind farms in the German Bight for different turbine spacings, stabilities and boundary layer heights. The results show that very large wind farms cause flow effects that small wind farms do not. These effects include, but are not limited to, inversion layer displacement, counterclockwise flow deflection inside the boundary layer and clockwise flow deflection above the boundary layer. Wakes of very large wind farms are longer for shallower boundary layers and smaller turbine spacings, reaching values of more than 100 km. The wake in terms of turbulence intensity is approximately 20 km long, where longer wakes occur for convective boundary layers and shorter wakes for stable boundary layers. Very large wind farms in a shallow, stable boundary layer can excite gravity waves in the overlying free atmosphere, resulting in significant flow blockage. The power output of very large wind farms is higher for thicker boundary layers, because thick boundary layers contain more kinetic energy than thin boundary layers. The power density of the energy input by the geostrophic pressure gradient limits the power output of very large wind farms. Because this power density is very low (approximately 2 W m−2), the installed power density of very large wind farms should be small to achieve a good wind farm efficiency.

scholarly journals The aerodynamics of the curled wake: a simplified model in view of flow control

2019 ◽  
Vol 4 (1) ◽  
pp. 127-138 ◽  
Author(s):  
Luis A. Martínez-Tossas ◽  
Jennifer Annoni ◽  
Paul A. Fleming ◽  
Matthew J. Churchfield
Keyword(s):  
Boundary Layer ◽  
Wind Farm ◽  
Stokes Equations ◽  
Large Eddy Simulations ◽  
Simplified Model ◽  
Navier Stokes ◽  
Navier Stokes Equations ◽  
Actuator Disk ◽  
Large Eddy ◽  
Good Agreement

Abstract. When a wind turbine is yawed, the shape of the wake changes and a curled wake profile is generated. The curled wake has drawn a lot of interest because of its aerodynamic complexity and applicability to wind farm controls. The main mechanism for the creation of the curled wake has been identified in the literature as a collection of vortices that are shed from the rotor plane when the turbine is yawed. This work extends that idea by using aerodynamic concepts to develop a control-oriented model for the curled wake based on approximations to the Navier–Stokes equations. The model is tested and compared to time-averaged results from large-eddy simulations using actuator disk and line models. The model is able to capture the curling mechanism for a turbine under uniform inflow and in the case of a neutral atmospheric boundary layer. The model is then incorporated to the FLOw Redirection and Induction in Steady State (FLORIS) framework and provides good agreement with power predictions for cases with two and three turbines in a row.

scholarly journals Comparison of Field Measurements and Large Eddy Simulations of the Scaled Wind Farm Technology (SWiFT) Site

2019 ◽  
Author(s):  
Myra L. Blaylock ◽  
Brent C. Houchens ◽  
David C. Maniaci ◽  
Thomas Herges ◽  
Alan Hsieh ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Wind Farm ◽  
Field Measurements ◽  
Operating Conditions ◽  
Large Eddy Simulations ◽  
Department Of Energy ◽  
Large Eddy ◽  
In Series ◽  
The Impact

Abstract Power production of the turbines at the Department of Energy/Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility located at the Texas Tech University’s National Wind Institute Research Center was measured experimentally and simulated for neutral atmospheric boundary layer operating conditions. Two V27 wind turbines were aligned in series with the dominant wind direction, and the upwind turbine was yawed to investigate the impact of wake steering on the downwind turbine. Two conditions were investigated, including that of the leading turbine operating alone and both turbines operating in series. The field measurements include meteorological evaluation tower (MET) data and light detection and ranging (lidar) data. Computations were performed by coupling large eddy simulations (LES) in the three-dimensional, transient code Nalu-Wind with engineering actuator line models of the turbines from OpenFAST. The simulations consist of a coarse precursor without the turbines to set up an atmospheric boundary layer inflow followed by a simulation with refinement near the turbines. Good agreement between simulations and field data are shown. These results demonstrate that Nalu-Wind holds the promise for the prediction of wind plant power and loads for a range of yaw conditions.

scholarly journals Large-Eddy Simulations of Stratified Atmospheric Boundary Layers: Comparison of Different Subgrid Models

2020 ◽  
Author(s):  
Srinidhi N. Gadde ◽  
Anja Stieren ◽  
Richard J. A. M. Stevens
Keyword(s):  
Boundary Layer ◽  
Boundary Layers ◽  
Large Scale ◽  
Wind Farm ◽  
Research Area ◽  
Large Eddy Simulations ◽  
Turbulence Energy ◽  
Atmospheric Boundary Layers ◽  
Smagorinsky Model ◽  
Large Eddy

Abstract The development and assessment of subgrid-scale (SGS) models for large-eddy simulations of the atmospheric boundary layer is an active research area. In this study, we compare the performance of the classical Smagorinsky model, the Lagrangian-averaged scale-dependent (LASD) model, and the anisotropic minimum dissipation (AMD) model. The LASD model has been widely used in the literature for 15 years, while the AMD model was recently developed. Both the AMD and the LASD models allow three-dimensional variation of SGS coefficients and are therefore suitable to model heterogeneous flows over complex terrain or around a wind farm. We perform a one-to-one comparison of these SGS models for neutral, stable, and unstable atmospheric boundary layers. We find that the LASD and the AMD models capture the logarithmic velocity profile and the turbulence energy spectra better than the Smagorinsky model. In stable and unstable boundary-layer simulations, the AMD and LASD model results agree equally well with results from a high-resolution reference simulation. The performance analysis of the models reveals that the computational overhead of the AMD model and the LASD model compared to the Smagorinsky model is approximately 10% and 30% respectively. The LASD model has a higher computational and memory overhead because of the global filtering operations and Lagrangian tracking procedure, which can result in bottlenecks when the model is used in extensive simulations. These bottlenecks are absent in the AMD model, which makes it an attractive SGS model for large-scale simulations of turbulent boundary layers.

scholarly journals Evaluating Terrain as a Turbulence Generation Method

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6858
Author(s):  
Patrick Hawbecker ◽  
Matthew Churchfield
Keyword(s):  
Boundary Layer ◽  
Mesoscale Model ◽  
Boundary Layer Height ◽  
Simulation Performance ◽  
Wind Speeds ◽  
Large Eddy ◽  
Mean Wind Speed ◽  
Speed Up ◽  
Capping Inversion ◽  
Turbulence Generation

When driving microscale large-eddy simulations with mesoscale model solutions, turbulence will take space to develop, known as fetch, on the microscale domain. To reduce fetch, it is common to add perturbations near the boundaries to speed up turbulence development. However, when simulating domains over complex terrain, it is possible that the terrain itself can quickly generate turbulence within the boundary layer. It is shown here that rugged terrain is able to generate turbulence without the assistance of a perturbation strategy; however, the levels of turbulence generated are improved when adding perturbations at the inlet. Flow over smoothed, but not flat, terrain fails to generate adequate turbulence throughout the boundary layer in all tests conducted herein. Sensitivities to the strength of the mean wind speed and boundary layer height are investigated and show that higher wind speeds produce turbulence over terrain features that slower wind speeds do not. Further, by increasing the height of the capping inversion, the effectiveness of topography alone to generate turbulence throughout the depth of the boundary is diminished. In all cases, the inclusion of a perturbation strategy improved simulation performance with respect to turbulence development.

scholarly journals Power Prediction of Wind Farms via a Simplified Actuator Disk Model

2020 ◽  
Vol 8 (8) ◽  
pp. 610
Author(s):  
Yen-Cheng Chiang ◽  
Yu-Cheng Hsu ◽  
Shiu-Wu Chau
Keyword(s):  
Large Eddy Simulation ◽  
Wind Farm ◽  
Computational Cost ◽  
Wind Farms ◽  
Power Prediction ◽  
Disk Model ◽  
Actuator Disk ◽  
Eddy Simulation ◽  
Proposed Model ◽  
Large Eddy

This paper aims to demonstrate a simplified nonlinear wake model that fills the technical gap between the low-cost and less-accurate linear formulation and the high-cost and high-accuracy large eddy simulation, to offer a suitable balance between the prediction accuracy and the computational cost, and also to establish a robust approach for long-term wind farm power prediction. A simplified actuator disk model based on the momentum theory is proposed to predict the wake interaction among wind turbines along with their power output. The three-dimensional flow field of a wind farm is described by the steady continuity and momentum equation coupled with a k-ε turbulence model, where the body force representing the aerodynamic impact of the rotor blade on the airflow is uniformly distributed in the Cartesian cells within the actuator disk. The characteristic wind conditions identified from the data of the supervisory control and data acquisition (SCADA) system were employed to build the power matrix of these typical wind conditions for reducing the computation demands to estimate the yearly power production. The proposed model was favorably validated with the offshore measurement of Horns Rev wind farm, and three Taiwanese onshore wind farms were forecasted for their yearly capacity factors with an average error less than 5%, where the required computational cost is estimated about two orders of magnitude smaller than that of the large eddy simulation. However, the proposed model fails to pronouncedly reproduce the individual power difference among wind turbines in the investigated wind farm due to its time-averaging nature.

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