scholarly journals Local and Mesoscale Impacts of Wind Farms as Parameterized in a Mesoscale NWP Model

2012 ◽  
Vol 140 (9) ◽  
pp. 3017-3038 ◽  
Author(s):  
Anna C. Fitch ◽  
Joseph B. Olson ◽  
Julie K. Lundquist ◽  
Jimy Dudhia ◽  
Alok K. Gupta ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Kinetic Energy ◽  
Wind Farm ◽  
Weather Prediction ◽  
Wind Farms ◽  
Mean Flow ◽  
Thrust Coefficient ◽  
Near Surface ◽  
Neutral Boundary Layer

Abstract A new wind farm parameterization has been developed for the mesoscale numerical weather prediction model, the Weather Research and Forecasting model (WRF). The effects of wind turbines are represented by imposing a momentum sink on the mean flow; transferring kinetic energy into electricity and turbulent kinetic energy (TKE). The parameterization improves upon previous models, basing the atmospheric drag of turbines on the thrust coefficient of a modern commercial turbine. In addition, the source of TKE varies with wind speed, reflecting the amount of energy extracted from the atmosphere by the turbines that does not produce electrical energy. Analyses of idealized simulations of a large offshore wind farm are presented to highlight the perturbation induced by the wind farm and its interaction with the atmospheric boundary layer (BL). A wind speed deficit extended throughout the depth of the neutral boundary layer, above and downstream from the farm, with a long wake of 60-km e-folding distance. Within the farm the wind speed deficit reached a maximum reduction of 16%. A maximum increase of TKE, by nearly a factor of 7, was located within the farm. The increase in TKE extended to the top of the BL above the farm due to vertical transport and wind shear, significantly enhancing turbulent momentum fluxes. The TKE increased by a factor of 2 near the surface within the farm. Near-surface winds accelerated by up to 11%. These results are consistent with the few results available from observations and large-eddy simulations, indicating this parameterization provides a reasonable means of exploring potential downwind impacts of large wind farms.

scholarly journals Wind Turbine Performance in Very Large Wind Farms: Betz Analysis Revisited

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1078 ◽  
Author(s):  
Jacob R. West ◽  
Sanjiva K. Lele
Keyword(s):  
Boundary Layer ◽  
Kinetic Energy ◽  
Wind Turbine ◽  
Wind Farm ◽  
Wind Farms ◽  
Mean Flow ◽  
Thrust Coefficient ◽  
Turbine Performance ◽  
Trade Offs ◽  
Mean Kinetic Energy

The theoretical limit for wind turbine performance, the so-called Betz limit, arises from an inviscid, irrotational analysis of the streamtube around an actuator disk. In a wind farm in the atmospheric boundary layer, the physics are considerably more complex, encompassing shear, turbulent transport, and wakes from other turbines. In this study, the mean flow streamtube around a wind turbine in a wind farm is investigated with large eddy simulations of a periodic array of actuator disks in half-channel flow at a range of turbine thrust coefficients. Momentum and mean kinetic energy budgets are presented, connecting the energy budget for an individual turbine to the wind farm performance as a whole. It is noted that boundary layer turbulence plays a key role in wake recovery and energy conversion when considering the entire wind farm. The wind farm power coefficient is maximized when the work done by Reynolds stress on the periphery of the streamtube is maximized, although some mean kinetic energy is also dissipated into turbulence. This results in an optimal value of thrust coefficient lower than the traditional Betz result. The simulation results are used to evaluate Nishino’s model of infinite wind farms, and design trade-offs described by it are presented.

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.

Mesoscale Influences of Wind Farms throughout a Diurnal Cycle

2013 ◽  
Vol 141 (7) ◽  
pp. 2173-2198 ◽  
Author(s):  
Anna C. Fitch ◽  
Julie K. Lundquist ◽  
Joseph B. Olson
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Diurnal Cycle ◽  
Wind Farm ◽  
Wind Farms ◽  
Temperature Perturbation ◽  
Mean Temperature ◽  
The Impact

Abstract Large wind farms are expected to influence local and regional atmospheric circulations. Using a mesoscale parameterization of the effects of wind farms that includes a momentum sink and a wind speed–dependent source of turbulent kinetic energy, simulations were carried out to quantify the impact of a wind farm on an atmospheric boundary layer throughout a diurnal cycle. The presence of a wind farm covering 10 km × 10 km is found to have a significant impact on the local atmospheric flow and on regions up to 60 km downwind at night. Daytime convective conditions show little impact of the wind farm on wind speeds, as the momentum deficits generated by the wind farm rapidly mix through the depth of the boundary layer. At night, the stable layer within the rotor area inhibits turbulent mixing of the momentum deficit, leading to a shallower wake and a greater reduction in the wind speed within the wake. Although a low-level jet forms at altitudes within the rotor area in the hours before dawn, it is completely eliminated within the wind farm. At night, a maximum warming of 1 K is seen at the bottom of the rotor area. Near the surface, there is less warming (0.5 K). Downwind, the surface temperature perturbation is small, with a cooling of up to 0.3 K. Over the simulation period, the mean temperature change over the wind farm area at 2 m is a very slight warming (0.2 K). Mean temperature changes downwind are negligible. Other influences on turbulent kinetic energy, surface heat fluxes, and boundary layer height, are discussed.

scholarly journals Set-point optimization in wind farms to mitigate effects of flow blockage induced by atmospheric gravity waves

2021 ◽  
Vol 6 (1) ◽  
pp. 247-271
Author(s):  
Luca Lanzilao ◽  
Johan Meyers
Keyword(s):  
Boundary Layer ◽  
Gravity Waves ◽  
Wind Farm ◽  
Wind Farms ◽  
Thrust Coefficient ◽  
Set Point ◽  
Coefficient Distribution ◽  
Atmospheric Gravity ◽  
Flow Blockage ◽  
Time Periodic

Abstract. Recently, it has been shown that flow blockage in large wind farms may lift up the top of the boundary layer, thereby triggering atmospheric gravity waves in the inversion layer and in the free atmosphere. These waves impose significant pressure gradients in the boundary layer, causing detrimental consequences in terms of a farm's efficiency. In the current study, we investigate the idea of controlling the wind farm in order to mitigate the efficiency drop due to wind-farm-induced gravity waves and blockage. The analysis is performed using a fast boundary layer model which divides the vertical structure of the atmosphere into three layers. The wind-farm drag force is applied over the whole wind-farm area in the lowest layer and is directly proportional to the wind-farm thrust set-point distribution. We implement an optimization model in order to derive the thrust-coefficient distribution, which maximizes the wind-farm energy extraction. We use a continuous adjoint method to efficiently compute gradients for the optimization algorithm, which is based on a quasi-Newton method. Power gains are evaluated with respect to a reference thrust-coefficient distribution based on the Betz–Joukowsky set point. We consider thrust coefficients that can change in space, as well as in time, i.e. considering time-periodic signals. However, in all our optimization results, we find that optimal thrust-coefficient distributions are steady; any time-periodic distribution is less optimal. The (steady) optimal thrust-coefficient distribution is inversely related to the vertical displacement of the boundary layer. Hence, it assumes a sinusoidal behaviour in the streamwise direction in subcritical flow conditions, whereas it becomes a U-shaped curve when the flow is supercritical. The sensitivity of the power gain to the atmospheric state is studied using the developed optimization tool for almost 2000 different atmospheric states. Overall, power gains above 4 % were observed for 77 % of the cases with peaks up to 14 % for weakly stratified atmospheres in critical flow regimes.

scholarly journals Parameterizations of Sea-Spray Impact on the Air–Sea Momentum and Heat Fluxes

2011 ◽  
Vol 139 (12) ◽  
pp. 3781-3797 ◽  
Author(s):  
J.-W. Bao ◽  
C. W. Fairall ◽  
S. A. Michelson ◽  
L. Bianco
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Weather Prediction ◽  
Heat Fluxes ◽  
Sea Spray ◽  
Surface Boundary ◽  
Near Surface ◽  
The Mean ◽  
Momentum And Heat Fluxes ◽  
The Impact

Abstract This paper focuses on parameterizing the effect of sea spray at hurricane-strength winds on the momentum and heat fluxes in weather prediction models using the Monin–Obukhov similarity theory (a common framework for the parameterizations of air–sea fluxes). In this scheme, the mass-density effect of sea spray is considered as an additional modification to the stratification of the near-surface profiles of wind, temperature, and moisture in the marine surface boundary layer (MSBL). The overall impact of sea-spray droplets on the mean profiles of wind, temperature, and moisture depends on the wind speed at the level of sea-spray generation. As the wind speed increases, the mean droplet size and the mass flux of sea-spray increase, rendering an increase of stability in the MSBL and the leveling-off of the surface drag. Sea spray also tends to increase the total air–sea sensible and latent heat fluxes at high winds. Results from sensitivity testing of the scheme in a numerical weather prediction model for an idealized case of hurricane intensification are presented along with a dynamical interpretation of the impact of the parameterized sea-spray physics on the structure of the hurricane boundary layer.

Boundary Layer and Surface Verification of the High-Resolution Rapid Refresh, Version 3

2020 ◽  
Vol 35 (6) ◽  
pp. 2255-2278
Author(s):  
Robert G. Fovell ◽  
Alex Gallagher
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Wind Speed ◽  
Prediction Models ◽  
Weather Prediction ◽  
Potential Temperature ◽  
Ground Level ◽  
Systematic Errors ◽  
Radiosonde Data ◽  
Near Surface

AbstractWhile numerical weather prediction models have made considerable progress regarding forecast skill, less attention has been paid to the planetary boundary layer. This study leverages High-Resolution Rapid Refresh (HRRR) forecasts on native levels, 1-s radiosonde data, and (primarily airport) surface observations across the conterminous United States. We construct temporally and spatially averaged composites of wind speed and potential temperature in the lowest 1 km for selected months to identify systematic errors in both forecasts and observations in this critical layer. We find near-surface temperature and wind speed predictions to be skillful, although wind biases were negatively correlated with observed speed and temperature biases revealed a robust relationship with station elevation. Above ≈250 m above ground level, below which radiosonde wind data were apparently contaminated by processing, biases were small for wind speed and potential temperature at the analysis time (which incorporates sonde data) but became substantial by the 24-h forecast. Wind biases were positive through the layer for both 0000 and 1200 UTC, and morning potential temperature profiles were marked by excessively steep lapse rates that persisted across seasons and (again) exaggerated at higher elevation sites. While the source or cause of these systematic errors are not fully understood, this analysis highlights areas for potential model improvement and the need for a continued and accessible archive of the data that make analyses like this possible.

scholarly journals Observed and simulated turbulent kinetic energy (WRF 3.8.1) overlarge offshore wind farms

2019 ◽  
Author(s):  
Simon K. Siedersleben ◽  
Andreas Platis ◽  
Julie K. Lundquist ◽  
Bughsin Djath ◽  
Astrid Lampert ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Wind Farm ◽  
Wind Farms ◽  
Horizontal Resolution ◽  
Offshore Wind ◽  
Vertical Resolution ◽  
Offshore Wind Farms ◽  
The Impact ◽  
Simulated Wind

Abstract. Because wind farms affect local weather and microclimates, parameterizations of their effects have been developed for numerical weather prediction models. While most wind farm parameterizations (WFP) include drag effects of wind farms, models differ on whether or not an additional turbulent kinetic energy (TKE) source should be included in these parameterizations to simulate the impact of wind farms on the boundary layer. Therefore, we use aircraft measurements above large offshore wind farms in stable conditions to evaluate WFP choices. Of the three case studies we examine, we find the simulated ambient background flow to agree with observations of temperature stratification and winds. This agreement allowing us to explore the sensitivity of simulated wind farm effects with respect to modeling choices such as whether or not to include a TKE source, horizontal resolution, vertical resolution, and advection of TKE. For a stably stratified marine atmospheric boundary layer (MABL), a TKE source and a horizontal resolution in the order of 5 km or finer are necessary to represent the impact of offshore wind farms on the MABL. Additionally, TKE advection results in excessively reduced TKE over the wind farms, which in turn causes an underestimation of the wind speed above the wind farm. Furthermore, using fine vertical resolution increases the agreement of the simulated wind speed with satellite observations of surface wind speed.

scholarly journals Set-point optimization in wind farms to mitigate effects of flow blockage induced by gravity waves

2020 ◽  
Author(s):  
Luca Lanzilao ◽  
Johan Meyers
Keyword(s):  
Boundary Layer ◽  
Gravity Waves ◽  
Wind Farm ◽  
Wind Farms ◽  
Thrust Coefficient ◽  
Set Point ◽  
Coefficient Distribution ◽  
Energy Gains ◽  
Flow Blockage ◽  
Time Periodic

Abstract. Recently, it has been shown that flow blockage in large wind farms may lift up the top of the boundary layer, thereby triggering atmospheric gravity waves in the inversion layer and in the free atmosphere. These waves impose significant pressure gradients in the boundary layer causing detrimental consequences in terms of farm's efficiency. In the current study, we investigate the idea of controlling the wind farm in order to mitigate the efficiency drop due to wind-farm induced gravity waves and blockage. The analysis is performed using a fast boundary layer model which divides the vertical structure of the atmosphere into three layers. The wind-farm drag force is applied over the whole wind-farm area in the lowest layer and is directly proportional to the wind-farm thrust set-point distribution. We implement an optimization model in order to derive the thrust-coefficient distribution which maximizes the wind-farm energy extraction. We use a continuous adjoint method to efficiently compute gradients for the optimization algorithm, which is based on a quasi-Newton method. Energy gains are evaluated with respect to a reference thrust-coefficient distribution based on the Betz–Joukowsky set point. We consider thrust coefficients that can change in space, as well as in time, i.e. considering time-periodic signals. However, in all our optimization results, we find that optimal thrust-coefficient distributions are steady; any time-periodic distribution is less optimal. The (steady) optimal thrust-coefficient distribution is inversely related to the vertical displacement of the boundary layer. Hence, it assumes a sinusoidal behaviour in the streamwise direction in subcritical flow conditions, whereas it becomes a U-shaped curve when the flow is supercritical. The sensitivity of the energy gain to the atmospheric state is studied using the developed optimization tool for almost two thousand different atmospheric states. Energy gains of up to 14 % are found for weakly stratified atmospheres in critical flow regimes.

scholarly journals Time-Dependent Upper Limits to the Performance of Large Wind Farms Due to Mesoscale Atmospheric Response

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6437
Author(s):  
Kelan Patel ◽  
Thomas D. Dunstan ◽  
Takafumi Nishino
Keyword(s):  
Wind Speed ◽  
Wind Farm ◽  
Weather Prediction ◽  
Wind Farms ◽  
Time Dependent ◽  
New Method ◽  
Offshore Wind ◽  
Dependent Manner ◽  
Upper Limits ◽  
Large Wind

A prototype of a new physics-based wind resource assessment method is presented, which allows the prediction of upper limits to the performance of large wind farms (including the power loss due to wind farm blockage) in a site-specific and time-dependent manner. The new method combines the two-scale momentum theory with a numerical weather prediction (NWP) model to assess the “extractability” of wind, i.e., how high the wind speed at a given site can be maintained as we increase the number of turbines installed. The new method is applied to an offshore wind farm site in the North Sea to demonstrate that: (1) Only a pair of NWP simulations (one without wind farm and the other with wind farm with an arbitrary level of flow resistance) are required to predict the extractability. (2) The extractability varies significantly from time to time, which may cause more than 30% of change in the upper limit of the performance of medium-to-high-density offshore wind farms. These results suggest the importance of considering not only the natural wind speed but also its extractability in the prediction of (both long- and short-term) power production of large wind farms.

scholarly journals Observations and simulations of a wind farm modifying a thunderstorm outflow boundary

2021 ◽  
Vol 6 (1) ◽  
pp. 1-13
Author(s):  
Jessica M. Tomaszewski ◽  
Julie K. Lundquist
Keyword(s):  
Wind Speed ◽  
Wind Farm ◽  
Surface Wind ◽  
Wind Farms ◽  
Surface Wind Speed ◽  
Near Surface ◽  
West Texas ◽  
Thunderstorm Outflow ◽  
Reflectivity Data ◽  
Outflow Boundary

Abstract. On 18 June 2019, National Weather Service (NWS) radar reflectivity data indicated the presence of thunderstorm-generated outflow propagating east-southeastward near Lubbock, Texas. A section of the outflow boundary encountered a wind farm and then experienced a notable reduction in ground-relative velocity, suggesting that interactions with the wind farm impacted the outflow boundary progression. We use the Weather Research and Forecasting model and its wind farm parameterization to address the extent to which wind farms can modify the near-surface environment of thunderstorm outflow boundaries. We conduct two simulations of the June 2019 outflow event: one containing the wind farm and one without. We specifically investigate the outflow speed of the section of the boundary that encounters the wind farm and the associated impacts on near-surface wind speed, moisture, temperature, and changes to precipitation features as the storm and associated outflow pass over the wind farm domain. The NWS radar and nearby West Texas Mesonet surface stations provide observations for validation of the simulations. The presence of the wind farm in the simulation clearly slows the progress of the outflow boundary by over 20 km h−1, similar to what was observed. Simulated perturbations of surface wind speed, temperature, and moisture associated with outflow passage were delayed by up to 6 min when the wind farm was present in the simulation compared to the simulation without the wind farm. However, impacts on precipitation were localized and transient, with no change to total accumulation across the domain.

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