Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

Abstract. Forecasts of wind power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind turbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate that a vertical grid with nominally 12-m vertical resolution is necessary for reproducing the observed power production, with statistical significance. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed and low turbulence conditions. We also find the WFP performance is independent of atmospheric stability, the number of wind turbines per model grid cell, and the upwind-downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed. </jats:p

US East Coast lidar measurements show offshore wind turbines will encounter very low atmospheric turbulence

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Bodini, N., Lundquist, J. K., & Kirincich, A. US East Coast lidar measurements show offshore wind turbines will encounter very low atmospheric turbulence. Geophysical Research Letters, 46(10), (2019):5582-5591, doi:10.1029/2019GL082636.The rapid growth of offshore wind energy requires accurate modeling of the wind resource, which can be depleted by wind farm wakes. Turbulence dissipation rate (ϵ) governs the accuracy of model predictions of hub‐height wind speed and the development and erosion of wakes. Here we assess the variability of turbulence kinetic energy and ϵ using 13 months of observations from a profiling lidar deployed on a platform off the Massachusetts coast. Offshore, ϵ is 2 orders of magnitude smaller than onshore, with a subtle diurnal cycle. Wind direction influences the annual cycle of turbulence, with larger values in winter when the wind flows from the land, and smaller values in summer, when the wind flows from open ocean. Because of the weak turbulence, wind plant wakes will be stronger and persist farther downwind in summer.Collection of the wind data was funded by the Massachusetts Clean Energy Center through agreements with WHOI and AWS Truepower. The authors appreciate the efforts of the MVCO/ASIT technicians and AWS staff who collected the data. This analysis was supported by the National Science Foundation CAREER Award (AGS‐1554055) to J. K. L. and N. B., and by internal funds from WHOI for A. K. This work was authored (in part) by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract DE‐AC36‐08GO28308. Funding was provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Wind Energy Technologies Office. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid‐up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. The lidar observations used here are described at https://www.masscec.com/masscec-metocean-data-initiative, and available at https://doi.org/10.26025/1912/24050. The postprocessed data and the scripts used for the Figures of the present paper can be found at https://github.com/nicolabodini/GRL_OffshoreTurbulence.2019-11-0

An LES-based airborne Doppler lidar simulator and its application to wind profiling in inhomogeneous flow conditions

Wind profiling by Doppler lidar is common practice and highly useful in a wide range of applications. Airborne Doppler lidar can provide additional insights relative to ground-based systems by allowing for spatially distributed and targeted measurements. Providing a link between theory and measurement, a first large eddy simulation (LES)-based airborne Doppler lidar simulator (ADLS) has been developed. Simulated measurements are conducted based on LES wind fields, considering the coordinate and geometric transformations applicable to real-world measurements. The ADLS provides added value as the input truth used to create the measurements is known exactly, which is nearly impossible in real-world situations. Thus, valuable insight can be gained into measurement system characteristics as well as retrieval strategies. As an example application, airborne Doppler lidar wind profiling is investigated using the ADLS. For commonly used airborne velocity azimuth display (AVAD) techniques, flow homogeneity is assumed throughout the retrieval volume, a condition which is violated in turbulent boundary layer flow. Assuming an ideal measurement system, the ADLS allows to isolate and evaluate the error in wind profiling which occurs due to the violation of the flow homogeneity assumption. Overall, the ADLS demonstrates that wind profiling is possible in turbulent wind field conditions with reasonable errors (root mean squared error of 0.36 m s−1 for wind speed when using a commonly used system setup and retrieval strategy for the conditions investigated). Nevertheless, flow inhomogeneity, e.g., due to boundary layer turbulence, can cause an important contribution to wind profiling error and is non-negligible. Results suggest that airborne Doppler lidar wind profiling at low wind speeds (<5ms −1) can be biased, if conducted in regions of inhomogeneous flow conditions

How does inflow veer affect the veer of a wind-turbine wake?

Stably stratified flow conditions often exhibit wind veer, or a change of wind direction with height. When wind turbines experience this veered flow, the resulting wake structure tends to exhibit a stretching into an ellipsoid, rather than a symmetric shape or a curled shape. Observational studies suggest that the magnitude of wake veer is less than the veer of the inflow, whereas large-eddy simulations with actuator disk models and actuator line models suggest a range of relationships between inflow veer and wake veer. Here we present a series of large-eddy simulations with a range of veer shapes, a range of magnitudes of veer, a range of wind speeds, and both rotational directions of the wind-turbine rotor investigating the effect on the wake deflection angle. These results can guide the application of wake steering in stably stratified flow

Does the rotational direction of a wind turbine impact the wake in a stably stratified atmospheric boundary layer?

Stably stratified atmospheric boundary layers are often characterized by a veering wind profile, inwhich the wind direction changes clockwise with height in the Northern Hemisphere. Wind-turbine wakes re-spond to this veer in the incoming wind by stretching from a circular shape into an ellipsoid. We investigate therelationship between this stretching and the direction of the turbine rotation by means of large-eddy simulations.Clockwise rotating, counterclockwise rotating, and non-rotating actuator disc turbines are embedded in windfields of a precursor simulation with no wind veer and in wind fields with a Northern Hemispheric Ekman spiral,resulting in six combinations of rotor rotation and inflow wind condition. The wake strength, extension, width,and deflection depend on the interaction of the meridional component of Ekman spiral with the rotational direc-tion of the actuator disc, whereas the direction of the disc rotation only marginally modifies the wake if no veeris present. The differences result from the amplification or weakening/reversion of the spanwise and the verticalwind components due to the effect of the superposed disc rotation. They are also present in the streamwise windcomponent of the wake and in the total turbulence intensity. In the case of an counterclockwise rotating actuatordisc, the spanwise and vertical wind components increase directly behind the rotor, resulting in the same rota-tional direction in the whole wake while its strength decreases downwind. In the case of a clockwise rotatingactuator disc, however, the spanwise and vertical wind components of the near wake are weakened or even re-versed in comparison to the inflow. This weakening/reversion results in a downwind increase in the strength ofthe flow rotation in the wake or even a different rotational direction in the near wake in comparison to the farwake. The physical mechanism responsible for this difference can be explained by a simple linear superpositionof a veering inflow with a Rankine vortex

Changing the rotational direction of a wind turbine under veering inflow: a parameter study

All current-day wind-turbine blades rotate in clockwise direction as seen from an upstream perspective. The choice of the rotational direction impacts the wake if the wind profile changes direction with height. Here, we investigate the respective wakes for veering and backing winds in both hemispheres by means of large-eddy simulations. We quantify the sensitivity of the wake to the strength of the wind veer, the wind speed, and the rotational frequency of the rotor in the Northern Hemisphere. A veering wind in combination with counterclockwise-rotating blades results in a larger streamwise velocity output, a larger spanwise wake width, and a larger wake deflection angle at the same downwind distance in comparison to a clockwise-rotating turbine in the Northern Hemisphere. In the Southern Hemisphere, the same wake characteristics occur if the turbine rotates counterclockwise. These downwind differences in the wake result from the amplification or weakening or reversion of the spanwise wind component due to the effect of the superimposed vortex of the rotor rotation on the inflow's shear. An increase in the directional shear or the rotational frequency of the rotor under veering wind conditions increases the difference in the spanwise wake width and the wake deflection angle between clockwise- and counterclockwise-rotating actuators, whereas the wind speed lacks a significant impact

The sensitivity of the fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme

Wind plant wake impacts can be estimated with a number of simulation methodologies, each with its own fidelity and sensitivity to model inputs. In turbine-free mesoscale simulations, hub-height wind speeds often significantly vary with the choice of a planetary boundary layer (PBL) scheme. However, the sensitivity of wind plant wakes to a PBL scheme has not been explored because, as of the Weather Research and Forecasting model v4.3.3, wake parameterizations were only compatible with one PBL scheme. We couple the Fitch wind farm parameterization with the new NCAR 3DPBL scheme and compare the resulting wakes to those simulated with a widely used PBL scheme. We simulate a wind plant in pseudo-steady states under idealized stable, neutral, and unstable conditions with matching hub-height wind speeds using two PBL schemes: MYNN and the NCAR 3DPBL. For these idealized scenarios, average hub-height wind speed losses within the plant differ between PBL schemes by between −0.20 and 0.22 m s−1, and correspondingly, capacity factors range between 39.5 %–53.8 %. These simulations suggest that PBL schemes represent a meaningful source of modeled wind resource uncertainty; therefore, we recommend incorporating PBL variability into future wind plant planning sensitivity studies as well as wind forecasting studies.</p

How does the rotational direction of an upwind turbine affect its downwind neighbour?

Wind-turbine blades rotate in clockwise direction looking downstream on the rotor. During daytime conditions of the atmospheric boundary layer, the rotational direction has no influence on the turbine wakes. In stably stratified conditions occurring during night, the atmospheric inflow is often characterized by a veering inflow describing a clockwise wind direction change with height in the Northern Hemisphere. A changing wind direction with height interacting with the rotor impacts its wake characteristics (wake elongation, width and deflection). We investigate the impact on the turbine performance (streamwise velocity for power, turbulence kinetic energy for loading) of a downwind turbine considering the four possible combinations of rotational directions of two 5 MW NREL rotors by means of large-eddy simulations. A counterclockwise rotating upwind turbine results in a 4.1% increase of the rotor averaged inflow velocity at the downwind rotor in comparison to a common clockwise rotating upwind turbine rotor. In case of two counterclockwise rotating rotors, the increase is 4.5%. This increase in streamwise velocity is accompanied by a 3.7% increase in rotor averaged turbulence kinetic energy. The performance difference of the downwind rotor (+4.8% increase of cumulative power of both wind turbines, if the upwind rotor rotates counterclockwise) results from the rotational direction dependent amplification or weakening of the spanwise and the vertical wind components, which is the result of the superposition of veering inflow and upwind rotor rotation

Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1)

Wind farms affect local weather and microclimates; hence, parameterizations of their effects have been developed for numerical weather prediction models. While most wind farm parameterizations (WFPs) 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 allows 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 on 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 deficit above the wind farm. Furthermore, using fine vertical resolution increases the agreement of the simulated wind speed with satellite observations of surface wind speed