Search NASA⌕ Search

SEARCH · Search NASA

Results for “Wind Direction”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Gaussian FLOWERS: Wind-rose-based analytical integration of Gaussian wake model for extremely fast AEP estimation

A major cost in the study of wind farm layout optimization is the repeated evaluation of the annual energy production (AEP). The current approach to estimating AEP requires a large set of flow simulations to be performed that cover each discrete wind speed and direction combination contained within the wind rose, followed by a probability-weighted sum of the power production resulting from each simulation. Even with inexpensive engineering wake models, this numerical integration scheme can lead to high computational costs. In this paper, we derive an analytical formulation for estimating farm AEP across every wind direction, based on a Gaussian wake velocity model, which reduces the number of wind farm simulations to a single function evaluation. As a result, we find that the Gaussian-FLOWERS approach reduces the time for AEP calculations by more than two orders of magnitude with a small trade-off in accuracy when compared to a conventional approach. This massive reduction in computation cost is useful to reduce overall costs in wind farm layout optimization studies.

17 WIND ENERGY↗
DOE OSTI2022

Evaluation of Turbulence and Dispersion in Multiscale Atmospheric Simulations over Complex Urban Terrain during the Joint Urban 2003 Field Campaign

Abstract This paper evaluates the representation of turbulence and its effect on transport and dispersion within multiscale and microscale-only simulations in an urban environment. These simulations, run using the Weather Research and Forecasting Model with the addition of an immersed boundary method, predict transport and mixing during a controlled tracer release from the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma. This work extends the results of a recent study through analysis of turbulence kinetic energy and turbulence spectra and their role in accurately simulating wind speed, direction, and tracer concentration. The significance and role of surface heat fluxes and use of the cell perturbation method in the numerical simulation setup are also examined. Our previous study detailed the model development necessary for our multiscale simulations, examined model skill at predicting wind speeds and tracer concentrations, and demonstrated that dynamic downscaling from mesoscale to microscale through a sequence of nested simulations can improve predictions of transport and dispersion relative to a microscale-only simulation forced by idealized meteorology. Here, predictions are compared with observations to assess qualitative agreement and statistical model skill at predicting wind speed, wind direction, tracer concentration, and turbulent kinetic energy at locations throughout the city. We also investigate the scale distribution of turbulence and the associated impact on model skill, particularly for predictions of transport and dispersion. Our results show that downscaled large-scale turbulence, which is unique to the multiscale simulations, significantly improves predictions of tracer concentrations in this complex urban environment. Significance Statement Simulations of atmospheric transport and mixing in urban environments have many applications, including pollution modeling for urban planning or informing emergency response following a hazardous release. These applications include phenomena with spatial scales spanning from millimeters to kilometers. Most simulations resolve flow only within the urban area of interest, omitting larger scales of turbulence and regional influences. This study examines a method that resolves both the small and large-scale flow features. We evaluate simulation accuracy by comparing predictions with observations from an experiment involving the release of a tracer gas in Oklahoma City, Oklahoma, with emphasis on correctly modeling turbulent fluctuations. Our results demonstrate the importance of resolving large-scale flow features when predicting transport and dispersion in urban environments.

42 ENGINEERING↗
DOE OSTI2021

Boundary Layer Climatology at ARM Southern Great Plains

Operational since 1992, the Atmospheric Radiation Measurement (ARM) southern great plains (SGP) site at Oklahoma, USA has become a reference research site for meteorological studies. Due to an open data policy the ARM data are used by researchers all over the world. In this report, we review the long-term climatology of the atmospheric boundary layer, SGP instrumentations, the site and some site-specific atmospheric conditions which potentially effect wind turbines within the region. As the atmospheric boundary layer is bounded and influenced by the surface, observations of surface radiation components and heat fluxes are crucial in understanding land-atmosphere interactions. The entrainment of air, updrafts, downdrafts and boundary layer height characteristics is needed for understanding the structure and growth of the atmospheric boundary layer. Therefore, measurements from both surface in-situ and remote sensing observations at SGP provide an overall climatology and their interactions from surface up to the boundary layer. Measurements from a 60 m meteorological tower, surface flux stations, disdrometers, soil temperature and moisture flux plates, coherent Doppler lidar, Raman lidar, radiosondes, and satellite data at SGP central facility were analyzed. All the measurements were generally within a few square kilometers of each other at the central facility. This report focuses on data from January 2010 to June 2020 at SGP central facility. The various sections describe the ARM SGP site and surrounding wind turbines; in-situ and remote sensing instrumentation used in the report; provides mathematical equations to analyze fluxes, turbulence and other boundary layer parameters; a climatological analysis of surface winds, fluxes and thermodynamic parameters for several years; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory; an analysis of the boundary layer winds and direction from a Doppler lidar; multi-year turbulence estimates through the boundary layer from a Doppler lidar; atmospheric boundary layer water vapor and relative humidity profiles from Raman lidar; cloud base height and boundary layer height from multiple sensors and satellite data; and finally site specific atmospheric conditions, such as nocturnal low-level jets. Diurnal, seasonal and yearly variations of surface, sub-surface and boundary layer quantities, such as wind speed, direction, temperature, atmospheric stability, soil temperature, and various atmospheric fluxes at SGP showed distinct trends useful for focused modeling studies. The applicability of surface similarity theory on ARM SGP data is also evaluated, which showed northerly flows are aligned with MO theory estimates compared to southerly flows. Boundary layer winds and direction profiles for several years from a Doppler lidar shows a consistent presence of a nocturnal low-level jet and predominant southerly wind directions through the boundary layer at SGP. The inter-annual variability at SGP is low (<3.5%), with a mean annual wind speed of approximately 7 m s -1 at 100 m above ground level. Boundary layer turbulence and moisture transport from Doppler and Raman lidars are evaluated, which provides evidence of increased water vapor mass flux into the great plains during nocturnal low-level jets. The moisture flux from nocturnal low-level jets is observed to be maximum during summer periods. A novel machine learning algorithm is implemented to accurately estimate the planetary boundary layer height, providing further insights into growth and destruction of the convective boundary layer height during various seasons and land-atmosphere conditions. The high frequency of low-level clouds during winter, spring and fall seasons is validated using the multi-sensor array and satellite estimates of cloud top height. Satellite vegetative fraction data provides insight into seasonal surface roughness and vegetation variability around SGP site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sensitivity Effects of High Temperature Overhead Conductors to Line Rating Variables

For traditional overhead transmission lines, the maximum allowable conductor operating temperature on ASCR, AAC, or AAAC lines for determining the static line ratings can be quite low, typically well under 100 C. At these low temperatures, the primary driver for determining static line ratings are assumptions made about the wind speed and direction and the ambient temperature. Assumptions for solar loading and emitted thermal radiation, driven by line emissivity and absorptivity, are secondary factors, and only provide small changes to the static ratings. However, when considering newer high temperature conductors such as ACSS, ACCR, ZTACIR, and ACCC® the maximum allowable conductor temperatures can be significantly higher, up to 250° C. This higher temperature shifts the importance of the emissivity assumptions of the overhead transmission line, due to the nature of the T4 dependence of the radiative heat loss compared to the T1 dependence of the convective heat loss, as well as shifting the dependency on local wind conditions. Typical assumptions in the United States for the emissivity/absorptivity of overhead transmission lines in determining the static ratings are to use a value of 0.5 for both parameters or set a value in the range of 0.7 to 0.9. Recent experimental tests at EPRI have shown that higher emissivity aging assumptions may not be valid in some regions of the US, and that actual values may be much lower (0.25-0.45) than older studies have predicted (0.8-0.9). Here, the assumptions of different US Regional Transmission Operators (RTOs) and different utilities within RTOs are examined for the static ratings for traditional lower operating temperatures up to 100° C as well as with the higher maximum temperature conductors associated with newer conductor designs at 250° C. The sensitivity of the static ratings is examined at both lower and higher temperature conductors with respect to overhead line emissivity and absorptivity, wind speed, wind direction, and solar loading, and ambient temperature. It is shown that the effects of the conductor absorptivity, solar flux and ambient temperature on the static rating are increased when the transmission line has a lower maximum conductor temperature. The effects of the conductor emissivity, wind direction and wind speed have increased effects on the static rating when the transmission line has a higher maximum conductor temperature. In addition, example weather data is used to calculate the conductor temperature with different line emissivity and absorptivity assumptions. This shows the effect of assumptions made for emissivity only has a minor impact for low temperature lines, but for high temperature transmission lines can cause a 150-200° C temperature swing.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Arctic Black Carbon Aerosol Deposition Study North Slope of Alaska 2020- Sonic Anemometer Measurements

Particles are removed from the atmosphere through both wet and dry deposition. These processes are poorly understood, though they constitute important uncertainties in climate and air quality models. This project aims to use observational constraints on particle fluxes to improve model representations of dry deposition. Within this data set, we measured wind properties using a sonic anemometer. Measurements were made at the meteorological tower between 9 Sept and 25 Oct 2021. This site is a coastal tundra location, and received snow during the project.

Gill Windmaster 3D Ultrasonic Anemometer↗
DOE OSTI2021

MADE3D: Enabling the next generation of high-torque density wind generators by additive design and 3D printing

Direct-drive wind turbine generators are increasing in popularity, thanks to recent project developments—especially offshore, where reliability and efficiency are major cost drivers. Yet, high capital costs are forcing many original equipment manufacturers to consider lightweight, high-torque density generators for next-generation multi-megawatt turbines that may be difficult to realize by traditional design or manufacturing methods. In this study, we present a new design framework enabled by advanced machine learning and multimaterial additive manufacturing to perform a magnetic topology optimization that maximizes the torque per rotor active mass for a 15-megawatt direct-drive permanent magnet wind generator. A comparison of the proposed approach against conventional topology optimization demonstrated a significant increase in computational efficiency and accuracy in performance predictions. Results using single and multimaterial compositions for rotor core and magnets identify a wider choice of 3D printable designs for a given specification. A hybrid combination of sintered and dysprosium-free polymer-bonded magnets shows good potential for torque performance by saving material costs up to 8.75%. More than 30% improvement in rotor torque densities is identified which can marginally improve the overall generator torque density. With the rapid evolution of multipowder deposition technolgies, this study can greatly inspire a new paradigm for design-driven manufacturing with novel material compositions and lightweight, low-cost, high-strength multimaterial geometries that were previously unexplored for direct-drive generators.

17 WIND ENERGY↗
DOE OSTI2021

MADE3D: Enabling the Next-Generation High-Torque- Density Wind Generators by Additive Design and 3D Printing

Direct-drive wind turbine generators are increasing in popularity, thanks to recent project developments - especially offshore, where reliability and efficiency are major cost drivers. Yet, high capital costs are forcing many original equipment manufacturers to consider lightweight, high-torque density generators for next-generation multi-megawatt turbines that may be difficult to realize by traditional design or manufacturing methods. In this study, we present a new design framework enabled by advanced machine learning and multimaterial additive manufacturing to perform a magnetic topology optimization that maximizes the torque per rotor active mass for a 15-megawatt direct-drive permanent magnet wind generator. A comparison of the proposed approach against conventional topology optimization demonstrated a significant increase in computational efficiency and accuracy in performance predictions. Results using single and multimaterial compositions for rotor core and magnets identify a wider choice of 3D printable designs for a given specification. A hybrid combination of sintered and dysprosium-free polymer-bonded magnets shows good potential for torque performance by saving material costs up to 8.75%. More than 30% improvement in rotor torque densities is identified which can marginally improve the overall generator torque density. With the rapid evolution of multipowder deposition technologies, this study can greatly inspire a new paradigm for design-driven manufacturing with novel material compositions and lightweight, low-cost, high-strength multimaterial geometries that were previously unexplored for direct-drive generators.

3D printing↗
DOE OSTI2021

Forecasting Dynamic Line Rating with Spatial Variation Considerations

Dynamic line rating (DLR) is a technology that allows the ampacity of an electrical conductor to be calculated using real-time or forecasted weather conditions. Historically, the ampacity of a conductor has been determined using a static line rating method which assumes conservative weather assumptions. Therefore, not only can DLR give a more accurate measurement of the true ampacity of a conductor, but it can also increase its ampacity during weather conditions with greater thermal mitigations. The two primary cooling factors in the ampacity calculations are wind speed and direction. In complex terrain, wind speed and direction can have large variations over short distances. Therefore, accurately identifying the limiting span of a transmission line requires high spatial resolution of the wind along its path. One solution is to install dense weather stations along their path, though this can become costly over long distances. Therefore, researchers have investigated the use of Computation Fluid Dynamic (CFD) simulations to accurately compute the wind field along the path of a transmission line and use these results to identify the limiting section of the conductor. This work presents a case study that evaluates the coupling of CFD simulations and forecasted weather simulations using the High-Resolution Rapid Refresh (HRRR) model points over a 2-year span within a region in south eastern Idaho. The primary goal of the work is the evaluation of the number of HRRR model points used, i.e., weather stations, along the path of the line and the accuracy of the resulting DLR ampacity. This was done using 4, 10, 17, 26, and 35 HRRR model points along two transmission line paths. The results indicate that as the number of model points are increased, the DLR ampacity of the lines decrease, yet converge as more points are added and demonstrate little change with additional HRRR points. It is expected that these results can help transmission line operators identify the number of weather stations that must be installed when coupled with CFD simulations and DLR ampacity to ensure accurate ratings and safe operations.

17 WIND ENERGY↗
DOE OSTI2021

Forecasting Dynamic Line Rating with Spatial Variation Considerations

Dynamic line rating (DLR) is a technology that allows the ampacity of an electrical conductor to be calculated using real-time or forecasted weather conditions. Historically, the ampacity of a conductor has been determined using a static line rating method which assumes conservative weather assumptions. Therefore, not only can DLR give a more accurate measurement of the true ampacity of a conductor, but it can also increase its ampacity during weather conditions with greater thermal mitigations. The two primary cooling factors in the ampacity calculations are wind speed and direction. In complex terrain, wind speed and direction can have large variations over short distances. Therefore, accurately identifying the limiting span of a transmission line requires high spatial resolution of the wind along its path. One solution is to install dense weather stations along their path, though this can become costly over long distances. Therefore, researchers have investigated the use of Computation Fluid Dynamic (CFD) simulations to accurately compute the wind field along the path of a transmission line and use these results to identify the limiting section of the conductor. This work presents a case study that evaluates the coupling of CFD simulations and forecasted weather simulations using the High-Resolution Rapid Refresh (HRRR) model points over a 2-year span within a region in south eastern Idaho. The primary goal of the work is the evaluation of the number of HRRR model points used, i.e., weather stations, along the path of the line and the accuracy of the resulting ampacity. This was done using 4, 10, 17, 26, and 35 HRRR model points along two transmission line paths. The results indicate that as the number of model points are increased, the DLR ampacity of the lines decrease, yet converge as more points are added and demonstrate little change with additional HRRR points. It is expected that these results can help transmission line operators identify the number of weather stations that must be installed when coupled with CFD simulations and DLR ampacity to ensure accurate ratings and safe operations.

17 WIND ENERGY↗
DOE OSTI2026

Statistical Correlation of Heliostat Pointing Deviation With Wind

This work was carried out as part of the Heliostat Consortium (HelioCon) Field Deployment subtask with the aim to develop a reduced order model framework for correlating wind speed and pointing deviation of a heliostat facet. There are only sparse field measurements of heliostat pointing deviations and accompanying wind conditions published in the literature. Heliostat test standards, such as IEC 62862-4-3, propose a suite of tests including laser pointing repeatability at wind speeds below 4 m/s, and provide technical requirements for heliostat slope and tracking deviations in coarse average wind speed bins of 4 m/s, 6 m/s, and 8 m/s. In addressing the gap of the variation of heliostat pointing deviation with wind speed, field measurements of laser pointing on a grid target and wind conditions were analyzed in this study at the Third-Party Metrology Platform at the National Laboratory of the Rockies (NLR) Flatirons Campus. Horizontal pointing deviations were found to follow a logarithmic relationship with peak wind speed, whereas vertical pointing deviations follow an exponential relationship with peak wind speed. Both horizontal and vertical pointing deviations also follow a second order polynomial relationship, as expected from the proportionality of elastic loads and deformations with the square of wind speed. The results indicate that heliostat facet pointing deviations in the vertical direction increase at a faster rate than in the horizontal direction with increasing wind speed over the tested range, however these are dependent on the heliostat structural design. Next steps are recommended for additional field measurements to confirm a linear relationship of pointing deviation with applied moment on a heliostat facet, and to distinguish between gravity-induced and wind-induced pointing deviations at different elevation angles. The derived correlations in the preliminary analysis in this report serve as a case study for heliostat developers and plant operators to estimate the wind-induced pointing deviations and their variation with peak gust wind speed. Next steps in future work would recommend higher resolution and longer duration datasets for different elevation angles and wind directions to reduce uncertainties and variance of collected laser beam spot data and their correlations with bin-averaged wind speed.

17 WIND ENERGY↗
DOE OSTI2025

GreenSight WxHive Unmanned Aerial System (UAS) Atmospheric Profiling at the SGP Central Facility

The GreenSight WxHive is capable of flying multiple nanodrones simultaneously to provide spatiotemporal atmospheric sampling. During the WH2yMSIE campaign, the WxHive would fly up to 5 nanodrones at once, performing profiling within the planetary boundary layer over the ARM SGP Central Facility site. The measurements provided by the WxHive include latitude, longitude, altitude, pressure, temperature, humidity, and wind speed and direction. See the attached WeatherHive User Guide for more details about the instrument and measurements.

Air pressure↗
DOE OSTI2024

Virtual tower measurements during the American WAKE ExperimeNt (AWAKEN)

Dual-Doppler lidar measurements were made during the American WAKE ExperimeNt to provide height-resolved measurements of wind speed and direction at multiple locations immediately south of the leading row turbines in the King Plains wind farm in Oklahoma. These so-called virtual tower measurements were performed to characterize the inflow into the wind farm and to assess possible upwind blockage effects due to the collective action of the wind farm. The campaign was conducted from 12 November 2022 to 17 October 2023, during which time 14 unique virtual tower locations were sampled with heights ranging from 240 to 490 m AGL. The wind retrieval algorithm provided estimates of the horizontal winds and their uncertainties with a vertical resolution of about 10 m, while also accounting for the tilt of the lidar platform. The virtual tower results are compared to collocated lidar wind profiling data at the A1 site, which was located roughly 2.4 rotor diameters south of the nearest turbine. The wind speed difference between the wind profiler and the virtual tower was found to be quite sensitive to atmospheric stability and wind direction below 250 m AGL. The largest differences were observed for inflow under stable conditions, where the profiler wind speeds were observed to be about 22% lower than the virtual tower near hub height. These results suggest that there are persistent horizontal gradients in the flow upwind of the wind farm which result in biased estimates using standard ground-based lidar wind profiling methods.

17 WIND ENERGY↗
DOE OSTI2021

An overview of wind-energy-production prediction bias, losses, and uncertainties

Abstract. The financing of a wind farm directly relates to the preconstruction energy yield assessments which estimate the annual energy production for the farm. The accuracy and the precision of the preconstruction energy estimates can dictate the profitability of the wind project. Historically, the wind industry tended to overpredict the annual energy production of wind farms. Experts have been dedicated to eliminating such prediction errors in the past decade, and recently the reported average energy prediction bias is declining. Herein, we present a literature review of the energy yield assessment errors across the global wind energy industry. We identify a long-term trend of reduction in the overprediction bias, whereas the uncertainty associated with the prediction error is prominent. We also summarize the recent advancements of the wind resource assessment process that justify the bias reduction, including improvements in modeling and measurement techniques. Additionally, because the energy losses and uncertainties substantially influence the prediction error, we document and examine the estimated and observed loss and uncertainty values from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 wind resource assessment standard. From our findings, we highlight opportunities for the industry to move forward, such as the validation and reduction of prediction uncertainty and the prevention of energy losses caused by wake effect and environmental events. Overall, this study provides a summary of how the wind energy industry has been quantifying and reducing prediction errors, energy losses, and production uncertainties. Finally, for this work to be as reproducible as possible, we include all of the data used in the analysis in appendices to the article.

17 WIND ENERGY↗
DOE OSTI2022

Low Space Harmonic Content Windings (LSHWs) Applied to Improve the Pareto Front in Design Optimization of Electric Machines

In design optimization of high performance electric machines where the power density is increasingly a key metric, it is often desirable to maximize the average torque output within a given volume. However, if a smooth output is also required, the torque ripple may become a hurdle as it tends to increase with the average torque for conventional windings. A direct benefit of low space harmonic content windings (LSHWs), featuring the suppression or elimination of targeted non-working orders in the winding magnetomotive force (MMF), is the torque ripple reduction. This paper provides a detailed analysis of torque ripple pairs and the space-time harmonic order mapping, with concise results that applies to both distributed windings and fractionalslot concentrated windings (FSCWs) of any slot/pole combination. Metamodel-based optimizations are performed to compare two LSHWs with a conventional winding. Improved Pareto fronts are validated, which confirms higher torque producing capabilities at various torque ripple thresholds for LSHWs.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Wind 2H2 Project (CRADA Final Report)

The Xcel-NREL Wind Electrolysis R&D Project is designed to gain knowledge and insight about producing hydrogen from electricity for use as a vehicle fuel and as a “stored wind”. The project will analyze producing hydrogen directly from wind as well as from the electric grid. In addition, it will look at storing hydrogen and then using it to put electricity back onto the grid. Modifications were made to the original scope to also include electric vehicles integration with the electric grid. This report addresses Task 8 portion of the CRADA, focused on testing and measuring the attributes of plug-in electric vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Wind 2H2 Project: CRADA Final Report (Project 2)

The Xcel-NLR Wind Electrolysis R&D Project is designed to gain knowledge and insight about producing hydrogen from electricity for use as a vehicle fuel and as a "stored wind". The project will analyze producing hydrogen directly from wind as well as from the electric grid. In addition, it will look at storing hydrogen and then using it to put electricity back onto the grid.

17 WIND ENERGY↗
DOE OSTI2026

Wind and Temperature Consensus at Horn Point, HU-Beltsville, Piney Run (Maryland) in support of CoURAGE

The Maryland Department of the Environment (MDE) operates a ground-based atmospheric profiling network consisting of collocated radar wind profilers (RWP) and radio acoustic sounding systems (RASS) as part of its Ambient Air Monitoring Program. This network provides continuous observations of wind and temperature structure in the lower troposphere to support air quality forecasting, regulatory analysis, and atmospheric research. The network currently includes three fixed sites across Maryland: Horn Point (HP, lower eastern shore) [38.587525°,-76.141006°], Howard University-Beltsville (HUB, central Maryland) [39.055277°, -76.878632°], and Piney Run (PR, western Maryland) [39.705950°, -79.012000°] The network is designed to capture regional variability in atmospheric transport and boundary-layer processes. These systems measure vertical profiles of horizontal wind speed and direction using Doppler radar techniques, with observations typically spanning from ~100 m above ground level up to approximately 2.5–4 km. Measurements are derived from the Doppler shift of backscattered electromagnetic signals, enabling retrieval of wind vectors at multiple altitudes with high temporal resolution (e.g., 30-minute averages reported every 6 minutes). Each radar wind profiler is paired with a Radio Acoustic Sounding System (RASS) to provide profiles of virtual temperature in the lower atmosphere (~100–200 m AGL) by measuring the propagation speed of acoustic waves. Together, the RWP/RASS system yields a coupled data set of thermodynamic and kinematic atmospheric structure, including additional parameters such as vertical velocity, radial velocity, signal-to-noise ratio, and spectral width for advanced analysis. There are two types of files for each station: wind data (files with a "w" prefix) and virtual temperature RASS data (files with a "t" prefix). The wind data files are in the format wYYDDD.cns, where YY is the 2-digit year and DDD is the day of the year. The RASS virtual temperature data files are in the format tYYDDD.cns. Each record has the following header structure: Line 1 : Station Name RASS files Line 2 : RASS rev DeTect_2.0, WINDS files Line 2 : WINDS rev ATI 5.1 Line 3 : N latitude, W longitude, and site elevation (m) Line 4 : Date and begin time of consensus: yy mm dd hh mn ss plus # minutes to add to get UTC Line 5 : Consensus averaging time (minutes); number of beams; number of range gates Line 6 : Number of records required to make consensus (num) total number of records (tot) and the consensus window size (m/s) in the format: num:tot (window) RASS files Line 7 : no. of coded cells, no. of spec, pulse width (ns), and inter-pulse period (µs), WINDS files Line 7 : No. of coded cells, no. of spectra, pulse width (ns), and inter-pulse period (µs), each with a pair of values: first value is for oblique beams, second for vertical RASS files Line 8 : Full scale Doppler value (m/s) Delay to first gate (ns) Number of gates Spacing of gates (ns), WINDS files Line 8 : Full scale Doppler velocity (m/s), oblique and vertical Vertical correction applied to oblique beams? (0 = no, 1 = yes) Delay to first gate (ns), oblique and vertical Number of gates, oblique and vertical Spacing of gates (ns), oblique and vertical Line 9 : Azimuth and elevation (9s indicate vertical beam not used) RASS files Line 10, values : HT = Height above ground (km), T = Uncorrected virtual temperature consensus (deg C), Tc = Corrected virtual temperature consensus (deg C), W = Vertical wind consensus (9s indicate vertical beam not used, w-component, positive upward, m/s), CNT = Number of records that made consensus (for the 3 values in same order), SNR = Average signal to noise ratio (dB) of records in consensus (same order) WINDS files Line 10, values : HT = Height above ground (km), SPD = Wind speed (m/s), DIR = Wind direction (deg E of N from N), RAD = Radial velocities for each beam (m/s) in order given in azimuth and elevation line (positive toward radar; 9s indicate vertical beam not used, CNT = Number of records that made consensus, SNR = Average signal to noise ratio (dB) of records in consensus

{"wind speed and direction",temperature}↗
DOE OSTI2020

The Effects of Wind Veer During the Morning and Evening Transitions

Direction and speed wind shear modify turbine performance by changing inflow conditions on turbine blades. Using observations from the 2013 CWEX campaign, we found the daily atmospheric boundary layer transitions (morning and evening) match periods of high electricity demand for a wind farm in central Iowa. Power production during these periods was undermined for large direction shear and low speed shear scenarios. The morning transition displayed larger direction shear over the rotor layer for most wind speeds compared to the evening period. This resulted in lower turbine performance for the morning compared to the evening and whole day. This study shows that the combined effect of direction and speed shear is affecting turbine operation during high electricity demand times of day, predominantly during the morning at this wind farm.

17 WIND ENERGY↗