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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Wind Measurements from Arc Scans with Doppler Wind Lidar

When defining optimal scanning geometries for scanning lidars for wind energy applications, we found that it is still an active field of research. Our paper evaluates uncertainties associated with arc scan geometries and presents recommendations regarding optimal configurations in the atmospheric boundary layer. The analysis is based on arc scan data from a Doppler wind lidar with one elevation angle and seven azimuth angles spanning 30° and focuses on an estimation of 10-min mean wind speed and direction. When flow is horizontally uniform, this approach can provide accurate wind measurements required for wind resource assessments in part because of its high resampling rate. Retrieved wind velocities at a single range gate exhibit good correlation to data from a sonic anemometer on a nearby meteorological tower, and vertical profiles of horizontal wind speed, though derived from range gates located on a conical surface, match those measured by mast-mounted cup anemometers. Uncertainties in the retrieved wind velocity are related to high turbulent wind fluctuation and an inhomogeneous horizontal wind field. Moreover, the radial velocity variance is found to be a robust measure of the uncertainty of the retrieved wind speed because of its relationship to turbulence properties. It is further shown that the standard error of wind speed estimates can be minimized by increasing the azimuthal range beyond 30° and using five to seven azimuth angles.

17 WIND ENERGY↗
DOE OSTI2016

Analysis of the Uncertainty in Wind Measurements from the Atmospheric Radiation Measurement Doppler Lidar during XPIA: Field Campaign Report

In March and April of 2015, the ARM Doppler lidar that was formerly operated at the Tropical Western Pacific site in Darwin, Australia (S/N 0710-08) was deployed to the Boulder Atmospheric Observatory (BAO) for the eXperimental Planetary boundary-layer Instrument Assessment (XPIA) field campaign. The goal of the XPIA field campaign was to investigate methods of using multiple Doppler lidars to obtain high-resolution three-dimensional measurements of winds and turbulence in the atmospheric boundary layer, and to characterize the uncertainties in these measurements. The ARM Doppler lidar was one of many Doppler lidar systems that participated in this study. During XPIA the 300-m tower at the BAO site was instrumented with well-calibrated sonic anemometers at six levels. These sonic anemometers provided highly accurate reference measurements against which the lidars could be compared. Thus, the deployment of the ARM Doppler lidar during XPIA offered a rare opportunity for the ARM program to characterize the uncertainties in their lidar wind measurements. Results of the lidar-tower comparison indicate that the lidar wind speed measurements are essentially unbiased (~1cm s-1), with a random error of approximately 50 cm s-1. Two methods of uncertainty estimation were tested. The first method was found to produce uncertainties that were too low. The second method produced estimates that were more accurate and better indicators of data quality. As of December 2015, the first method is being used by the ARM Doppler lidar wind value-added product (VAP). One outcome of this work will be to update this VAP to use the second method for uncertainty estimation.

Atmospheric boundary layer, lidar-derived wind spe↗
DOE OSTI2014

Estimating the Wind Resource in Uttarakhand: Comparison of Dynamic Downscaling with Doppler Lidar Wind Measurements

Previous estimates of the wind resources in Uttarakhand, India, suggest minimal wind resources in this region. To explore whether or not the complex terrain in fact provides localized regions of wind resource, the authors of this study employed a dynamic down scaling method with the Weather Research and Forecasting model, providing detailed estimates of winds at approximately 1 km resolution in the finest nested simulation.

17 WIND ENERGY↗
DOE OSTI2017

Validating precision estimates in horizontal wind measurements from a Doppler lidar

Results from a recent field campaign are used to assess the accuracy of wind speed and direction precision estimates produced by a Doppler lidar wind retrieval algorithm. The algorithm, which is based on the traditional velocity-azimuth-display (VAD) technique, estimates the wind speed and direction measurement precision using standard error propagation techniques, assuming the input data (i.e., radial velocities) to be contaminated by random, zero-mean, errors. For this study, the lidar was configured to execute an 8-beam plan-position-indicator (PPI) scan once every 12 min during the 6-week deployment period. Several wind retrieval trials were conducted using different schemes for estimating the precision in the radial velocity measurements. Here, the resulting wind speed and direction precision estimates were compared to differences in wind speed and direction between the VAD algorithm and sonic anemometer measurements taken on a nearby 300 m tower.

17 WIND ENERGY↗
DOE OSTI2016

POD-based constrained sensor placement and field reconstruction from noisy wind measurements: A perturbation study

Sensor placement at the extrema of Proper Orthogonal Decomposition (POD) is efficient and leads to accurate reconstruction of the wind field from a limited number of measure- ments. In this paper we extend this approach of sensor placement and take into account measurement errors and detect possible malfunctioning sensors. We use the 48 hourly spa- tial wind field simulation data sets simulated using the Weather Research an Forecasting (WRF) model applied to the Maine Bay to evaluate the performances of our methods. Specifically, we use an exclusion disk strategy to distribute sensors when the extrema of POD modes are close. It turns out that this strategy can also reduce the error of recon- struction from noise measurements. Also, by a cross-validation technique, we successfully locate the malfunctioning sensors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

TURBULENCE IN THE SOLAR WIND MEASURED WITH COMET TAIL TEST PARTICLES

By analyzing the motions of test particles observed remotely in the tail of Comet Encke, we demonstrate that the solar wind undergoes turbulent processing enroute from the Sun to the Earth and that the kinetic energy entrained in the large-scale turbulence is sufficient to explain the well-known anomalous heating of the solar wind. Using the heliospheric imaging (HI-1) camera on board NASA's STEREO-A spacecraft, we have observed an ensemble of compact features in the comet tail as they became entrained in the solar wind near 0.4 AU. We find that the features are useful as test particles, via mean-motion analysis and a forward model of pickup dynamics. Using population analysis of the ensemble's relative motion, we find a regime of random-walk diffusion in the solar wind, followed, on larger scales, by a surprising regime of semiconfinement that we attribute to turbulent eddies in the solar wind. The entrained kinetic energy of the turbulent motions represents a sufficient energy reservoir to heat the solar wind to observed temperatures at 1 AU. We determine the Lagrangian-frame diffusion coefficient in the diffusive regime, derive upper limits for the small scale coherence length of solar wind turbulence, compare our results to existing Eulerian-frame measurements, and compare the turbulent velocity with the size of the observed eddies extrapolated to 1 AU. We conclude that the slow solar wind is fully mixed by turbulence on scales corresponding to a 1–2 hr crossing time at Earth; and that solar wind variability on timescales shorter than 1–2 hr is therefore dominated by turbulent processing rather than by direct solar effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Development of a Ballon-Borne Barge-Mounted Wind Measurement Platform

Sandia National Laboratories (SNL) is developing a low-cost, environmentally safe, and weather-proof sensor system that can be deployed offshore for extended periods of time for wind resource monitoring. The system has clear economic benefits over meteorological (met) tower approaches and is easily relocated to multiple locations across a project site. The end development goal is a buoy or barge-based, balloon-borne atmospheric measurement platform that operates autonomously in all but the most severe weather conditions, provides data of comparable accuracy to a met tower, and provides more accurate wind data at higher altitudes than floating lidar at half the cost.

17 WIND ENERGY↗
DOE OSTI2013

KINETIC PLASMA TURBULENCE IN THE FAST SOLAR WIND MEASURED BY CLUSTER

The k-filtering technique and wave polarization analysis are applied to Cluster magnetic field data to study plasma turbulence at the scale of the ion gyroradius in the fast solar wind. Waves are found propagating in directions nearly perpendicular to the background magnetic field at such scales. The frequencies of these waves in the solar wind frame are much smaller than the proton gyrofrequency. After the wavevector k is determined at each spacecraft frequency f{sub sc}, wave polarization property is analyzed in the plane perpendicular to k. Magnetic fluctuations have {delta}B > {delta}B{sub Parallel-To} (here the Parallel-To and refer to the background magnetic field B{sub 0}). The wave magnetic field has right-handed polarization at propagation angles {theta}{sub kB} < 90 Degree-Sign and >90 Degree-Sign . The magnetic field in the plane perpendicular to B{sub 0}, however, has no clear sense of a dominant polarization but local rotations. We discuss the merits and limitations of linear kinetic Alfven waves (KAWs) and coherent Alfven vortices in the interpretation of the data. We suggest that the fast solar wind turbulence may be populated with KAWs, small-scale current sheets, and Alfven vortices at ion kinetic scales.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Development of a Balloon-Borne Barge-Mounted Wind Measurement Platform

Atmospheric measurements are collected from anemometer modules (cup-version pictured) that are attached to a tether line between a balloon and barge at user-specified intervals. Each module samples wind speed, wind direction, pressure, temperature, relative humidity, and GPS-derived latitude, longitude, and altitude in situ at 1 Hz or faster and transmits the data wirelessly to a base station on a barge. Fiber-optic based distributed temperature sensing (DTS) also provides an almost continuous atmospheric temperature profile with a vertical spatial resolution of 0.25 m.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

2013 LIDAR Campaign at Buena Vista Wind Farm: An Examination of Hill "Speedup" Flows

In June 2013, two Laser and Detection Ranging (lidar) units (ZephIR 300, Natural Power, North Ledbury, England) were deployed at the Buena Vista Wind Farm in the Altamont Hills region of California until mid-August of that year. This was the third field campaign at Buena Vista for the 12-ERD-069 project, following a winter campaign in 2011-2012 and a summer campaign in 2012. The lidar data provided wind measurements at the base (“flatland” lidar) and along the slope (“hill” lidar) of a ridge to study the flow as it moved up and along the ridge towards turbine A08 under varying stability conditions. The lidars measured wind speed, direction and turbulence at ten measurement heights including ones equivalent to the turbine rotor-disk. Instrument placement is shown in Figures 1 and 2. The placement of the two lidars was based on wind direction measurements taken at the hill lidar location during summer of 2012. The predominant wind direction in 2013 was nearly identical to 2012 and the lidar locations proved optimal for capturing wind flow as it approached A08 from the southwest. SCADA data provided 10-minute nacelle wind speed and power data for the nearby turbines.

17 WIND ENERGY↗
DOE OSTI2014

Assessment and Optimization of Lidar Measurement Availability for Wind Turbine Control (Poster)

Integrating Lidar to improve wind turbine controls is a potential breakthrough for reducing the cost of wind energy. By providing undisturbed wind measurements up to 400m in front of the rotor, Lidar may provide an accurate update of the turbine inflow with a preview time of several seconds. Focusing on loads, several studies have evaluated potential reductions using integrated Lidar, either by simulation or full scale field testing.

17 WIND ENERGY↗