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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Can reanalysis products outperform mesoscale numerical weather prediction models in modeling the wind resource in simple terrain?

Mesoscale numerical weather prediction (NWP) models are generally considered more accurate than reanalysis products in characterizing the wind resource at heights of interest for wind energy, given their finer spatial resolution and more comprehensive physics. However, advancements in the latest ERA-5 reanalysis product motivate an assessment on whether ERA-5 can model wind speeds as well as a state-of-the-art NWP model – the Weather Research and Forecasting (WRF) Model. We consider this research question for both simple terrain and offshore applications. Specifically, we compare wind profiles from ERA-5 and the preliminary WRF runs of the Wind Integration National Dataset (WIND) Toolkit Long-term Ensemble Dataset (WTK-LED) to those observed by lidars at a site in Oklahoma, United States, and in a United States Atlantic offshore wind energy area. We find that ERA-5 shows a significant negative bias (~-1ms-1) at both locations, with a larger bias at the land-based site. WTK-LED-predicted wind speed profiles show a limited negative bias (~-0.5ms-1) offshore and a slight positive bias (~+0.5ms-1) at the land-based site. On the other hand, we find that ERA-5 outperforms WTK-LED in terms of the centered root-mean-square error (cRMSE) and correlation coefficient, for both the land-based and offshore cases, in all atmospheric stability conditions. We find that WTK-LED's higher cRMSE is caused by its tendency to overpredict the amplitude of the wind speed diurnal cycle. At the land-based site, this is partially caused by wind plant wake effects not being accurately captured by WTK-LED.

17 WIND ENERGY↗
DOE OSTI2025

Flexible PCB Windings Size Optimization for Winding AC Resistance Minimization Under the Sinusoidal Voltage Regime

In this paper, optimization of the winding AC resistance of the flexible printed circuit board (FPCB) wire windings is performed. A one-dimensional model of the FPCB winding is introduced and an equation for the FPCB winding AC resistance and its low and medium frequency approximation are derived. The approximate FPCB winding AC resistance equation is used to derive optimum thickness of the FPCB winding conductor thickness at which minimum of winding AC resistance (global optimum) is achieved. The Finite Element Method analysis and experimental verification of derived equations (winding resistance, impedance, power loss, and temperature measurements) is performed in order validate derived model and winding resistance equation.

42 ENGINEERING↗
DOE OSTI2018

Analysis of Wind Speed Shear and Turbulence LiDAR Measurements to Support Offshore Wind in the Northeast United States

In this paper, we present wind speed measurements collected at 40m to 200m above sea-level to support the New England Aqua Ventus I 12 MW Floating Offshore Wind Farm to be located 17km offshore the Northeast United States. The high-altitude wind speed data are unique and represent some of the first measurements made offshore in this part of the country which is actively being developed for offshore wind. Multiple LiDAR measurements were made using a DeepCLiDAR floating buoy and LiDARs located on land on a nearby island. The LiDARs compared favorably thereby confirming the LiDAR buoy measurements. Wind speed shear profiles are presented. The measurements are compared against industry standard mesoscale model outputs and offshore design codes including the American Bureau of Shipping, American Petroleum Institute, and DNV-GL guides. Significant variation in the vertical wind speed profile occurs throughout the year. This variation is not currently addressed in offshore wind design standards which typically recommend the use of only a few values for wind shear in operational and extreme conditions. The mean wind shears recorded were also higher than industry recommended values. Additionally, turbulence measurements made from the LiDAR, although not widely accepted in the scientific community, are presented and compared against industry guidelines.

American Petroleum Institute↗
DOE OSTI2019

Winds of Change: Assessing Wind Energy Efficiency in Complex Terrain

In 2015, the Department of Energy (DOE) and the National Oceanic and Atmospheric Administration (NOAA) initiated a four-year study, the Second Wind Forecast Improvement Project (WFIP2), which aims to improve the accuracy of meteorological models that forecast wind speed in complex terrain for applications in wind energy (Wilczak et al.2019). As a part of WFIP2, a dataset was collected in the Columbian River and Basin regions of Oregon and Washington which led to significant wind forecast model improvements (Kenyon et al.2018). Similar to the observations performed in Oregon and Washington, Light Detection and Ranging (LiDAR) systems were deployed at three observation points at the Lawrence Livermore National Laboratory Site 300 Experimental Test Site as part of WFIP2. Site 300, located in the rolling hills approximately ten kilometers from the Altamont Pass Wind Resource Area, represents a second complex terrain location for validating and evaluating the model improvements made using the original Columbian River dataset. The three LiDARsystems continuously collected wind speed and direction data at heights ranging from 10 meters to 150 meters. The data were used to better understand how wind flow is modified over hills and valleys in the Altamont Pass Wind Resource Area and to determine the optimal hub height for new turbine installations in the region. We observed five popular turbine models that are installed in the Altamont Wind Resource Area Using the collected data and comparisons of existing turbine models in the area, the most efficient turbine model for the Altamont Wind ResourceArea based on power output was determined to be the Mitsubishi 1.0MW. Future work related to this research includes further comparing turbine models based on factors including overall cost and effects on wildlife as well as determining optimal spacing between turbine units.

17 WIND ENERGY↗
DOE OSTI2017

The Value of Wind Technology Innovation: Implications for the U.S. Power System, Wind Industry, Electricity Consumers, and Environment

Improvements to wind technologies have, in part, led to substantial deployment of U.S. wind power in recent years. The degree to which technology innovation will continue is highly uncertain adding to uncertainties in future wind deployment. We apply electric sector modeling to estimate the potential wind deployment opportunities across a range of technology advancement projections. The suite of projections considered span a wide range of possible cost and technology innovation trajectories, including those from a recent expert elicitation of wind energy experts, a projection based on the broader literature, and one reflecting estimates based on a U.S. DOE research initiative. In addition, we explore how these deployment pathways may impact the electricity system, electricity consumers, the environment, and the wind-related workforce. Overall, our analysis finds that wind technology innovation can have consequential implications for future wind power development throughout the United States, impact the broader electricity system, lower electric system and consumer costs, provide potential environmental benefits, and grow the U.S. wind workforce.

17 WIND ENERGY↗
DOE OSTI2015

Wind Vision: A New Era for Wind Power in the United States

With more than 4.5% of the nation's electricity supplied by wind energy today, the Department of Energy has collaborated with industry, environmental organizations, academic institutions, and national laboratories to develop a renewed Wind Vision, documenting the contributions of wind to date and envisioning a future where wind continues to provide key contributions to the nation’s energy portfolio. Building on and updating the 2008 20% Wind Energy by 2030 report, the new Wind Vision Report quantifies the economic, environmental, and social benefits of a robust wind energy future and the actions that wind stakeholders can take to make it a reality.

17 WIND ENERGY↗
DOE OSTI2024

Doppler Lidar Motion-Correction Wind Profiles (DLMCPROF-WIND) Value-Added Product Report

Wind speed and direction, together with pressure, temperature, and relative humidity, are the most fundamental atmospheric state parameters. Accurate measurement of these parameters is crucial for numerical weather prediction. Vertically resolved wind measurements in the atmospheric boundary layer are particularly important for modeling pollutant and aerosol transport. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility currently operates several scanning coherent Doppler lidar (DL) systems that provide accurate height-resolved measurements of wind speed and direction. These instruments operate in the near infrared (IR;1.5 microns) and provide range-resolved measurements of radial velocity, attenuated aerosol backscatter, and signal-to-noise ratio (SNR). The systems are operated using a fixed scan schedule consisting of plan position indicator (PPI) or Doppler Beam-Swing (DBS) scans. PPI scans are performed by scanning the beam in azimuth while maintaining a fixed elevation angle, and DBS scans are similar but typically also include a vertical beam. Radial velocity data from these scans are processed to yield profiles of wind speed direction. For stationary ground-based deployments, the Doppler Lidar Horizontal Wind Profiles (DLPROF-WIND) Value-Added-Product (VAP) provides height- and time-resolved measurements of the winds (Newsom and Krishnamurthy 2022). For operation on a moving platform, modifications to the existing DLPROF-WIND VAP are required to compensate for the effects of the platform motion. This report describes a parallel VAP, DLMCPROF-WIND, that was developed for computing motion-compensated wind profiles from ARM Doppler lidar data acquired during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign, when the lidar was deployed on the German icebreaker Polarstern.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

Low altitude wind shear statistics derived from measured and FAA proposed standard wind profiles

Wind shear statistics were calculated for a simulated data set using wind profiles proposed as a standard and compared to statistics derived from measured wind profile data. Wind shear values were grouped in altitude bands of 100 ft between 100 and 1400 ft, and in wind shear increments of 0.025 kt/ft between + or - 0.600 kt/ft for the simulated data set and between + or - 0.200 kt/ft for the measured set. No values existed outside the + or - 0.200 kt/ft boundaries for the measured data. Frequency distributions, means, and standard deviations were derived for each altitude band for both data sets, and compared. Also, frequency distributions were derived for the total sample for both data sets and compared. Frequency of occurrence of a given wind shear was about the same for both data sets for wind shears, but less than + or 0.10 kt/ft, but the simulated data set had larger values outside these boundaries. Neglecting the vertical wind component did not significantly affect the statistics for these data sets. The frequency of occurrence of wind shears for the flight measured data was essentially the same for each altitude band and the total sample, but the simulated data distributions were different for each altitude band. The larger wind shears for the flight measured data were found to have short durations.

Dunham, R. E., Jr.↗
NASA NTRS1989

Wind models for the NSTS ascent trajectory biasing for wind load alleviation

New concepts are presented for aerospace vehicle ascent wind profile biasing. The purpose for wind biasing the ascent trajectory is to provide ascent wind loads relief and thus decrease the probability for launch delays due to wind loads exceeding critical limits. Wind biasing trajectories to the profile of monthly mean winds have been widely used for this purpose. The wind profile models presented give additional alternatives for wind biased trajectories. They are derived from the properties of the bivariate normal probability function using the available wind statistical parameters for the launch site. The analytical expressions are presented to permit generalizations. Specific examples are given to illustrate the procedures. The wind profile models can be used to establish the ascent trajectory steering commands to guide the vehicle through the first stage. For the National Space Transportation System (NSTS) program these steering commands are called I-loads.

Smith, O. E.↗
NASA NTRS1990

Wind models for the NSTS ascent trajectory biasing for wind load alleviation

New concepts are presented for aerospace vehicle ascent wind profile biasing. The purpose for wind biasing the ascent trajectory is to provide ascent wind loads relief and thus decrease the probability for launch delays due to wind loads exceeding critical limits. Wind biasing trajectories to the the profile of monthly mean winds have been widely used for this purpose. The wind profile models presented give additional alternatives for wind biased trajectories. They are derived from the properties of the bivariate normal probability function using the available wind statistical parameters for the launch site. The analytical expressions are presented to permit generalizations. Specific examples are given to illustrate the procedures. The wind profile models can be used to establish the ascent trajectory steering commands to guide the vehicle through the first stage. For the National Space Transportation System (NSTS) program these steering commands are called I-loads.

Smith, O. E.↗
NASA NTRS1993

Derivation of satellite wind model functions using operational surface wind analyses - An altimeter example

One year of global surface wind products from multiple operational numerical weather prediction (NWP) forecast/analysis systems are used as comparison data to derive an empirical wind speed model function for the Geosat altimeter. The resulting model function is nearly identical to the modified Chelton-Wentz model for wind speeds from 4.5 to 15 m/s. Highly skewed distributions at low wind speeds are consistent with specular reflections and antenna mispointing errors hypothesized by others on the basis of extremely limited data. Mesoscale variability in the wind field and synoptic scale errors in the NWP products are shown to account for about 30 percent of the observed scatter of sigma(0) at each wind speed. The remaining scatter is largest at low winds, and decreases to a nearly constant value of about 12 percent at speeds greater than 7 m/s. Model function uncertainty expressed more traditionally in units of wind speed is examined for historical model functions as well as the present NWP-based model. The historical models have significant biases at high wind speeds owing to the lack of comparison in situ data used in their construction. The present study demonstrates that modern operational NWP surface wind products are sufficiently accurate to allow development of fully empirical model functions and associated error analyses.

Freilich, Michael H.↗
NASA NTRS1996

Wind Variability of B Supergiants: The Two-component Stellar Wind of gamma Arae - No. 2

The stellar wind of the rapidly rotating early-B supergiant, gamma Ara, is studied using time series, high-resolution IUE spectroscopy secured over approx. 6 days in 1993 March. Results are presented based on an analysis of several line species, including N(N), C(IV), Si(IV), Si(III), C(II), and Al(III). The wind of this star is grossly structured, with evidence for latitude-dependent mass loss which reflects the role of rapid rotation. Independent, co-existing time variable features are identified at low-velocity (redward of approx. -750 km/s) and at higher-speeds extending to approx. -1500 km/s. The interface between these structures is 'defined' by the appearance of a discrete absorption component which is extremely sharp (in velocity space). The central velocity of this 'Super DAC' changes only gradually, over several days, between approx. -400 and -750 km/s in most of the ions. However, its location is shifted redward by almost 400 km/s in Al(III) and C(II), indicating that the physical structure giving rise to this feature has a substantial velocity and ionization jump. Constraints on the relative ionization properties of the wind structures are discussed, together with results based on SEI line-profile-fitting methods. The overall wind activity in gamma Ara exhibits a clear ion dependence, such that low-speed features are promoted in low-ionization species, including Al(III), C(II), and Si(III). We also highlight that - in contrast to most OB stars - there are substantial differences in the epoch-to-epoch time-averaged wind profiles of gamma Ara. We interpret the results in terms of a two-component wind model for gamma Ara, with an equatorially compressed low ionization region, and a high speed, higher-ionization polar outflow. This picture is discussed in the context of the predicted bi-stability mechanism for line-driven winds in rapidly rotating early-B type stars, and the formation of compressed wind regions in rapidly rotating hot stars. The apparent absence of a substantial shift in the wind ionization mixture of gamma Ara, and the normal nature of its photospheric spectrum, suggests wind-compression as the likely dominant cause for the observed equatorial density enhancements.

Prinja, R. K.↗
NASA NTRS2015

Assimilation of Wind Profiles from Multiple Doppler Radar Wind Profilers for Space Launch Vehicle Applications

Space launch vehicles utilize atmospheric winds in design of the vehicle and during day-of-launch (DOL) operations to assess affects of wind loading on the vehicle and to optimize vehicle performance during ascent. The launch ranges at NASA's Kennedy Space Center co-located with the United States Air Force's (USAF) Eastern Range (ER) at Cape Canaveral Air Force Station and USAF's Western Range (WR) at Vandenberg Air Force Base have extensive networks of in-situ and remote sensing instrumentation to measure atmospheric winds. Each instrument's technique to measure winds has advantages and disadvantages in regards to use for vehicle engineering assessments. Balloons measure wind at all altitudes necessary for vehicle assessments, but two primary disadvantages exist when applying balloon output on DOL. First, balloons need approximately one hour to reach required altitude. For vehicle assessments this occurs at 60 kft (18.3 km). Second, balloons are steered by atmospheric winds down range of the launch site that could significantly differ from those winds along the vehicle ascent trajectory. Figure 1 illustrates the spatial separation of balloon measurements from the surface up to approximately 55 kft (16.8 km) during the Space Shuttle launch on 10 December 2006. The balloon issues are mitigated by use of vertically pointing Doppler Radar Wind Profilers (DRWPs). However, multiple DRWP instruments are required to provide wind data up to 60 kft (18.3 km) for vehicle trajectory assessments. The various DRWP systems have different operating configurations resulting in different temporal and spatial sampling intervals. Therefore, software was developed to combine data from both DRWP-generated profiles into a single profile for use in vehicle trajectory analyses. Details on how data from various wind measurement systems are combined and sample output will be presented in the following sections.

Decker, Ryan K.↗
DOE OSTI2023

A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models

Abstract In 2022, wind generation accounted for ~10% of total electricity generation in the United States. As wind energy accounts for a greater portion of total energy, understanding geographic and temporal variation in wind generation is key to many planning, operational, and research questions. However, in-situ observations of wind speed are expensive to make and rarely shared publicly. Meteorological models are commonly used to estimate wind speeds, but vary in quality and are often challenging to access and interpret. The Plant-Level US multi-model WIND and generation (PLUSWIND) data repository helps to address these challenges. PLUSWIND provides wind speeds and estimated generation on an hourly basis at almost all wind plants across the contiguous United States from 2018–2021. The repository contains wind speeds and generation based on three different meteorological models: ERA5, MERRA2, and HRRR. Data are publicly accessible in simple csv files. Modeled generation is compared to regional and plant records, which highlights model biases and errors and how they differ by model, across regions, and across time frames.

17 WIND ENERGY↗
DOE OSTI2014

Prediction and analysis of infra and low-frequency noise of upwind horizontal axis wind turbine using statistical wind speed model

Despite increasing concern about low-frequency noise of modern large horizontal-axis wind turbines (HAWTs), few studies have focused on its origin or its prediction methods. In this paper, infra- and low-frequency (the ILF) wind turbine noise are closely examined and an efficient method is developed for its prediction. Although most previous studies have assumed that the ILF noise consists primarily of blade passing frequency (BPF) noise components, these tonal noise components are seldom identified in the measured noise spectrum, except for the case of downwind wind turbines. In reality, since modern HAWTs are very large, during rotation, a single blade of the turbine experiences inflow with variation in wind speed in time as well as in space, breaking periodic perturbations of the BPF. Consequently, this transforms acoustic contributions at the BPF harmonics into broadband noise components. In this study, the ILF noise of wind turbines is predicted by combining Lowson’s acoustic analogy with the stochastic wind model, which is employed to reproduce realistic wind speed conditions. In order to predict the effects of these wind conditions on pressure variation on the blade surface, unsteadiness in the incident wind speed is incorporated into the XFOIL code by varying incident flow velocities on each blade section, which depend on the azimuthal locations of the rotating blade. The calculated surface pressure distribution is subsequently used to predict acoustic pressure at an observing location by using Lowson’s analogy. These predictions are compared with measured data, which ensures that the present method can reproduce the broadband characteristics of the measured low-frequency noise spectrum. Further investigations are carried out to characterize the IFL noise in terms of pressure loading on blade surface, narrow-band noise spectrum and noise maps around the turbine.

36 MATERIALS SCIENCE↗