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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The Vineyard Wind Power Purchase Agreement: Insights for Estimating Costs of U.S. Offshore Wind Projects

This report analyzes the power purchase agreements (PPAs) between Massachusetts electric distribution utilities (EDC) and Vineyard Wind LLC filed on July 31, 2018, and derives insights for estimating cost of U.S. offshore wind systems and broader cost modeling activities. The documented price for delivery of offshore wind generation and renewable energy certificates under the Vineyard Wind/electric distribution utilities PPA is 74 $/megawatt-hour (MWh) (2022$) for facility 1 (400 MW) and 65 $/MWh (2023$) for facility 2 (400 MW). However, this PPA price does not comprise the complete set of expected revenue sources and tax benefits available to the Vineyard Wind LLC project. A comprehensive accounting of expected revenue sources inclusive of those that are exogenous to the reported PPA is conducted in this study to estimate the project's levelized revenue of energy (LROE). This allows for a more equivalent comparison of the PPA pricing with bottom-up modeled (unsubsidized) levelized cost of energy (LCOE) estimates. LROE from the Vineyard LLC/EDC PPA is estimated to be 98$/MWh (2018$). This LROE estimate for the first commercial-scale offshore wind project in the United States appears to be within the range of LROE estimated for offshore wind projects recently tendered in Northern Europe with a start of commercial operation by the early 2020s. This suggests that a cost and risk premium for the initial set of U.S. offshore wind projects may be less pronounced than anticipated by many industry observers and analysts.

17 WIND ENERGY↗
DOE OSTI2023

IEA Wind TCP Task 26: Wind Technology, Cost, and Performance Trends for Denmark, Germany, Ireland, Japan, Norway, Sweden, the European Union, and the United States 2016-2019

The Cost of Wind Energy represents an international collaboration dedicated to exploring the historical and future cost of wind energy in addition to the investigating the market value wind energy may provide. The countries that are currently represented by participating organizations in IEA Wind TCP Task 26 included in this report are Denmark, Germany, Ireland, Japan, Norway, Sweden, the European Union, and the United States. This manuscript documents technology and cost trends from 2008 through 2019 and discusses the trends from 2016 through 2019 that affected the cost of land-based wind energy within each country. The cost of wind energy during this period is compared with the market value of wind energy in the respective electricity market for each country.

17 WIND ENERGY↗
DOE OSTI2021

Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas

The Outer Continental Shelf along the U.S. east coast exhibits abundant wind resources and is now a geographic focus for offshore wind deployments. This analysis derives and presents expected extreme wind and wave conditions for the sixteen lease areas that are currently being developed. Using the homogeneous ERA5 reanalysis dataset it is shown that the fifty-year return period wind speed (U50) at 100 m a.s.l. in the lease areas ranges from 29.2 to 39.7 ms -1 . After applying corrections to account for spectral smoothing and averaging period, the associated pseudo-point U50 estimates are 34 to 46 ms -1 . The derived uncertainty in U50 estimates due to different distributional fitting is smaller than the uncertainty associated with under-sampling of the interannual variability in annual maximum wind speeds. It is shown that, in the northern lease areas, annual maximum wind speeds are generally associated with intense extratropical cyclones rather than cyclones of tropical origin. Extreme wave statistics are also presented and indicate that the 50-year return period maximum wave height may substantially exceed 15 m. From this analysis, there is evidence that annual maximum wind speeds and waves frequently derive from the same cyclone source and often occur within a 6 h time interval.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

JHTDB-wind: a web-accessible large-eddy simulation database of a wind farm with virtual sensor querying

This paper introduces JHTDB-wind (https://turbulence.idies.jhu.edu/datasets/windfarms, last access: 11 November 2025), a publicly accessible database containing large-eddy simulation (LES) data from wind farms. Building on the framework of the Johns Hopkins Turbulence Database (JHTDB), which hosts direct numerical simulation (DNS) and some LES datasets of canonical turbulent flows, JHTDB-wind stores the 4D space–time history of the flow and provides users the ability to access and query the data via a web-based virtual sensor interface. The initial dataset comprises LES results from a large wind farm with 10×6 turbines, modeled using a filtered actuator line method, under conventionally neutral atmospheric conditions. These data comprise 1 h (hour) of flow field data (velocity, pressure, potential temperature deviation, subgrid-scale (SGS) eddy viscosity, and turbine forces, approximately 15 TB (terabytes) and wind turbine data – including both turbine-level operational quantities and blade-level aerodynamic quantities (approximately 1.3 TB) – stored in Zarr and Parquet formats, respectively. Data retrieval is facilitated by the giverny Python package, allowing remote users to query the database in Python or MATLAB (C and Fortran support are available for flow field data). This paper details the simulation setup and demonstrates data access through examples that analyze wind farm flow structures and turbine performance. The framework is extensible to future datasets, including the JHTDB-wind diurnal cycle simulation analyzed in Xiao et al. (2025).

17 WIND ENERGY↗
DOE OSTI2016

FAST Modularization Framework for Wind Turbine Simulation: Full-System Linearization: Preprint

The wind engineering community relies on multiphysics engineering software to run nonlinear time-domain simulations e.g. for design-standards-based loads analysis. Although most physics involved in wind energy are nonlinear, linearization of the underlying nonlinear system equations is often advantageous to understand the system response and exploit well-established methods and tools for analyzing linear systems. This paper presents the development and verification of the new linearization functionality of the open-source engineering tool FAST v8 for land-based wind turbines, as well as the concepts and mathematical background needed to understand and apply it correctly.

17 WIND ENERGY↗
DOE OSTI2024

Tropical Cyclone Wind Shear-Relative Asymmetry in Reanalyses

Abstract While tropical cyclones (TCs) are axisymmetric vortices to the first order, they often exhibit noteworthy structural asymmetries. These often result from environmental vertical wind shear, which tilts the vortex and induces a wavenumber 1 pattern in the circulation and precipitation fields. Reanalyses and climate models have improved in representing the TC structure and climatology, but their relatively coarse resolution and dependence on parameterized physics cast doubt on their ability to capture the asymmetric TC structure. We perform the most comprehensive process-oriented assessment of TC asymmetry to date in reanalyses. Specifically, we analyze the composite shear-relative TC structure in ERA5 and Climate Forecast System Reanalysis (CFSR), which vary in their resolutions, physical parameterization suites, and data assimilation techniques. These structures are compared with aircraft reconnaissance radar observations. In agreement with the observations, the strongest tangential winds are usually found left-of-shear, while inner core rainfall, ascent, vortex tilt, and low-level inflow are favored directly downshear or in the downshear-left quadrant. Outer rainband convection generally peaks in the downshear-right quadrant. Thermodynamic asymmetries are also apparent, with anomalous low-level moisture right-of-shear, midlevel warmth in the upshear-right quadrant (uptilt), and cloud properties suggestive of a realistic precipitation life cycle from growth to fallout. We also decompose rainfall contributions from the convective parameterization and large-scale cloud schemes and highlight the roles of vorticity advection, buoyancy advection, and diabatic processes in driving asymmetric vertical motions in the inner core and outer rainband regions. Our results suggest that process-level studies of TC asymmetry and TC–wind shear interaction under future warming are viable using climate models. Significance Statement Asymmetries are common in tropical cyclones (TCs), influencing their intensity, track, and hazards. Vertical wind shear often plays a leading-order role in causing these asymmetries. It is uncertain how well asymmetric structures and processes are captured in reanalyses and global climate models (GCMs) with grid spacings of 0.25° and coarser. In this study, we first evaluate TC asymmetry in reanalyses, which have the benefit of being forced by observations. This helps to assess whether the resolutions associated with GCMs sufficiently capture asymmetric structures and processes and motivates upcoming work with free-running GCMs to study how TC asymmetry may change in a warming climate.

Carstens, Jacob D.↗
NASA NTRS1973

Monthly and annual percentage levels of wind speed differences computed by using FPS-16 radar/Jimsphere wind profile data from Cape Kennedy, Florida

The percentage levels of wind speed differences are presented computed from sequential FPS-16 radar/Jimsphere wind profiles. The results are based on monthly profiles obtained from December 1964 to July 1970 at Cape Kennedy, Florida. The profile sequences contain a series of three to ten Jimspheres released at approximately 1.5-hour intervals. The results given are the persistence analysis of wind speed difference at 1.5-hour intervals to a maximum time interval of 12 hours. The monthly percentage of wind speed differences and the annual percentage of wind speed differences are tabulated. The percentage levels are based on the scalar wind speed changes calculated over an altitude interval of approximately 50 meters and printed out every 25 meters as a function of initial wind speed within each five-kilometer layer from near sea level to 20 km. In addition, analyses were made of the wind speed difference for the 0.2 to 1 km layer as an aid for studies associated with take-off and landing of the space shuttle.

Susko, M.↗
NASA NTRS1977

Analysis of vector wind change with respect to time for Cape Kennedy, Florida: Wind aloft profile change vs. time, phase 1

Wind vector change with respect to time at Cape Kennedy, Florida, is examined according to the theory of multivariate normality. The joint distribution of the four variables represented by the components of the wind vector at an initial time and after a specified elapsed time is hypothesized to be quadravariate normal; the fourteen statistics of this distribution, calculated from fifteen years of twice daily Rawinsonde data are presented by monthly reference periods for each month from 0 to 27 km. The hypotheses that the wind component changes with respect to time is univariate normal, the joint distribution of wind component changes is bivariate normal, and the modulus of vector wind change is Rayleigh, has been tested by comparison with observed distributions. Statistics of the conditional bivariate normal distributions of vector wind at a future time given the vector wind at an initial time are derived. Wind changes over time periods from one to five hours, calculated from Jimsphere data, are presented.

Adelfang, S. I.↗
NASA NTRS1991

The dependence of wind stress on wave height and wind speed

Three near-neutral boundary layer data sets were investigated with the aim of finding a dependence of wind stress on both wind speed and significant wave height. The data set most representative of open-ocean wave height, wind speed, and momentum flux conditions, was selected and analyzed by means of the least-squares method to produce a new parameterization for the wind stress as a function of both wind speed and significant wave height. This study shows that the wind stress, and consequently the drag coefficient, decreases with increasing wave height for a fixed wind speed. The study also shows that the curvature of the wind profile decreases with increasing wave height and that the C(DN) = A + BU-bar(10) form for the drag coefficient parameterization is inadequate. A drag coefficient that applies to both smooth and rough flows is proposed. These results are more applicable for open-ocean deep-water conditions and less applicable for sheltered, closed, shallow water sites.

Blake, Reginald A.↗
NASA NTRS1994

A comparison of winds from the STRATAN data assimilation system to balanced wind estimates

Winds derived from a stratospheric and tropospheric data assimilation system (STRATAN) are compared with balance winds derived from National Meteorological Center/Climate Analysis Center (NMC/CAC) heights. At middle latitudes in the lower stratosphere, the results show that STRATAN winds are comparable to the balance winds. In addition STRATAN winds provide useful horizontal divergence analyses, and hence, vertical velocity fields. More generally, the STRATAN winds are useful in a more extended domain than the balanced winds. In particular, they are useful in the Tropics and the upper stratosphere where the balanced winds fail. The assimilation also captures the quasi-biennial oscillation, but does not do a good job of representing tropical waves.

Coy, Lawrence↗
NASA NTRS2002

Profiling Tropospheric Winds with the Goddard Lidar Observatory for Winds (GLOW)

The Goddard Lidar Observatory for Winds (GLOW) is a mobile direct detection Doppler lidar system designed to measure wind profiles from the surface into the lower stratosphere. Recently, the GLOW lidar has participated in several field deployments measuring tropospheric winds in a variety of conditions including both daytime and night operation. More than 50 hours of line-of-sight wind profit data were obtained in September, 2000 during a three week intercomparison experiment at the Ground Winds facility in North Glen, NH. Typical clear air lidar wind profiles extended to altitudes of 20 km with a 1 km vertical resolution and 1 minute averaging. An additional 40 hours of lidar profiles of wind speed and direction were obtained during HARGLO-2, an intercomparison experiment held at Wallops Flight Facility, VA in November, 2001. A description of the mobile system is presented along with the examples of validated lidar wind profiles obtained during these experiments.

Gentry, Bruce M.↗
NASA NTRS2010

Compact, High Energy 2-micron Coherent Doppler Wind Lidar Development for NASA's Future 3-D Winds Measurement from Space

This paper presents an overview of 2-micron laser transmitter development at NASA Langley Research Center for coherent-detection lidar profiling of winds. The novel high-energy, 2-micron, Ho:Tm:LuLiF laser technology developed at NASA Langley was employed to study laser technology currently envisioned by NASA for future global coherent Doppler lidar winds measurement. The 250 mJ, 10 Hz laser was designed as an integral part of a compact lidar transceiver developed for future aircraft flight. Ground-based wind profiles made with this transceiver will be presented. NASA Langley is currently funded to build complete Doppler lidar systems using this transceiver for the DC-8 aircraft in autonomous operation. Recently, LaRC 2-micron coherent Doppler wind lidar system was selected to contribute to the NASA Science Mission Directorate (SMD) Earth Science Division (ESD) hurricane field experiment in 2010 titled Genesis and Rapid Intensification Processes (GRIP). The Doppler lidar system will measure vertical profiles of horizontal vector winds from the DC-8 aircraft using NASA Langley s existing 2-micron, pulsed, coherent detection, Doppler wind lidar system that is ready for DC-8 integration. The measurements will typically extend from the DC-8 to the earth s surface. They will be highly accurate in both wind magnitude and direction. Displays of the data will be provided in real time on the DC-8. The pulsed Doppler wind lidar of NASA Langley Research Center is much more powerful than past Doppler lidars. The operating range, accuracy, range resolution, and time resolution will be unprecedented. We expect the data to play a key role, combined with the other sensors, in improving understanding and predictive algorithms for hurricane strength and track. 1

Singh, Upendra N.↗
NASA NTRS2011

Quality-Controlled Wind Data from the Kennedy Space Center 915 Megahertz Doppler Radar Wind Profiler Network

The National Aeronautics and Space Administration s (NASA) Kennedy Space Center (KSC) has installed a five-instrument 915-Megahertz (MHz) Doppler Radar Wind Profiler (DRWP) system that records atmospheric wind profile properties. The purpose of these profilers is to fill data gaps between the top of the KSC wind tower network and the lowest measurement altitude of the KSC 50-MHz DRWP. The 915-MHz DRWP system has the capability to generate three-dimensional wind data outputs from approximately 150 meters (m) to 6,000 m at roughly 15-minute (min) intervals. NASA s long-term objective is to combine the 915-MHz and 50-MHz DRWP systems to create complete vertical wind profiles up to 18,300 m to be used in trajectory and loads analyses of space vehicles and by forecasters on day-of-launch (DOL). This analysis utilizes automated and manual quality control (QC) processes to remove erroneous and unrealistic wind data returned by the 915-MHz DRWP system. The percentage of data affected by each individual QC check in the period of record (POR) (i.e., January to April 2006) was computed, demonstrating the variability in the amount of data affected by the QC processes. The number of complete wind profiles available at given altitude thresholds for each profiler in the POR was calculated and outputted graphically, followed by an assessment of the number of complete wind profiles available for any profiler in the POR. A case study is also provided to demonstrate the QC process on a day of a known weather event.

Dryden, Rachel L.↗
NASA NTRS2012

He II lambda-4686 in Eta Carinae: Collapse of the Wind-Wind Collision Region During Periastron Passage

The periodic spectroscopic events in Eta Carinae are now well established and occur near the periastron passage of two massive stars in a very eccentric orbit. Several mechanisms have been proposed to explain the variations of different spectral features, such as an eclipse by the wind-wind collision boundary, a shell ejection from the primary star or accretion of its wind onto the secondary. All of them have problems explaining all the observed phenomena. To better understand the nature of the cyclic events we performed a dense monitoring of Eta Carinae with 5 Southern telescopes during the 2009 low excitation event, resulting in a set of data of unprecedented quality and sampling. The intrinsic luminosity of the He II lambda-4686 emission line (L approx 310 solar L) just before periastron reveals the presence of a very luminous transient source of extreme UV radiation emitted in the wind-wind collision (WWC) region. Clumps in the primary's wind probably explain the flare-like behavior of both the X-ray and He II lambda-4686 light-curves. After a short-lived minimum, He II lambda-4686 emission rises again to a new maximum, when X-rays are still absent or very weak. We interpret this as a collapse of the WWC onto the "surface" of the secondary star, switching off the hard X-ray source and diminishing the WWC shock cone. The recovery from this state is controlled by the momentum balance between the secondary's wind and the clumps in the primary's wind.

Teodoro, M.↗
NASA NTRS2015

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

Atmospheric wind data are required by space launch vehicles in order to assess flight vehicle loads and performance on day-of-launch. Space 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 within vehicle trajectory analyses. Balloons measure wind at all altitudes necessary for vehicle assessments, but two primary disadvantages exist when applying balloon output. First, balloons require approximately one hour to reach required altitudes. 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. These issues are mitigated by use of vertically pointing Doppler Radar Wind Profilers (DRWPs). However, multiple DRWP instruments are required to provide wind data over altitude ranges necessary 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. This paper will present details of the splicing software algorithms and will provide sample output.

Decker, Ryan K.↗
DOE OSTI2020

A Distributed Reinforcement Learning Yaw Control Approach for Wind Farm Energy Capture Maximization: Preprint

In this paper, we present a reinforcement-learning based distributed approach to wind farm energy capture maximization using yaw control, also known as wake steering. In order to maximize the power output of a wind farm, it is often necessary for individual turbines to decrease their own power output through yaw misalignment so as to deflect their wakes away from downstream turbines. Although using model-based methods to achieve yaw misalignment is one option, a model-free method might be better suited to incorporate factors that are difficult to model or changing conditions. We propose an algorithm that adapts concepts of temporal difference reinforcement learning distributed to a multi-agent environment that allows individual turbines to act so as to optimize overall wind farm output and react to unforeseen disturbances.

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