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DOE OSTI2019

Tonopah Test Range Air Monitoring: CY2018 Meteorological, Radiological, and Wind Transported Particulate Observations

In 1963, the U.S. Department of Energy (DOE) (formerly the Atomic Energy Commission [AEC]), implemented Operation Roller Coaster on the Tonopah Test Range (TTR) and an adjacent area of the Nevada Test and Training Range (NTTR) (formerly the Nellis Air Force Range). This operation resulted in radionuclide-contaminated soils at the Double Tracks site and Clean Slate I, II, and III sites. This report documents observations made during ongoing monitoring of radiological, meteorological, and dust conditions at stations installed adjacent to the Clean Slate sites and at the TTR Sandia National Laboratories (SNL) Range Operations Center (ROC). The primary objective of the monitoring effort is to support the DOE Environmental Management Nevada Program (EM NV) in the safe remediation of the environmental legacy of nuclear device development and testing by determining if wind blowing across the Clean Slate sites is transporting particles of radionuclide-contaminated soil beyond the physical and administrative boundaries of the sites, and to provide information for designing long-term monitoring of the sites. The monitoring program in 2018 included five stations. Station 400, located within TTR Area 3 and near the ROC, monitors conditions near the local workforce center. Stations 401 and 403 are located on the northern and southeastern perimeter fence lines, respectively, of the Clean Slate III site. Stations 404 and 405 are along the northern and eastern boundary fence, respectively, at Clean Slate II. The stations are generally downwind of the contaminated areas during either northwesterly or southerly winds, which are the predominant wind directions. The stations—which are similar in design to the Community Environmental Monitoring Program (CEMP) stations operating at locations surrounding the Nevada National Security Site and TTR—include meteorological instruments and continuous-flow, low-volume air samplers. Three pressurized ionization chambers for measuring gamma energy are in use at Stations 400, 401, and 403. Saltation sensors and saltation traps are deployed at the stations adjacent to the Clean Slate sites. Detailed meteorological data are recorded on data loggers, with periodic uploads via a satellite system to the Western Regional Climate Center (WRCC) at Desert Research Institute (DRI), to monitor instrument and site conditions. Air filter samples are collected every two weeks and the deposits in the saltation traps are collected when a sufficient sample mass for analysis has accumulated (generally a six- to eight-month interval). Monitoring at TTR in calendar year (CY) 2018 provided surveillance of both ambient conditions, and ground disturbance associated with remediation activities at Clean Slate II and III. The first half of CY2018 data from Stations 404 and 405 at Clean Slate II were collected during remediation activities at that site, and data collected during the final third of the year at Stations 401 and 403 at Clean Slate III coincided with remediation work at the site. Ambient conditions prevailed at Station 400 throughout the year. Dust transport by suspension and saltation is strongly dependent on wind speed. Concentrations of PM 10 (particulate matter of aerodynamic diameter ≤10 micrometers [μm], a size fraction of small particles that are suspended in the air and can be easily inhaled) remain low until winds exceed approximately 32 kilometers per hour (km/hr) (20 miles per hour [mph]). Saltation particle counts also increase above the same general threshold wind speed. Wind speeds in excess of 32 km/hr (20 mph) occur less than three percent of the time at the sites. Ground disturbing remediation activities were carried out at Clean Slate II from October 31, 2017, until July 26, 2018. Station 404 is located closest to the remediation area and is downwind of the area when winds are from the south. By late November, analysis of dust from the air sampler at Station 404 registered increases in plutonium-239+240 ( 239+240 Pu) concentrations. Peak plutonium concentrations, accompanied by elevated gross alpha concentrations and the detection of americium-241 ( 241 Am) by gamma spectroscopy, occurred between March and May 2018. During spring and early summer of 2018, elevated radionuclide concentrations were also measured in dust collected from the air sampler at Station 405, which is more than twice the distance from the remediation activity as Station 404. A minor but sustained increase in gross alpha concentration of suspended dust collected at Stations 400, 401, and 403 was also observed starting in May 2018 and continuing into August. Stations 401 and 403 are approximately 4.8 to 6.4 km (three to four miles) from Clean Slate II and Station 400 is approximately 13 km (eight miles) from that site. The radionuclide content of material that saltated into the passive Big Spring Number Eight (BSNE) traps during the Clean Slate II remediation period increased in both the traps facing toward and away from the fenced contamination area at Station 404, with the largest increases in concentration (almost five times the previous 239+240 Pu concentration) observed in the traps facing the fenced area. The radionuclide concentration in material in the trap facing away from the fence more than doubled from that measured in 2017. A similar increase was observed for the saltation trap facing away from the fenced area at Station 405, although no increase was observed for material captured in the trap facing the fenced area. Particles ranging in size from 50 to 500 µm generally move by saltation processes and are not expected to significantly contribute to dose for someone breathing in the standard respiratory zone for adult humans (1.5 to 1.7 m [4.9 to 5.6 ft] above ground level) because they are too large to be entrained in the air as suspended dust. Remediation activities at Clean Slate III began on September 5, 2018, and continued until a brief hiatus started on December 20, 2018. Although Station 401 is much closer to the remediation area than Station 403, the first increase in gross alpha and 239+240 Pu concentrations was noted in dust from filters collected at Station 403 in early November 2018. The highest radionuclide concentrations of 2018 at the Clean Slate III stations were recorded in air samples taken from Stations 401 and 403 in late December 2018 and these concentrations were comparable between the two station locations. Gamma rate data measured by the PICs was slightly higher than the annual average at Stations 401 and 403 after remediation activities began, but no single measurement was outside of the range observed in 2018 prior to remediation activities. No increase in radionuclide concentration was observed for the Clean Slate III remediation time period on air filters collected from the other stations. Radiological monitoring at Station 400—which is located at the ROC, and therefore the closest regularly staffed work location to the Clean Slate sites—recorded a higher mean gross alpha activity from dust collected on air sampler filters than in previous years. The individual biweekly air filters yielded measurements of gross alpha that were at or below the mean plus one standard deviation measured in CY2017, except for the period from April 25, 2018, through September 12, 2018. Nonetheless, gamma spectroscopy of all air filters from Station 400 identified only naturally occurring radionuclides, with no detection of americium-241 ( 241 Am) (which is used as an indicator of plutonium-241[ 241 Pu]). Alpha spectroscopy of selected air filters collected at Station 400 did not detect plutonium-238 ( 238 Pu) or 239+240 Pu above the analytical detection limit. Gross beta and gamma exposure rate data were comparable to data from regional CEMP stations. No saltation traps are deployed at Station 400. Considering the ambient monitoring periods during CY2018, the monitoring stations adjacent to the Clean Slate sites recorded above-background 238 Pu and 239+240 Pu concentrations (SNL, 1998; Turner et al., 2003) in samples collected by passive saltation traps and on selected air filters. These observations were consistent with previous years and indicated that radionuclide movement occurred under ambient conditions by processes of both saltation and suspension. The presence of radionuclides in all saltation traps, both upwind and downwind of the fenced contamination areas, was consistent with previous radiological survey results (EG&G, 1979) that show lower concentration radiologically contaminated material dispersed outside the fenced area. Although 239+240 Pu concentrations in the air filter samples were sometimes orders of magnitude higher than background, the concentrations were below risk-based action levels defined for an industrial area worker scenario (U.S. DOE, 2014). The interception of airborne dust with above-background radionuclide concentrations demonstrates that dispersal processes are continuing. Strong winds are the driver for both suspension and saltation of dust and soil. The recorded wind speed and PM10 during remediation activities at Clean Slate II and III identified discrete wind events lasting approximately five to eight hours each, which accounted for the greatest PM 10 concentrations at the monitoring stations. These events captured the effect of winds from the northwest and from the south. The observed differences in dust loading and radionuclide concentrations for the monitoring stations when they were either upwind or downwind of the contamination area identify the remediation area as a source of plutonium contaminated dust. The increase in concentration of radionuclides in airborne dust during the remediation activities, compared with measurements under previous ambient conditions (mean 239+240 Pu concentrations during remediation activities are approximately nine to 40 times higher compared to pre-remediation concentrations, depending on monitoring station), highlights the impact of land disturbance on wind-borne contaminant transport from the Clean Slate test areas. The meteorological and particulate matter monitoring indicated that conditions for wind-borne contaminant movement exist at the Clean Slate sites, and that transport of radionuclide-contaminated soil by both suspension and saltation occurred under ambient conditions and accelerated when the sites were disturbed. The 239+240 Pu alpha spectroscopy results indicated that airborne concentrations during remediation activities ranged from 2 × 10-16 to 380 × 10-16 µCi/ml. These results can be compared to the derived air concentration limit for 239 Pu of 6 × 10-11 µCi/ml for occupational workers contained in Code of Federal Regulations 10 CFR 835, Occupational Radiation Protection. Even though the air sampling results document an increase in concentration during remediation activities, the observed concentrations are less than 0.06 percent of the occupational limit. The Corrective Action Unit (CAU) closure strategy uses a risk-based approach, whereby acceptable contaminant concentrations are determined as a function of anticipated human exposure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Modeling and Analysis of Wind Turbine Wake Vortex Evolution Due to Time-Constant Spatial Variations in Atmospheric Flow

Modern utility-scale wind turbines are evolving toward larger, lighter, and more flexible designs to meet the growing demand for renewable energy while minimizing logistical costs. However, these advancements in lightweight design result in heightened aeroelastic sensitivity, leading to complex interactions which affect the rotor’s capacity to withstand aerodynamic loading and the cascading effects that manifest in the wake’s vortex-structure evolution under variable atmospheric conditions. In this paper, we analyze the influence of stream-wise fluctuating atmospheric flow conditions on wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex–wake interactions for a range of conditions with spatially variant atmospheric flow. CODEF solutions for turbine operation in wind conditions featuring only one parameter fluctuation are compared to wind conditions with several wind parameter variations in combination. By isolating individual inflow variations and comparing them to multi-parameter scenarios, we determine the contributions of each atmospheric factor to rotor dynamics, wake evolution, and downstream wind farm interactions. The purpose of this paper is to analyze the effects of spatial variations in atmospheric flow on the topological evolution of wind turbine vortex wakes, which constitutes a gap in the current understanding of wind turbine wake dynamics. The insights gained from this study are particularly valuable for the development of wind farm control strategies aimed at mitigating the adverse effects of wake interactions, enhancing energy capture, and improving the overall stability of wind farm operations. With these insights, we aim to contribute to the development of modeling and simulation tools to optimize utility-scale wind power plants operating in diverse atmospheric environments.

Farrell, Alayna (ORCID:000000023555720X)↗
NASA NTRS1992

Recommendations for a wind profiling network to support Space Shuttle launches

The feasibility is examined of a network of clear air radar wind profilers to forecast wind conditions before Space Shuttle launches during winter. Currently, winds are measured only in the vicinity of the shuttle launch site and wind loads on the launch vehicle are estimated using these measurements. Wind conditions upstream of the Cape are not monitored. Since large changes in the wind shear profile can be associated with weather systems moving over the Cape, it may be possible to improve wind forecasts over the launch site if wind measurements are made upstream. A radar wind profiling system is in use at the Space Shuttle launch site. This system can monitor the wind profile continuously. The existing profiler could be combined with a number of radars located upstream of the launch site. Thus, continuous wind measurements would be available upstream and at the Cape. NASA-Marshall representatives have set the requirements for radar wind profiling network. The minimum vertical resolution of the network must be set so that the wind shears over the depths greater than or = 1 km will be detected. The network should allow scientists and engineers to predict the wind profile over the Cape 6 hours before a Space Shuttle launch.

Zamora, R. J.↗
NASA NTRS1995

Basic principles and recent observations of rotationally sampled wind

The concept of rotationally sampled wind speed is described. The unusual wind characteristics that result from rotationally sampling the wind are shown first for early measurements made using an 8-point ring of anemometers on a vertical plane array of meteorological towers. Quantitative characterization of the rotationally sampled wind is made in terms of the power spectral density function of the wind speed. Verification of the importance of the new concept is demonstrated with spectral analyses of the response of the MOD-OA blade flapwise root bending moment and the corresponding rotational analysis of the wind measured immediately upwind of the MOD-OA using a 12-point ring of anemometers on a 7-tower vertical plane array. The Pacific Northwest Laboratory (PNL) theory of the rotationally sampled wind speed power spectral density function is tested successfully against the wind spectrum measured at the MOD-OA vertical plane array. A single-tower empirical model of the rotationally sampled wind speed is also successfully tested against the measurements from the full vertical plane array. Rotational measurements of the wind velocity with hotfilm anemometers attached to rotating blades are shown to be accurate and practical for research on winds at the blades of wind turbines. Some measurements at the rotor blade of a MOD-2 turbine using the hotfilm technique in a pilot research program are shown. They are compared and contrasted to the expectations based upon application of the PNL theory of rotationally sampled wind to the MOD-2 size and rotation rate but without teeter, blade bending, or rotor induction accounted for. Finally, the importance of temperature layering and of wind modifications due to flow over complex terrain is demonstrated by the use of hotfilm anemometer data, and meteorological tower and acoustic doppler sounder data from the MOD-2 site at Goodnoe Hills, Washington.

Connell, James R.↗
NASA NTRS1995

A perturbation calculation of the dynamical effects of cosmic rays and interstellar gas on the solar wind

The modulation of galactic cosmic rays and other energetic particles by the solar wind produces a gradient in their pressure, which in turn influences the wind dynamics. The basic equations describing this interaction are presented in the 'hydrodynamic' approximation. A perturbation solution of the equations is presented for the case in which both the galactic cosmic ray pressure, and the pressure of the anomalous cosmic ray component accelerated at the wind termination shock, are small compared with the wind ram pressure. Analytical expressions for the deceleration of the wind and the modification of the shock and its location are derived in this case. These effects are estimated to have a relative magnitude of several percent in the solar wind. The interstellar neutral gas which penetrates the heliosphere is ionized, predominantly by photoionization and charge exchange with the wind, and may also have a significant dynamical effect on the wind. The basic equations describing this interaction are also presented, A perturbation solution is presented under the assumption that the mass loading and momentum-loading of the wind by the interstellar pickup ions is small compared with the wind ram pressure. Analytical expressions for the deceleration of the wind, the contribution of the pickup ions to the wind pressure, and the modification of the termination shock location are derived. Again, with the exception of pickup ion pressure which is large compared with solar wind thermal pressure, the effects are estimated to be several percent in relative magnitude in the solar wind.

Lee, M. A.↗
NASA NTRS1999

GHRS Observations of Cool, Low-Gravity Stars: The Outer Atmosphere and Wind of the Nearby K Supergiant Lambda Velorum - 5

UV spectra of lambda Velorum taken with the Goddard High Resolution Spectrograph (GHRS) on the Hubble Space Telescope are used to probe the structure of the outer atmospheric layers and wind and to estimate the mass-loss rate from this K5 lb-II supergiant. VLA radio observations at lambda = 3.6 cm are used to obtain an independent check on the wind velocity and mass-loss rate inferred from the UV observations, Parameters of the chromospheric structure are estimated from measurements of UV line widths, positions, and fluxes and from the UV continuum flux distribution. The ratios of optically thin C II] emission lines indicate a mean chromospheric electron density of log N(sub e) approximately equal 8.9 +/- 0.2 /cc. The profiles of these lines indicate a chromospheric turbulence (v(sub 0) approximately equal 25-36 km/s), which greatly exceeds that seen in either the photosphere or wind. The centroids of optically thin emission lines of Fe II and of the emission wings of self-reversed Fe II lines indicate that they are formed in plasma approximately at rest with respect to the photosphere of the star. This suggests that the acceleration of the wind occurs above the chromospheric regions in which these emission line photons are created. The UV continuum detected by the GHRS clearly traces the mean flux-formation temperature as it increases with height in the chromosphere from a well-defined temperature minimum of 3200 K up to about 4600 K. Emission seen in lines of C III] and Si III] provides evidence of material at higher than chromospheric temperatures in the outer atmosphere of this noncoronal star. The photon-scattering wind produces self-reversals in the strong chromospheric emission lines, which allow us to probe the velocity field of the wind. The velocities to which these self-absorptions extend increase with intrinsic line strength, and thus height in the wind, and therefore directly map the wind acceleration. The width and shape of these self-absorptions reflect a wind turbulence of approximately equal 9-21 km/s. We further characterize the wind by comparing the observations with synthetic profiles generated with the Lamers et al. Sobolev with Exact Integration (SEI) radiative transfer code, assuming simple models of the outer atmospheric structure. These comparisons indicate that the wind in 1994 can be described by a model with a wind acceleration parameter beta approximately 0.9, a terminal velocity of 29-33 km/s, and a mass-loss rate approximately 3 x 10(exp -9) solar M/yr. Modeling of the 3.6 cm radio flux observed in 1997 suggests a more slowly accelerating wind (higher beta) and/or a higher mass-loss rate than inferred from the UV line profiles. These differences may be due to temporal variations in the wind or from limitations in one or both of the models. The discrepancy is currently under investigation.

Carpenter, Kenneth G.↗
NASA NTRS2014

Temporal Variability of Upper-level Winds at the Eastern Range, Western Range and Wallops Flight Facility

Space launch vehicle commit-to-launch decisions include an assessment of the upper-level (UL) atmospheric wind environment to assess the vehicle's controllability and structural integrity during ascent. These assessments occur at predetermined times during the launch countdown based on measured wind data obtained prior to the assessment. However, the pre-launch measured winds may not represent the wind environment during the vehicle ascent. Uncertainty in the UL winds over the time period between the assessment and launch can be mitigated by a statistical analysis of wind change over time periods of interest using historical data from the launch range. Without historical data, theoretical wind models must be used, which can result in inaccurate wind placards that misrepresent launch availability. Using an overconservative model could result in overly restrictive vehicle wind placards, thus potentially reducing launch availability. Conversely, using an under-conservative model could result in launching into winds that might damage or destroy the vehicle. A large sample of measured wind profiles best characterizes the wind change environment. These historical databases consist of a certain number of wind pairs, where two wind profile measurements spaced by the time period of interest define a pair.

Decker, Ryan K.↗
NASA NTRS2021

VLTI-MATISSE Chromatic Aperture-Synthesis Imaging of η Carinae’s Stellar Wind Across the Brα Line: Periastron Passage Observations in February 2020

Context: Eta Carinae is a highly eccentric, massive binary system (semimajor axis∼15.5 au) with powerful stellar winds and a phase-dependent wind-wind collision (WWC) zone. The primary star, ηCar A, is a luminous blue variable (LBV); the secondary, η Car B, is a Wolf-Rayet or O star with a faster but less dense wind. Aperture-synthesis imaging allows us to study the mass loss from the enigmatic LBV η Car. Understanding LBVs is a crucial step toward improving our knowledge about massive stars and their evolution. Aims: Our aim is to study the intensity distribution and kinematics of η Car’s WWC zone. Methods: Using the VLTI-MATISSE mid-infrared interferometry instrument, we perform Brα imaging of η Car’s distorted wind. Results: We present the first VLTI-MATISSE aperture-synthesis images of η Car A’s stellar wind in several spectral channels distributed across the Brα 4.052 μm line (spectral resolving power R∼960). Our observations were performed close to periastron passage in February 2020 (orbital phase∼14.0022). The reconstructed iso-velocity images show the dependence of the primary stellar wind on wavelength or line-of-sight (LOS) velocity with a spatial resolution of 6 mas (∼14 au). The radius of the faintest outer wind regions is∼26 mas (∼60 au). At several negative LOS velocities, the primary stellar wind is less extended to the northwest than in other directions. This asymmetry is most likely caused by the WWC. Therefore, we see both the velocity field of the undisturbed primary wind and the WWC cavity. In continuum spectral channels, the primary star wind is more compact than in line channels. A fit of the observed continuum visibilities with the visibilities of a stellar wind CMFGEN model (CMFGEN is an atmosphere code developed to model the spectra of a variety of objects) provides a full width at half maximum fit diameter of the primary stellar wind of 2.84±0.06 mas (6.54±0.14 au). We compare the derived intensity distributions with the CMFGEN stellar wind model and hydrodynamic WWC models.

G Weigelt↗
DOE OSTI2014

Empirical Analysis of the Variability of Wind Generation in India: Implications for Grid Integration

We analyze variability in load and wind generation in India to assess its implications for grid integration of large scale wind projects using actual wind generation and load data from two states in India, Karnataka and Tamil Nadu. We compare the largest variations in load and net load (load -wind, i.e., load after integrating wind) that the generation fleet has to meet. In Tamil Nadu, where wind capacity is about 53% of the peak demand, we find that the additional variation added due to wind over the current variation in load is modest; if wind penetration reaches 15% and 30% by energy, the additional hourly variation is less than 0.5% and 4.5% of the peak demand respectively for 99percent of the time. For wind penetration of 15% by energy, Tamil Nadu system is found to be capable of meeting the additional ramping requirement for 98.8percent of the time. Potential higher uncertainty in net load compared to load is found to have limited impact on ramping capability requirements of the system if coal plants can me ramped down to 50percent of their capacity. Load and wind aggregation in Tamil Nadu and Karnataka is found to lower the variation by at least 20% indicating the benefits geographic diversification. These findings suggest modest additional flexible capacity requirements and costs for absorbing variation in wind power and indicate that the potential capacity support (if wind does not generate enough during peak periods) may be the issue that has more bearing on the economics of integrating wind

17 WIND ENERGY↗
DOE OSTI2025

Land-Based Wind Reference Architecture

This report describes a summary and the final deliverables for the Wind Reference Architecture project funded by the Department of Energy's (DOE) Wind Energy Technology Office (WETO). The project objective was to further refine the reference architecture of the existing wind power plant reference architecture developed by Idaho National Laboratory (INL) and Sandia National Laboratories (SNL) by expanding the wind turbine generator (WTG) into a separate individual wind turbine reference architecture. Additional details regarding the wind turbine system and how it integrates with a wind power plant were researched and reflected in the reference architecture. This addition is important because it allows researchers to understand the components and devices in a wind turbine, how they function and how a wind turbine integrates into a wind power plant to be able to perform cybersecurity evaluations on the system. The communication and control systems were the focus while developing this reference architecture to understand the cybersecurity posture of a wind turbine and power plant. The information technology (IT) and operational technology (OT) systems perspective are integral in helping improve the cybersecurity posture by creating a starting point to study how wind energy can be safely designed and deployed in our power grid from an integrated systems standpoint. A holistic wind power plant and turbine reference architecture and simulation was developed and made open-sourced for further research efforts.

17 WIND ENERGY↗
DOE OSTI2024

Identification of Climatological Representative Days in the Mid-Atlantic for High-Fidelity Offshore Wind Energy Modeling

The goal of reaching 30 GW of offshore wind energy by 2030 becomes more realistic with the continued approval of offshore wind energy areas by the Biden Administration. In the Mid-Atlantic, where wind energy projects are in the most advanced stages of development, there is increased research focus on the eventual interaction of these wind farms. These interactions, in the form of wakes and cluster wakes, or wakes from multiple wind farms, could have detrimental effects on power production and forecastability for downwind wind farms (Pryor et al. 2022, Golbazi et al. 2022, Rosencrans et al. 2023). To help alleviate these issues, numerical simulations in the form of numerical weather prediction (NWP) and large eddy simulations (LES) can provide insight into when cluster wake situations may occur, but running such simulations can be expensive and difficult to run for multiple years. In this study, we leverage and build upon existing techniques in the literature (Fischereit et al. 2022) to identify climatologically representative days for wind energy areas in the Mid-Atlantic where conditions would promote cluster wake situations. We select meteorological variables (wind speed, wind direction, atmospheric stability, boundary-layer height, TKE) critical to understanding wind energy production and wake propagation. We then consider two different NWP datasets of varying spatial and temporal resolution: ERA5 provides data at hourly intervals from 1940 to present at 0.25 deg (31 km) spatial resolution (Hersbach et al. 2020), and the NOW-23 dataset provides data at 5-minute resolution for 21 years at 2-km spatial resolution (Bodini et al. 2020). Our first step is to compare these two datasets for an overlapping 21-year time period. Initial results show that the required number of days to represent the long-term climate increases with each additional variable considered. In their study of the German Bight, Fischereit et al. (2022) found that they could represent the long-term wind and wave climate in a "near-perfect" way with -180 days, by reaching a Perkins Skill Score (PSS) of 0.9; our investigation of the mid-Atlantic wind resource region with ERA5 and NOW-23 data suggests that we will need -100 days to reach a PSS of 0.9. As we expand our parameter space to include multiple variables, the number of required days will likely grow. These results will ultimately be used to select case studies to best represent cluster wake conditions that apply to this region for the lifetime of likely wind farms in this mid-Atlantic region.

clusterwakes↗
DOE OSTI2024

Studying Wind Loading on CSP Collectors to Improve Performance and Reliability

Electricity generation through Concentrating Solar-thermal Power (CSP) adds the advantage of thermal energy storage and heat production. CSP collector costs constitute nearly one-third of total plant costs. Managing wind loading, especially dynamic wind loading caused by the turbulent wind flow, is a significant design challenge. Traditional collector designs rely on wind tunnel experiments and numerical simulations, which do not fully capture dynamic effects. Here, we provide an overview of NREL's activities on wind loading on CSP collectors, aiming to improve their reliability and cost-efficiency. We present insights from field measurements at operational parabolic trough and power-tower CSP plants. Over two years, we measured turbulent wind fields and resulting structural loads in a parabolic trough plant, revealing wind, turbulence, and collector field interactions. Similar measurements are ongoing at the Crescent Dunes heliostat field. These campaigns show how atmospheric turbulence, wind direction, and collector orientation affect dynamic wind loading. Upwind collector structures can generate turbulent structures, causing fluctuating loads at downstream collectors, impacting fatigue lifetime and optical efficiency. Preliminary results indicate that interior collectors experience higher turning moments than those at the edges, suggesting higher drive wear. At Crescent Dunes, we use instrumented heliostats at the field's edge and interior to study the translation of turbulent wind to dynamic structural loads. The campaign is still ongoing, and we will present first findings. Another focus of our work is tying the experimental wind loading findings to optical performance of the collectors, using simulation tools. For example, we derive torsional errors of the parabolic troughs - the angular offset from the sun position along a collector row. This error is impacted by wind-induced mirror deformations. Future work will focus on continuing the measurement efforts and combining them with computational fluid dynamic simulations. By providing detailed field measurements and validated models, our efforts aim to enhance understanding of wind loading on CSP collectors, improving their structural integrity and optical performance.

CSP↗
DOE OSTI2017

Final Technical Report: The Incubation of Next-Generation Radar Technologies to Lower the Cost of Wind Energy

The National Wind Institute (NWI) at Texas Tech University (TTU) has had an impressive and well documented 46-year history of wind related research activities (http://www.depts.ttu.edu/nwi/). In 2011 with funding from the United States Department of Energy (DOE), an NWI team applied radar technologies and techniques to document the complex flows occurring across a wind plant. The resulting efforts yielded measurements that exceeded the capabilities of commercial lidar technologies with respect to maximum range, range resolution and scan speed. The NWI team was also the first to apply dual-Doppler synthesis and objective analysis techniques to resolve the full horizontal wind field (i.e. not just the line-of-sight wind speeds) to successfully define turbine inflow and wake flows across large segments of wind plants. While these successes advanced wind energy interests, the existing research radar platforms were designed to serve a diversity of meteorological applications, not specifically wind energy. Because of this broader focus and the design choices made during their development, the existing radars experienced technical limitations that inhibited their commercial viability and wide spread adoption. This DOE project enabled the development of a new radar prototype specifically designed for the purpose of documenting wind farm complex flows. Relative to other “off the shelf” radar technologies, the specialized transmitter and receiver chains were specifically designed to enhance data availability in non-precipitating atmospheres. The new radar prototype was integrated at TTU using components from various suppliers across the world, and installed at the Reese Technology Center in May 2016. Following installation, functionality and performance testing were completed, and subsequent comparative analysis indicated that the new prototype greatly enhances data availability by a factor of 3.5-50 in almost all atmospheric conditions. The new prototype also provided enhanced signal quality in clear air (i.e. non-precipitating) environments, mitigated atmospheric attenuation, and extended the useful range of data collection to beyond 30km in cooperative atmospheric conditions. Additionally, the new DOE-X prototype appears to benefit from Bragg scattering when the thermal stratification of the atmosphere is strong (i.e. nocturnal hours). This result was not possible in any capacity with the previous technology. Combined, these developments represent the achievement of all project objectives, advance the Technical Readiness Level (TRL) to a level of 7, and open the door for more widespread adoption and usage in the wind energy sector. At the same time, radar induced artifacts from multi-trip echoes and ground targets increased with the new technology, and these required additional attention for some applications. Commercialization activity accelerated in parallel with the DOE funded project, as SmartWind Technologies, L.L.C., was contracted to provide two new radar systems to DONG Energy to monitor the Westermost Rough wind plant off the east coast of the United Kingdom. These new early stage commercial radars systems were closely related to the DOE prototype, but maintain more robust ancillary support systems. The radars were installed during the summer of 2016, and have been operational since that time. Additionally, commercially funded advancements have since been made in processing sophistication to mitigate the previously identified radar artifacts. TTU and SmartWind Technologies stand ready to provide public and private partners focused on wind plant optimization with this new capability. Ancillary interests have also been identified as the initial deployments of the technology have shown the ability to identify and track avian and drone activity, opening up multi-purpose operational opportunities.

17 WIND ENERGY↗
DOE OSTI2021

Wind Plant Performance Prediction Benchmark Phase 1 (Technical Report)

Financial risk resulting from the uncertainty associated with developing, owning, and operating wind power plants remains a barrier to reducing the levelized cost of energy (LCOE). On average, modern wind power plants in the U.S. underperform their expected annual energy output by 3.5-4.5% , with many underperforming by over 10%. To compensate for this uncertainty, investors require a larger return on investment (ROI) and apply "knock-down" factors that mask much of the underlying sources of uncertainty. Wind energy projects thus have reduced access to low-cost capital. Furthermore, operating wind plants often take a simple approach to estimating operations & maintenance (O&M) costs (e.g. straight-line estimates based on similar plants), which can eat into profits. To overcome these issues, the wind industry must improve the models they use for estimating wind plant performance and operations. An industry consortium (IC) requested that the National Renewable Energy Laboratory (NREL) lead a Department of Energy (DOE) working group to benchmark the accuracy of wind power plant energy predictions against real operational data. The IC was also motivated by DOE and NREL's potential to characterize systematic energy underperformance, identify sources of uncertainty, and explore root causes. The Wind Plant Performance Prediction (WP3) project was created out of this request, and this report represents the successful completion of Phase 1 of the WP3 project. During the project, wind plant owners provided both pre-construction and operational data to NREL. The pre-construction data was provided to wind resource assessment (WRA) consultants so they could conduct energy yield assessments (EYA). NREL took all of the completed EYAs, along with the operational data, and conducted an operational assessment to benchmark the EYA results against actual operational data. Given the large amounts of sensitive data required for this effort, as well as historical opposition to sharing data within industry, successful completion of Phase 1 represents an unprecedented milestone for industry data sharing. To improve the accuracy and confidence of pre-construction EYAs, wind plant owners and investors need better, more certain, energy yield predictions. The WP3 Benchmark Project is an industry-driven response to this reality. For the first time, industry has taken the important step of working together at scale, sharing valuable operational data with DOE and NREL in order to investigate the sources of bias and uncertainty in these energy estimates. This IC provides wind plant preconstruction and operational data to NREL in an organized and documented fashion and provides guidance and feedback as needed. The IC also provides introspection of the design of experiment, key metrics of success, data challenges, analysis best practices, and quality of results.

17 WIND ENERGY↗
DOE OSTI2024

Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.

Array↗
DOE OSTI2024

2022 Component Innovation Awardee: Pecos Wind Power

Distributed wind energy systems supply electricity for nearby homes and businesses, often in remote and rural regions. Systems capable of capturing energy in areas with low wind speeds make it possible to deploy these clean energy systems in many geographic locations. Pecos Wind Power's 85-kilowatt (kW) horizontal-axis PW85 wind turbine shows potential to reduce the levelized cost of energy by approximately 55% when compared to typical small wind systems while achieving utility-scale capacity factors of more than 40% in areas with lower wind speeds. To maximize cost competitiveness, the Pecos Wind Power turbine needs a blade optimized for low wind speeds. Through its 2022 Competitiveness Improvement Project (CIP) award, Pecos Wind Power and partner Wetzel Wind Energy Services will model, optimize, fabricate, and validate a 14.5-meter wind turbine blade made specifically for these applications. Three prior CIP awards supported Pecos Wind Power's initial development of the PW85 turbine.

CIP↗
DOE OSTI2023

A Multi-Fidelity Gaussian Process Regression Method for Probabilistic Wind Farm Power Curve Estimation

Accurate estimation of the power curve for wind turbines or wind farms is crucial to ensure their efficient operation and management. However, conventional methods for power curve estimation rely either on expensive and infrequent measurements or on low-quality numerical simulations. Moreover, the majority of previous studies on power curve estimation for wind turbines or wind farms focused on deterministic estimation, which provides a point estimate of the relationship between wind speed and power generation. Nevertheless, the deterministic approach fails to consider the inherent uncertainty associated with wind energy production resulting from varying turbine characteristics. This can lead to inaccurate power generation estimation and suboptimal decisions regarding energy management. In this paper, a kernel density estimation (KDE) based Multi-Fidelity Gaussian Process Regression (MFGPR) model is proposed to fuse theoretical power curve data and the ground true measurements to create a mapping of wind speed and wind power. By conducting a case study on an actual wind farm in China, the efficacy of the proposed MFGPR model was demonstrated in characterizing the variability of wind power. The probabilistic MFGPR model was also able to generate confidence intervals that encompassed the measured power, thereby improving the accuracy and confidence in wind power estimation or wind resource assessment. Overall, the proposed MFGPR model offers a reliable approach to integrate high-fidelity ground measurements and theoretical power curve data, resulting in precise wind resource assessment and power estimation.

Gaussian process regression↗
DOE OSTI2013

An Industry/Academe Consortium for Achieving 20% wind by 2030 through Cutting-Edge Research and Workforce Training

In January 2010, the University of Minnesota, along with academic and industry project partners, began work on a four year project to establish new facilities and research in strategic areas of wind energy necessary to move the nation towards a goal of 20% wind energy by 2030. The project was funded by the U.S. Department of Energy with funds made available through the American Recovery and Reinvestment Act of 2009. $7.9M of funds were provided by DOE and $3.1M was provided through matching funds. The project was organized into three Project Areas. Project Area 1 focused on design and development of a utility scale wind energy research facility to support research and innovation. The project commissioned the Eolos Wind Research Field Station in November of 2011. The site, located 20 miles from St. Paul, MN operates a 2.5MW Clipper Liberty C-96 wind turbine, a 130-ft tall sensored meteorological tower and a robust sensor and data acquisition network. The site is operational and will continue to serve as a site for innovation in wind energy for the next 15 years. Project Areas 2 involved research on six distinct research projects critical to the 20% Wind Energy by 2030 goals. The research collaborations involved faculty from two universities, over nine industry partners and two national laboratories. Research outcomes include new knowledge, patents, journal articles, technology advancements, new computational models and establishment of new collaborative relationships between university and industry. Project Area 3 focused on developing educational opportunities in wind energy for engineering and science students. The primary outcome is establishment of a new graduate level course at the University of Minnesota called Wind Engineering Essentials. The seminar style course provides a comprehensive analysis of wind energy technology, economics, and operation. The course is highly successful and will continue to be offered at the University. The vision of U.S. DOE to establish unique, open-access research facilities and creation of university-industry research collaborations in wind energy were achieved through this project. The University of Minnesota, through the establishment of the Eolos Wind Energy Consortium and the Eolos Wind Research Field Station continue to develop new research collaborations with industry partners.

17 WIND ENERGY↗