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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Inertia estimation for power grids: A review of methods, challenges, and future prospects

The electric power grid is undergoing a significant transformation, shifting from traditional synchronous generators to inverter-based resources (IBRs) such as solar photovoltaics, wind turbines, and energy storage systems. This evolution leads to a reduction in system inertia, a critical attribute for maintaining frequency stability in response to disturbances. Consequently, the ability to monitor and estimate system inertia has become increasingly essential. This paper provides a comprehensive review of existing inertia estimation methodologies, analyzing them from multiple perspectives, including the types of data utilized, underlying estimation principles, operational modes, and system-wide applicability. A comparative summary table is included to distill commonalities and key characteristics across various studies. In addition, the paper examines practical implementations of inertia estimation across several major power systems worldwide, including the U.S. interconnections, the Nordic power system, and the U.K. grid. Key challenges are identified, particularly in estimating contributions from virtual inertia sources and load-induced inertia in increasingly converter-dominated networks. To address these emerging challenges, the paper proposes an integrated framework for real-time inertia estimation and monitoring. This framework encompasses critical components such as data acquisition, inertia estimation from both synchronous and non-synchronous sources, load-induced effects, optimization techniques, forecasting, and virtual inertia scheduling. Collectively, these elements enable dynamic, system-wide monitoring and adaptive control of grid inertia.

Inertia estimation↗
DOE OSTI2021

Sustainable Recycling of Rare-Earth Elements from NdFeB Magnet Swarf: Techno-Economic and Environmental Perspectives

Rare-earth elements (REEs) are increasingly susceptible to supply risks due to their limited geographical availability and growing demand in clean energy applications such as neodymium-iron-boron (NdFeB) magnets used in electric vehicles and wind turbines. When NdFeB magnets are produced, 6–73% of swarf is generated during the manufacturing steps. This paper presents an innovative technology that utilizes copper nitrate to dissolve REEs in NdFeB magnet swarf and subsequently recovers ~97% of them as mixed rare-earth oxides (REOs) of purity higher than 99.5%. Techno-economic analysis (TEA) and life cycle assessment (LCA) quantified the economic and environmental impacts of adopting the proposed acid-free dissolution technology, projecting a net profit margin of 12–43% and a global warming impact reduction by up to 73% compared to the prevailing REO production routes in China. As copper nitrate is the single largest contributor to the cost and environmental footprint, recycling of copper nitrate was investigated as well as using alternative copper salts (e.g., copper acetate), revealing significant improvements in TEA and LCA results. Dysprosium was a major revenue source, highlighting the importance of targeting electric vehicle magnets that are rich in dysprosium. As the REO market is volatile, sensitivity analysis was employed to evaluate the profitability of the proposed technology under different REO prices over the last 11 years. Overall, our results confirmed the economic and environmental viability of the proposed technology for sustainable recycling of REEs from the NdFeB magnet swarf.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1986

The acoustic field of a point source in a uniform boundary layer over an impedance plane

The acoustic field of a point source in a boundary layer above an impedance plane is investigated anatytically using Obukhov quasi-potential functions, extending the normal-mode theory of Chunchuzov (1984) to account for the effects of finite ground-plane impedance and source height. The solution is found to be asymptotic to the surface-wave term studies by Wenzel (1974) in the limit of vanishing wind speed, suggesting that normal-mode theory can be used to model the effects of an atmospheric boundary layer on infrasonic sound radiation. Model predictions are derived for noise-generation data obtained by Willshire (1985) at the Medicine Bow wind-turbine facility. Long-range downwind propagation is found to behave as a cylindrical wave, with attention proportional to the wind speed, the boundary-layer displacement thickness, the real part of the ground admittance, and the square of the frequency.

Zorumski, W. E.↗
DOE OSTI2021

2020 Component Innovation Awardee: Carter Wind Turbines

With support from the Competitiveness Improvement Project's Component Innovation Award, Carter Wind Energy aims to address the need for lower-cost, more-reliable distributed wind energy generation. The company plans to increase efficiency and improve the energy capture of its Carter Model 300 midsize, self-erecting wind turbine. This fact sheet provides an overview of Carter Wind Energy's project, how the company will achieve the goals of the award, and how the project fits within the overall Competitiveness Improvement Project.

CIP↗
NASA NTRS1979

Results of a utility survey of the status of large wind turbine development

Wind energy conversion systems were surveyed from a utility viewpoint to establish the state of the art with regard to: (1) availability of the type of machines; (2) quality of power generation; (3) suitability for electrical grid; (4) reliability; and (5) economics. Of the 23 designs discussed, 7 have vertical axis wind turbines, 9 have upwind horizontal axis turbines, and 7 have downwind horizontal axis turbines.

Watts, A.↗
DOE OSTI2020

Opportunities for and challenges to further reductions in the “specific power” rating of wind turbines installed in the United States

A wind turbine’s “specific power” rating relates its capacity to the swept area of its rotor in terms of Watt per square meter. For a given generator capacity, specific power declines as rotor size increases. In land-rich but capacity-constrained wind power markets, such as the United States, developers have an economic incentive to maximize megawatt-hours per constrained megawatt, and so have favored turbines with ever-lower specific power. To date, this trend toward lower specific power has pushed capacity factors higher while reducing the levelized cost of energy. We employ geospatial levelized cost of energy analysis across the United States to explore whether this trend is likely to continue. We find that under reasonable cost scenarios (i.e. presuming that logistical challenges from very large blades are surmountable), low-specific-power turbines could continue to be in demand going forward. Beyond levelized cost of energy, the boost in market value that low-specific-power turbines provide could become increasingly important as wind penetration grows.

geospatial modeling↗
NASA NTRS1981

The NASA-LeRC wind turbine sound prediction code

Since regular operation of the DOE/NASA MOD-1 wind turbine began in October 1979 about 10 nearby households have complained of noise from the machine. Development of the NASA-LeRC with turbine sound prediction code began in May 1980 as part of an effort to understand and reduce the noise generated by MOD-1. Tone sound levels predicted with this code are in generally good agreement with measured data taken in the vicinity MOD-1 wind turbine (less than 2 rotor diameters). Comparison in the far field indicates that propagation effects due to terrain and atmospheric conditions may be amplifying the actual sound levels by about 6 dB. Parametric analysis using the code has shown that the predominant contributions to MOD-1 rotor noise are: (1) the velocity deficit in the wake of the support tower; (2) the high rotor speed; and (3) off column operation.

Viterna, L. A.↗
NASA NTRS2009

Adaptive Control of a Utility-Scale Wind Turbine Operating in Region 3

Adaptive control techniques are well suited to nonlinear applications, such as wind turbines, which are difficult to accurately model and which have effects from poorly known operating environments. The turbulent and unpredictable conditions in which wind turbines operate create many challenges for their operation. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility scale, variable-speed horizontal axis wind turbine. The objective of the adaptive pitch controller in Region 3 is to regulate generator speed and reject step disturbances. The control objective is accomplished by collectively pitching the turbine blades. We use an extension of the Direct Model Reference Adaptive Control (DMRAC) approach to track a reference point and to reject persistent disturbances. The turbine simulation models the Controls Advanced Research Turbine (CART) of the National Renewable Energy Laboratory in Golden, Colorado. The CART is a utility-scale wind turbine which has a well-developed and extensively verified simulator. The adaptive collective pitch controller for Region 3 was compared in simulations with a bas celliansesical Proportional Integrator (PI) collective pitch controller. In the simulations, the adaptive pitch controller showed improved speed regulation in Region 3 when compared with the baseline PI pitch controller and it demonstrated robustness to modeling errors.

Frost, Susan A.↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part I: Dynamical Downscaling

Abstract New simulations at 12-km grid spacing with the Weather and Research Forecasting (WRF) Model nested in the MPI Earth System Model (ESM) are used to quantify possible changes in wind power generation potential as a result of global warming. Annual capacity factors (CF; measures of electrical power production) computed by applying a power curve to hourly wind speeds at wind turbine hub height from this simulation are also used to illustrate the pitfalls in seeking to infer changes in wind power generation directly from low-spatial-resolution and time-averaged ESM output. WRF-derived CF are evaluated using observed daily CF from operating wind farms. The spatial correlation coefficient between modeled and observed mean CF is 0.65, and the root-mean-square error is 5.4 percentage points. Output from the MPI-WRF Model chain also captures some of the seasonal variability and the probability distribution of daily CF at operating wind farms. Projections of mean annual CF (CF A ) indicate no change to 2050 in the southern Great Plains and Northeast. Interannual variability of CF A increases in the Midwest, and CF A declines by up to 2 percentage points in the northern Great Plains. The probability of wind droughts (extended periods with anomalously low production) and wind bonus periods (high production) remains unchanged over most of the eastern United States. The probability of wind bonus periods exhibits some evidence of higher values over the Midwest in the 2040s, whereas the converse is true over the northern Great Plains. Significance Statement Wind energy is playing an increasingly important role in low-carbon-emission electricity generation. It is a “weather dependent” renewable energy source, and thus changes in the global atmosphere may cause changes in regional wind power production (PP) potential. We use PP data from operating wind farms to demonstrate that regional simulations exhibit skill in capturing actual power production. Projections to the middle of this century indicate that over most of North America east of the Rocky Mountains annual expected PP is largely unchanged, as is the probability of extended periods of anomalously high or low production. Any small declines in annual PP are of much smaller magnitude than changes due to technological innovation over the last two decades.

Meteorology & Atmospheric Sciences↗
NASA NTRS1995

Analysis methods for wind turbine control and electrical system dynamics

The integration of new energy technologies into electric power systems requires methods which recognize the full range of dynamic events in both the new generating unit and the power system. Since new energy technologies are initially perceived as small contributors to large systems, little attention is generally paid to system integration, i.e. dynamic events in the power system are ignored. As a result, most new energy sources are only capable of base-load operation, i.e. they have no load following or cycling capability. Wind turbines are no exception. Greater awareness of this implicit (and often unnecessary) limitation is needed. Analysis methods are recommended which include very low penetration (infinite bus) as well as very high penetration (stand-alone) scenarios.

Hinrichsen, E. N.↗
DOE OSTI2026

Turbine Damage Probability

Damage probability maps for offshore wind turbines exposed to tropical cyclones (TCs) under both historical and future climate scenarios along the U.S. Atlantic and Gulf Coasts are presented in this dataset. TCs are generated using the Risk Analysis Framework for Tropical Cyclones (RAFT), forced by CMIP6 historical and future global climate simulations. Maximum wind speeds for 20- and 50-year TCs are processed through a fragility function specific to offshore wind (OSW) turbines in order to estimate the probability of damage – specifically yielding and buckling – based on wind speed intensity.

17 WIND ENERGY↗
DOE OSTI2022

A reference open-source controller for fixed and floating offshore wind turbines

Abstract. This paper describes the development of a new reference controller framework for fixed and floating offshore wind turbines that greatly facilitates controller tuning and represents standard industry practices. The reference wind turbine controllers that are most commonly cited in the literature have been developed to work with specific reference wind turbines. Although these controllers have provided standard control functionalities, they are often not easy to modify for use on other turbines, so it has been challenging for researchers to run representative, fully dynamic simulations of other wind turbine designs. The Reference Open-Source Controller (ROSCO) has been developed to provide a modular reference wind turbine controller that represents industry standards and performs comparably to or better than existing reference controllers. The formulation of the ROSCO controller logic and tuning processes is presented in this paper. Control capabilities such as tip speed ratio tracking generator torque control, minimum pitch saturation, wind speed estimation, and a smoothing algorithm at near-rated operation are included to provide modern controller features. A floating offshore wind turbine feedback module is also included to facilitate growing research in the floating offshore arena. All of the standard controller implementations and control modules are automatically tuned such that a non-controls engineer or automated optimization routine can easily improve the controller performance. This article provides the framework and theoretical basis for the ROSCO controller modules and generic tuning processes. Simulations of the National Renewable Energy Laboratory (NREL) 5 MW reference wind turbine and International Energy Agency 15 MW reference turbine on the University of Maine semisubmersible platform are analyzed to demonstrate the controller's performance in both fixed and floating configurations, respectively. The simulation results demonstrate ROSCO's peak shaving routine to reduce maximum rotor thrusts by over 10 % compared to the NREL 5 MW reference wind turbine controller on the land-based turbine and to reduce maximum platform pitch angles by nearly 30 % when using the platform feedback routine instead of a more traditional low-bandwidth controller.

17 WIND ENERGY↗
DOE OSTI2021

Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets

This dataset contains turbine- and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in Steady State (FLORIS) model, version 2.3.0. The 252,500 cases include 500 unique wind plants generated randomly by a specialized Plant Layout Generator (PLayGen) that samples randomized realizations of wind plant layouts from one of four canonical configurations: (i) cluster, (ii) single string, (iii) multiple string, (iv) parallel string. Other wind plant layout parameters were also randomly sampled, including the number of turbines (25-200) and the mean turbine spacing (3D-10D, where D denotes the turbine rotor diameter). For each layout, 500 different sets of atmospheric conditions were randomly sampled. These include wind speed in 0-25 m/s, wind direction in 0 deg.-360 deg., and turbulence intensity chosen from low (6%), medium (8%), and high (10%). For each atmospheric inflow scenario, the individual turbine yaw angles were randomly sampled from a one-sided truncated Gaussian on the interval 0 deg.-30 deg. oriented relative to wind inflow direction. This random data is supplemented with a collection of yaw-optimized samples where FLORIS was used to determine turbine yaw angles that maximize power production for the entire plant. To generate this data, a subset of cases were selected (50 atmospheric conditions from 50 layouts each for a total of additional 2,500 cases) for which FLORIS was re-run with wake steering control optimization. The IEA onshore reference turbine, which has a 130 m rotor diameter, a 110 m hub height, and a rated power capacity of 3.4 MW was used as the turbine for all simulations. The simulations were performed using NREL's Eagle high performance computing system in February 2021 as part of the Spatial Analysis for Wind Technology Development project funded by the U.S. Department of Energy Wind Energy Technologies Office. The data was collected, reformatted, and preprocessed for this OEDI submission in May 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub repository under explore_wind_plant_data_h5.ipynb.

AI↗
DOE OSTI2022

Design Guidelines for Deployable Wind Turbines for Defense and Disaster Response Missions

Access to on-site electrical energy is critical to ensuring a successful military or humanitarian response to conflicts and disasters. These missions typically rely on access to liquid fuel that could be vulnerable to disruption or attack during transport. Generating power on location with wind technology can reduce this risk and enhance mission reach by diversifying energy sources. Common characteristics of these missions are short planning and execution time horizons and a global scope of potential locations. Compared to conventional wind turbine applications, defense and disaster response applications place a premium on rapid shipping and installation, short-duration operation (days to months), and quick teardown upon mission completion. These design drivers depart from features found in conventional distributed wind turbines, thus necessitating unique design guidance. The supporting information for this guidance comes from available relevant references, technical analyses, and input from industry and military stakeholders. This poster serves as a summary of project publications which presents the best currently available design guidance for deployable wind turbines to facilitate the effective development and acquisition of technology solutions to support mission success. This Defense and Disaster Deployable Turbine Project (D3T) is a multi-laboratory effort led by Sandia National Laboratories and funded by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Wind Energy Technologies Office.

deployable wind↗
DOE OSTI2024

Analysis of the Aeroelastic Dynamics of Lightweight Flexible Variations of the SNL-NRT Turbine

Current trends show that wind turbines are growing in size to meet a rising demand for renewable energy generation, and their upscaled rotors have inherently become more flexible to maintain a proportionally lighter design. This is because larger rotors must be less massive relative to their diameter to minimize the levelized cost of energy (LCOE), which means that blades that are notably less stiff are produced as a result. These structural changes to blades are often reflected in their compromised aeroelastic stability and amplified deformation during operation, which has the potential to decrease the blade’s expected lifetime and the performance of the machine overall. Variations in blade flexibility are also known to influence vortex-wake structures downstream of the turbine, causing patterns of velocity deficit to evolve in ways that affect the performance of other turbines in the farm. This research explores how the increased flexibility of modern utility-scale wind turbine blades influences rotor aeroelastic behavior and interactions with farm flow. High-fidelity simulations of Sandia National Laboratories’ (SNL) National Rotor Testbed (NRT) wind turbine are presented. Flexible variations of the NRT baseline blade are simulated in a variety of realistic operational conditions typically expected at the SNL’s SWiFT facility in Lubbock, Texas. Solutions are then compared to investigate how specific changes to the structural properties of the NRT baseline blade’s design and construction can influence its aeroelastic response at the rotor and the evolution of the turbine’s wake.

Farrell, Alayna (ORCID:000000023555720X)↗
DOE OSTI2022

The Circular Economy Life Cycle Assessment and Visualization Framework: A Multistate Case Study of Wind Blade Circularity in United States

A circular economy (CE) aims to decouple human activities from economic activities and resource use, and its overall goal is reducing or avoiding negative environmental externalities. The newly developed Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework simulates changes in supply chain environmental impacts as it transitions toward circularity. This study expands CELAVI by incorporating detailed spatial resolution and real-world road routes connecting all facilities within the system. The case study on end-of-life decision making of wind turbine blades in the states of Iowa and Missouri explores how supply chain circularity and environmental impacts are affected by pathway costs and level of wind turbine installations. It demonstrates how high circularity costs might be beneficial for circularity transitions given revenue generated from circular pathways. Finally, impacts have important contributions to the supply chain design and thus show the importance of including detailed spatial resolution in CELAVI and CE studies in general.

circular economy↗