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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Urban heat islands can influence the wind energy resource during heatwaves

Urban wind energy is critical for sustainable electricity generation in cities. However, little research has explored how the urban heat island (UHI) effect influences wind energy, particularly in heatwaves when energy demand surges. In this study, we examine wind energy distribution in the Boston–Providence metropolitan area during heatwaves, using Weather Research and Forecasting (WRF) model integrated with Building Energy Parameterization/Building Energy Model (BEP/BEM). Two scenarios, a realistic case and a hypothetical case without urban warmth, were compared to isolate UHI impacts. Results reveal that UHI induces a "wind energy loss zone" in this urban area, reducing wind power density (WPD) by 20–30 W/m 2 at 50–100 m, while suburban/rural areas exhibit a "wind energy gain zone," with WPD increases up to 40 W/m 2 at 150–200 m. These losses diminish with distance from urban centers and become negligible beyond main urban and suburban sprawl. Heatwave expands the urban "loss zone", while amplifying wind energy gains in suburban/rural areas, driven by stronger thermal gradients and weakened background winds that intensify air convergence in urban and urban-rural circulations, thereby exacerbating urban wind energy losses by 15–20 %. An analysis of 235 wind farms using turbine power curves reveals that built areas dependent on stand-alone or off-grid turbines face significant energy deficits during a heatwave. Wind energy drops by up to 25 %, while cooling-related building energy demand rises 30–40 % during a heatwave. These findings underscore the need for strategic urban wind energy planning to ensure reliable power during extreme heat.

Energy - Wind↗
DOE OSTI2016

Simulating effects of a wind-turbine array using LES and RANS

Growth in wind power production has motivated investigation of wind-farm impacts on in situ flow fields and downstream interactions with agriculture and other wind farms. These impacts can be simulated with both large-eddy simulations (LES) and mesoscale wind-farm parameterizations (WFP). The Weather Research and Forecasting (WRF) model offers both approaches. We used the validated generalized actuator disk (GAD) parameterization in WRF-LES to assess WFP performance. A 12-turbine array was simulated using the GAD model and the WFP in WRF. We examined the performance of each scheme in both convective and stable conditions. The GAD model and WFP produced qualitatively similar wind speed deficits and turbulent kinetic energy (TKE) production across the array in both stability regimes, though the magnitudes of velocity deficits and TKE production levels were underestimated and overestimated, respectively. While wake growth slowed in the latter half of the WFP array as expected, wakes did not approach steady state by the end of the array as simulated by the GAD model. A sensitivity test involving the deactivation of explicit TKE production by the WFP resulted in turbulence levels within the array well that were below those produced by the GAD in both stable and unstable conditions. Finally, the WFP overestimated downwind power production deficits in stable conditions because of the lack of wake stabilization in the latter half of the array.

17 WIND ENERGY↗
DOE OSTI2017

2016 Cost of Wind Energy Review

This report uses representative utility-scale projects to estimate the levelized cost of energy (LCOE) for land-based and offshore wind power plants in the United States. Data and results detailed here are derived from 2016 commissioned plants. More specifically, analysis detailed here relies on recent market data and state-of-the-art modeling capabilities to maintain an up-to-date understanding of wind energy cost trends and drivers. This report is intended to provide insight into current component-level costs as well as a basis for understanding variability in LCOE across the country. This publication represents the sixth installment of this annual report.

17 WIND ENERGY↗
DOE OSTI2020

Prognosis of Wind Turbine Gearbox Bearing Failures Using SCADA and Modeled Data

Predictive maintenance and condition monitoring systems for wind turbines have seen increased adoption to minimize downtime, reducing operation and maintenance costs. On today’s wind power plants, the integrated supervisory control and data acquisition (SCADA) system provides low- frequency operational data that can be leveraged to quantify a wind turbine’s health. The aim of this study is to utilize machine-learning techniques to predict axial cracking failures in wind turbine gearbox bearings up to 1 month ahead of time. The failures are assumed to have occurred when the investigated bearing was replaced. While current SCADA systems show the overall condition of a wind turbine, often they do not allow for the investigation of specific gearbox bearings’ health. To enrich bearing fault signatures, additional data are computed through physics-based models using gearbox design information. Based on SCADA data, modeled data, and bearing failure log data from an actual wind plant, the performances of different machine-learning models on unseen data are then evaluated using industry-standard metrics such as precision, recall, and F1 score. Results show the overall system performance enhancement in predicting bearing failure when modeled data are included with SCADA data. The reduction in terms of false alarms is about 50%, and improvement in terms of precision and F1 score is about 33% and 12% respectively, based on the best modeling case in this study.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
NASA NTRS1992

A Mars 1 Watt vortex wind energy machine

A Martian wind power generator capable of surviving impact and fulfilling the long-term (2-5 yr) low-level power requirements (1-2 W) of an unmanned surface probe is presented. Attention is given to a tornado vortex generator that was chosen on the basis of its capability to theoretically augment the available power that may be extracted for average Martian wind speeds of about 7.5 m/s. The generator offers comparable mass-to-power ratios with solar power sources.

Ralston, Michael↗
NASA NTRS1979

Solar thermal power generation. A bibliography with abstracts

Bibliographies and abstracts are cited under the following topics: (1) energy overviews; (2) solar overviews; (3) conservation; (4) economics, law; (5) thermal power; (6) thermionic, thermoelectric; (7) ocean; (8) wind power; (9) biomass and photochemical; and (10) large photovoltaics.

Source record↗
NASA NTRS2022

Power Rover

The Power Rover project is a North Dakota State University (NDSU) undergraduate investigation into the design of a rover that would generate, store, and deliver power to other rovers and equipment on the surface of Mars funded through the NASA X-Hab challenge. X-Hab is a portion of NASA that challenges students to act as a new set of eyes and design engineered solutions that address critical needs of the Artemis program. The goal of this specific project was to design, build, and test an Earth-based prototype of a Martian rover called the Power Rover. The Power Rover is a solar, nuclear, and wind powered tele-operated rover that can generate, store, and deliver power to other rovers or equipment on the Martian surface that are in critical power situations. Due to the large complexity of the project, it was assigned to three senior design groups within the NDSU Mechanical Engineering and Electrical Engineering departments. These groups include an electrical team, power generation and storage team, and structure and drivetrain team. This report will detail the information, findings, final design solutions, and testing that have been made by the NDSU teams during the fall and spring semesters of the 2021-2022 academic school year.

Alex Johnson↗
DOE OSTI2015

2015 Key Wind Program and National Laboratory Accomplishments

The U.S. Department of Energy (DOE) Wind Program is committed to helping the nation secure cost-competitive sources of renewable energy through the development and deployment of innovative wind power technologies. By investing in improvements to wind plant design, technology development, and operation as well as developing tools to identify the highest quality wind resources, the Wind Program serves as a leader in making wind energy technologies more competitive with traditional sources of energy and a larger part of our nation’s renewable energy portfolio.

wind, accomplishments↗
DOE OSTI2023

Machine Learning–Adjusted WRF Forecasts to Support Wind Energy Needs in Black Start Operations

Abstract The push for increased capacity of renewable sources of electricity has led to the growth of wind-power generation, with a need for accurate forecasts of winds at hub height. Forecasts for these levels were uncommon until recently, and that, combined with the nocturnal collapse of the well-mixed boundary layer and daytime growth of the boundary layer through the levels important for energy generation, has contributed to errors in numerical modeling of wind generation resources. The present study explores several machine learning algorithms to both forecast and correct standard WRF Model forecasts of winds and temperature at hub height within wind turbine plants over several different time periods that are critical for the anticipation of potential blackouts and aiding in black start operations on the power grid. It was found that mean square error for day-2 wind forecasts from the WRF Model can be improved by over 90% with the use of a multioutput neural network, and that 60-min forecasts of WRF error, which can then be used to adjust forecasts, can be made with an LSTM with great accuracy. Nowcasting of temperature and wind speed over a 10-min period using an LSTM produced very low error and especially skillful forecasts of maximum and minimum values over the turbine plant area.

17 WIND ENERGY↗
NASA NTRS1974

A brief summary of the attempts to develop large wind-electric generating systems in the U.S.

Interest in developing large wind-electric generating systems in the United States was stimulated primarily by one man, Palmer C. Putnam. He was responsible for the construction of the largest wind-power system ever built - the 1250 kilowatt Smith-Putnam wind-electric plant. The existence of this system prompted the U.S. Federal Power Commission to investigate the potential of using the winds as a source energy. Also, in 1933 prior to Putnam's effort, there was an abortive attempt by J. D. Madaras to develop a wind system based on the Magnus effect. These three projects comprise the only serious efforts in America to develop large wind driven plants. In this paper, the history of each project is briefly described. Also discussed are some of the reasons why wind energy was not seriously considered as a major source of energy for the U.S.

Savino, J. M.↗
DOE OSTI2016

Floating Offshore Wind in Hawaii: Potential for Jobs and Economic Impacts from Three Future Scenarios

Construction of the first offshore wind power plant in the United States began in 2015, off the coast of Rhode Island, using fixed platform structures that are appropriate for shallow seafloors, like those located off the East Coast and mid-Atlantic. However, floating platforms, which have yet to be deployed commercially, will likely need to be anchored to the deeper seafloor if deployed in Hawaiian waters. To analyze the employment and economic potential for floating offshore wind off Hawaii's coasts, the Bureau of Ocean Energy Management commissioned the National Renewable Energy Laboratory (NREL) to analyze two hypothetical deployment scenarios for Hawaii: 400 MW of offshore wind by 2050 and 800 MW of offshore wind by 2050. The results of this analysis can be used to better understand the general scale of economic opportunities that could result from offshore wind development.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A heuristic tool to assess regional impacts of renewable energy infrastructure on conservation areas

Wind and hydropower are important renewable components of national energy portfolios, but their infrastructure negatively affects biodiversity. Regional development requires identification of scenarios that minimize the cumulative impacts of multiple facilities. We introduce the cumulative impact plot (CIP) to quantify cumulative impacts of renewable energy development within a region. Summed impacts of facilities are plotted as a function of the number of facilities, with facilities ranked by increasing (the best-case scenario) or decreasing (worst-case scenario) individual impact. These curves represent lower and upper bounds to which alternative development scenarios (e.g., facilities ranked by generating capacity) can be compared. We used CIPs to assess overlap of potential wind and hydropower facilities with two types of conservation area in the United States: (1) federally protected lands and (2) critical habitats of federally threatened and endangered species. Here, we evaluated two alternative scenarios: facilities ranked by (A) decreasing generating capacity and (B) increasing distance from urban centers. Differences between the best-case and worst-case scenarios were large, thus revealing opportunities to develop facilities with limited impact on conservation areas. Alternative scenarios maximizing energy density generally resulted in conservation area overlap intermediate to best-case and worst-case scenarios. CIPs can also identify the proportion of wind versus hydropower favored under alternative scenarios. Build-out scenarios aimed at minimizing conservation area overlap favor hydropower, whereas alternative scenarios favor wind power. We conclude that CIPs can (1) complement—but should not replace—project-level environmental impact assessment, (2) integrate strategic, cumulative, and scenario-based assessments, and (3) harness rapidly growing geospatial data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

Digitally enhanced services for wind power could reduce Operations and Maintenance (O&M) costs as well as the Levelised Cost Of Energy (LCOE). Therefore, there is a continuous need for advanced monitoring techniques which can exploit the opportunities of Internet of Things (IoT) and Big Data Analytics, revolutionizing the future of the energy sector. The heart of wind turbines is a rather complex epicyclic gearbox. Among others, extremely critical gearbox components which are often responsible for machinery stops are the rolling element bearings. The vibration signatures of bearings are rather weak compared to other components, such as gears, and as a result an extended number of signal processing techniques and tools have been proposed during the last decades, focusing towards accurate, early, and on time bearing fault detection with limited false alarms and missed detections. Envelope Analysis is one of the most important methodologies, where an envelope of the vibration signal is estimated usually after filtering around a frequency band excited by impacts due to the bearing faults. Different tools, such as Kurtogram, have been proposed in order to accurately select the optimum filter parameters (center frequency and bandwidth). Cyclic Spectral Correlation and Cyclic Spectral Coherence, based on Cyclostationary Analysis, have been proved as very powerful tools for condition monitoring. The monitoring techniques seem to have reached a mature level in case a machinery operates under steady speed and load. On the other hand, in case the operating conditions change, it is still unclear whether the change of the monitoring indicators is due to the change of the health of the machinery or due to the change of the operating parameters. Recently, the authors have proposed a new tool called IESFOgram, which is based on Cyclic Spectral Coherence and can automatically select the filtering band. Furthermore, the Cyclic Spectral Coherence is integrated along the selected frequency band leading to an Improved Envelope Spectrum. In this paper, the performance of the tool is evaluated and further extended on cases operating under different speeds and different loads. The effectiveness of the methodology is tested and validated on the National Renewable Energy Laboratory (NREL) wind turbine gearbox vibration condition monitoring benchmarking data set which includes various faults with different levels of diagnostic complexity as well as various speed and load operating conditions.

17 WIND ENERGY↗
DOE OSTI2020

Grand Challenges in the Science of Wind Energy

The energy system of the future that depends on 80% or more renewable energy will put new demands on the wind systems that support it. There are significant areas of scientific uncertainly that need to be addressed to enable the innovation required for success. This presentation, based on a 2019 article in Science, lays out those areas of scientific challenges and proposes an integrated wind energy discipline that encompasses the needed research.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2016

Mergers of charged black holes: gravitational-wave events, short gamma-ray bursts, and fast radio bursts

The discoveries of GW150914, GW151226, and LVT151012 suggest that double black hole (BH–BH) mergers are common in the universe. If at least one of the two merging black holes (BHs) carries a certain amount of charge, possibly retained by a rotating magnetosphere, the inspiral of a BH–BH system would drive a global magnetic dipole normal to the orbital plane. The rapidly evolving magnetic moment during the merging process would drive a Poynting flux with an increasing wind power. The magnetospheric activities during the final phase of the merger would make a fast radio burst (FRB) if the BH charge can be as large as a factor of q-hat ∼(10{sup −9}--10{sup −8}) of the critical charge Q {sub c} of the BH. At large radii, dissipation of the Poynting flux energy in the outflow would power a short-duration high-energy transient, which would appear as a detectable short-duration gamma-ray burst (GRB) if the charge can be as large as q-hat ∼(10{sup −5}--10{sup −4}). The putative short GRB coincident with GW150914 recorded by Fermi GBM may be interpreted with this model. Future joint GW/GRB/FRB searches would lead to a measurement or place a constraint on the charges carried by isolate BHs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Simulation of the Multi-Wake Evolution of Two Sandia National Labs/National Rotor Testbed Turbines Operating in a Tandem Layout

The future of wind power systems deployment is in the form of wind farms comprised of scores of such large turbines, most likely at offshore locations. Individual turbines have grown in span from a few tens of meters to today’s large turbines with rotor diameters that dwarf even the largest commercial aircraft. These massive dynamical systems present unique challenges at scales unparalleled in prior applications of wind science research. Fundamental to this effort is the understanding of the wind turbine wake and its evolution. Furthermore, the optimization of the entire wind farm depends on the evolution of the wakes of different turbines and their interactions within the wind farm. In this article, we use the capabilities of the Common ODE Framework (CODEF) model for the analysis of the effects of wake–rotor and wake-to-wake interactions between two turbines situated in a tandem layout fully and partially aligned with the incoming wind. These experiments were conducted in the context of a research project supported by the National Rotor Testbed (NRT) program of Sandia National Labs (SNL). Results are presented for a layout which emulates the turbine interspace and relative turbine emplacement found at SNL’s Scaled Wind Technologies Facility (SWiFT), located in Lubbock, Texas. The evolution of the twin-wake interaction generates a very rich series of secondary transitions in the vortex structure of the combined wake. These ultimately affect the wake’s axial velocity patterns, altering the position, number, intensity, and shape of localized velocity-deficit zones in the wake’s cross-section. This complex distribution of axial velocity patterns has the capacity to substantially affect the power output, peak loads, fatigue damage, and aeroelastic stability of turbines located in subsequent rows downstream on the farm.

Baruah, Apurva (ORCID:0000000252354068)↗
DOE OSTI2014

Analysis of surface integrity of grinded gears using Barkhausen noise analysis and x-ray diffraction

The contribution is focused to present results of study grinded gears made of 18CrNiMo7-6 steel used in the wind power plant for support (service) purposes. These gears were case-hardened due to standard hard case and soft core formation. This heat treatment increases wear resistance and fatigue strength of machine parts. During serial production some troubles with surface integrity have occurred. When solving complex problems lots of samples were prepared. For grinding of gears were used different parameters of cutting speed, number of material removal and lots from different subsuppliers. Material characterization was carried out using Barkhausen noise analysis (BNA) device; X-ray diffraction (XRD) measurement of surface residual stresses was done as well. Depth profile of measured characteristics, e.g. magnetoelastic parameter and residual stress was obtained by step by step layers' removing using electrolytic etching. BNA software Viewscan was used to measure magnetizing frequency sweep (MFS) and magnetizing voltage sweep (MVS). Scanning of Magnetoelastic parameter (MP) endwise individual teeth were also carried out with Viewscan. These measurements were done to find problematic surface areas after grinding such as thermal damaged locations. Plots of the hardness and thickness of case-hardened layer on cross sections were measurered as well. Evaluation of structure of subsurface case-hardened layer and core was made on etched metallographic patterns. The aim of performed measurements was to find correlation between conditions of grinding, residual stresses and structural and magnetoelastic parameters. Based on correlation of measured values and technological parameters optimizing the production of gears will be done.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗