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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 415 records · Page 23
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DOE OSTI2024

Land Resources for Wind Energy Development Requires Regionalized Characterizations

Estimates of the land area occupied by wind energy differ by orders of magnitude due to data scarcity and inconsistent methodology. Here, we developed a method that combines machine learning-based imagery analysis and geographic information systems and examined the land area of 318 wind farms (15,871 turbines) in the U.S. portion of the Western Interconnection. We found that prior land use and human modification in the project area are critical for land-use efficiency and land transformation of wind projects. Projects developed in areas with little human modification have a land-use efficiency of 63.8 ± 8.9 W/m 2 (mean ±95% confidence interval) and a land transformation of 0.24 ± 0.07 m 2 /MWh, while values for projects in areas with high human modification are 447 ± 49.4 W/m 2 and 0.05 ± 0.01 m 2 /MWh, respectively. We show that land resources for wind can be quantified consistently with our replicable method, a method that obviates >99% of the workload using machine learning. To quantify the peripheral impact of a turbine, buffered geometry can be used as a proxy for measuring land resources and metrics when a large enough impact radius is assumed (e.g., >4 times the rotor diameter). Our analysis provides a necessary first step toward regionalized impact assessment and improved comparisons of energy alternatives.

17 WIND ENERGY↗
DOE OSTI2020

Multifaceted drivers for onshore wind energy repowering and their implications for energy transition

Wind energy is anticipated to become a backbone of the future energy system. Ageing wind turbine fleets, increasing land-use constraints and rising relevance of societal factors make the deployment of land-based (onshore) wind energy ever more complicated. Consequently, repowering is expected to become a rapidly growing point of focus for the wind industry. Here we propose a more holistic and socially informed project-level approach to analyse repowering activity that enables a more robust understanding of the process and potentials. We demonstrate that for wind pioneer in Denmark, only 67% of the capacity removed in repowering projects was related to the physical space needed for a new turbine. Other factors that drive repowering include regulation (for example, noise-related, 8–17%), development principles (for example, aesthetics, 7–20%) and political bargaining (4–13%). The recognition of repowering as a negotiated process between host communities and wind developers will probably be critical to unlock the full potential of wind energy in the future.

17 WIND ENERGY↗
DOE OSTI2024

Distributional Equity in the Employment and Wage Impacts of Energy Transitions

We use restricted-access, geocoded data on the near-universe of workers in 23 US states to quantify the impact of wind energy development on local earnings and employment, by race, ethnicity, sex, and educational attainment. We find significant impacts that persist for several years beyond the project construction phase. Our estimates are larger than those from previous studies but still small relative to typical economic multipliers for fiscal spending or investment in other industries. We find the largest percentage increases for black workers and workers who either do not have a high school diploma or who have a college degree. We also find the economic gains for men to be much larger than those for women. Finally, we find estimates from data aggregated to the county level to be significantly lower than our worker-level estimates. We suggest a number of areas for further study building off the justice implications of our findings.

employment↗
DOE OSTI2024

Validation of new and existing methods for time-domain simulations of turbulence and loads

We seek to obtain a second-by-second match between the simulated and measured structural loads of a utility-scale wind turbine. To obtain the one-to-one load simulations, we start with the furthest upstream component of the modeling chain: the turbulent inflow. We consider new and existing methods to generate constrained-turbulence flow fields. The new method is based on large-eddy simulations (LES) and machine learning (ML). The existing methods include Kaimal-based TurbSim and the superstatistical wind field model. The inflow measurements used to constrain these simulations are obtained with a nacelle-mounted scanning lidar. We compare the flow fields for the different inflow simulation approaches and validate their associated load predictions against measurements collected in the Rotor Aero-dynamics, Aeroelastics, and Wake (RAAW) field campaign. We find that the rotor-position control developed for this study is key in enabling the time match between measurements and simulations. When this control approach is used, the load simulation performance tracks with the inflow simulation fidelity, with LES+ML yielding errors ≤ 4% for the damage-equivalent loads of flapwise bending moment, and tower fore-aft bending moments.

17 WIND ENERGY↗
DOE OSTI2024

Control of Floating Offshore Wind Energy Systems: An Introduction to the Special Issue

As the global demand for renewable energy sources intensifies amid the urgent fight against climate change [1] , offshore wind energy has emerged as a promising and crucial component of the sustainable energy portfolio. Fixed-bottom offshore wind farms have already demonstrated their potential; however, they are limited to relatively shallow waters, typically no deeper than 60 m.

climate change↗
DOE OSTI2020

An investigation into the potential for wind turbines to cause barotrauma in bats

The high rates of bat mortality caused by operating wind turbines is a concern for wind energy and wildlife stakeholders. One theory that explains the mortality is that bats are not only killed by impact trauma, but also by barotrauma that results from exposure to the pressure variations caused by rotating turbine blades. To date, no published research has calculated the pressure changes that bats may be exposed to when flying near wind turbines and then used these data to estimate the likelihood that turbines cause barotrauma in bats. To address this shortcoming, we performed computational fluid dynamics simulations of a wind turbine and analytical calculations of blade-tip vortices to estimate the characteristics of the sudden pressure changes bats may experience when flying near a utility-scale wind turbine. Because there are no data available that characterize the pressure changes that cause barotrauma in bats, we compared our results to changes in pressure levels that cause barotrauma and mortality in other mammals of similar size. This comparison shows that the magnitude of the low-pressures bats experience when flying near wind turbines is approximately 8 times smaller than the pressure that causes mortality in rats, the smallest mammal for which data are available. The magnitude of the high-pressures that bats may experience are approximately 80 times smaller than the exposure level that causes 50% mortality in mice, which have a body mass similar to several bat species that are killed by wind turbines. Further, our results show that for a bat to experience the largest possible magnitude of low- and high-pressures, they must take very specific and improbable flight paths that skim the surface of the blades. Even a small change in the flight path results in the bat being hit by the blade or experiencing a much smaller pressure change. Accordingly, if bats have a physiological response to rapid low- and high-pressure exposure that is similar to other mammals, we conclude that it is unlikely that barotrauma is responsible for a significant number of turbine-related bat fatalities, and that impact trauma is the likely cause of the majority of wind-turbine-related bat fatalities.

17 WIND ENERGY↗
DOE OSTI2022

FY2021 Isolated Grids and Grid-Connected Turbine Reference Systems

For individuals, businesses, and communities focused on building resilient electrical grid infrastructure, wind energy can provide an affordable, accessible, and compatible distributed energy resource option that also enhances the capabilities of local grid operations. However, there are technical barriers to realizing the market value and resilience benefits of distributed wind, and there is little to no ability to quantify those benefits so that stakeholders can compare grid investment options. The central aims of this report are: (1) to drive technology transfer of the methods and technologies developed under the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project and (2) increase the number of referenceable case studies available to stakeholders interested in additional value-added capabilities of wind systems beyond bulk energy supply. We achieve this aim by applying three major methods developed under MIRACL to two real-world distributed wind reference systems. The two real-world distributed wind reference systems are the isolated grid of St. Mary’s, Alaska, and the two 10.5-megawatt (MW) front-of-the-meter wind turbine deployments owned and operated by Iowa Lakes Electric Cooperative (ILEC).

17 WIND ENERGY↗
DOE OSTI2024

Performance Testing of Moving Bed Gasifier Using Biomass and Waste Fuels to Generate Low-Cost Clean Hydrogen

Our need for hydrogen is growing as the world transitions toward a low-carbon future. Hydrogen provides long-term energy storage for grid stability in a solar- and wind-dominated power market and can be used to decarbonize other sectors. One promising process for generating low-cost hydrogen that produces net-negative carbon is to gasify biomass with a mixture of legacy coal wastes, waste plastics, and other wastes with carbon capture. Use of waste fuels lowers costs and diverts waste from landfills. EPRI is leading a project, funded by the U.S. Department of Energy, to conduct performance testing of modular, moving-bed gasification for the generation of low-cost, clean hydrogen from biomass mixed with legacy coal waste, waste plastic, and/or refuse derived fuels. The work scope includes preparation of multiple pellet feedstocks using biomass (both woody biomass and corn stover) with a mixture of legacy coal waste, plastic waste (wire insulation), and refuse-derived fuel (RDF). These pelletized feedstocks are being qualified based on performance testing of selected fuel blend compositions in updraft moving-bed gasifier located in Sardinia, Italy. Testing is being conducted to obtain relevant data to advance the modular design of the moving-bed gasification process, and successfully use these feedstocks to produce a high hydrogen content raw syngas that can be shifted to produce clean hydrogen. Testing results will be used to determine the effects of the various fuels on feedstock development, the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics), and impacts on gasifier operations.

08 HYDROGEN↗
DOE OSTI2023

The Wind Data Hub, also known as The Data Archive and Portal.

The Wind Data Hub, or WDH (formerly known as the Data Archive and Portal), is established by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy’s Wind Energy Technologies Office (WETO). The WDH provides secure, timely, easy, and open access to all laboratory, field, and benchmark model data produced by land-based and offshore projects funded by WETO.

17 WIND ENERGY↗
DOE OSTI2024

Airport and Heliport Setbacks

This dataset represents a first-order quantification of airport and heliport setback requirements based on the Federal Aviation Administration (FAA) 14 CFR Part 77.9. It defines the following FAA notice criteria that we use to create runway buffers. Runways longer than 3,200 feet receive a 20,000 foot buffer, runways less than 3,200 feet long receive a buffer of 10,000 feet, and heliports receive a buffer of 5,000 feet. A setback requirement is a minimum distance from an airport or heliport that an energy project may be developed. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

airport↗
DOE OSTI2024

Wind Turbine Oil and Gas Pipeline Setbacks: Ordinances (2022) and Extrapolated Trends, 115 Hub Height 170 Rotor Diameter

This dataset represents wind energy setback requirements from oil and gas pipelines. A setback requirement is a minimum distance from a pipeline that an energy project may be developed. As of April 2022, no ordinances were discovered for any counties. Such ordinances are likely to arise as regulations continue to expand. Therefore, this dataset applies a median setback equivalent to 1.1 times the turbine tip-height, sourced from trends in other infrastructure. A TIF data file and a PNG map of the data are provided, showing areas where wind energy is prohibited or permitted across the contiguous United States. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

Array↗
DOE OSTI2021

An RTDS-Based Testbed for Investigating the Impacts of Transmission-Level Disturbances on Solar PV Operation

The increasing penetration of renewable energy resources such as solar and wind via power electronic inverters is challenging grid dynamics, as well as grid planning, operation, and protection. Recently, the North American Electric Reliability Corporation (NERC) has reported a series of similar events of the unintended loss of solar generation in Southern California over a large geographic area following the transmission-level disturbances. These events highlight the importance of understanding the characteristics of the transmission-side disturbances propagating into the distribution systems and their impacts on the operation of inverter-based resources. In this paper, a real-time electromagnetic simulation testbed is constructed for real-time electromagnetic simulations to generate realistic transmission-level disturbances and investigate their impacts on the solar PV operation under different fault types and locations, solar penetration levels, and loading levels. Through the simulation analysis and grid strength assessment, it is found that the grid strength at points of integration (POIs) of solar PVs significantly affects the transient stability of solar generators. Particularly, undesirable transient stability events are more likely to occur at the weak POIs following the transmission-level disturbances. Moreover, undesirable transient stability events become severer when the transmission-level disturbance is closer to the weak POIs or the disturbances become more serious. Additionally, the impact of the transmission-level disturbances on the solar PVs at the weak POIs exacerbate with the increasing solar penetration levels and loading levels. Thus, it is important to study and develop new technologies for grid planning, operation, and protection in weak grid conditions to address the emerging issues of integrating the high penetration of solar PVs and other IBRs.

14 SOLAR ENERGY↗
DOE OSTI2021

A VLA Survey of Late-time Radio Emission from Superluminous Supernovae and the Host Galaxies

We present the results of 3 GHz radio continuum observations of 23 superluminous supernovae (SLSNe) and their host galaxies by using the Karl G. Jansky Very Large Array conducted 5–21 yr after the explosions. The sample consists of 15 Type I and 8 Type II SLSNe at z < 0.3, providing one of the largest samples of SLSNe with late-time radio data. We detected radio emission from one SLSN (PTF10hgi) and five hosts with a significance of >5σ. No time variability is found in late-time radio light curves of the radio-detected sources in a timescale of years except for PTF10hgi, whose variability is reported in a separate study. Comparison of star formation rates (SFRs) derived from the 3 GHz flux densities with those derived from SED modeling based on UV–NIR data shows that four hosts have an excess of radio SFRs, suggesting obscured star formation. Upper limits for undetected hosts and stacked results show that the majority of the SLSN hosts do not have a significant obscured star formation. By using the 3 GHz upper limits, we constrain the parameters for afterglows arising from interaction between initially off-axis jets and circumstellar medium (CSM). Here, we found that the models with higher energies ( E iso ≳ several × 10 53 erg) and CSM densities ( n ≳ 0.01 cm –3 ) are excluded, but lower energies or CSM densities are not excluded with the current data. We also constrained the models of pulsar wind nebulae powered by a newly born magnetar for a subsample of SLSNe with model predictions in the literature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Biases in preconstruction estimates of wind plant annual energy production

Estimating the energy yield of a wind plant during the preconstruction phase is a historically difficult task, even with industry improvements in these estimations. We build on prior research comparing the realized energy production of wind plants and their estimated annual energy production P50 values (median energy production), using owner-provided energy production and losses. We produced similar results to prior studies but with a slightly increasing bias of overestimating median energy production (a bias between realized and estimated energy production of −7.4 % to −6.6 %, depending on the scenario, as opposed to −6.7 % to −5.5 % from earlier studies). In addition to assessing annual energy production P50 bias, we compared both the 1-year and the long-term annual energy production P90 and uncertainty energy yield assessment estimates to the observed long-term-corrected energy production. We found that neither the energy yield assessment uncertainty nor the P90 is conservative enough compared to the observed distribution of prediction errors, suggesting significant room for improvement in the energy yield assessment process.

17 WIND ENERGY↗
DOE OSTI2023

Grand challenges in the digitalisation of wind energy

The availability of large amounts of data is starting to impact how the wind energy community works. From turbine design to plant layout, construction, commissioning, and maintenance and operations, new processes and business models are springing up. This is the process of digitalisation, and it promises improved efficiency and greater insight, ultimately leading to increased energy capture and significant savings for wind plant operators, thus reducing the levelised cost of energy. Digitalisation is also impacting research, where it is both easing and speeding up collaboration, as well as making research results more accessible. This is the basis for innovations that can be taken up by end users. But digitalisation faces barriers. This paper uses a literature survey and the results from an expert elicitation to identify three common industry-wide barriers to the digitalisation of wind energy. Comparison with other networked industries and past and ongoing initiatives to foster digitalisation show that these barriers can only be overcome by wide-reaching strategic efforts, and so we see these as “grand challenges” in the digitalisation of wind energy. They are, first, creating FAIR data frameworks; secondly, connecting people and data to foster innovation; and finally, enabling collaboration and competition between organisations. The grand challenges in the digitalisation of wind energy thus include a mix of technical, cultural, and business aspects that will need collaboration between businesses, academia, and government to solve. Working to mitigate them is the beginning of a dynamic process that will position wind energy as an essential part of a global clean energy future.

17 WIND ENERGY↗
DOE OSTI2023

Reducing Uncertainty in Offshore Wind Energy Yield Estimates via a Metocean Reference Site

The offshore wind industry is burgeoning in the coastal waters of the United States, specifically along the Atlantic. For wind energy to be successful, reliable observations and model simulations are needed for resource assessment and forecasting. While many of these activities have already begun, there is currently an absence of observations at hub-height in these waters, with the closest available hub-height measurements usually taken onshore. Deployment of floating lidars has occurred through various federally funded projects, but only encapsulates time periods of a couple of years at best. Private industry is also beginning to leverage floating lidars, but this data is often proprietary, and not shared with the general public. In this work, we make the case for a metocean reference site for long-term offshore wind energy. Specifically, we quantify the impact of having a metocean reference site compared to other methods of determining hub-height winds and energy production. We use an offshore floating lidar to directly measure the wind resource, and compare these measurements to predictions derived from other widely-available surface meteorological variables. These prediction methods (vertical extrapolation, machine learning, and NWP output) produce a variety of vertical wind speed profiles, of which produce different energy yield estimates for a reference offshore turbine (Figure 1). While some methods perform reasonably well against the lidar, the uncertainty in these energy yield estimates has financial implications, further illustrating the need for long-term measurements in coastal waters.

machine learning↗