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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Integration of Storage in the DC Link of a Full Converter-Based Distributed Wind Turbine

Energy storage is known to support the dispatchability of variable renewable resources. In this paper, we model a battery energy storage system (BESS) integrated with the DC link of a Type IV full converter-based wind turbine and the necessary controls to achieve efficient dispatch. To support the validation of control methodologies, we build a detailed model of a Type IV research wind turbine at the National Renewable Energy Laboratory (NREL), the Controls Advanced Research Turbine (CART 3), and we integrated a lithium-ion BESS model in grid-following mode into the model. The simulation results illustrate the sizing and control of the DC link-integrated BESS for a given variable wind resource and varying dispatch strategies (i.e., under constant, uncertain, and ramping wind scenarios). The integrated storage can smooth variabilities in distributed wind output, hedge against uncertainties, provide the ramping capability, as well as support stability under voltage and frequency transients. All of these have been illustrated in MATLAB/Simulink.

DC-link voltage↗
NASA NTRS1991

Integration of the TDWR and LLWAS wind shear detection system

Operational demonstrations of a prototype TDWR/LLWAS (Terminal Doppler Weather Radar/Low Level Wind shear Alarm System) integrated wind shear detection system were conducted. The integration of wind shear detection systems is needed to provide end-users with a single, consensus source of information. A properly implemented integrated system provides wind shear warnings of a higher quality than stand-alone LLWAS or TDWR systems. The algorithmic concept used to generate the TDWR/LLWAS integrated products and several case studies are discussed, indicating the viability and potential of integrated wind shear detection systems. Implications for integrating ground and airborne wind shear detection systems are briefly examined.

Cornman, Larry↗
DOE OSTI2020

The Potential Impact of Offshore Wind Energy on a Future Power System in the U.S. Northeast

This study aims to understand and quantify the potential impact of offshore wind on a future electricity system in the U.S. Northeast. In this analysis, a detailed representation of the Northeast power system is adopted, using a generation portfolio for 2024 paired with offshore wind nameplate capacities of 0 gigawatts (GW), 2 GW, and 7 GW. The analysis identifies points of offshore wind interconnection in the ISO-New England and New York Independent System Operator control areas and uses hourly wind profiles from the Wind Integration National Dataset Toolkit. Hourly simulations of the 2024 power system operations show an ability to accommodate the prescribed offshore wind capacities by adapting the system's generation dispatch. Curtailment levels of offshore wind range between 4% and 5%. Offshore wind generation displaces primarily natural-gas combined-cycle generation; however, requires increased flexibility from combined cycles through more frequent start-ups. The number of hours with transmission congestion increases because of offshore wind injection, with varying impact on a subregional level. Offshore wind's capacity credit was found to be 14.5%-28.3% and is lower than estimated in other large-scale power system studies, in part because this study considered a different weather year and a power system representation with higher shares of solar PV and onshore wind. The reliability contribution of resources is a topic area identified for more research and collaboration. The 7-GW scenario shows a reduction in locational marginal price of 11%, with production cost savings of up to 18% compared to the 0-GW scenario.

17 WIND ENERGY↗
DOE OSTI2025

Using multiple high-resolution datasets to benchmark the energy exascale earth system model (E3SM) for renewable resource assessment

The United States is accelerating its shift toward a renewable energy system. However, renewable resources, which harness energy from the Earth system, are susceptible to both present-day climate variability and future climate change. For example, variations in regional climate can alter renewable energy production patterns and site viability. The use of high-resolution climate model projections can therefore facilitate and may be critical to long-term planning of renewable energy investments. However, climate models must first be validated for renewable resource assessment. This research employs multiple high-spatiotemporal-resolution datasets to assess the capability of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 North American Regionally Refined Model (E3SMv2-NARRM) for predicting multi-year climatological values of solar and wind energy capacity factors in the continental U.S., with a focus on regional and seasonal variability. Present-day E3SMv2-NARRM simulations are compared with reported utility-scale production data obtained from the Energy Information Administration (EIA). In addition, E3SMv2-NARRM data are evaluated against non-climate benchmark models from the National Renewable Energy Laboratory, including the Wind Integration National Dataset Toolkit and the National Solar Radiation Database (NSRDB), as well as three wind energy datasets from PLUSWIND. Our analysis indicates that solar capacity factors from E3SM closely match those from the NSRDB dataset. However, both datasets tend to overestimate values by 10% in comparison to EIA data. Furthermore, biases in wind capacity factors within E3SM are notably pronounced in the West Coast regions, where the seasonal cycle diverges from EIA data.

Energy forecasting, Capacity factor, Renewable ene↗
DOE OSTI2022

System Modeling Frameworks for Wind Turbines and Plants: Review and Requirements Specifications

System modeling frameworks for wind turbines and plants are used by research groups and industry to design wind energy systems that take into account key trade-offs across performance, cost, and reliability at both the turbine and plant level. The frameworks are exercised using a variety of multi-disciplinary design, analysis and optimization (MDAO) methods. To improve inter-operability and foster collaboration, this report proposes a classification system for the frameworks along dimensions of model fidelity and scope. The classification system is first motivated with reviews the state-of-the-art in the development of software frameworks for integrated wind turbine and plant simulation. Within each major wind turbine and power plant subsystem, a matrix is developed for the disciplines used and the fidelity levels with which each discipline can be modeled. The existing frameworks are then classified according to the matrix. Next, an ontology is proposed that will allow for standardizing how data is transferred between the most common discipline-fidelity combinations used in the frameworks. A common representation of data creates the ability to 1) share system descriptions and analysis results, supporting more transparent benchmarks and comparison, and 2) integrate models together into workflows within and across organizations for improving the efficiency and performance of wind turbine and power plant design processes. Ultimately, this integration leads to better overall wind energy system designs with high performance and low costs.

17 WIND ENERGY↗
NASA NTRS1992

Air/ground wind shear information integration: Flight test results

An element of the NASA/FAA wind shear program is the integration of ground-based microburst information on the flight deck, to support airborne wind shear alerting and microburst avoidance. NASA conducted a wind shear flight test program in the summer of 1991 during which airborne processing of Terminal Doppler Weather Radar (TDWR) data was used to derive microburst alerts. High level microburst products were extracted from TDWR, transmitted to a NASA Boeing 737 in flight via data link, and processed to estimate the wind shear hazard level (F-factor) that would be experienced by the aircraft in the core of each microburst. The microburst location and F-factor were used to derive a situation display and alerts. The situation display was successfully used to maneuver the aircraft for microburst penetrations, during which in situ 'truth' measurements were made. A total of 19 penetrations were made of TDWR-reported microburst locations, resulting in 18 airborne microburst alerts from the TDWR data and two microburst alerts from the airborne in situ measurements. The primary factors affecting alerting performance were spatial offset of the flight path from the region of strongest shear, differences in TDWR measurement altitude and airplane penetration altitude, and variations in microburst outflow profiles. Predicted and measured F-factors agreed well in penetrations near microburst cores. Although improvements in airborne and ground processing of the TDWR measurement would be required to support an airborne executive-level alerting protocol, the feasibility of airborne utilization of TDWR data link data has been demonstrated.

Hinton, David A.↗
DOE OSTI2025

Deep Reinforcement Learning Based Control of Wind Turbines for Fast Frequency Response

In order to fulfill vital auxiliary grid services, such as load regulation, spin and non-spin reserve provision, and frequency support during emergencies, there is often a requirement for certain wind farms to operate in de-loaded modes. Leveraging the swift response capabilities of wind farms, this study demonstrates that reserving power in de-loaded modes can significantly enhance power grid stability and reliability during system contingencies. Controlling wind farms optimally for frequency support is intricate due to the nonlinearity of models and controllers and the complexity of wind farm interactions with power systems. Here, to address this challenge, this paper introduces a novel approach that integrates wind turbines into reinforcement learning-based solutions for frequency response. This innovative methodology utilizes the state-of-the-art reinforcement learning algorithm known as the surrogate-gradient-based evolutionary strategy. The proposed learning-based algorithm provides continuous control of wind farm output to rapidly stabilize system frequency and prevent unnecessary trips of under-frequency load shedding relays. To facilitate efficient training, parallel computing techniques are employed. The proposed methodology is evaluated on a modified IEEE-39 bus system, and simulation results reveal its efficacy in reliably supporting power system frequency and preventing the need for unnecessary load shedding.

Gao, Wei [Argonne National Laboratory (ANL), Argon↗
NASA NTRS1973

Percy Thomas wind generator designs

The technical and economic feasibilities of constructing a windpowered generator with a capacity of 2,000 to 4,000 kilowatt are considered. Possible benefits of an integrated wind generating electric energy source in an electric utility network are elaborated. Applications of a windpowered waterpump, including its use as a pumping source for hydroelectric pump storage operations, are also mentioned. It is concluded that the greatest potential of the wind generator is to generate heat directly and not conversion to electricity and then to heat.

Lines, C. W.↗
DOE OSTI2021

Chapter 9: Impact of Variable Renewable Energy Sources on Bulk Power System Planning and Operations

Wind and solar photovoltaics (PV) have experienced remarkable growth in recent years, with many consequent benefits within and outside of power systems. At the same time, wind and solar PV have unique characteristics relative to the historically dominant dispatchable technologies like coal, gas, and nuclear power plants that have required and will continue to require changes in power system planning and operations. This chapter discusses planning and operational challenges of integrating wind and solar PV into bulk power systems. We first present the key characteristics of wind and solar PV that differentiate it from conventional technologies, such as variable and uncertain electricity generation, asynchronous interconnection to the power system, and near-zero marginal costs. We then link these characteristics to power system planning and operational challenges at low through high wind and solar penetrations. Finally, we discuss near- and long-term solutions to those challenges, such as diversifying the generation mix and wind and solar fleets, improving system flexibility, diversifying ancillary service products, and integrating generation and transmission planning.

bulk power system↗
NASA NTRS1991

Absolute wind velocities in the lower thermosphere of Venus using infrared heterodyne spectroscopy

NASA's IR Telescope Facility and the McMath Solar Telescope have yielded absolute wind velocities in the Venus thermosphere for December 1985 to March 1987 with sufficient spatial resolution for circulation model discrimination. A qualitative analysis of beam-integrated winds indicates subsolar-to-antisolar circulation in the lower thermosphere; horizontal wind velocity was derived from a two-parameter model wind field of subsolar-antisolar and zonal components. A unique model fit common to all observing periods possessed 120 m/sec subsolar-antisolar and 25 m/sec zonal retrograde components, consistent with the Bougher et al. (1986, 1988) hydrodynamical models for 110 km.

Goldstein, Jeffrey J.↗
DOE OSTI2020

US East Coast synthetic aperture radar wind atlas for offshore wind energy

We present the first synthetic aperture radar (SAR) offshore wind atlas of the US East Coast from Georgia to the Canadian border. Images from RADARSAT-1, Envisat, and Sentinel-1A/B are processed to wind maps using the geophysical model function (GMF) CMOD5.N. Extensive comparisons with 6008 collocated buoy observations of the wind speed reveal that biases of the individual systems range from -0.8 to 0.6 m s -1 . Unbiased wind retrievals are crucial for producing an accurate wind atlas, and intercalibration of the SAR observations is therefore applied. Wind retrievals from the intercalibrated SAR observations show biases in the range of to -0.2 to 0.0 m s -1 , while at the same time improving the root-mean-squared error from 1.67 to 1.46 m s -1 . The intercalibrated SAR observations are, for the first time, aggregated to create a wind atlas at the height 10 m a.s.l. (above sea level). The SAR wind atlas is used as a reference to study wind resources derived from the Wind Integration National Dataset Toolkit (WTK), which is based on 7 years of modelling output from the Weather Research and Forecasting (WRF) model. Comparisons focus on the spatial variation in wind resources and show that model outputs lead to lower coastal wind speed gradients than those derived from SAR. Areas designated for offshore wind development by the Bureau of Ocean Energy Management are investigated in more detail; the wind resources in terms of the mean wind speed show spatial variations within each designated area between 0.3 and 0.5 m s -1 for SAR and less than 0.2m s -1 for the WTK. Our findings indicate that wind speed gradients and variations might be underestimated in mesoscale model outputs along the US East Coast.

17 WIND ENERGY↗
NASA NTRS2000

Wind Tunnel Management and Resource Optimization: A Systems Modeling Approach

Time, money, and, personnel are becoming increasingly scarce resources within government agencies due to a reduction in funding and the desire to demonstrate responsible economic efficiency. The ability of an organization to plan and schedule resources effectively can provide the necessary leverage to improve productivity, provide continuous support to all projects, and insure flexibility in a rapidly changing environment. Without adequate internal controls the organization is forced to rely on external support, waste precious resources, and risk an inefficient response to change. Management systems must be developed and applied that strive to maximize the utility of existing resources in order to achieve the goal of "faster, cheaper, better". An area of concern within NASA Langley Research Center was the scheduling, planning, and resource management of the Wind Tunnel Enterprise operations. Nine wind tunnels make up the Enterprise. Prior to this research, these wind tunnel groups did not employ a rigorous or standardized management planning system. In addition, each wind tunnel unit operated from a position of autonomy, with little coordination of clients, resources, or project control. For operating and planning purposes, each wind tunnel operating unit must balance inputs from a variety of sources. Although each unit is managed by individual Facility Operations groups, other stakeholders influence wind tunnel operations. These groups include, for example, the various researchers and clients who use the facility, the Facility System Engineering Division (FSED) tasked with wind tunnel repair and upgrade, the Langley Research Center (LaRC) Fabrication (FAB) group which fabricates repair parts and provides test model upkeep, the NASA and LARC Strategic Plans, and unscheduled use of the facilities by important clients. Expanding these influences horizontally through nine wind tunnel operations and vertically along the NASA management structure greatly increases the complexity of developing a model that can be used for successfully implementing a standardized management planning tool. The objective of this study was to implement an Integrated Wind Tunnel Planning System to improve the operations within the aeronautics testing and research group, in particular Wind Tunnel Enterprise. The study included following steps: Conducted literature search and expert discussions (NASA and Old Dominion University faculty), Performed environmental scan of NASA Langley wind tunnel operations as foundation for problem definition. Established operation requirements and evaluation methodologies. Examined windtunnel operations to map out the common characteristics, critical components, and system structure. Reviewed and evaluated various project scheduling and management systems for implementation, Evaluated and implemented "Theory of Constraints (TOC)" project scheduling methodology at NASA Langley wind tunnel operations together with NASA staff.

Jacobs, Derya, A.↗
DOE OSTI2025

Control Oriented Models for Co-Design: Technical Overview of MT HVDC, MVDC, and Solid State Transformer Building Blocks

The electric power system is shifting toward a power electronics–enabled grid, where converter based “building blocks” (e.g., high voltage direct current (HVDC) links, multi terminal HVDC (MT HVDC) networks, medium voltage DC (MVDC) links, and solid state transformers (SSTs)) provide fast, precise control of power flows, voltage, and frequency. This report develops and applies publicly shareable electromagnetic transient (EMT) and phasor models to examine how such building blocks can be composed and coordinated to support offshore wind integration, inter area transfers, feeder support, and resilience. Section 2 documents a modular multilevel converter (MMC)–based MT HVDC modeling framework and two use cases: a compact WSCC/IEEE 9 bus test system and a 240 bus “mini WECC” case with five offshore wind plants (OWFs). Phasor to EMT transfer, initialization, and sanity checks are summarized, and neutral demonstrations of normal and contingency operation are reported. Section 3 frames the problem of wind plant inertial frequency response (IFR): shaping energy release and recovery to improve nadir while avoiding aerodynamic stall; representative simulations illustrate the issues without disclosing proprietary control. Section 4 develops MVDC concepts through an IEEE 16 bus loop and an Olympic Peninsula case study that compares AC vs. MVDC corridors and shows how feeder headroom can be pooled via DC couplers. Section 5 surveys SST architectures and identifies a gap: scalable, communication free coordination of multiple SSTs for islanded feeder networks. Across the report, novel methods and configurations under separate publication and IP review are not disclosed; only topic oriented, replicable setups and non proprietary results are shown. These models and use cases are intended as foundations for future publications and co design studies on architecture, control, and coordination of PE enabled grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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↗
NASA NTRS2003

Neural Flight Control System

The Neural Flight Control System (NFCS) was developed to address the need for control systems that can be produced and tested at lower cost, easily adapted to prototype vehicles and for flight systems that can accommodate damaged control surfaces or changes to aircraft stability and control characteristics resulting from failures or accidents. NFCS utilizes on a neural network-based flight control algorithm which automatically compensates for a broad spectrum of unanticipated damage or failures of an aircraft in flight. Pilot stick and rudder pedal inputs are fed into a reference model which produces pitch, roll and yaw rate commands. The reference model frequencies and gains can be set to provide handling quality characteristics suitable for the aircraft of interest. The rate commands are used in conjunction with estimates of the aircraft s stability and control (S&C) derivatives by a simplified Dynamic Inverse controller to produce virtual elevator, aileron and rudder commands. These virtual surface deflection commands are optimally distributed across the aircraft s available control surfaces using linear programming theory. Sensor data is compared with the reference model rate commands to produce an error signal. A Proportional/Integral (PI) error controller "winds up" on the error signal and adds an augmented command to the reference model output with the effect of zeroing the error signal. In order to provide more consistent handling qualities for the pilot, neural networks learn the behavior of the error controller and add in the augmented command before the integrator winds up. In the case of damage sufficient to affect the handling qualities of the aircraft, an Adaptive Critic is utilized to reduce the reference model frequencies and gains to stay within a flyable envelope of the aircraft.

Gundy-Burlet, Karen↗
DOE OSTI2023

Neutrino-driven Winds in Three-dimensional Core-collapse Supernova Simulations

Abstract In this paper, we analyze the neutrino-driven winds that emerge in 12 unprecedentedly long-duration 3D core-collapse supernova simulations done using the code F ornax . The 12 models cover progenitors with zero-age main-sequence mass between 9 and 60 solar masses. In all our models, we see transonic outflows that are at least 2 times as fast as the surrounding ejecta and that originate generically from a proto−neutron star surface atmosphere that is turbulent and rotating. We find that winds are common features of 3D simulations, even if there is anisotropic early infall. We find that the basic dynamical properties of 3D winds behave qualitatively similarly to those inferred in the past using simpler 1D models, but that the shape of the emergent wind can be deformed, very aspherical, and channeled by its environment. The thermal properties of winds for less massive progenitors very approximately recapitulate the 1D stationary solutions, while for more massive progenitors they deviate significantly owing to aspherical accretion. The Y e temporal evolution in winds is stochastic, and there can be some neutron-rich phases. Though no strong r -process is seen in any model, a weak r -process can be produced, and isotopes up to 90 Zr are synthesized in some models. Finally, we find that there is at most a few percent of a solar mass in the integrated wind component, while the energy carried by the wind itself can be as much as 10%–20% of the total explosion energy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Super-Resolution for Renewable Energy Resource Data with Wind from Reanalysis Data and Application to Ukraine

With a potentially increasing share of the electricity grid relying on wind to provide generating capacity and energy, there is an expanding global need for historically accurate, spatiotemporally continuous, high-resolution wind data. Conventional downscaling methods for generating these data based on numerical weather prediction have a high computational burden and require extensive tuning for historical accuracy. In this work, we present a novel deep learning-based spatiotemporal downscaling method using generative adversarial networks (GANs) for generating historically accurate high-resolution wind resource data from the European Centre for Medium-Range Weather Forecasting Reanalysis version 5 data (ERA5). In contrast to previous approaches, which used coarsened high-resolution data as low-resolution training data, we use true low-resolution simulation outputs. We show that by training a GAN model with ERA5 as the low-resolution input and Wind Integration National Dataset Toolkit (WTK) data as the high-resolution target, we achieved results comparable in historical accuracy and spatiotemporal variability to conventional dynamical downscaling. This GAN-based downscaling method additionally reduces computational costs over dynamical downscaling by two orders of magnitude. We applied this approach to downscale 30 km, hourly ERA5 data to 2 km, 5 min wind data for January 2000 through December 2023 at multiple hub heights over Ukraine, Moldova, and part of Romania. With WTK coverage limited to North America from 2007–2013, this is a significant spatiotemporal generalization. The geographic extent centered on Ukraine was motivated by stakeholders and energy-planning needs to rebuild the Ukrainian power grid in a decentralized manner. This 24-year data record is the first member of the super-resolution for renewable energy resource data with wind from the reanalysis data dataset (Sup3rWind).

17 WIND ENERGY↗
DOE OSTI2023

Optimal Dispatch for the US Virgin Islands to Increase Renewable Rates in Saint Croix

The US Virgin Islands, like many other small island nations, face significant challenges related to its energy supply. Their dependency on imported fossil fuels not only drives up energy costs, but also contributes to different environmental problems. Nevertheless, their generally sunny and windy climate makes this archipelago an ideal location for renewable energy development. Increasing the use of sources such as wind, and solar can help reduce their energy dependency, lower their levelized cost of electricity, and improve the health and wellbeing of local communities. In this paper, an optimal dispatcher is employed to analyze the implications on energy security of employing different technology options according to the plans of the local system operator. In this context, short term stability is ensured by inserting operational constraints in the energy management system based on stability analysis developed in PSCAD. The results highlight the usefulness of integrating PV and battery system, while further analysis are required to justify integrating wind power.

energy islands↗