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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Manufacturing Process Innovation Awardee: Bergey Windpower Co.

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Bergey Windpower Co. for manufacturing process innovation. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗
DOE OSTI2025

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Component Innovation Awardee: Windurance LLC

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Windurance LLC for component innovation. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗
DOE OSTI2025

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Small Turbine Certification and/or Listing Awardee: NPS Solutions LLC

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by NPS Solutions LLC for Small Turbine Certification and/or Listing. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗
DOE OSTI2025

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Small Turbine Certification and Listing Awardee: Uprise Energy

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Uprise Energy for small turbine certification and listing. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗
DOE OSTI2025

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Technology Commercialization Awardee: EWT Americas Inc.

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by EWT Americas, Inc., for technology commercialization. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗
NASA NTRS1984

Comparison of theoretical and flight-measured local flow aerodynamics for a low-aspect-ratio fin

Flight test and theoretical aerodynamic data were obtained for a flight test fixture mounted on the underside of an F-104G aircraft. The theoretical data were generated using two codes, a two dimensional transonic code called Code H, and a three dimensional subsonic and supersonic code call wing-body. Pressure distributions generated by the codes for the flight test fixture as well as boundary layer displacement thickness generated by the two dimensional code were compared to the flight test data. The two dimensional code pressure distributions compared well except at the minimum pressure point and trailing edge. Shock locations compared well except at high transonic speeds. The three dimensional code pressure distributions compared well except at the trailing edge of the flight test fixture. The two dimensional code does not predict displacement thickness of the flight test fixture well.

Johnson, J. B.↗
NASA NTRS1975

A distributed computing approach to mission operations support

Computing mission operation support includes orbit determination, attitude processing, maneuver computation, resource scheduling, etc. The large-scale third-generation distributed computer network discussed is capable of fulfilling these dynamic requirements. It is shown that distribution of resources and control leads to increased reliability, and exhibits potential for incremental growth. Through functional specialization, a distributed system may be tuned to very specific operational requirements. Fundamental to the approach is the notion of process-to-process communication, which is effected through a high-bandwidth communications network. Both resource-sharing and load-sharing may be realized in the system.

Larsen, R. L.↗
NASA NTRS1987

Proton beam generation of whistler waves in the earth's foreshock

It is shown that proton beams, often observed upstream of the earth's bow shock and associated with the generation of low-frequency hydromagnetic fluctuations, are also capable of generating whistler waves. The waves can be excited by an instability driven by two-temperature streaming Maxwellian proton distributions which have T (perpendicular)/T(parallel) much greater than 1. It can also be excited by gyrating proton beam distributions. These distributions generate whistler waves with frequencies ranging from 10 to 100 times the proton cyclotron frequency (in the solar wind reference frame) and provide another mechanism for generating the '1-Hz' waves often seen in the earth's foreshock.

Wong, H. K.↗
NASA NTRS2016

Investigating Global Ion and Neutral Atom Populations with IBEX and Voyager

The main objective of this project was to investigate pickup ion (PUI) production in the solar wind and heliosheath (the region between the termination shock and the heliopause) and compute the distributed energetic neutral atom fluxes throughout the helioshpere. The simulations were constrained by comparing the model output against observations from Ulysses, New Horizons, Voyager 1 and 2, and IBEX space probes. As evidenced by the number of peer reviewed journal publications resulting from the project (13 plus three submitted) and their citation rate (156 citations over three years), the project has made a lasting contribution to the field. The outcome is a significant improvement of our understanding of the pickup ion production and distribution in the distant heliosphere. The team has accomplished the entire set of tasks A-H set forth in the proposal. Namely, the transport modeling framework has been augmented with two populations of pickup ions (PUIs), the boundary conditions for the plasma and interstellar neutral hydrogen were verified against Ulysses and New Horizons PUI and an optimal set of velocity diffusion parameters established. The multi-component fluxes of PUIs were computed and isotropic velocity distributions generated for each cell in the computer simulation that covered the heliosphere from 1.5 AU to the heliopause. The distributions were carefully compared with in situ measurements at 3 AU (Ulysses), 12 AU (New Horizons), and 80-90 AU (Voyager 1 and 2) as well as those inferred from ENA fluxes measured by Cassini and IBEX (Wu et al., 2016). Some examples of modeldata comparison are shown in Figure 1. We have used coupled MHD-plasma and kinetic-neutral code to investigate the likely range of plasma and magnetic field parameters in the local interstellar medium (LISM), based on the assumption that the shape of the IBEX ribbon could be used to determine the orientation of the interstellar magnetic field. While the magnetic field is believed to be oriented toward the center of the ribbon, constraining its strength requires comparing the model-predicted angular diameter and circularity of the ribbon with the observations. The study, published in Heerikhuisen et al. (2014), found that the most likely range for the LISM magnetic field strength is between 0.2 and 0.3 nT, which is less than previously thought. Figure 2 shows the IBEX data (left) and compares it to the simulation with a 0.2 nT interstellar magnetic field (center) and a 0.4 nT (right).

Florinski, Vladimir↗
DOE OSTI2020

Production of b b ¯ at forward rapidity in p + p collisions at s = 510 GeV

The cross section of bottom quark-antiquark ( b b ¯ ) production in p + p collisions at s = 510 GeV is measured with the PHENIX detector at the Relativistic Heavy Ion Collider. The results are based on the yield of high mass, like-sign muon pairs measured within the PHENIX muon arm acceptance ( 1.2 < | y | < 2.2 ). The b b ¯ signal is extracted from like-sign dimuons by utilizing the unique properties of neutral B meson oscillation. We report a differential cross section of d σ b b ¯ → μ ± μ ± / d y = 0.16 ± 0.01 ( stat ) ± 0.02 ( syst ) ± 0.02 ( global ) nb for like-sign muons in the rapidity and p T ranges 1.2 < | y | < 2.2 and p T > 1 GeV / c , and dimuon mass of 5 – 10 GeV / c 2 . The extrapolated total cross section at this energy for b b ¯ production is 13.1 ± 0.6 ( stat ) ± 1.5 ( syst ) ± 2.7 ( global ) μ b . The total cross section is compared to a perturbative quantum chromodynamics calculation and is consistent within uncertainties. The azimuthal opening angle between muon pairs from b b ¯ decays and their p T distributions are compared to distributions generated using ps pythia 6, which includes next-to-leading order processes. The azimuthal correlations and pair p T distribution are not very well described by pythia calculations, but are still consistent within uncertainties. Flavor creation and flavor excitation subprocesses are favored over gluon splitting.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2023

State-Level Trends in Renewable Energy Procurement via Solar Installation versus Green Electricity

In recent years, options for procuring renewable energy have increased, ranging from rooftop solar installation to utility green pricing to Community Choice Aggregation. These options vary in terms of costs and benefits to the consumer as well as grid integration implications. However, little is known regarding how the presence of a wide range of voluntary utility-scale renewable procurement options as well as their growth could affect adoption of distributed residential solar. To examine this relationship, we fit a two-stage least squares random effects regression model on panel data from 2016 to 2019 for all fifty US states plus the District of Columbia, controlling for variables that measure state-level policies, economic factors, and resource availability. Although there was no evidence of a strong relationship between demand for utility-scale and distributed options across all states, the state-level correlations suggest a wide variation between states including a positive, zero or negative relationship between utility-scale and distributed generation.

consumer demand↗
DOE OSTI2023

Robust Distribution State Estimation for Reliable Locational Marginal Pricing under Cyber-Attacks

Here this paper examines the impact of false data injection (FDI) cyber-attacks on distribution system state estimation (DSSE) and the resulting distribution locational marginal price (DLMP) in power markets. Two robust high-breakdown regression estimators, namely S- and MM- estimators, are implemented to provide resistance against FDI attacks targeting measurements and grid topology, creating leverage points. The introduced estimators are compared to the weighted least squares (WLS) with a bad data detection and rejection module (BDD) and the robust Huber M-estimator. The proposed estimators are shown to be effective and compare favorably to both existing Huber M- and the WLS with BDD in the presence of topology FDI attacks. Both the S- and MM-estimators provide good performance in the case of clean and corrupted measurements. Their performance is comparable in this case to the Huber M- and the WLS, followed by a BDD module. The simulation considered a modified distribution IEEE 13 and 34-bus systems where the impact of FDI attack scenarios is shown on the state and the DLMP pricing in the presence of distributed Generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1986

Comparison of theoretical and flight-measured local flow aerodynamics for a low-aspect-ratio fin

Flight test and theoretical aerodynamic data were obtained for a flight test fixture mounted on the underside of an F-104G aircraft. The theoretical data were generated using two codes: a two-dimensional transonic code called code H, and a three-dimensional subsonic and supersonic code called wing-body. Pressure distributions generated by the codes for the flight test fixture, as well as compared with the flight-measured data. The two-dimensional code pressure distributions compared well except at the minimum pressure point and the trailing edge. Shock locations compared well except at high transonic speeds. However, the two-dimensional code did not adequately predict the displacement thickness of the flight test fixture. The three-dimensional code pressure distributions compared well except at the trailing edge of the flight test fixture.

Johnson, J. Blair↗
DOE OSTI2022

Considerations for Developing a Regulatory Roadmap for Distributed Energy Resource (DER) Integration in Colombia

The USAID-NREL Partnership in Colombia, in conjunction with SURE and USEA, selected four action plan teams from the Young Professionals Leadership Program to receive tailored NREL technical assistance to support action plan implementation. The four plans selected represent various aspects associated with planning for the efficient integration of DERs, including electric mobility, residential and commercial energy applications, distributed generation modeling, and regulatory considerations. In response to national grid modernization, decentralization, digitalization, and electrification trends, CREG is looking to update Colombia's electric distribution code, with an emphasis on the integration of electric vehicles and charging stations, but also energy storage systems, non-conventional sources of renewable energy, and other distributed energy resources (DERs). CREG aims to establish the general steps that must be carried out to update the distribution code for the integration of DERs, with a view to the design and development of new markets. The objective of the TA provided to CREG was to support them in identifying and outlining the general processes and approaches to consider when updating Colombia's distribution code for the integration of electric vehicles, distributed renewable energy systems, and energy storage systems, with a view to the design and development of new markets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Disaggregating Future Retail Electricity Rate Growth [Slides]

Recent Berkeley Lab research found that modest retail rate increases over the past 10 years were mostly driven by large increases in capital expenditures (CapEx) that were offset in part by substantial wholesale price reductions. Decision-makers are increasingly concerned about the potential future rate impacts of a number of policies and industry trends that support rapid decarbonization, electrification, and grid modernization. Using historical FERC Form 1 data and the existing literature on policies and industry trends that are likely to affect utility-incurred costs and retail sales, Berkeley Lab researchers developed ranges of forecasted growth rates for cost-related rate drivers (i.e., fuel and purchased power; transmission, distribution, generation, and other categories of both non-fuel operations & maintenance and CapEx) and non-cost related rate drivers (i.e., retail sales, peak demand, and customers). These were then used as inputs to a pro-forma utility financial model (FINDER) that estimated the growth in retail electric rates between 2020 and 2030 for a prototypical vertically-integrated investor-owned utility in the United States. The analysis produced the following results: 1. Assuming average growth rates in all rate drivers, future retail rate growth is driven by sizable increases in all CapEx costs, where fuel and purchased power costs are replaced by generation CapEx as the largest rate component between 2020 and 2030. 2. Growth in sales/peak demand/customers, generation CapEx costs, and fuel and purchased power (FPP) costs, in isolation, produce the most uncertainty in rate growth. Specifically, a 1% increase in the compound annual growth rate (CAGR) of retail sales, coincident peak demand (CP), and customers (Sales-CP-Cust) results in a 0.88-0.93% decrease in the CAGR of rates, in isolation. However, a 1% increase in the CAGR of generation CapEx budgets results in a 0.07-0.14% increase in the CAGR of rates, while a 1% increase in the CAGR of FPP costs causes a 0.10-0.14% increase in the CAGR of rates, all else being equal. 3. Taking into account the correlation and variability of the growth in all rate drivers jointly, generation CapEx is expected to be both the largest and most uncertain rate component by 2030 (20-25% share of the retail rate). Transmission and distribution CapEx, along with fuel and purchased power costs are each expected to comprise between 12% and 17% of retail rates.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Layered Coordination Architecture for Resilient Restoration of Power Distribution Systems

The current practices for restoring critical services in the distribution system during a disaster, align with the traditional centralized ideology of distribution systems operations. A central processor evaluates the distribution system after a disruption and attains a restoration plan. However, the centralized operational paradigm is susceptible to single-point failures, requires full situational awareness of the distribution system, and poses scalability challenges for large multifeeder distribution systems. This motivates a distributed decision-making paradigm where multiple agents solve smaller subproblems and jointly coordinate their individual decisions to achieve the global/network-level objective. Toward this goal, we propose a layered architecture for distributed algorithms for resilience and a two-stage distributed algorithm for distribution system restoration. The proposed distributed decision-making framework enables the bottom-up restoration of the distribution system using all available resources, including distributed generation, while only requiring local awareness and limited communications with neighboring connected regions. The proposed framework is robust to single-point failures, enables autonomy using distributed algorithms, and had reduced computational cost compared to centralized optimization solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗