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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 325 records · Page 18

H2@Scale - Validating an Electrolysis System with High Output Pressure: Cooperative Research and Development Final Report, CRADA Number CRD-18-00741

Electrolysis has been a commercially available product for a while and electrolyzers have been a proven capability to provide additional benefits (e.g. controllable load for grid services) in addition to production of hydrogen. The hydrogen output is typically compressed for storage and dispensing. Compression adds cost and decreases system reliability. Honda’s electrolyzer systems have been developed to include electrochemical compression to leverage the production system itself for at least partial compression. In this project, the team will evaluate Honda’s PEM based electrochemical compression system. The system is capable of compressing hydrogen up to 70 MPa electrochemically. Validation testing is the next step to accelerate this technology into the marketplace, as the validation will provide needed data under a variety of operation conditions and controls. These operating conditions and controls are based on over a decade of NLR research and development with low-temperature electrolysis. The validation testing will include preparing NLR’s site for third party evaluation, benchmark testing of Honda’s stack and system, and simulating operation connected to renewables or in a grid service profile. NLR’s Energy System Integration Lab will be the location for the electrolyzer validation research and integrated into the Hydrogen Infrastructure Test & Research Facility (HITRF). This will build into the existing retail style hydrogen fueling station for a fully integrated experimental setup.

08 HYDROGEN↗

A Physical Model Enhanced Data Driven Method for High-Resolution Residential Load Profile Generation

Residential buildings account for significant energy consumption, creating opportunities to offer grid services. As electric utilities seek to implement effective system operation strategies, understanding residential energy consumption patterns becomes essential; However, the time intervals of load profiles measured by utilities' smart meters are typically from 15 minutes to 60 minutes. The low-resolution data make it hard to extract appliance-level load information, which is critical for providing grid services. This paper presents a load profile generator designed to produce synthetic load profiles for residential buildings that emphasizes the importance of accurate representations of realistic energy consumption patterns. The generator takes realistic low-resolution residential load measurements and weather data as inputs, producing 1-minute interval profiles that match the characteristics of the original profiles. Further, this generator can be used to populate load profiles in areas where actual measurements are limited to improve the ability of utilities to analyze their distribution systems. By providing more high-resolution residential building load profiles, this tool supports electric utilities to enhance their residential building load control strategies and improve overall grid stability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Design and engineering challenges of a multi-energy hard x-ray camera for long-pulse profile measurements at WEST tokamak

The WEST tokamak has recently been prepared for long pulse operation with a water-cooled full first wall. Heating is provided by radiofrequency systems, including Lower Hybrid Current Drive (LHCD). The Princeton Plasma Physics Laboratory has developed a multi-energy hard x-ray camera for profile measurements at WEST. The camera is based on a new generation of 2D pixel array detectors that allow the energy threshold to be independently set for each pixel. The diagnostic will provide spatial, temporal and energy resolved measurements of the hard x-ray emission from the full plasma cross-section, investigating several physical quantities such as the electron temperature from continuum emission, the fast electron tail density produced by radiofrequency current drive and runaway electrons, as well as characteristic tungsten x-rays due to beam-target emission at the edge. Overall, this work describes the engineering challenges that the WEST long pulse scenario poses for this diagnostic and how the design addresses and solves them. Vacuum, thermal stress and heat transfer calculations are presented and discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Roles of Hydrogen Bonds and Alignment in Oriented Attachment of Gibbsite Nanoparticles: Insights from Molecular Dynamics

Oriented attachment (OA) of nanoparticles is an important crystal growth pathway in the synthesis of hierarchical structures. Although a significant understanding of OA has been made, the effect of atomistic misalignment and the roles of solvent/particle and particle/particle interactions on the structure–energy relationship during an OA remain elusive. In this study, we perform molecular dynamics simulations to calculate the potential of mean force (PMF) profile for gibbsite particle translation on a gibbsite slab with 1 or 2 intervening water layers (1W or 2W). The structures of the gibbsite surfaces and the confined water are analyzed to determine how the number and type of hydrogen bonds (H-bonds) influence the free energy profile during the translation. The PMF profile exhibits a periodicity of length 5.078 Å, consistent with the gibbsite unit cell size along the translation direction. The changes in the surface–water and water–water hydrogen bond network and water and surface OH groups’ orientations during the translation are strongly coupled with the changes in the PMF profile in the 1W case. However, when increasing the number of intervening water layers from 1W to 2W, the particle/slab misalignment becomes a dominant factor controlling the behavior of the PMF profile. We also establish a method to quantify misalignment between the particle and the slab, which exhibits a strong correlation with the free energy for the 2W case. These results shed more light into the roles of particle/slab misalignment and hydrogen bond network in the OA of mineral particles in aqueous solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energy Snapshot - Commonwealth of the Northern Mariana Islands

This profile provides a snapshot of the energy landscape of the Commonwealth of the Northern Mariana Islands (CNMI), a commonwealth in political union with the United States that is located in the northern Pacific Ocean. CNMI's electricity rates for residential customers range from $0.21 to $0.35 U.S. dollars (USD) per kilowatt-hour (kWh), above the average U.S. residential rate of $0.13 USD/kWh.

44 EE - Strategic Programs, Energy Transition Init↗

Extracting energy from ocean thermal and salinity gradients to power unmanned underwater vehicles: State of the art, current limitations, and future outlook

Thermal gradient energy-generation technologies for powering unmanned underwater vehicles (UUVs) or autonomous sensing systems in the ocean are mainly in the research development phase or commercially available at a limited scale, and salinity-gradient energy-generation technologies have not been adequately researched yet. The demand for self-powered UUVs suitable for long-term deployments has been growing, and further research related to small-scale ocean gradient energy systems is needed. In this study, we conducted a comprehensive review about harvesting energy from ocean thermal or salinity gradients for powering UUVs, focusing on gliders and profiling floats. Thermal gradient energy systems for UUVs based on phase change materials (PCM) cannot provide the energy required for powering autonomous sensing systems because of the systems' low energy conversion efficiency. Besides reducing energy consumption by developing more efficient electrical-mechanical systems, enhancing the thermal conductivity of the PCMs may help address this challenge by increasing the power generation rate of the UUVs. Several other emerging technologies, such as thermoelectric generators, shape memory alloys, and small-scale thermodynamic cycle systems, have shown potential for powering UUVs, but they are still only at the laboratory testing or conceptual design phase. The most advanced power generation technologies based on salinity gradients, reverse electrodialysis and pressure-retarded osmosis, are still not economically viable for large-scale deployment, mainly because of the high cost of the components required to operate in harsh saline environments. Our feasibility evaluation showed that existing salinity gradient power generation technologies are not directly feasible for powering UUVs in the open ocean.

16 TIDAL AND WAVE POWER↗

Preventive Power Outage Estimation Based on a Novel Scenario Clustering Strategy

The increasing occurrence of extreme weather events is challenging power grid operation. For extreme weather events, the system operator is responsible for estimating the power outages and scheduling the restoration resources. This paper proposes an outage evaluation framework to identify the possible unserved load profiles, vulnerable areas, and mobile energy adequacy. The outputs of an outage prediction model tool are used to generate numerous faulted line scenarios. Next, each scenario's nodal unserved load profile is obtained by solving a three-phase restoration model that considers repair crews and mobile energy resources (MERs). Then, a novel scenario clustering strategy is developed to cluster the unserved load profiles into multiple representative profiles which the system operator can focus on. Finally, case studies on a distribution system evaluate the damage caused by an extreme weather event and verify the effectiveness of the proposed scenario clustering strategy.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗

Energy-Efficient Adaptive Cruise Control Using Eco-Driving Algorithm

SwRI Eco-Driving Algorithm – Objectives and Method – Required Information Streams and Velocity Profile Realization ▪ Impact on Energy Consumption – Study 1 – NEXTCAR II • Individual (ego/eco) vehicle on Blanco Road, San Antonio, TX – Study 2 – DOE EEMS • Entire Urban Corridor – N High Street, Columbus, OH

Bhagdikar, Piyush↗

Turbine-based Power System Tool

Advanced research tools are essential to illustrate the effects of turbine-based power system operations on the electric grid network. This paper presents the development of an open-source tool to visualize the operation of turbine-based electricity generation. The tool exposes power system models, control parameters, and corresponding values of the turbine model and its electrical system, allowing them to customize the simulation according to their needs. The developed tool enables users to simulate power profiles for different turbinebased energy generation such as wind, tidal, and gas turbines. It allows users to investigate the details of the generated profiles of various types of turbine systems at various scales. It can provide valuable insights into model development and facilitate the analysis of integrated power systems. By enabling access to turbine-based operations visualization, the tool aims to bridge the gap between advanced research tools and users, facilitating broader adoption of renewable energy technologies and aiding in developing sustainable power systems.

Kini, Roshan L.↗

Multi-objective Decisions on Integrated Energy Systems Planning and Operation for Industrial Combined Heat and Power Supply

Unlike the power sector—which can transmit electricity over long distances via established grids—the industrial sector poses a unique challenge due to its geographically concentrated large-scale heat processes. Enhancing energy security in such industrial parks provides a dual benefit: reduced exposure to volatile fossil fuel prices and improved economic viability, largely driven by economies of scale in energy supply and distribution. This study presents a comprehensive technoeconomic analysis of a nuclear energy hub, employing a mechanism-focused approach to evaluate uncertainties in operational strategies and capacity optimization. Load profiles from three major energy intesive industries—chemical, refinery, and steelmaking—are examined, each presenting unique challenges and opportunities for nuclear energy integration. We adopt a multi-objective optimization framework, converting multiple objectives into a single objective function through the e-constraint method. The findings highlight clear trade-offs between system conditions and varying levels of energy independence. Overall, this analysis is granular enough to address industry-specific concerns yet sufficiently generalizable to provide actionable insights into the feasibility of nuclear-based clean heat solutions for the industrial sector.

25 - ENERGY STORAGE↗

Targeted Dy intercalation under graphene/SiC for tuning its electronic band structure

Metal intercalation of graphene is a promising method to tune its electronic band structure and generate novel electronic and topological phases. The tuning depends critically on the ability to bond the intercalated atoms at predesigned, subsurface interlayer locations because the emerging band structure depends on metal location. In this work, we have studied Dy intercalation under single-layer graphene (SLG) on SiC using spot profile analysis–low-energy electron diffraction and scanning tunneling microscopy (STM). The experimental work is complemented with density-functional theory (DFT) analysis. Because different diffraction spots originate from different subsurface interlayer regions, it is possible to identify changes in the intercalation location by monitoring the spot intensity as a function of growth conditions. DFT calculations of the chemical potential as a function of intercalated Dy coverage support the variation of the stability of the intercalated phase at different intercalated locations. The preferred location is confirmed from STM studies showing the removal of the 6 × 6 moiré corrugation at the preferred location, observed at higher Dy coverage.

2-dimensional systems↗

Behavioral and Population Data-Driven Distribution System Load Modeling

Distribution system residential load modeling and analysis for different geographic areas within a utility or an independent system operator territory are critical for enabling small-scale, aggregated distributed energy resources to participate in grid services under Federal Energy Regulatory Commission Order No. 2222 [1]. In this study, we develop a methodology of modeling residential load profiles in different geographic areas with a focus on human behavior impact. First, we construct a behavior-based load profile model leveraging state-of-the-art appliance models. We simulate human activity and occupancy using Markov chain Monte Carlo methods calibrated with the American Time Use Survey data set. Second, we link our model with cleaned Current Population Survey data from the U.S. Census Bureau. Finally, we populate two sets of 500 households using California and Texas census data, respectively, to perform an initial analysis of the load in different geographic areas with various group features (e.g., different income levels). To distinguish the effect of population behavior differences on aggregated load, we simulate load profiles for both sets assuming fixed physical household parameters and weather data. Analysis shows that average daily load profiles vary significantly by income and income dependency varies by locality.

American Time Use Survey↗

Representative Period Selection for Robust Capacity Expansion Planning in Low-carbon Grids

With the increasing urgency to decarbonize power systems, while mitigating extreme events, capacity expansion models can play a vital role in reliably planning the expansion of power systems and facilitating the integration of renewable energy sources. Optimizing capacity expansion generally involves selecting surrogate representative days from forecasts of load and the generation profiles of variable renewable energy resources. To properly select those representative days, we propose a novel input-based approach in combination with the k-means clustering algorithm that utilize three unique operational inputs: load shedding, renewable curtailment, and transmission congestion. The proposed method allows for more robust and cost-effective capacity planning. The method is validated using a capacity expansion model and a production cost model based on California Independent System Operator (CAISO)'s decarbonization goals, and results in reduced costs and drastically lower load shedding.

Anderson, Osten P.↗

Energy Snapshot - St. Lucia

This profile provides a snapshot of the electricity capacity and generation profile of Saint Lucia, one of six Caribbean countries that make up the Windward Islands - the southern arc of the Lesser Antilles chain - at the eastern end of the Caribbean Sea.

44 EE - Strategic Programs, Energy Transition Init↗

Degeneracy in Intercalated Pb Phases under Buffer-Layer Graphene on SiC(0001) and Diffuse Moiré Spots in Surface Diffraction

First-principles density functional theory (DFT) is used to analyze the stability of Pb intercalated phases under buffer layer graphene on SiC(0001) as a function of the supercell size, Pb coverage, and degree of Pb ordering. By comparing the chemical potentials of such two-dimensional Pb structures, here we find that there is a family of structurally distinct thermodynamically preferred Pb subsurface configurations with minute stability differences. These differences are comparable to the thermal energies at about 450 °C, where the Pb intercalated phases are grown. High-resolution surface-diffraction experiments using Spot Profile Analysis Low-Energy Electron Diffraction (SPA-LEED) confirm this high degree of degeneracy of the Pb intercalated phases from broad, low-intensity moiré spots observed exclusively from intercalated Pb. The low intensity of the moiré spots implies the coexistence of structurally different subsurface Pb phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A flexible proton beam imaging energy spectrometer (PROBIES) for high repetition rate or single-shot high energy density (HED) experiments (invited)

The PROBIES diagnostic is a new, highly flexible, imaging and energy spectrometer designed for laser-accelerated protons. The diagnostic can detect low-mode spatial variations in the proton beam profile while resolving multiple energies on a single detector or more. When a radiochromic film stack is employed for “single-shot mode,” the energy resolution of the stack can be greatly increased while reducing the need for large numbers of films; for example, a recently deployed version allowed for 180 unique energy measurements spanning ~3 to 75 MeV with <0.4 MeV resolution using just 20 films vs 180 for a comparable traditional film and filter stack. When utilized with a scintillator, the diagnostic can be run in high-rep-rate (>Hz rate) mode to recover nine proton energy bins. Here, we also demonstrate a deep learning-based method to analyze data from synthetic PROBIES images with greater than 95% accuracy on sub-millisecond timescales and retrained with experimental data to analyze real-world images on sub-millisecond time-scales with comparable accuracy.

3D printing↗

Phase space distribution functions and energy distributions of dark matter particles in haloes

ABSTRACT For a spherical dark matter halo with isotropic velocity distribution, the phase space distribution function (DF), the energy distribution, and the density profile form a set of self-consistent description of its equilibrium state, and knowing one is sufficient to determine the other two. The Navarro–Frenk–White density profile (NFW profile) is known to be a good approximation to the spherically averaged density distribution in simulated haloes. The DARKexp energy distribution is also known to compare well with the simulated energy distribution. We present a quantitative assessment of the NFW and DARKexp fits to the simulated DF and energy distribution for a wide range of haloes in a dark-matter-only simulation from the IllustrisTNG Project. As expected, we find that the NFW fits work well except at low energy when the density at small radii deviates from the NFW profile. Further, the NFW and DARKexp fits have comparable accuracy in the region where both fit well, but the DARKexp fits are better at low energy because they require matching of the central gravitational potential. We also find an approximate relation between the energy scale parametrizing the DARKexp energy distribution and that defined by the characteristic density and radius of the NFW profile. This relation may be linked to the relaxation process during halo formation.

Astronomy & Astrophysics↗

The good, the bad, and the ugly: Data-driven load profile discord identification in a large building portfolio

Reducing the overall energy consumption and associated greenhouse gas emissions in the building sector is essential for meeting our future sustainability goals. Recently, smart energy metering facilities have been deployed to enable monitoring of energy consumption data with hourly or subhourly temporal resolution. This unprecedented data collection has created various opportunities for advanced data analytics involving load profiles (e.g., building energy benchmarking programs, building-to-grid integration, and calibration of urban-scale energy models). These applications often need preprocessing steps to detect daily load profile discords, such as: 1) outliers due to system malfunctions (the bad) and 2) irregular energy consumption patterns, such as those resulting from holidays (the ugly) compared to normal consumption patterns (the good). However, current preprocessing methods predominantly focus on filtering using statistical threshold values, which fail to capture the contextual discords of daily profiles. In addition, discord detection algorithms in building research are often aimed at finding individual building-level discords, which are not suitable at a large scale. Thus, here, we develop a method for automated load profile discord identification (ALDI) in a large portfolio of buildings (more than 100 buildings). Specifically, ALDI 1) uses the matrix profile (MP) method to quantify the similarities of daily subsequences in time series meter data, 2) compares daily MP values with typical-day MP distributions using the Kolmogorov-Smirnov test, and 3) identifies daily load profile discords in a large building portfolio. We evaluate ALDI using the metering data of both an academic campus and a residential neighborhood. Our results demonstrate that ALDI efficiently discovers measurement errors by system malfunctions and low energy consumption days in the academic campus portfolio, and it detects unique load shape patterns likely driven by occupant behavior and extreme weather conditions in the residential neighborhood.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗