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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Disaggregating Smart Meter Data to Identify Electric Loads and Control Opportunities

As utility data, such as smart meter data, becomes more broadly available, there is general interest in using it to improve utility operations and enable adoption of other advanced technology - such as solar photovoltaics (PV), energy storage, and controls. We explore one such use case - identifying electric resistance water heaters from smart meter data, as well as characterizing their potential for load-shifting to support grid voltage stability under high-penetration PV adoption. This paper shows the limitation of typical 15-minute data, and how shortterm capture of additional 1-minute data is needed to enable the desired application. Results indicate about 4 kWh water heating load can be shifted to align with peak sun hours in a low use home. This methodology is an example, and can be adapted to other grid-integrated efficient building use cases.

14 SOLAR ENERGY↗
DOE OSTI2025

Development and characterization of a laser-gated, high resolution x-ray radiography platform for high energy density experiments using toroidally bent crystals

Bent crystal x-ray imagers are a well-established diagnostic tool to study high energy density (HED) objects by acquiring two-dimensional x-ray radiographs. Often, studying these HED objects requires very high spatial resolution, which is limited by astigmatism when using spherically bent crystals. By using toroidal-shaped crystals instead, astigmatism can be reduced and the overall spatial resolution of the instrument improved. Here, the development and characterization of a laser-gated x-ray radiography platform at the National Ignition Facility using a toroidal crystal is presented. This includes measurements of the spatial and temporal profile, which is determined by the x-ray source. In conclusion, to properly validate the reduced astigmatism, a new multi-plane grid approach was implemented, which, for the first time, allows a depth of field measurement, alignment verification and x-ray source size estimate in a single shot, demonstrating the current platform’s capability to provide sub-10 μm resolution over a 0.9 mm depth of field with a temporal resolution of 110 ps.

Crystal optics↗
DOE OSTI2023

Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022

Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transportation Energy & Mobility Pathway Options (TEMPO) model and published in demand-side grid (dsgrid) toolkit format. Data are available for three adoption scenarios: "AEO Reference Case", which is aligned with the U.S. EIA Annual Energy Outlook 2018 (linked below), "EFS High Electrification", which is aligned with the High Electrification scenario of the Electrification Futures Study (linked below), and "All EV Sales by 2035", which assumes that average passenger light-duty EV sales reach 50% in 2030 and 100% in 2035. The charging shapes are derived from two key assumptions of which data users should be aware: "ubiquitous charger access", meaning that drivers of vehicles are assumed to have access to a charger whenever a trip is not in progress, and "immediate charging", meaning that immediately after trip completion, vehicles are plugged in and charge until they are either fully recharged or taken on another trip. These assumptions result in a bounding case in which vehicles' state of charge is maximized at all times. This bounding case would minimize range anxiety, but is unrealistic from the point of view of both electric vehicle service equipment (EVSE) (i.e., charger) access, and plug-in behavior as it can result in dozens of charging sessions per week for battery electric vehicles (BEVs) that in reality are often only plugged in a few times per week.

Array↗
DOE OSTI2023

Are You Philanthropy-Ready? How to Work with Foundations on Mission-Aligned Community Solar

Community solar is emerging as a popular way to deliver a range of economic and social benefits that go beyond clean energy. The US Department of Energy (DOE) has set a goal for America to deploy enough community solar projects to power the equivalent of five million households by 2025 and create $1 billion in energy bill savings. To reach the goal, DOE has created the Community Power Accelerator, as part of the National Community Solar Partnership (NCSP). The Accelerator is an online ecosystem bringing together developers, lenders, foundations, community organizations, and other stakeholders to support the deployment of mission-aligned community solar. The Accelerator is especially focused on projects that deliver "meaningful benefits" to customers and communities, including: access by low- to moderate-income households; greater bill savings; resilience and grid benefits; community ownership; and local workforce development. Many philanthropic organizations are looking at community solar as a way to capture these benefits in their grant-making and investment programs, while also reducing pollution and promoting environmental justice. To help community-based organizations (CBOs), non-profit organizations, and mission-aligned developers seeking philanthropic support, Berkeley Lab and the National Renewable Energy Lab prepared Are You Philanthropy-Ready? How to Work with Foundations on Mission-Aligned Community Solar. The guide provides an overview of how foundations work, gives tips on what they seek in a fundable project, and provides guidance on crafting effective proposals. In short, this guide aims to help the fund-seeker become philanthropy-ready.

14 SOLAR ENERGY↗
NASA NTRS2001

Learning Sequences of Actions in Collectives of Autonomous Agents

In this paper we focus on the problem of designing a collective of autonomous agents that individually learn sequences of actions such that the resultant sequence of joint actions achieves a predetermined global objective. We are particularly interested in instances of this problem where centralized control is either impossible or impractical. For single agent systems in similar domains, machine learning methods (e.g., reinforcement learners) have been successfully used. However, applying such solutions directly to multi-agent systems often proves problematic, as agents may work at cross-purposes, or have difficulty in evaluating their contribution to achievement of the global objective, or both. Accordingly, the crucial design step in multiagent systems centers on determining the private objectives of each agent so that as the agents strive for those objectives, the system reaches a good global solution. In this work we consider a version of this problem involving multiple autonomous agents in a grid world. We use concepts from collective intelligence to design goals for the agents that are 'aligned' with the global goal, and are 'learnable' in that agents can readily see how their behavior affects their utility. We show that reinforcement learning agents using those goals outperform both 'natural' extensions of single agent algorithms and global reinforcement, learning solutions based on 'team games'.

Turner, Kagan↗
DOE OSTI2025

Techno-Economic Analysis for the Addition of a Thermal Energy Storage System to a Central Plant

Increasing energy demand and rising peak loads present significant challenges for energy management in commercial and institutional settings. As climate change drives greater cooling needs, central plants must navigate the complex tradeoffs between operational efficiency, cost control, and grid stability. Thermal energy storage (TES) systems offer a viable solution by shifting energy consumption from peak to off-peak periods, thereby reducing peak demand, lowering utility expenses, and improving grid resilience. However, the success of TES implementation hinges on appropriate system sizing, effective control strategies, and alignment with local utility rate structures. This article presents a techno-economic analysis of integrating a chilled water TES system into the central plant at California State University, Dominguez Hills. Drawing on historical load profiles and utility tariffs, we assess three TES sizing approaches and their corresponding control strategies from both energy and economic perspectives. This article utilizes a model-based approach to assess the impact of TES sizing and control strategies on the techno-economic feasibility of integrating TES into an existing central plant. The models employed for this analysis were calibrated using 4 years of historical data. Here, the results demonstrated that utility tariffs and the campus's operational profiles dictate the most feasible sizing and control methods. The findings offer valuable insights for institutions and commercial building managers exploring sustainable energy solutions. By demonstrating how optimized TES strategies can improve operational efficiency while achieving financial savings, this study highlights the potential for TES to align performance with cost effectiveness in real-world applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1983

A survey of grid generation techniques in computational fluid dynamics

The use of numerically-generated body-conforming coordinate systems has become well-established in computational fluid dynamics, allowing general codes to be written which can treat boundaries of arbitrary shape. There is now a rapidly increasing interest in the dynamic coupling of the grid with the physical solution so that the grid lines continually move to achieve concentration in regions of strong variation of the physical solution and alignment with shocks, flame fronts, etc. Such adaptive coordinate systems have been developed using a variety of techniques for sensing and reacting to the developing regions of concentration and/or alignment. This paper reviews the techniques and applications of these dynamically adaptive systems and other systems.

Thompson, J. F.↗
NASA NTRS2002

Triangle Geometry Processing for Surface Modeling and Cartesian Grid Generation

Cartesian mesh generation is accomplished for component based geometries, by intersecting components subject to mesh generation to extract wetted surfaces with a geometry engine using adaptive precision arithmetic in a system which automatically breaks ties with respect to geometric degeneracies. During volume mesh generation, intersected surface triangulations are received to enable mesh generation with cell division of an initially coarse grid. The hexagonal cells are resolved, preserving the ability to directionally divide cells which are locally well aligned.

Aftosmis, Michael J.↗
DOE OSTI2019

Impedance Characterization of Utility-Scale Renewable Energy and Storage Systems: Preprint

This paper presents the impedance characterization of utility-scale wind turbines and PV/storage inverters using a multimegawatt grid simulator-based grid integration testbed. The paper describes testbed components including a 7 MVA grid simulator, 5 MW dynamometer, medium-voltage measurement system, and real-time control system used for automated impedance characterization of wind turbines and inverters. Different aspects of impedance measurement are discussed, including the selection of the magnitude and type of perturbation, measurement of frequency cross-coupling between sequence impedance responses, and the alignment of the reference frame for sequence impedance measurement. The paper also demonstrates high-fidelity validation of EMT simulation models and characterization of grid-forming inverters using impedance measurements.

17 WIND ENERGY↗
DOE OSTI2018

Fabrication of Low-Tortuosity Ultrahigh-Area-Capacity Battery Electrodes through Magnetic Alignment of Emulsion-Based Slurries

High energy–density, low–cost batteries are critically important to a variety of applications ranging from portable electronics to electric vehicles (EVs) and grid–scale storage. While tremendous research effort has been focused on new materials or chemistries with high energy–density potential, design innovations such as low–tortuosity thick electrodes are another promising path toward higher energy density and lower cost. Growing demand for fast–charging batteries has also highlighted the need for negative electrodes that can accept high rate charging without metal deposition; low tortuosity can be a benefit in this regard. However, a general and scalable fabrication method for low–tortuosity electrodes is currently lacking. Here an emulsion–based, magnetic–alignment approach to producing thick electrodes (>400 µm thickness) with ultrahigh areal capacity (up to ≈14 mAh cm –2 vs 2–4 mAh cm –2 for conventional lithium ion) is reported. The process is demonstrated for LiCoO 2 and meso–carbon microbead graphite. The LiCoO 2 cathodes are confirmed to have low tortuosity via DC–depolarization experiments and deliver high areal capacity (>10 mAh cm –2 ) in galvanostatic discharge tests at practical C–rates and model EV drive–cycle tests. Lastly, this simple fabrication method can potentially be applied to many other active materials to enable thick, low–tortuosity electrodes.

25 ENERGY STORAGE↗
DOE OSTI2026

Comparison of structurally diverse simulation models for prediction of epidemic outcomes caused by a long-distance dispersed pathogen

Long-distance dispersal (LDD) pathogens pose substantial challenges for epidemic control due to their ability to generate new infection foci at great distances. While various modeling approaches have been developed to understand and manage such outbreaks, little work has compared how models of different structures behave under shared conditions. Here, in this study, we compare four structurally distinct epidemiological models — EPIMUL, GEMF, PoPS, and Warwick — each adapted to simulate the spread of wheat stripe rust (WSR), a wind-dispersed LDD pathogen, under identical epidemiological parameters and dispersal kernel. Using data from a controlled field experiment, we evaluate the ability of each model to replicate disease prevalence under nine intervention scenarios that vary in timing and culling area. While the models differ substantially in design — ranging from spatial grid-based to network-based and raster-based frameworks — the shared dispersal kernel allowed for close alignment in their predictions. All models accurately captured general epidemic trends, particularly the strong effect of early intervention on disease suppression. We qualitatively compared their behavioral responses across scenarios and also evaluated an ensemble prediction by averaging across model outputs. Our findings highlight how integrating shared epidemiological components into distinct modeling frameworks can improve consistency and accuracy, while reinforcing the importance of early culling in managing LDD pathogen outbreaks.

Dispersal kernel↗
DOE OSTI2023

Clean Energy Cybersecurity Accelerator Cohort 1: Authentication and Authorization

In the 2023 National Cybersecurity Strategy, the Biden-Harris Administration defines the need for a "defensible, resilient digital ecosystem where it is costlier to attack systems than defend them." The strategy cites the Clean Energy Cybersecurity Accelerator (CECA) as an exemplary effort to bolster the security and resilience of clean energy generation. These efforts help "secure the clean energy grid of the future and [generate] security best practices that extend to other critical infrastructure sectors" and promise broad and far-reaching impacts to bridge the capabilities of private industry and the needs of energy production. Cohort 1 of CECA launched in the fall of 2022 with a focus on solutions that provide strong authentication and authorization for industrial control systems to mitigate attacks on the energy grid. Authentication and authorization verify that the identity (authentication) and permissions (authorization) of a user or device are aligned with their assigned roles. Weaknesses in either can have serious repercussions. To assess the strength of Cohort 1's solutions, CECA devised threat scenarios grounded in historical precedents: the CECA team reviewed exploits from real-world case studies of state-sponsored actors to match the assessment's attack paths and targets. Cohort 1 results provided the energy industry, product vendors, and related agencies valuable insights into the efficacy and applicability of solutions in common system configurations under realistic threat scenarios. The results of the assessment highlight points for interrogation and improvement in subsequent technology iterations. CECA's evaluations are part of an ongoing conversation and collaboration to bolster U.S. cyber resilience against adversaries today and in the future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Cybersecurity Operational Research, Experimentation, Innovation, and Integration (COREII)

The Department of Energy’s Cybersecurity, Energy Security, and Emergency Response Office (CESER) has partnered with Idaho National Laboratory (INL) and energy companies to develop COREII. This research initiative aims to align with the national cybersecurity strategy, enhance the resilience of critical energy infrastructure, facilitate efforts to improve grid-enhancing technologies (GET) and major effects from other critical and emerging technologies, and to enable discovery of innovative solutions for emerging cybersecurity challenges

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Modeling Arctic boundary layer cloud streets at grey-zone resolutions

To better understand how model resolution affects the formation of Arctic boundary layer clouds, we investigated the influence of grid spacing on simulating cloud streets that occurred near Utqiagvik (formerly Barrow), Alaska on 2 May 2013 and were observed by the Moderate Resolution Imaging Spectroradiometer (MODIS). The Weather Research and Forecasting model was used to simulate the clouds using nested domains with increasingly fine resolution ranging from a horizontal grid spacing of 27 km in the boundary-layer-parameterized mesoscale domain to a grid spacing of 0.111 km in the large-eddy-permitting domain. We investigated the model-simulated mesoscale environment, horizontal and vertical cloud structures, boundary layer stability, and cloud properties, all of which were subsequently used to interpret the observed roll-cloud case. Increasing model resolution led to a transition from a more buoyant boundary layer to a more shear-driven turbulent boundary layer. The clouds were stratiform-like in the mesoscale domain, but as the model resolution increased, roll-like structures, aligned along the wind field, appeared with ever smaller wavelengths. A stronger vertical water vapor gradient occurred above the cloud layers with decreasing grid spacing. With fixed model grid spacing at 0.333 km, changing the model configuration from a boundary layer parameterization to a large-eddy-permitting scheme produced a more shear-driven and less unstable environment, a stronger vertical water vapor gradient below the cloud layers, and the wavelengths of the rolls decreased slightly. In this study, only the large-eddy-permitting simulation with gird spacing of 0.111 km was sufficient to model the observed roll clouds.

Lai, Hui-Wen↗
NASA NTRS2024

A Fair, Economically-Efficient, Incentive-Aligned, Scalable Airspace Auction Mechanism for UAV Traffic Management

Unmanned Aerial Vehicles (UAVs) are increasingly used in a wide range of applications such as cinematography, package delivery, and surveying. As a result, regulators have become interested in developing UAV Traffic Management (UTM) systems to coordinate UAV traffic. One possible framework for UTM is a combinatorial auction. Under this framework, airspace is modeled as a grid of space-time cells. UAV operators bid on sets of cells which collectively form flight paths for their UAVs. An ideal airspace auction should: be fair, be incentive-aligned, be scalable, allocate airspace economically-efficiently, enable price discovery, and reduce the work required to participate where possible. In this paper, we propose the first auction mechanism for airspace allocation that meets the criteria above. Our mechanism: (a) is provably economically-efficient, fair and incentive-aligned, (b) shares pricing information with bidders and (c) has features which reduce the burden of participating. We evaluate our mechanism on scenarios based on a Japan Aerospace Exploration Agency (JAXA) case study and find that it can scale to 26,000 bids.

Robert Allan Morris↗
DOE OSTI2025

Distribution System Blackstart and Restoration Using DERs and Dynamically Formed Microgrids

Extreme weather events have led to long-duration outages in the distribution system (DS), necessitating novel approaches to blackstart and restore the system. Existing blackstart solutions utilize blackstart units to establish multiple microgrids (MGs), sequentially energize non-blackstart units, and restore loads. However, these approaches often result in isolated MGs. In DERs-aided blackstart, the continuous operation of these MGs is limited by the finite energy capacity of commonly used blackstart units like battery energy storage (BES)-based gridforming inverters (GFMIs). To address this issue, this article proposes a holistic blackstart and restoration framework that incorporates synchronization between dynamic MGs and the entire DS with the transmission grid (TG). To support synchronization, we leveraged virtual synchronous generator-based control for GFMIs to estimate their frequency response to load pick-up events using only initial/final quasi-steady-state points. Subsequently, a synchronization switching condition is developed to model synchronizing switches, aligning them seamlessly with a linearized branch flow problem. Finally, we designed a bottomup blackstart and restoration framework that considers the switching structure of the DS, energizing/synchronizing switches, DERs with grid-following inverters, and BES-based GFMIs with frequency security constraints. In conclusion, the proposed framework is validated in IEEE-123-bus system, considering cases with two and four GFMIs under various TG recovery instants.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Examples of State and Utility Actions on Proactive Planning and Investments

As states across the U.S. confront rising electricity demand, clean energy deployment, grid modernization imperatives, and the integration of large new loads, some regulators and utilities are shifting away from reactive, “just-in-time” investment approaches toward more proactive planning and investment frameworks. This report compiles examples of jurisdictional and utility actions that reshape planning processes, cost recovery mechanisms, and performance oversight to anticipate—rather than simply respond to—future grid needs. Several themes emerge from state actions examined in this report. First, legislatures and commissions are increasingly directing utilities to proactively upgrade their distribution and transmission systems, reflecting a shift toward a forward-looking system that aligns planning with state policy goals. Second, states are establishing long-term, iterative planning frameworks that often feature multi-year horizons, biannual or annual compliance reporting, structured opportunities for stakeholder engagement, and emphasis on collaboration among utilities, regulators, and stakeholders. Third, states are actively investigating innovative cost recovery mechanisms designed to support accelerated electrification and grid modernization, while balancing consumer advocates’ concerns regarding the ratepayer financial risks of premature investments. Fourth, performance metrics and reporting requirements are being developed to ensure transparency and accountability for proactive investments. Fifth, methodological improvements in planning—such as aligning load forecasting assumptions, incorporating sensitivities, and considering load management potential across building, vehicles, storage, and demand response—are recurring areas of stakeholder focus across jurisdictions. Overall, these developments signify a growing recognition among state regulators, utilities, and stakeholders that proactive planning—supported by clear definitions, consistent and transparent methodologies, robust performance metrics, and innovative cost recovery mechanisms—is a tool that can be used to address the scale and urgency of contemporary grid needs.

electricity market↗
DOE OSTI2019

Impedance Characterization of Utility-Scale Renewable Energy and Storage Systems

This paper presents the impedance characterization of utility-scale wind turbines and PV/storage inverters using a multimegawatt grid simulator-based grid integration testbed. The paper describes the testbed components including a 7 MVA grid simulator, 5 MW dynamometer, medium-voltage measurement system, and a real-time control system used for automated impedance characterization of wind turbines and inverters. Different aspects of impedance measurement are discussed, including the selection of the magnitude and type of perturbation, measurement of frequency cross-coupling between sequence impedance responses, and the alignment of the reference frame for sequence impedance measurement. The paper also demonstrates high-fidelity validation of EMT simulation models from turbine manufacturers and characterization of grid-forming inverters using impedance measurements.

24 POWER TRANSMISSION AND DISTRIBUTION↗