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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Distributed Energy Resource Visual Emulator: Phase 1

To help federal energy managers assess, monitor, and manage cybersecurity while achieving decarbonization, the National Renewable Energy Laboratory's Distributed Energy Resource Cybersecurity Framework (DER-CF) offers a comprehensive, web-based assessment tool focusing on cyber governance or policies, technical management, and physical security. The DER-CF currently presents users with a series of pertinent cybersecurity questions, which are used to generate a site-specific report and recommendations. This paper outlines a technical approach to integrate the DER-CF with another key asset—NREL's Advanced Research on Integrated Energy Systems (ARIES) Cyber Range—to visualize cybersecurity resilience and compliance and to enhance the usability and accessibility of the DER-CF. The result is a new tool called the Distributed Energy Resource Visual Emulator (DER-VE). Its development will include regular conversations with stakeholders to assess the effectiveness of these efforts, refine the visualization capability, and ensure its value to our partners. Phase 0 of the integration project was concluded in 2021. Phase 1, completed in 2022, has two components: The first is developing a working visualization of system compliance using the DER-CF, and the second is planning the design of a server application that takes input data from the DER-CF and creates a personal emulated environment of the user's system or a selected reference architect. Major components that were addressed in this phase are the DER-CF output, compliance visualization, data model, and compliance server design.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Agentic artificial intelligence for multistage physics experiments at a large-scale user facility particle accelerator

We present a language-model-driven agentic artificial intelligence (AI) system to autonomously execute multistage physics experiments on a production synchrotron light source. Implemented at the Advanced Light Source particle accelerator, the system translates natural language user prompts into structured execution plans that combine archive data retrieval, control-system channel resolution, automated script generation, controlled machine interaction, and analysis. In a representative machine physics task, we show that preparation time was reduced by 2 orders of magnitude relative to manual scripting even for a system expert, while operator-standard safety constraints were strictly upheld. Core architectural features, plan-first orchestration, bounded tool access, and dynamic capability selection, enable transparent, auditable execution with fully reproducible artifacts. These results establish a blueprint for the safe integration of agentic AI into accelerator experiments and demanding machine physics studies, as well as routine operations, with direct portability across accelerators worldwide and, more broadly, to other large-scale scientific infrastructures.

Accelerator/storage ring control systems↗
DOE OSTI2021

AI-Guided Reasoning-Based Operator Support System for the Nuclear Power Plant Management

The Decision-making process in the Nuclear Power Plant (NPP) control room faces some challenges: operator incomplete knowledge, insufficient time for responding to the highly dynamic events, and a large number of indicators to monitor. Because of the complexity of the NPP system, it is hard to pre-plan all the failures/mitigative actions. An intelligent operator support system is vital to mitigate these shortcomings. In this paper, an AI declarative approach (Answer Set Programming (ASP)) is employed to represent our knowledge of the nuclear power plant in the form of logic rules. This represented knowledge is structured to form a reasoning-based operator support system. When an incident occurs, this ASP-based reasoning support system is demonstrated to be capable of fault identification (diagnosis), informing the operator of different scenarios and consequences, and generating the control options (decision making).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Geophysical Imaging of Flow and Transport (GIFT): FY24 Status Report

The GIFT (Geophysical Imaging of Flow and Transport) system will improve predictive capabilities as a platform for collecting multi-physical (MP) time-lapse datasets from well-controlled laboratory experiments. This will enable more accurate prediction of multi-phase fluid flow during delivery and transport of insitu remedial amendments as important components of the overall Hanford Site cleanup mission. Design and construction of the GIFT system, which consists of a meter-scale test cell and a network of custom gas circulation and analysis systems, was accomplished in fiscal year (FY) 2024, with plans to add liquid circulation to the system and use this new capability for multi-phase deep vadose experiments starting in FY25.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Mooring System Cost Estimates for Wave Energy Farms in Shared Mooring Arrays

As wave energy converters (WECs) become more advanced and cost-efficient, so too must their mooring systems. A key question in the development plans for WECs is the cost of the mooring system, particularly for large wave farms. WEC devices deployed in a WEC farm array, where each device can be connected by shared mooring lines in various array layouts, have potential to reduce mooring system costs significantly. This paper presents the modeling and designing of mooring systems for large WEC arrays and the calculation of the cost of each mooring system to determine the change in cost as the number of WECs in a farm increases. A baseline mooring system for a single floating oscillating water column (OWC) WEC was developed for this analysis. The mooring system utilizes four anchored mooring lines connected to a square assembly of wire rope mooring lines, supported by four floating buoys, and attached to the floating WEC by four polyester rope mooring lines. This assembly, referred to as a floating cell, can be tiled to form various rectangular WEC arrays. The objective of this analysis is to determine how the mooring system cost changes as more WECs are added to an array layout, each with their own interconnected floating cell. To do this, complete mooring systems need to be designed for each WEC array layout. To narrow down the design space of a WEC array mooring system, a couple assumptions were made. It was assumed that the floating cell parameters of the baseline design were to stay constant across all floating cells in the WEC array. It was also assumed that the anchored mooring lines would be of the baseline configuration, a predominantly chain mooring line with a short section of polyester rope near the fairlead, and a drag-embedment anchor. These anchored lines were assumed to extend from the outer edges of the WEC array, inline with the headings of the wire rope mooring lines of the floating cells, or diagonal if extending from a corner of the WEC array. Full mooring systems were designed for 2xN and NxN WEC array layouts and efficiently simulated in the mooring dynamics simulation tool, MoorDyn, to ensure all dynamic constraints were met. The system costs were calculated and then refined by shortening unnecessary chain line lengths and reducing the chain diameters of the downstream anchored mooring lines. It was found that, in general, mooring system costs per WEC decrease when WECs are installed in an array. Compared to the baseline mooring system for a single WEC, the 2x3 mooring system array had the lowest mooring system cost per WEC, reducing the cost per WEC by 59%. The 3x3 and 4x4 array mooring systems also saw significant reductions in cost per WEC but had negligible cost savings between the two designs, primarily because the larger 4x4 mooring system requires larger chain diameters, which increases cost. These results provide an interesting glimpse into modeling, designing, and calculating the cost of mooring systems for large WEC arrays.

cost↗
DOE OSTI2024

Enhancing Power Grid Resilience with Causal Loops Diagram and Bayesian Networks

Enhancing power grid resilience through improved analysis and planning of Distributed Energy Resources is a key for power system planner. This paper explores the integration of Causal Loop Diagrams (CLDs) and Bayesian Networks (BNs) for enhancing resilience in power systems, focusing on Distributed Energy Resources (DER) planning. By automating CLD analysis in Python's matplotlib, we present a tool for rapid model validation and structural accuracy, crucial for power system planners. This hybrid approach utilizes BNs for inferential depth and CLDs for dynamic system modeling, offering a comprehensive framework for policy formulation and collaborative strategy development against disruptions. Here, we highlight the tool's capability to identify and analyze interconnected feedback loops, facilitating a deeper understanding of DER integration's impact on network resilience. This work aims to bridge quantitative analysis and qualitative insights, addressing the limitations of each method while providing a robust model for power system resilience assessment.

14 SOLAR ENERGY↗
DOE OSTI2022

Case Study: Resilience Benefits of Distributed Wind Against Fuel and Weather Hazards in Alaska

In this case study of St. Mary’s Village, Alaska, we present a resilience evaluation exercise. A resilience framework is employed to identify system characteristics, relevant metrics, and resilience hazards and to assess the performance against the hazards with and without a distributed wind system installed. The results show the resilience benefits provided by the distributed wind installation against fuel shortage hazards and cold weather hazards. The resilience benefits can be assigned monetary values, which will be highly dependent on actual circumstances of the hazard, but provide insight into value streams of distributed wind that are not usually considered. For example, the single 900 kW turbine was found to prevent an average of 14,643 kWh of load from being dropped during a two-day diesel fuel shortage event, which saved the community $447,592 from the prevented outages. This case study serves as an example for novel power system resilience analysis and builds understanding of resilience hazards that are common across many power systems.

Culler, Megan J.↗
DOE OSTI2025

Transmission and Distribution Coordination

This webinar explores planning the future grid and interconnected energy system while examining balancing generation (G), transmission (T), distribution (D), & customer (C) resources all while also increasingly capturing engineering details in planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Nodal Capacity Expansion Modeling with ReEDS: A Case Study of the RTS-GMLC Test System

Test systems play an important role in power systems analysis and are used extensively for a wide range of purposes like reliability analysis, production cost modeling, studying the impacts of load shifting, and many more. These test systems have continued to evolve over the years to keep pace with changing system compositions due to technology and policy changes. In this work, we apply the Regional Energy Deployment System (ReEDS) model, a large-scale capacity expansion model (CEM), on the nodal RTS-GMLC system to perform capacity expansion of the bus-level test system. This work both demonstrates that a large-scale CEM can successfully be applied to nodal systems, and that the CEM can allow a test system to be evolved to meet desired criteria. The process allowed the coupling of CEM data not available in the test system (such as capital costs) with test system data to provide plausible system evolutions in line with scenario specifications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Enhancing grid reliability and resilience through novel DER control, total situational awareness and integrated distribution-transmission representation

High penetration of distributed energy resources (DERs) can lead to overvoltage and thermal violations, miscoordination of protection devices and potential adverse control interactions. The challenges are exacerbated by a lack of operator situational awareness of behind-the-meter DERs, and T&D interactions. Furthermore, the large attack surface of a DER environment creates significant cyber security challenges. The motivation is to address these barriers. The main goal is to enable extreme levels of DERs in distribution systems while simultaneously enhancing their reliability and resiliency. This is achieved by a data-driven approach for operation, planning and control of distribution systems with total situational awareness and real-time DER control enabled by a network of edge intelligent devices, a cloud-based analytical platform, and secure communications.

14 SOLAR ENERGY↗
DOE OSTI2023

SATS Enhanced Capabilities and Demonstration of Improved Ramp Rates for In-Cell Testing

This report presents the development of the second-generation Severe Accident Test Station, referred to as SATS 2.0. SATS 2.0 represents a major advancement in addressing critical research needs for the United States nuclear industry, particularly in relation to fuel fragmentation, relocation, and dispersal (FFRD) concerns associated with the nuclear industry’s goal to extend fuel burnup beyond a peak rod average of 62 GWd/tU. The central objective of SATS 2.0 was the deployment a new furnace capable of achieving heating rates up to 100°C/s. This achievement addresses critical capability gaps, enabling assessment of prioritized research objectives established by the Electric Power Research Institute’s (EPRI) Collaborative Research on Advanced Fuel Technologies (CRAFT) working group. These research objectives are directly related to high-burnup loss-of-coolant accident (LOCA) conditions and the effects of prolonged exposure to elevated temperatures, both of which are crucial to enhancing nuclear safety and efficiency. The SATS 2.0 system builds upon prior experience with the original SATS system, which focused on evaluating accident-tolerant fuel (ATF) cladding concepts during accident conditions. However, the new system not only expands upon prior core capabilities by achieving higher heating rates with a better furnace but also plans to incorporate novel auxiliary systems to create a versatile platform for addressing current research needs. For example, a system was developed for the quantification and characterization of fission gas released during high-temperature transients. Additionally, in situ measurement capabilities were developed, such as digital image correlation which enabled the real-time capture of strain related to balloon and burst events and fiber-optic sensors that allowed for high-fidelity characterization of temperature gradients. Demonstration tests of the new 12-lamp furnace achieved heating rates up to 120°C/s. Notably, SATS 2.0 demonstrated its capacity to simulate LOCA burst tests at different pressures, yielding burst data that align with historical empirical models. Moreover, the system exhibited its capability to simulate complex conditions observed in anticipated operational occurrences, while effectively mitigating temperature overshoots. These accomplishments mark significant progress toward overcoming FFRD challenges and advancing the United States nuclear industry's safety basis and technical capabilities for extended burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

A Report on Actions for Medium- and Heavy-Duty Vehicle Energy and Emissions Innovation

A Report on Actions for Medium- and Heavy-Duty Vehicle Energy and Emissions Innovation (the MHDV Plan) summarizes strategies and actions to substantially reduce emissions in the U.S. commercial on-road medium- and heavy-duty vehicle (MHDV) sector. This includes all on-road vehicles over 8,500 pounds used for commercial purposes. The intended audience of this report are industry and stakeholders who will take on the suite of actions needed to drive forward MHDV emissions reduction and decarbonization in a sustainable and economic way.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Evaluation of Extreme Weather Impacts on Utility-scale Photovoltaic Plant Performance in the United States

The global energy system is undergoing significant changes, including a shift in energy generating technologies to more renewable energy sources. However, the dependence of renewable energy sources on local environmental conditions could also increase disruptions in service through exposures to compound, extreme weather events. By fusing three diverse datasets (operations and maintenance tickets, weather data, and production data), this analysis presents a novel methodology to identify and evaluate performance impacts arising from extreme weather events across diverse geographical regions. Text analysis of maintenance tickets identified snow, hurricanes, and storms as the leading extreme weather events affecting photovoltaic plants in the United States. Statistical techniques and machine learning were then implemented to identify the magnitude and variability of these extreme weather impacts on site performance. Impacts varied between event and non-event days, with snow events causing the greatest reductions in performance (54.5%), followed by hurricanes (12.6%) and storms (1.1%). Machine learning analysis identified key features in determining if a day is categorized as low performing, such as low irradiance, geographic location, weather features, and site size. The analysis improves our understanding of compound, extreme weather event impacts on photovoltaic systems, which can inform planning activities, especially as the industry continues to expand into new geographic and climatic regions around the world.

14 SOLAR ENERGY↗
DOE OSTI2021

Insights for Canadian electricity generation planning from an integrated assessment model: Should we be more cautious about hydropower cost overruns?

Hydropower accounts for approximately 60% of electricity generation in Canada, with growth expected in the coming decades as part of renewable energy transitions; however, frequent cost overruns threaten the viability of this growth. Here, using the integrated assessment model GCAM, we develop an endogenous representation of hydropower for Canada that accounts for market dynamics, thus permitting analysis of hydropower competition with other electricity generation technologies, both with and without cost overruns. Results show that modelling hydropower resources endogenously increases Canadian hydropower deployment relative to an assumption of fixed hydropower production, from 417 to 495 TWh annually by 2050. In scenarios that apply cost overruns at historical levels, hydropower loses market share to more easily scalable technologies like wind power. When including high cost overrun assumptions, the model determines that hydropower falls from about 73% to 65% of Canadian electricity generation by 2050, while wind power increases from about 8% to 11%. Countries may be better able to achieve electrification and renewable energy targets at lower cost by avoiding large-scale, overrun-prone hydropower and nuclear generation projects. Model results support that cost overruns are important considerations for policy decisions related to electricity sector development in Canada and elsewhere.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Inequality and the Future of Electric Mobility in 36 U.S. Cities: An Innovative Methodology and Comparative Assessment

Electric vehicles are seen as one of the technological solutions to transition our transportation systems away from carbon, and cities offer unique opportunities to electrify transportation. To be equitable, however, this transition will not merely require technological innovations. Acknowledging socio-spatial inequalities and creating strategies to address them are critical - yet relatively underexplored - dimensions of the transportation transition. This paper integrates relevant literature into a micro-urban social typology (MUST) approach that uses agglomerative clustering techniques to examine, first, the factors and attributes defining transportation inequities within 36 U.S. cities, and, second, the implications of these inequities for policies that foster a more equitable transportation transition. By combining socio-spatial and transportation data, we identified five MUSTs: Wealthy, Urban Disadvantaged, Urban Renters, Middle-Class Homeowners, and Rural/Exurban. Rather than being tied to any particular indicator (e.g., homeownership), these MUSTs contain intersecting factors and features of inequities. We compare transportation and health outcomes across MUSTs, and the results suggest that user-centric strategies and public investments are necessary to foster true transportation equity. These must go beyond the electrification of private vehicles and should be tailored to the specific characteristics of each MUST. These could include electric carpooling for the rural/exurban MUST and electrification of transit for the urban disadvantaged and renter MUSTs. Our typology offers a critical next step toward informing transportation transition policies to target critical sociodemographic, economic, and techno-infrastructural factors.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗