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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Data Management for Digital Twin Implementation: Enhancing Existing SCADA Architecture for INL's CITRC Test Distribution System

The United States power grid will continue to experience stress from aging infrastructure, extreme weather, and increasing loads. In order to strengthen resiliency, researchers need to run tests and simulations that model real-life infrastructure. Idaho National Laboratory (INL) is creating a digital twin of its Critical Infrastructure Test Range Complex (CITRC). CITRC is an at-scale grid testbed which can be configured in utility-realistic distribution scenarios for a variety of tests, such as advanced grid protection and control. A digital twin of this infrastructure would support in-depth tests/simulations without risking physical consequences, before trialing devices under test at-scale. This project focuses on the data acquisition part of constructing a digital twin. It investigates the Supervisory Data Acquisition and Control (SCADA) system of CITRC and explores ways to utilize this system for the twin. Future “ideal” at-scale implementations such as upgraded equipment, modern communication protocols, and automation applications are also explored.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Forecasting EV Charging Demand on the Distribution System

The U.S. transportation and electricity sectors have historically operated independently, but the growth of electric vehicles (EVs) is driving their convergence. After decades of stagnant demand, utilities must prepare for rising load growth, driven in part by transportation electrification. Utilities must anticipate when and where these new loads will materialize to effectively manage EV growth and maintain grid reliability. This presentation outlines NREL's approach to developing high-resolution EV load datasets for distribution planning, with insights from the Multi-State Transportation Electrification Impact Study on EV and load forecasting, infrastructure requirements, and managed charging strategies.

25 ENERGY STORAGE↗
DOE OSTI2026

Development Fiber Optic Distributed System for Direct Detection of Subsurface Gases Leakages

Carbon, natural gas, and hydrogen gas storage is an emerging solution to safeguard us against pollution, support goals of negative carbon emission, and protect sources of renewable energy. Properly constructed storage wells provide a virtually impervious barrier to any unintended subsurface transmission. The ability to ensure the long-term integrity of such wells is vital to the success of any storage operation and be successful in the public eyes. Therefore, robust monitoring of any gas migration into the subsurface is highly sought. A fiber-optic distributed chemical sensor (DCS) enables monitoring of long-term well integrity along its depth, ensuring the success of any storage operation and bolsters public acceptance of the safety of the reservoir via leak early detection. The same technique can be applied to gas monitoring in pipeline networks and nuclear stockpile monitoring applications. Fiber based Raman spectroscopy enables DCS, as optical fibers can be deployed in virtually any environment and relay spectroscopic information over long distances back to the user. Hollow core fibers (HCF) make excellent DCSs as the air core of the fiber allows gas from the environment to diffuse into the core, which interacts with the laser signal that is carried in the air core. This work builds upon the previous LDRD project, Fiber Optic System for Direct Detection of Carbon Dioxide Leakage in Carbon Storage Wells (21-FS-003), in which the feasibility of Raman spectroscopy detection of Carbon Dioxide (CO2) in HCF detection was demonstrated. We mitigated the risk of this DCS technology by establishing and completing five objectives. The first objective was to model and optically characterize HCF uptake of CO2, establishing the relationship between HCF length, gas diffusion time, detectable gas concentration, and measured Raman intensity. In objective two, we developed a fiber core drilling recipe to enable additional diffusion ports in the fiber core and established a method for maintaining fiber strength and integrity post drilling. Objective three characterized the drilled fibers against the undrilled fibers, establishing the differences in the gas mechanics and optical properties and provided parameters to iterate the drilling process. In objective four, a fusion splicing technique was developed to join the HCF to conventional single-mode fibers, localizing the gas detection point at the drilled HCF hole, emulating a DCS. Lastly, objective five was the testing of the sensor in Edgar Mines at Colorado School of Mines on a CO2 pipeline with a simulated leak, to showcase the ability to detect CO2 leaks. This capstone result showed CO2 leak detection in < 10 minutes, raising the technology readiness level of HCF segments as deployable DCS.

organic↗
DOE OSTI2024

The power reliability event simulator tool (PRESTO): A novel approach to distribution system reliability analysis and applications

The growing interest in onsite solar photovoltaic and energy storage systems is partially motivated by customer concerns regarding grid reliability. However, accurately assessing the effectiveness of PVESS in mitigating these interruptions requires a comprehensive understanding of location-specific outage patterns and the ability to simulate realistic scenarios. To address the gap, we introduce the Power Reliability Event Simulation TOol (PRESTO), the first publicly available tool that simulates location-specific power interruptions at the county level. PRESTO allows for a more realistic assessment of system reliability by considering the unpredictability and location-specific patterns of power interruptions. We applied PRESTO in a case study of a single-family home across three U.S. counties, examining the performance of a solar photovoltaic system with 10kWh of battery storage during short-duration power interruptions. Our findings show that this system reliably met 93% of energy demand for essential non-heating and cooling loads, fully serving these loads in 84% of events, despite the constraints of daily time-of-use bill management which limits the battery's state-of-charge reserve. However, when heating and cooling loads were included, system performance decreased significantly, with only 70% of demand met and full service in 43% of events. These results highlight the challenges of using solar photovoltaic and energy storage systems for short-duration outages, emphasizing the need to consider factors like battery size and grid charging strategies to improve reliability. Our study demonstrates the practical applications of PRESTO, providing valuable insights into potential mitigation strategies including grid charging and optimizing battery size.

14 SOLAR ENERGY↗
DOE OSTI2025

Mini Guide: Community Engagement Approaches for Distribution System Resilience

The focus on electric grid resilience has gained significant momentum in recent years. The imperatives behind this focus are multifaceted, including the escalating threats of climate change, extreme weather events, and cyber and physical attacks. These challenges expose the vulnerabilities of the country’s aging grid infrastructure and underscore the important

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DOE OSTI2025

Advanced Intelligent Sensor Development and Demonstration for Future Distribution Systems with High Penetration DERs

The nation’s electric grid is evolving to supply the electricity needed for economic growth, health, and quality of life. As the DOE has pointed out “Old Tools Won’t Solve New Problems” This project conceived, designed, built, and demonstrated a new tool that promises to make the emerging grid dependable at a lower cost. The tool is a smart sensor with the sensitivity and the bandwidth to measure actionable information about grid health that was unmeasurable.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Current Best Practices on Wildfire Risk Reduction for Electric Transmission and Distribution Systems

This report provides a set of best practices in response to Section 4(d) of Executive Order 14308, Empowering Commonsense Wildfire Prevention and Response. The information contained herein is expected to be used in conjunction with other materials at the Federal Energy Regulatory Commission Wildfire Risk Mitigation Technical Conference (Docket No. AD25-16-000), with possible direction to the North American Electric Reliability Corporation to take action. The objective of this report is to provide an overview of existing and emerging best practices currently employed or planned by utilities for wildfire mitigation, demonstrating how these efforts align with the executive order’s emphasis on reducing electric utility–caused wildfires while also balancing cost-effectiveness. Additionally, while most practices in utility-developed wildfire mitigation plans focus on risk reduction through robustness and operational reliability, this report also discusses best practices for resilience. The best practices are adopted from publicly available utility wildfire mitigation plans from the United States and Canada, recent findings from wildfire risk reduction research, and industry engagement.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Data-Driven Protection Software to classify fault locations by protective zone in distribution systems with high PV penetration

The software contains (a) the source codes to generate Point-on-Wave (PoW) transient data for any feeder model in Alternative Transient Program (ATP) format. Codes provide options to change different steady state settings, including the loading condition and PV capacity and transient state setting like faults type, location and initiation time (b) data post-processing source code to converted data from native format to COMTRADE, csv, HDF5 (c) Docker container to train CNN to classify fault locations by protective zone. The container takes dataset and other training parameters (sampling rate, training epochs, batch size etc) as input to train CNN. The container writes back the trained CNN model, training and testing metrics and plots to the local workstation

Ramesh, Meghana↗
DOE OSTI2025

Graph-Learning-Assisted State and Event Tracking for Solar-Penetrated Power Grids with Heterogeneous Data Sources

Unlike transmission systems, distribution systems do not typically contain sufficient metering to enable real-time state estimation. The lack of sufficient real-time measurements prohibits accurate and timely monitoring of the state of distribution systems. As a result, control and optimal operation of distribution systems, especially those containing large numbers of renewable generation units are not possible without proper data and information about the current state of the system. The main motivation of this project is to address this shortcoming by developing an approach which provides “predicted” real-time measurements so that they can be used to execute a distribution system state estimator. Thus, the objective of the project is to make the distribution systems fully observable, such that the hosting capacity for solar generation can be accurately estimated, and unnecessary solar curtailments can be avoided. In order to accomplish this goal, the project investigated the use of a grid-model-informed machine learning (ML) tool which integrates heterogeneous data streams obtained from AMI meters, SCADA as well as PMU measurements and created synchronous measurement snapshots for the state estimator (SE); and developed a hybrid robust SE which provides not only accurate state estimates but also real-time feedback for the ML model refinement.

14 SOLAR ENERGY↗
DOE OSTI2025

A matheuristic for design and dispatch of a utility-connected distributed energy system

Modeling distributed power generation systems often requires complicated mathematical expressions that present challenges for commercial optimization solvers. Here, this paper presents a matheuristic to solve a mixed-integer optimization model that informs decisions regarding the design and dispatch of a utility-connected microgrid. We deploy a genetic algorithm to search the system design space and a linear program to solve the economic dispatch problem. The model is a component of a web tool that requires solutions within a few minutes. Our method yields objective function values within 5% of an exogenously produced optimal in fewer than 30 seconds for 90% of our test cases compared to only 10% of our test cases by a traditional optimization solver in the same amount of time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Meta-Learning Enhanced Physics-Informed Graph Attention Convolutional Network for Distribution Power System State Estimation

Promptly perceiving distribution system states is challenged by frequent topology changes and uncertain power injections. To address these issues, a Meta-learning enhanced physics-informed graph attention convolutional network (Meta-PIGACN) model is proposed to handle topological variability in distribution system state estimation (DSSE). Specifically, physics information is integrated into the graph convolutional network, enabling a physics-informed edge-weighting process that incorporates physical information to control the aggregation of neighboring nodes. Besides, the graph attention mechanism automatically adjusts the importance of different neighboring nodes, allowing the capture and preservation of inherent system features across varying topologies, thereby improving state estimation accuracy. Furthermore, meta-learning is proposed to acquire empirical knowledge across multiple topologies so that the model can rapidly adapt to new configurations through iterative gradient descent updates even in large-scale systems. In conclusion, the simulation results based on the 33/118/1746-node distribution systems show the high accuracy and efficiency of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Advance Distribution Management System (ADMS)

This presentation explores the transition from traditional distribution management systems to Advanced Distribution Management Systems (ADMS) as a foundation for smart grid development. It highlights the key benefits of ADMS, including enhanced reliability, improved operational efficiency, and increased situational awareness. The presentation also addresses common implementation challenges such as system integration, data management, and organizational readiness. It concludes with a forward-looking perspective on the evolving role of ADMS and essential takeaways for utilities and stakeholders.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Integrated Distribution Planning

The contemporary distribution planning landscape is comprised of an increasing number of factors that require integration into the engineering of the modern electric grid. Expectations for electric utilities to accommodate heightened awareness of stakeholders' interest in things like decarbonization, resilience and equity are growing. As these interests are formed into objectives, many jurisdictions will experience increasing levels of load modifying technologies like DER, building and industrial electrification and electric vehicles which prove not only to challenge the capabilities of the grid; but the processes by which planning for it is traditionally done. Other related factors that strain the conventional distribution planning mold are the swelling amount and sources of data associated with these technologies and the need it creates for improved capabilities in the processes and tools that manage it. As the complexity of the distribution system expands, so will the distribution system's effects on the transmission and generation systems that it is a part of. Forecasting distribution system load and DER are examples of areas where this complexity will manifest, and harmonizing distribution forecasting with transmission and generation forecasting requires higher amounts of intentionality as these typically separate processes become a solitary one. Of course, core activities do not cease as a utility begins to integrate these other factors, and in this webinar we explore specifics of how distribution planning can be expected to evolve as progress towards Integrated Distribution System Planning is made.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Laboratory Evaluation of Federated, Hierarchical Controls for Distribution Power System Management: Preprint

The connection of more loads and distributed energy resources (DERs) to the distribution power system brings both challenges and opportunities to system operators. There are opportunities to aggregate flexible loads and DERs to provide transmission grid services, but the coordinated actions of DERs being managed by independent, third-party DER aggregators to support transmission system operations can present challenges. We developed a federated DER management architecture and control framework that aims to manage heterogeneous DERs to deliver reliable transmission grid services while respecting distribution system constraints. The controls include stochastic day-ahead optimization, model predictive control, and a simple real-time management scheme. We present simulation results obtained from a realistic laboratory test bed of federated controls managing DERs within a substation service area to make the substation net power follow the optimal net power determined by the day-ahead optimization based on cost and limiting reverse power flow.

24 POWER TRANSMISSION AND DISTRIBUTION↗