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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 37 records · Page 2

GridCoPilot for Thermal Events: An LLM-Based Platform for Power Grid Reliability Analysis

Large Language Models show promise for translating natural language into database queries, but deploying such systems in safety-critical domains requires high reliability. We present an application of GridCoPilot to thermal event analysis (heatwaves and coldwaves) that affect power grid reliability. Our approach uses a LangChain SQL Agent to translate natural language queries into auditable SQL statements, with deterministic visualization routines that parse the structured query results. We introduce structural framing as a design principle, we integrate a NERC-region-level event library with county-level meteorology and decompose the combined data into three relational tables (event metadata, county-level event details, and a county-to-NERC subregion mapping), using prompt-guided joins to direct the model toward correct multi-table queries. For two core analytical patterns (identifying worst events by region and by region-year), the system achieved 100% SQL accuracy across all 16 NERC subregions and both event types (64 queries total). These results validate the approach for target use cases, though performance on diverse natural language formulations requires further investigation. We discuss design trade-offs, failure modes including JSON output truncation, and pathways for extending this approach to other hazard domains.

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Grid Strength Analysis for Integrating 30 GW of Offshore Wind Generation by 2030 in the U.S. Eastern Interconnection

Offshore wind is a key player in the transition to a decarbonized electric gird, and the United States has set ambitious goals of integrating 30 GW of offshore wind capacity by 2030 and 110 GW by 2050. To facilitate this integration, the National Renewable Energy Laboratory and the Pacific Northwest National Laboratory are conducting the Atlantic Offshore Wind Transmission Study to assess transmission solutions. To achieve the 110-GW target by 2050, meticulous planning for network expansion and resource allocation is essential; however, meeting the 2030 goals requires integrating offshore wind power with minimal system upgrades, thus necessitating a careful study of grid strength and stability. The study team developed the Automated System-wide Strength Evaluation Tool (ASSET) to assess system strength under various operating conditions and contingencies, focusing on the proposed integration of 30 GW of offshore wind power by 2030. In this paper, we provide a summary of key features of the ASSET software and results of the grid strength analysis for integrating 30 GW of offshore wind generation by 2030 in the U.S. Eastern Interconnection.

Automated System-wide Strength Evaluation Tool (AS↗

Grid impact analysis using controller-hardware-in-the-loop for high-power vehicle charging stations

A controller-hardware-in-the-loop (CHIL) architecture for the evaluation of grid impacts arising from high-power vehicle charging stations is presented in this paper. Unlike simulation-based studies, the proposed method can be used to capture the interactions of the grid and the charging load along with charger controllers in real time. The proposed method can be used to evaluate the impact of charging load on the grid in terms of voltage variations and line congestion. The proposed CHIL platform allows for de-risking the vehicle charging station deployment by simulating the complex interactions among all the components of a vehicle charging station - i.e., the grid, vehicle, and charger controller - in a realistic manner before using the charging station in a grid. Further, the proposed CHIL approach can be used to evaluate the voltage regulation causalities of the vehicle charging station. Experimental results are presented in the paper to illustrate the applicability of the proposed method in a laboratory environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Cost-Benefit Analysis of Grid-Supportive Loads for Fast Frequency Response

Flexibility in inverter-based loads could be used to support the converter-dominated power grid by offering a rapid, autonomous, and adjustable power reserve during system transients to help maintain system stability. Based on technical potential, ancillary service (AS) value, and implementation costs, this study illustrates the cost-benefit analysis of grid-supportive loads (GSLs) for the supply of fast frequency response (FFR). The net benefit for each GSL is demonstrated using a case study and relevant data sources. The findings suggest that implementation costs for enabling GSL features are low compared to the value that grid operators get from the acquisition of responsive reserve services. The authors believe that, given the rising popularity of renewable energy sources, GSLs can be a useful tool for grid stability in low-inertia systems.

cost-benefit analysis↗

Grid Voltage Control Analysis for Heavy-Duty Electric Vehicle Charging Stations

This paper presents an analysis of grid voltage control strategies for heavy-duty electric vehicle charging stations. The performance of three voltage control approaches—including power factor control, standardized volt-volt ampere reactive (VAR) curve control, and customized volt-VAR curve control—are investigated and evaluated for three different sizes of charging stations, including a single-port charging station, a midsized three-port charging station, and six-port travel center. The charging stations are placed on multiple locations of four different types of distribution systems to obtain a comprehensive performance analysis of the voltage control approaches under different scenarios. To quantitively compare the performance of the three voltage control approaches, a series of metrics are designed to quantify the performance and contribute to the comprehensive analysis.

47 OTHER INSTRUMENTATION↗

HexWeather: Hexagonal Spatial Data Aggregation for Weather-Driven Grid Resilience Analysis

Extreme weather accounts for over 8 0 % of major U.S. power outages since 2000, highlighting the need for spatial tools that align weather data with the irregular boundaries of electric infrastructure. This paper introduces HexWeather, a modular, resolution-aware framework for aggregating historical and forecasted weather data using Uber's H3 hexagonal spatial indexing system. Unlike traditional methods that rely on state or county-level grids, HexWeather enables weather analysis across custom geographies such as utility service areas where public datasets are often unavailable or misaligned. Using Open-Meteo data, we evaluate how H3 resolution affects anomaly detection, spatial variability, and forecast uncertainty across three scales: state, county, and utility. Results show that while coarse resolutions suffice for broad trend tracking, finer resolutions are essential for identifying localized variability and operational risks. By applying metrics like Z-score standard deviation and interquartile range, HexWeather quantifies the spatial spread of both historical anomalies and forecasted conditions, allowing users to assess resolution adequacy for each analysis. This framework supports rapid weather data reuse, reproducible anomaly detection, and predictive modeling for infrastructure resilience. By bridging spatial misalignment in traditional datasets and enabling retrospective and forward-looking analysis within the same pipeline, HexWeather lays the groundwork for better post event analysis, outage prediction, and resilience planning.

Morris, Jacob [ORNL]↗

Power Grid Contingency Analysis with Machine Learning: A Brief Survey and Prospects

We briefly review previous applications of machine learning (ML) in power grid analyses and introduce our ongoing effort toward developing a generative-adversarial (GA) model for fast and reliable grid contingency analyses. According to our review, the persisting limitation of traditional ML techniques in grid analyses is the need for an exhaustive amount of training data for model generalization and accurate predictions. GA models overcome this limitation by first learning true data distribution from a small training set, from which new samples assimilating true data are generated with some variations. Subsequently, GA models can transfer learn or super-generalize with increased accuracy, that is, accurately predict n - (k + 2) contingencies from a small n - k training set and generated n - (k + 1) data. The joint effort between Idaho National Lab and Florida State University strives to develop a zero-shot and deep learning-based contingency analysis tool, named Smart Contingency Analysis Neural Network (SCANN), by leveraging the aforementioned advantages of GA models. The basic architecture of SCANN stems from the Latent Encoding of Atypical Perturbations network combined with an adversarial network, and it is designed to generate imbalanced power flow data from learned true data distributions for prediction purposes. Here we also introduce the abstract concept of resilience-chaos plots, a new resilience characterization tool proposed to complement SCANN by aiding in the assessment of large amounts of high-order contingency predictions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Analysis of Grid Operator Survey Responses: Inexperience, Workload and Fatigue in the Control Room

Although a wide array of tools and technologies have been developed over the last decade to support power grid operators, deployment of these tools has been less successful. One reason for unsuccessful deployment may be an inadequate understanding of the factors that contribute to operator error in the control room. An analysis of operators’ current vulnerabilities may provide the baseline understanding needed to inform new technology integration. In an attempt to learn more about these vulnerabilities and their perceived impact on human error we collected and analyzed survey data from 20 electric grid control room operators. We asked survey respondents to consider the various operator, technology and interaction vulnerabilities that may arise during work in the control room and record their attitudes and experiences toward each. Results suggest operator inexperience, high mental workload and fatigue are the most common vulnerabilities experienced during a shift. Survey results were analyzed to explore these vulnerabilities in greater depth.

Inexperience, Workload, Fatigue↗

Grid Resilience Analysis on Geothermal District Heating and Cooling Implementation Alongside Four Existing Oil and Gas Wells in Tuttle, Oklahoma

This study builds on the existing techno economic and environmental life cycle assessments performed for a geothermal district heating and cooling system implementation in Tuttle Oklahoma with four existing oil and gas wells. Its resilience in meeting the peak annual heating and cooling loads of the district assuming a temporary disconnection from the electrical grid is assessed both qualitatively and quantitatively. Attributes of resilience and qualitative criteria established by Kolker et al. (2022) for geothermal district heating systems are applied to the proposed case to highlight its vulnerabilities. Results indicate that increasing the redundancy and diversity in the physical configuration of the distributional piping can considerably increase the system's resilience. A quantitative assessment executed via the REopt tool predicts that the ancillary electricity required to power the geothermal system's heating and cooling can be met by an onsite emergency diesel generator during times of grid outages for over 28 days.

district heating and cooling↗

Grid Resilience Analysis on Geothermal District Heating and Cooling Implementation Alongside Four Existing Oil and Gas Wells in Tuttle, Oklahoma: Preprint

This study builds on the existing techno-economic and environmental life cycle assessments performed for a geothermal district heating and cooling system implementation in Tuttle Oklahoma with four existing oil and gas wells. Its resilience in meeting the peak annual heating and cooling loads of the district assuming a temporary disconnection from the electrical grid is assessed both qualitatively and quantitatively. Attributes of resilience and qualitative criteria established by Kolker et al. (2022) for geothermal district heating systems are applied to the proposed case to highlight its vulnerabilities. Results indicate that increasing the redundancy and diversity in the physical configuration of the distributional piping can considerably increase the system’s resilience. A quantitative assessment executed via the REopt tool predicts that the ancillary electricity required to power the geothermal system’s heating and cooling can be met by an onsite emergency diesel generator during times of grid outages for over 28 days.

district heating and cooling↗

Grid Value Analysis of Geothermal Systems for End-Use Applications

Fuel based end-uses for residential, commercial, and industrial consumers require a technology change to achieve economy-wide decarbonization. Space heating accounts for 42% of residential and 32% of commercial energy demand, much of which is currently met through carbon emitting fuels. Industrial energy use is heavily fuel based with electricity currently representing 13% of energy demand. Geothermal heat pumps (GHPs) and geothermal direct use can eliminate the need for CO2 emitting and simultaneously allow for more efficient electrification of end uses. Past work has assessed the impact on total energy costs and generation investments but did not identify specific grid services benefited. Energy usage in residential and commercial structures was assessed by leveraging data from ComStock and ResStock models. These models utilize housing attributes, occupancy patterns, weather data, and sophisticated energy simulations to generate hourly load profiles for individual buildings identified by unique IDs associated with their locations. Industrial sector energy use was evaluated using information from the Manufacturing Energy Consumption Survey (MECS) as well as plant utilization data from the US Census to estimate hourly plant operations. The change in end-use demand for electricity, natural gas, and other fuels was calculated for different technologies that could meet this need. Using the ReEDS capacity expansion model, we produce regional price profiles that capture the grid benefit associated with the amount and timing of energy shifts in the power system from the adoption of geothermal systems relative to other technologies that could meet space heating, space cooling, and process heat requirements. We find that geothermal systems for meeting end-use demand add value to the energy system. In buildings where geothermal systems increase grid costs, these values are offset by reduced fuel costs and benefits to externalities, including emissions and health impacts.

decarbonization↗

EMP-Resilient Electric Grid Transformer Analysis

The response of a high - voltage (HV) transformer to fast rise time voltages, such as that from a electromagnetic pulse (EMP) can result in interruption of power distribution and possibly system failure. To help identify these potential occurrences, it is necessary to develop a transformer model that not only captures the input/output response of the transformer but also the internal behavior. The model constructed should cover the frequency band of interest while capturing the internal physical and electrical characteristics. This broad-band, high-fidelity model would enable the prediction of unwanted effects through simulation. A proposed modeling scheme for a HV transformer is described in Part 1 of this report. Part 2 of this report details assessments of internal voltage and electrical field holdoff testing of transformer insulation dielectric breakdown, including comparison of low frequency (DC/60 Hz) holdoff to rise times characteristic of lightning (1 s) and EMP E1 transients (10 - 30 ns). This initial project is a path toward establishing electrical grid transformer failure criteria for EMP voltage transients. We developed modeling methods and measured breakdown electrical field statistical distributions for direct current, 60 Hz, lightning and EMP characteristic voltage rise times. Methods of nanosecond-scale capacitive discharge unit high voltage source development, suggestions for derating of 60 Hz insulation maximum electrical fields for EMP nanosecond pulse voltage withstand rating, and potential methods for increasing transformer resilience to such fast rise time pulses are described.

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Testing and Analysis of Grid Forming Inverter Control for Achieving Resilient and Economic Operation of an Islanded Microgrid

This investigation examines the feasibility of operating a battery energy storage system (BESS) in parallel with synchronous generation by using grid forming (GFM) control in order to achieve frequency control objectives while mitigating increases to operating costs in the context of an islanded microgrid. The BESS GFM control system, which is based on conventional droop techniques, is modeled along with the overall microgrid using the Real Time Digital Simulator (RTDS) to allow for integration of genset controller hardware. A series of simulations are performed to test the voltage and frequency regulation capability of the BESS control system when the primary frequency regulating genset is tripped offline. The results of the simulations suggest that the GFM control scheme will successfully maintain frequency and voltage stability, which will enable operation without a back-up genset while not compromising the microgrid resiliency to contingencies.

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