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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

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↗
DOE OSTI2024

Tools And Methods to Analyze Plant Outage Schedule and Assist Schedulers in Improving Outage Resilience

Refueling outages of nuclear power plants (NPPs) are considered one of the most critical phases throughout the plant lifetime. In such instances, tens of thousands of activities (e.g., maintenance, surveillance) are performed in a short amount of time (typically 2-3 weeks unless major backfitting or modernization projects are carried out) by a large number of crews (e.g., electricians, mechanics) that are hired as contractors. As a consequence, a plant outage can be expensive not only in terms of costs (e.g., contractor labor, material), but also in terms of loss generation since the plant is taken off the grid during the full outage duration (an indicative metric is about 1.2M$/day of loss of revenue). Thus, there is a continuous need to decrease the economic impact of outages on plant finances. This can be done by: decreasing the frequency of plant outages (e.g., from 18 to 24 months), reducing the time to complete the outage, and reducing the risk of outage delays. The Optimization of Outage Activities project under the Risk Informed Systems Analysis Pathway (RISA) sponsored by Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program focuses on developing tools and methods to support NPPs with outage schedule optimization. The developed tools and methods are designed to analyze plant outage schedule with the goal of identify critical elements in the schedule that might pose a high risk of delays. These methods and tools can be considered resource-centric in the sense that they address outage challenges as a resource optimization problem. In this context, resources are either time and crews; outage delays occurs when either (or both) resources are insufficient to complete the set of tasks assigned at a specific time instant of the outage. This report provides details on how plant resources (time and crews) can be allocated in such a way that delays are minimized. In this respect, two classes of methods have been developed: the first one focuses on the time resource and how variability of the time to complete outage tasks may impact outage delays. The second one integrates available resources to assess when dailies activities should be performed such that the risk of outage delays are minimized.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

EAGLE-I Power Outage Data 2025

The provided EAGLE-I historic dataset includes power outage information at the county level for 2025 at 15-minute intervals collected by the EAGLE-I program at ORNL. The data has been collected from utility's public outage maps using an ETL process. The dataset details FIPS code, county name, state name, total number of customers without power, and a date/timestamp. For detailed metadata, refer to the linked metadata DOI.

EAGLE-I↗
DOE OSTI2026

Enhancing Building Resilience: Maintaining Energy Efficiency and Thermal Comfort During Power Outages in Cold Climates

The increasing frequency and intensity of extreme weather events, such as heatwaves and cold snaps, present significant challenges to building energy performance and occupant comfort. Highly correlated with climate events are widespread long duration power interruptions that may affect thousands of buildings and millions of customers. This study evaluates the impact of building energy performance and occupant thermal comfort in medium-sized office buildings in a cold climate region. Using energy models representing pre-1980 and 2019 vintages, simulations were conducted to assess energy performance under typical weather conditions and occupant thermal comfort during power interrupted extreme cold snap and heatwave climate events under both current 2020s and future 2050s weather conditions. The results show a projected 33% increase in cooling energy demand and a 19% reduction in heating energy by 2050. Findings reveal that older buildings are more susceptible to cold discomfort during cold snaps, while modern airtight buildings are more vulnerable to overheating during heatwaves. Various passive energy efficiency measures, such as improved infiltration control, thermal windows, solar-controlled windows, and cool envelopes, were evaluated for their ability to mitigate thermal discomforts. Solar controlled windows and weatherstripping contribute to reducing cold thermal discomfort by 21% during a power-interrupted cold snap. Solar-controlled windows were found to reduce hot thermal discomfort by 34% during a future power-interrupted heatwave. The study highlights the importance of targeted retrofitting strategies to enhance thermal resilience, especially during power outages, to ensure occupant safety and comfort during extreme climate events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Methods and Tools To Assess Robustness of Nuclear Plant Outages

Refueling outages are one of the most challenging phases in a nuclear power plant (NPP) operating cycle. Refueling outages are extremely costly for an NPP due to the large amount of required resources and because of lost revenue due to plant being off the grid. Outage durations have steadily decreased across the industry over that last few decades primarily due to improved planning and coordination, but there are still many plants that struggle to meet the performance metrics accomplished by other utilities. Schedule resilience is one of the issues. NPP outages require scheduling thousands of activities within 30 days on average. Despite detailed planning, once the outage starts, numerous emergent issues typically appear along with schedule delays requiring continuous replanning and adjustment. When schedule disruption occurs during an outage, plant staff make urgent efforts to recover but are often not able to maintain the planned outage duration. These outage delays can cost a utility several million dollars per day. Tools that could help outage schedulers create a more resilient schedule and allow them to optimally reschedule emergent work could significantly reduce outage delays. One key aspect of creating a resilient schedule is to have accurate estimates for activity duration. Another important outage scheduling capability is the ability to schedule emergent work with minimal disruption. This paper focuses on developing tools and methods to support NPPs with outage schedule optimization and it describes the initial development of tools to support outage management that leverage computational and machine learning methods.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data Analytics Methods to Measure Plant Outage Resilience

Every 18 or 24 months nuclear power plants (depending on plant configuration, pressurized or boiling water reactor respectively) undergo a period of outage where the plant is taken offline and a large number of maintenance and surveillance activities (that cannot be performed while plant is running) are performed in typically 2–3 weeks. Planning of a plant outage is very challenging since all the activities are required to be performed in the shortest amount of time given available resources (typically contractor crews hired for the duration of the outage). Consequently, plant outages can be costly due the actual loss of power generation and crew costs and, because of it, there is a need to maximize resource usage in the outage planning phase and reduce the risk of outage delays. This paper is addressing these needs by providing a set of analytical methods designed to analyze plant outage schedule and identify critical elements based on available resources (time and crews). These methods are based on natural language processing and optimization algorithms. In this respect, two classes of methods have been developed: one that focuses on the time resource and how variability in the time to complete outage tasks may impact outage delays, and one that minimizes the risk of outage delays by integrating available resources to assess when daily activities should be performed.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2017

Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas

Natural and anthropogenic hazards are frequently responsible for disaster events, leading to damaged physical infrastructure, which can result in loss of electrical power for affected locations. Remotely-sensed, nighttime satellite imagery from the Suomi National Polar-orbiting Partnership (Suomi-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) can monitor power outages in disaster-affected areas through the identification of missing city lights. When combined with locally-relevant geospatial information, these observations can be used to estimate power outages, defined as geographic locations requiring manual intervention to restore power. In this study, we produced a power outage product based on Suomi-NPP VIIRS DNB observations to estimate power outages following Hurricane Sandy in 2012. This product, combined with known power outage data and ambient population estimates, was then used to predict power outages in a layered, feedforward neural network model. We believe this is the first attempt to synergistically combine such data sources to quantitatively estimate power outages. The VIIRS DNB power outage product was able to identify initial loss of light following Hurricane Sandy, as well as the gradual restoration of electrical power. The neural network model predicted power outages with reasonable spatial accuracy, achieving Pearson coefficients (r) between 0.48 and 0.58 across all folds. Our results show promise for producing a continental United States (CONUS)- or global-scale power outage monitoring network using satellite imagery and locally-relevant geospatial data.

da/night band↗
DOE OSTI2022

Exceedance Probabilities and Recurrence Intervals for Extended Power Outages in the United States

This report provides estimates of recurrence intervals and conditional exceedance probabilities for major power outages by U.S. region between 2015 and 2021. Additionally, we provide estimates for grid management, particularly outages caused by California’s public safety power shutoffs (PSPS), and for natural outages caused by major hurricanes. Outage recurrence intervals are the average number of years between outage events, and conditional exceedance probabilities are the likelihoods that a customer who experiences a major power outage will experience an outage exceeding a given duration. Major outage events are those that affect 10,000 or more customers, as defined by the U.S. Department of Energy’s (DOE’s) Electric Emergency Incident and Disturbance Report, called OE-417 (DOE 2020). These results can be applied to determine the likelihood of experiencing long-duration outages, which can be integrated into cost-benefit analyses of resilience solutions and broader energy resilience studies.

Ericson, Sean [National Renewable Energy Laborator↗
DOE OSTI2024

Quantifying the economic costs of power outages owing to extreme events: A systematic review

Quantifying the economic cost of long-duration power outages is crucial to justifying investments in resiliency and reliability improvements. However, extensive study on the subject complicates the identification of power outage costs and determining the most suitable approach to quantify them for an individual, specific facility, particularly in the context of extreme events. Here, this research provides a systematic review of economic studies estimating the impact of environmental disasters at the microeconomic and macroeconomic levels. Of 326 articles, evaluating the costs of power outages in extreme events, this work identified 22 studies that attempted to quantify the economic costs. These findings indicate that quantifying power outage costs lacks standardization, posing challenges for comparing different studies. Most analyses aiming to quantify these costs for utilities, sectors, and the overall economy rely on outdated survey data, which offer generalized rather than specific cost estimations. The costs of power outages exhibit a significant dependence on factors such as the sector involved, the type of customer affected, and the outage duration. To quantify industry costs, the research in this study suggests that using the National Renewable Energy Laboratory's online, open-access Customer Damage Function Calculator is the best option for individual-level assessments of industries, hospitals, offices, education centers, and similar facilities. However, the Interruption Cost Estimate Calculator can estimate outage costs across industrial, commercial, and residential sectors for macroeconomic outcomes. Finally, this article discusses the relative strengths of these methods and tools and the potential directions for future research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

A Hybrid Dynamic/Steady-State Tool With Protection Simulation for Cascading-Outage Analysis of Extreme Events in Power Systems

The bulk electric power grid is subject to vulnerabilities from component outages, which in certain combinations (extreme events) might lead to cascading outages. Some of these outages can be severe enough to trigger brownouts and blackouts. Much is known about mitigating the first few failures near the beginning of a cascade, but there are few established methods and tools for directly analyzing the risks of cascading component outages over a longer time scale. Current power system tools have limited ability to perform detailed and accurate cascading-outage analysis, which could be computationally intensive. The Dynamic Contingency Analysis Tool (DCAT) enables power system planning engineers to more realistically assess the consequences of extreme contingencies and potential cascading events across their systems and interconnections. DCAT has several unique features: (i) detailed hybrid dynamic and steady-state analysis of power systems to mimic real-world cascading outages, (ii) detailed modeling of protection systems embedded in the dynamic simulation, (iii) simulation of corrective action after transients, (iv) simulation of islanding , and (v) high-performance computing capability to simulate a large number of contingencies in a reasonable time. DCAT outputs will help find technically sound solutions to reduce the risk of cascading outages. This paper provides details of DCAT methodology and shows its capabilities with extreme events on real-world cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Integrated Framework of Multisource Data Fusion for Outage Location in Looped Distribution Systems

Accurate outage location is essential for expediting post-outage power restoration, minimizing outage duration, and enhancing the resilience of distribution networks. With the advent of advanced metering infrastructure, data-driven outage location methods have significantly advanced beyond traditional approaches that rely on manual inspections. However, existing methods still face critical challenges, like reliance on single-source data, limited ability to handle partially observable systems or difficulties with loop networks. To the best of our knowledge, no single approach has comprehensively addressed all of these challenges at once. To this end, this paper proposes a comprehensive multisource data fusion framework for outage locations via probabilistic graph networks. The framework consists of three key phases. First, a novel method for reconstituting distribution networks with loops is developed, transforming looped networks into multiple radial subnetworks that retain all outage causalities of the original network. Second, Bayesian network (BN) models are established for each subnetwork, integrating multiple data sources and network structures. Finally, a joint Gibbs sampling mechanism, featuring forward and backward information flow, is designed to merge data from separate BN models and maximize the utilization of limited evidence, ensuring accurate outage location identification. In conclusion, the framework was validated on two modified public test systems, and comparative studies confirmed its effectiveness.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Lagrange-Based Options for Relay Satellites to Eliminate Earth-Mars Communications Outages During Solar Superior Conjunctions

Recent conjunction class Mars human mission plans have generally assumed that there will inevitably be periods of communications outages between Earth and Mars. This has significant cost and risk implications for not only Mars missions, but also precursor missions in the lunar environment. But are there ways to avoid these outages? The potential exists for communications to be interrupted by Solar Superior Conjunctions (SSCs). Depending on the communications system, used, there can be communications outages up to as many as 78 days. The higher bandwidth systems experience the greatest outage. If these communications channels are interrupted due to an SSC, there are of course resulting challenges to mission operations. An outage of a few days to a few weeks could allow minor disturbances to become major concerns or even trigger subsystems failures. An inability to consult with the ground at the wrong time could result in loss of mission, loss of an element, or loss of life. Each planet in the solar system has a set of five Lagrange points associated with it and the Sun. At any given point in time, a planet or either its L4 or L5 point is visible to any other planet in the solar system, regardless of the position of the sun relative to the two. Thus, L4 and L5 have high value as relay systems to prevent communications outages. There are four sets of solar Lagrange points that may be of potential use in this study: Mars-Sun L4 and L5 points, Earth-Sun L4 and L5, Venus-Sun L4 and L5, and Mercury-Sun L4 and L5. A candidate relay satellite system will be identified, with consideration of both new technology developments and existing telecommunications satellites. This system may have implications for not only the Mars human mission architectures, but also Gateway and human lunar surface architectures as these other studies are tasked with paving the way to human Mars missions. If Mars communications outages can be eliminated, then the degree of autonomy necessary in Mars and precursor systems may be reduced.

Relay Satellite↗
DOE OSTI2024

Estimating Critical Customer Outages Resulting from Extreme Hurricanes

US power outage data has been collected by organizations such as Oak Ridge National Laboratory (ORNL) through Environment for Analysis Geo-Located Energy Infrastructure (EAGLE-I: freely available) and poweroutage.us (commercial data: available to purchase). However, these sources do not provide information specific to outages of critical customers. Critical customers include entities, facilities, and individuals whose continuous access to electricity is essential for public safety, emergency response, disaster recovery, the well-being of vulnerable populations, public safety and order, and public utilities such as natural gas, communications, water and sanitation. Identification and geolocation of critical customers is crucial for understanding and addressing the effects of power outages on essential services and ensuring that necessary measures are taken to maintain their operations during power disruptions. This work is a first step towards estimating the occurrences of critical customer outages and developing a critical customer power outage data repository. This work estimates outage incidents of critical customers through spatiotemporal mapping of power outage data, weather data, building data, and critical infrastructure network data. Our results show that critical customer effects vary across different counties. We provide appropriate mathematical explanations and simplifications to define and systematize the proposed approach.

Bhusal, Narayan [ORNL] (ORCID:0000000222752145)↗
DOE OSTI2024

Analysis and Mitigation of Cascading Outages Using an Interaction Graph Addressing Transient Stability

Cascading outages of power systems pose great threats to system security and reliability, potentially leading to large-scale blackouts. For analysis and mitigation of cascading outages, this paper proposes a transient stability-incorporated interaction graph. This graph statistically quantifies the interactions among line outages and instabilities of generators, which can model propagation paths and patterns of cascading outages. Compared with an interaction graph that only models line outages, this new interaction graph provides important insights on how transient instability occurs along with cascading outages. It also offers more effective strategies for mitigating outage propagation. The proposed interaction graph can be constructed from datasets of historical or simulated cascading events. It is demonstrated on an NPCC 140-bus system with mitigation strategies.

Guo, Zhenping↗
DOE OSTI2026

Consumer safety-oriented scheduling of rotating power outages during heat waves

Extreme heat events have widespread effects on power systems, reducing available generation capacity, limiting transmission capabilities, and causing unusual demand patterns on the consumer side. As these combined effects expose bulk transmission systems to potential large-scale blackouts, utilities may be required to schedule and apply rotating outages, by temporarily and alternately disconnecting distribution substations to reduce overload. However, utilities lack mechanisms to inform these events, exacerbating the negative effects of heat waves on affected communities. This paper introduces a novel framework for scheduling rotating outages during heat waves while considering impacts on consumers’ safety. Instead of random sequential load shedding, we propose a methodology to rotate power outages considering a metric that quantifies the indoor overheating risk of groups of consumers during a power outage. The overheating risk is derived from a detailed building simulation using CityBES, where the buildings are modeled based on available data—use type, year built, floor area, number of stories, location—while presence of air conditioning and occupancy are calibrated from smart meter data. Based on the metric, an algorithm to schedule the rotating outages is applied to prioritize feeders for disconnection at each hour according to their overheating risk to meet a utility load reduction target. Applied to two substations and seven feeders in the Portland General Electric territory, the results show that this approach effectively leads to the lowest overheating risk during the resulting outage schedules, with an average 10.1% lower overheating compared to uninformed schedules.

Building thermal simulation↗
DOE OSTI2025

Evaluating the Impact of Power Outages on Occupancy Patterns During the 2021 Texas Power Crisis

Large-scale power outages, such as those caused by extreme weather events, have a big impact on human behavior. A short power outage is merely a nuisance for most, and may not change people's locations. An outage that lasts for a few hours can result in spoiled food and medical supplies, and people will have to restock spoiled items. Long outages result in temperatures outside tolerable levels in homes, and may prompt people to acquire supplies, such as generators and gas, or change location. The long outages during Winter Storm Uri in Texas resulted in millions of dollars in property damage due to freezing pipes. This level of damage is expected to result in a sharp increase in supply runs and contractor activity. In this paper, we present a tool to explore differences in visiting patterns before, during, and after power outages. It allows to compare different points of interest like medical facilities, grocery stores, hardware stores, and other types of businesses.

big data↗
DOE OSTI2024

Historical Power Outages of the United States and the Social Vulnerability Index

Several works have been documented in the literature to study the societal effect of power outages and to analyze their correlation with the Social Vulnerability Index (SVI). Because the SVI is calculated based on the summed rank of multiple vulnerability factors for environmental hazards, it can include factors irrelevant to power outages caused by extreme events. This work performs a detailed correlation analysis for social vulnerability and power outages by considering different SVI themes (e.g., socioeconomic status, household composition, racial and ethnic minority status, and housing and transportation) and power outages with and without a threshold for extreme weather events. Although there is some relation between specific themes and aspects of power outages and the SVI in the results, there is no strong distinction between power outage durations and low vs. high SVI values. These results point to the need for further research that grounds the specific factors and methods used to develop SVI and related indices to energy services and power systems disruptions.

Bhusal, Narayan↗