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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The System Modeling and Analysis of Resiliency in STEReO (SMARt-STEReO)

NASA's Scalable Traffic Management for Emergency Response Operations (STEReO) project aims to leverage Unmanned Aerial Systems (UAS) and UAS Traffic Management (UTM) to improve asset coordination and overall emergency response. One application of STEReO is wildfire response, which is the focus of this research. In order to implement the operations described in the STEReO project, these additions must have tangible benefits and proven safety. To this end, the System Modeling and Analysis of Resiliency in STEReO (SMARt-STEReO) project constructs a simulation model, developed through the Python modeling and resiliency analysis package fmdtools. The model describes wildfire response operations, including current operational concepts and emerging concepts utilizing UAS as described in STEReO. While previous simulation models focus primarily on fire propagation with some models including emergency response intervention, SMART-STEReO evaluates the system performance and resilience benefits gained by the addition of UAS and UTM. Due to the novelty and complexity of the model, initial model verification and validation efforts are conducted and a detailed description of the model is provided. Preliminary results from experimental analysis on the SMARt-STEReO model indicate that when compared to current operations, the addition of UAS in wildfire operations results in improved response efforts, in terms of fewer acres burned, as well as improved system resilience in response to a given fault.

Sequoia Andrade↗
NASA NTRSDate not supplied

Toward Monitoring and Predicting Cognitive Resilience

"Toward Monitoring and Predicting Cognitive Resilience" for IWS 2023 session DS04, Monitoring Cognitive Resilience. Definitions and characterizations of Cognitive Resilience are presented, along with other considerations for monitoring and predicting it in the context of space radiation and other stressors. This session will feature “lightning-style" talks focused on how HRP research could be used in conjunction with work from interagency partnerships to monitor or predict cognitive resilience for astronauts followed by facilitated panel discussion focused on key questions.

cognition↗
DOE OSTI2016

Analyzing Resiliency of the Smart Grid Communication Architectures

Smart grids are susceptible to cyber-attack as a result of new communication, control and computation techniques employed in the grid. In this paper, we characterize and analyze the resiliency of smart grid communication architecture, specifically an RF mesh based architecture, under cyber attacks. We analyze the resiliency of the communication architecture by studying the performance of high-level smart grid functions such as metering, and demand response which depend on communication. Disrupting the operation of these functions impacts the operational resiliency of the smart grid. Our analysis shows that it takes an attacker only a small fraction of meters to compromise the communication resiliency of the smart grid. We discuss the implications of our result to critical smart grid functions and to the overall security of the smart grid.

None, None↗
DOE OSTI2016

Analyzing Resiliency of the Smart Grid Communication Architectures

Smart grids are susceptible to cyber-attack as a result of new communication, control and computation techniques employed in the grid. In this paper, we characterize and analyze the resiliency of smart grid communication architecture, specifically an RF mesh based architecture, under cyber attacks. We analyze the resiliency of the communication architecture by studying the performance of high-level smart grid functions such as metering, and demand response which depend on communication. Disrupting the operation of these functions impacts the operational resiliency of the smart grid. Our analysis shows that it takes an attacker only a small fraction of meters to compromise the communication resiliency of the smart grid. We discuss the implications of our result to critical smart grid functions and to the overall security of the smart grid.

Anas AlMajali, Anas↗
DOE OSTI2017

Increasing Resiliency Through Renewable Energy Microgrids

This paper describes a methodology to quantify the economic and resiliency benefit provided by renewable energy (RE) in a hybrid RE-storage-diesel microgrid. We present a case study to show how this methodology is applied to a multi-use/ multi-function telecommunications facility in southern California. In the case study, we first identify photovoltaic (PV) and battery energy storage system (BESS) technologies that minimize the lifecycle cost of energy at the site under normal, grid-connected operation. We then evaluate how those technologies could be incorporated alongside existing diesel generators in a microgrid to increase resiliency at the site, where resiliency is quantified in terms of the amount of time that the microgrid can sustain the critical load during a grid outage. We find that adding PV and BESS to the existing backup diesel generators with a fixed fuel supply extends the amount of time the site could survive an outage by 1.8 days, from 1.7 days for the existing diesel-only backup system to 3.5 days for the PV/diesel/BESS hybrid system. Furthermore, even after diesel fuel supplies are exhausted, the site can continue to operate critical loads during daytime hours using just the PV/BESS when there is sufficient solar resource. We find that the site can save approximately 100,000 dollars in energy costs over the 25-year lifecycle while doubling the amount of time they can survive an outage. Here, the methodology presented here provides a template for increasing resiliency at telecomm sites by implementing renewable energy solutions, which provide additional benefits of carbon emission reduction and energy cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Proactive Operations and Investment Planning via Stochastic Optimization to Enhance Power Systems Extreme Weather Resilience

We present novel stochastic optimization models to improve power systems resilience to extreme weather events. We consider proactive redispatch, transmission line hardening, and transmission line capacity increases as alternatives for mitigating expected load shed due to extreme weather. Our model is based on linearized or "DC" optimal power flow, similar to models in widespread use by independent system operators (ISOs) and regional transmission operators (RTOs). Our computational experiments indicate that proactive redispatch alone can reduce the expected load shed by as much as 25% relative to standard economic dispatch. This resiliency enhancement strategy requires no capital investments and is implementable by ISOs and RTOs solely through operational adjustments. We additionally demonstrate that transmission line hardening and increases in transmission capacity can, in limited quantities, be effective strategies to further enhance power grid resiliency, although at significant capital investment cost. We perform a cross validation analysis to demonstrate the robustness of proposed recommendations. Our proposed model can be augmented to incorporate a variety of other operational and investment resilience strategies, or combination of such strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Evaluating the resilience benefits of marine energy in microgrids

Marine energy resources could promote clean energy and resilience of coastal and island microgrids, and thus, these applications are a key future market for marine energy development. To demonstrate these benefits, this paper illustrates how inclusion of wave resources into energy resilience solutions can improve overall grid efficiency and sustainability, as well as maintain electricity supply during grid outages. The paper describes a case study evaluation of the potential to add wave energy to the Moloka’i grid as Hawaii strives to meet a 100% clean energy target. The Microgrid Component Optimization for Resilience tool is used to simulate operation in off- grid conditions and size different combinations of wave, solar photovoltaic (PV), wind, storage, and fuel resources required to meet resilience objectives. This research in- vestigates how including wave resources in a microgrid contributes to reducing biofuel generation, producing a zero-greenhouse gas emission profile, and avoiding the over-sizing of PV and battery systems to accommodate periods of unavailability or high demand. Insight from this paper supports the value proposition of wave resources for future markets and informs the relationship between marine generators and microgrids or isolated grids.

Newman, Sarah F.↗
DOE OSTI2024

Thermal Resilience of Residential Building with Thermally Anisotropic Building Envelope Connected to Geothermal Sources

Heat waves and cold snaps have become more frequent and more intense because of climate change. A heat wave and a cold snap are a period of excessively hot and cold weather, respectively, that poses severe risks to building occupants’ health, especially for vulnerable people. They increase electrical energy consumption and put high stress on the grid which leads to potential power outages. Therefore, it is critical to assess and actively improve the thermal resilience of buildings to cope with heat waves, cold snaps, and power outages. The thermally anisotropic building envelope (TABE) is a novel active building envelope that can save energy while maintaining thermal comfort in buildings by redirecting heat and coolness from building envelopes to hydronic loops. When connecting to a ground thermal loop (GL), TABE can utilize the relatively stable temperature of the ground to protect the indoor environment during heat waves and cold snaps. This study assesses the thermal resilience of residential buildings that installed TABE and used ground thermal energy to supply the hydronic loops, abbreviated as ground thermal loop or TABE+GL. The simulation and analysis are conducted for the US Department of Energy prototype single-family detached residential building in the hot climate of Miami, Florida and Tucson, Arizona, and the cold climate of Denver, Colorado, and Rochester, Minnesota. Heat waves and cold snaps were obtained from the historical weather data of 1998-2020 for the studied regions. Three thermal resilience metrics, including the standard effective temperature (SET) degree-hours, the Heat Index, and the Hours of Safety (HOS) were used to quantify the effect of TABE+GL. The results showed that buildings installed TABE+GL could significantly reduce the average SET degree-hours above 30°C, increase HOS, and greatly improve thermal resilience.

Shen, Zhenglai↗
DOE OSTI2025

Overcoming Resilience Challenges on the Outer Banks of North Carolina

In 2021, the Town of Nags Head, located in the Outer Banks region of North Carolina, was among the first cohort of coastal and island communities to participate in the U.S. Department of Energy's Energy Transitions Initiative Partnership Project (ETIPP), which offers technical assistance and cash awards to competitively selected coastal, remote, and island communities seeking to transform their energy systems and increase their energy resilience. As a barrier island separated from mainland North Carolina, Nags Head experiences impacts from extreme weather events, including power outages, especially during hurricane season. To address challenges, the Nags Head ETIPP team sought to improve the town's disaster resilience by ensuring that critical facilities can remain powered during and after extreme events. With support from experts at Sandia National Laboratories, the National Renewable Energy Laboratory, and the Coastal Studies Institute, the community team identified the following goals for its participation in ETIPP: 1. Identify and prioritize critical facilities that, when powered during disruptions, support the town's resilience. 2. Analyze the potential for on-site solar photovoltaic (PV) and storage systems at 2-4 prioritized critical facilities owned and/or operated by the town. 3. Analyze the potential for interconnecting solar PV and storage systems at a cluster of public and privately owned facilities into a resilient microgrid. 4. Explore finance options and utility interconnection requirements and compensation mechanisms. 5. Summarize outcomes and next steps for town leadership.

25 ENERGY STORAGE↗
DOE OSTI2025

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗
DOE OSTI2025

Demystifying the Resilience of Large Language Models: An End-to-End Perspective

Deep neural networks are known to be resilient to random bit-wise faults in their parameters. However, this resilience has primarily been established through evaluations of classification models. The extent to which this claim holds for large-language models remains underexplored. In this work, we conduct an extensive measurement study on the impact of random bitwise faults in commercial-scale language models. We perform an in-depth analysis of the resulting generation outputs. We first expose that these language models are not truly resilient to random bit-flips. While aggregate metrics such as accuracy may suggest resilience, an in-depth inspection of the generated outputs shows significant degradation in text quality. Our analysis also shows that tasks requiring more complex reasoning suffer more from performance and quality degradation. Moreover, we extend our analysis to models with augmented reasoning capabilities, such as Chain-of-Thought or Mixture of Experts architectures, and characterize their failure scenarios under random bit-flips.

Sun, Yu↗
DOE OSTI2020

Power System Resilience Enhancement in Typhoons Using a Three-Stage Day-Ahead Unit Commitment

In this work, we propose a three-stage resilient unit commitment model which considers uncertain typhoon paths and line outages to improve the power system resilience against typhoon events. The proposed solution coordinates resources in response to the worst-case scenario for each possible typhoon path. The optimal decision is based on the characterization of the power system schedule into three stages of preventive control, emergency control, and restoration. Preventive control is performed before the typhoon occurs by quickly adjusting the three-stage resilient unit commitment schedule; emergency control is conducted during the typhoon by shedding local loads to meet the power balance, while other control strategies are assumed to be unavailable due to possible interruptions in the communication system; restoration is realized after the typhoon, when resources are optimally dispatched to repair the outages of critical devices and recover the normal operation state of the power system quickly. Considering the typhoon path uncertainty, we have introduced a stochastic model for possible typhoon paths where all possible affected lines along each typhoon path are assumed to be on outage during the typhoon. Accordingly, we explore the strategy for co-optimizing the three stages in unit commitment. The proposed model is tested on the IEEE 118-bus system and the real-world provincial system to verify its effectiveness.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Deep Reinforcement Learning based Model-free On-line Dynamic Multi-Microgrid Formation to Enhance Resilience

Multi-microgrid formation (MMGF) is a promising solution for enhancing power system resilience. This paper proposes a new deep reinforcement learning (RL) based model-free on-line dynamic MMGF scheme. Additionally, the dynamic MMGF problem is formulated as a Markov decision process, and a complete deep RL framework is specially designed for the topologytransformable micro-grids. In order to reduce the large action space caused by flexible switch operations, a topology transformation method is proposed and an action-decoupling Q-value is applied. Then, a convolutional neural network (CNN) based multi-buffer double deep Q-network (CM-DDQN) is developed to further improve the learning ability of the original DQN method. The proposed deep RL method provides real-time computing to support the on-line dynamic MMGF scheme, and the scheme handles a long-term resilience enhancement problem using an adaptive on-line MMGF to defend changeable conditions. The effectiveness of the proposed method is validated using a 7-bus system and the IEEE 123-bus system. The results show strong learning ability, timely response for varying system conditions and convincing resilience enhancement.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Vulnerability Assessment and Resiliency Planning: The National Renewable Energy Laboratory's Process and Best Practices; May 23, 2014 - June 5, 2015

The National Renewable Energy Laboratory (NREL) is a U.S. Department of Energy (DOE) research laboratory that employs more than 2,500 people. The laboratory focuses on renewable energy and energy-efficiency research and has two campuses along the Front Range of Colorado. In 2014, NREL worked with Abt Environmental Research (then called Stratus Consulting Inc.) to develop a vulnerability assessment and resiliency action plan as part of NREL's Climate Change Resiliency and Preparedness (CCRP) project. This guide describes the process that NREL undertook during this project. NREL used a participatory approach to vulnerability assessment and resiliency planning that emphasized organizational context, building internal capacity, and the application of climate science in a practical and actionable manner.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Energy Resilience Assessment Methodology

With increasing utility grid outages in the United States, there is growing interest in assessing risk and developing mitigations to reduce the impact of grid outages and other power disruptions. The U.S. Department of Energy's National Renewable Energy Laboratory worked with military bases and stakeholders in their local community to develop a replicable energy resilience assessment methodology for sites, bases, and campuses to assess energy risks and develop prioritized solutions to increase site resilience. This includes steps to assess the baseline resilience of the site, identify and score hazards and vulnerabilities, analyze risks based on hazard likelihood and vulnerability probability and consequence, identify and prioritize mitigation actions based on cost, difficulty, and risk reduction, and then develop an action plan and implement solutions. The method focuses on risks to a site's primary missions, infrastructure, and population, as well as risks to infrastructure and population in the surrounding community that may impact the site.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Grid Resilience to Extreme Events (ResiliEX 2.0)

The Grid Resilience to Extreme Events (ResiliEX) 2.0 workshop, co-hosted by Pacific Northwest National Laboratory and Seattle City Light, was held at the Seattle City Hall April 23–25, 2024. This is the second workshop of its kind, with the first one having occurred in Seattle in November 2022. Participants from the second workshop hailed from research organizations, utilities, professional associations, consultants, government organizations, and communities. The purpose of the workshop was to Connect scientists, energy professionals, and policy experts to build knowledge and partnerships Advance the understanding of the science of extreme events and application to the energy system Promote grid planning and engineering that addresses the increasingly complex interdependencies as society combats the climate crisis Understand the role of different decision-makers and policymakers in increasing and accelerating grid resilience Identify new approaches, processes, and structures that should be pursued to increase grid resilience to extreme events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Assessing the Energy Resilience of Office Buildings: Development and Testing of a Simplified Metric for Real Estate Stakeholders

Increasing concern over higher frequency extreme weather events is driving a push towards a more resilient built environment. In recent years there has been growing interest in understanding how to evaluate, measure, and improve building energy resilience, i.e., the ability of a building to provide energy-related services in the event of a local or regional power outage. In addition to human health and safety, many stakeholders are keenly interested in the ability of a building to allow continuity of operations and minimize business disruption. Office buildings are subject to significant economic losses when building operations are disrupted due to a power outage. We propose “occupant hours lost” (OHL) as a means to measure the business productivity lost as the result of a power outage in office buildings. OHL is determined based on indoor conditions in each space for each hour during a power outage, and then aggregated spatially and temporally to determine the whole building OHL. We used quasi-Monte Carlo parametric energy simulations to demonstrate how the OHL metric varies due to different building characteristics across different climate zones and seasons. The simulation dataset was then used to develop simple regression models for assessing the impact of ten key building characteristics on OHL. The most impactful were window-to-wall ratio and window characteristics. The regression models show promise as a simple means to assess and screen for resilience using basic building characteristics, especially for non-critical facilities where it may not be viable to conduct detailed engineering analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗