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At least 343 records · Page 19

Consumer Benefits of Clean Energy: The resilience value of residential solar + storage systems in the continental U.S.

Meeting national and state decarbonization goals requires a transition to clean energy technologies. Energy efficiency, demand flexibility, renewable energy and storage can reduce consumers’ electricity bills, lower total electricity system costs, and provide health and resilience benefits. Berkeley Lab developed a series of briefs that explore these consumer benefits of a clean energy transition. Clean energy resources that are located behind the meter have the potential to benefit the hosting customers by providing affordability, environmental, and reliability and resilience value. Solar plus storage systems (PVESS) are clean energy resources that can supply backup power without requiring fuel resupply or increasing local emissions. This report examines the regional value of PVESS for resilience by calculating a benefit-cost ratio (BCR) that considers the annual resiliency benefits of PVESS and the annualized cost of the investment. In addition, we estimate the expected technical mitigation potential of PVESS systems at the county-level to these expected events, and characterize the customer interruption costs by determining the value of lost load at the state level.

14 SOLAR ENERGY↗

Developing Data-Driven Synthetic Infrastructure Models for Resilience Analysis

Research on infrastructure resilience has produced promising methods to simulate and optimize complex networks to improve performance. However, restrictions on sharing infrastructure models and the steep cost of developing and maintaining infrastructure models presents a roadblock to adoption. To overcome this limitation, this research focuses on methods to create data-driven infrastructure models that will help improve infrastructure resilience and security. The analysis couples incomplete utility data, geospatial data, machine learning, and synthetic network generation methods to rapidly develop and update infrastructure models. The methods are validated using realistic utility models and site-specific data, with a focus on Puerto Rico due to its unique infrastructure challenges and available data. This research highlights promising opportunities for the use of synthetic network generation and machine learning to create infrastructure models when very little data is available. Results demonstrate that hybrid methods, which combine sparse utility data with synthetic models, can enhance model accuracy, and machine learning can predict model attributes using training data from other models. However, the complexity of infrastructure systems means that even minor changes in network connectivity can significantly impact simulation results. Resilience analysis using synthetic infrastructure models shows that while some system behaviors are preserved, the magnitude of disruptions may not be accurately represented, indicating the need for more research and validation before using synthetic models for critical infrastructure investment decisions. The framework outlined in this report represents a significant advance to infrastructure model development and could be applied to additional domains and sites. Future research will continue to streamline and validate methods to help reduce roadblocks to resilience analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Guide for Public Utility Commissions: Building Internal Technical Capacity and Recruiting Talent for Grid Resilience

This guide offers insight into how PUCs can strategically expand their technical workforce to meet evolving gird resilience demands. It outlines critical skill sets needed to support informed regulatory decision-making around resilience, such as modeling and weather forecasting, electric power systems analysis, and advanced data interpretation. In addition, it provides strategies for developing technical talent both internally and through additional recruitment efforts. Two appendices provide a list of grid resilience training resources and a compendium of sample job descriptions that reflect grid resilience technical expertise for PUC consideration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Best Practices for Resilience Hub Development and Management

The Carbon League and its community partners in East St. Louis, Illinois, have identified five facilities to serve as resilience hubs. These hubs are intended to support the local community through a range of services and resources during blue-sky (everyday), gray-sky (pre-event), and black-sky (emergency) conditions. Transforming these facilities into fully functional resilience hubs requires a broad operational improvement and programmatic planning roadmap. This memo outlines best practices to guide the development of these resilience hubs in East St. Louis, including recommendations for infrastructure services; safety and physical protection; community services; operational protocols; and a phased implementation strategy aligned with realistic funding and capacity constraints. Infrastructure recommendations include strengthening electric power, communications, water, sanitation, and transportation/logistics capabilities, all of which are essential for hubs that may serve as cooling and warming centers, distribution points, and information hubs during emergencies. Safety recommendations focus on accessibility, emergency action planning, indoor air quality, and secure storage of critical equipment. A phased roadmap provides guidance from immediate, low-cost readiness actions to long-term optimization and community integration. Performance metrics and maintenance protocols ensure continuous improvement and operational readiness. This guidance draws on best practices that can be used to support the development of resilient, community-centered hubs capable of enhancing public safety, health, and well-being during everyday operations and emergencies alike.

99 GENERAL AND MISCELLANEOUS↗

Historical Contingency in Microbial Resilience to Hydrologic Perturbations

Development of reliable biogeochemical models requires a mechanistic consideration of microbial interactions with hydrology. Microbial response to and its recovery after hydrologic perturbations (i.e., resilience) is a critical component to understand in this regard, but generally difficult to predict because the impacts of future events can be dependent on the history of perturbations (i.e., historical contingency). Fundamental issues underlying this phenomenon include how microbial resilience to hydrologic perturbations is influenced by historical contingency and how their relationships vary depending on the characteristics of microbial functions. To answer these questions, we considered a simple microbial community composed of two species that redundantly consume a common substrate but specialize in producing distinct products and developed a continuous flow reactor model where the two species grow with trade-offs along the flow rate. Simulations of this model revealed that (1) the history of hydrologic perturbations can lead to the shifts in microbial populations, which consequently affect the community's functional dynamics, and (2) while historical contingency in resilience was consistently predicted for all microbial functions, it was more pronounced for specialized functions, compared to the redundant function. As a signature of historical contingency, our model also predicted the emergence of hysteresis in the transitions across conditions, a critical aspect that can affect transient formation of intermediate compounds in biogeochemistry. This work presents microbial growth traits and their functional redundancy or specialization as fundamental factors that control historical contingencies in resilience.

59 BASIC BIOLOGICAL SCIENCES↗

Framework for Assessing Impact of Wave-Powered Desalination on Resilience of Coastal Communities

Coastal communities face unique challenges in maintaining continuous service from critical infrastructure. This research advances capabilities for evaluating the impact of using wave energy to desalinate water on the resilience of coastal communities. The study focuses on the feasibility of using wave energy conversion to provide drinking water to communities in need and applying resilience metrics to quantify its impact on the community. To assess the feasibility of wave-powered desalination, this research couples the open-source software Wave Energy Converter SIMulator (WEC-Sim) and Water Network Tool for Resilience (WNTR). This research explores variations in both the wave resource (location, seasonality, and duration) and the ability to maintain drinking water service during a disruption scenario by applying the simulation framework to three case studies, which are based on communities in Puerto Rico. The simulation framework provides a contextualized assessment of the ability of wave-powered desalination to improve the resilience of coastal communities, which can serve as a methodology for future studies seeking the integration of wave-powered desalination with water distribution systems.

16 TIDAL AND WAVE POWER↗

Assessing Resilience in Lane Detection Methods: Infrastructure-Based Sensors and Traditional Approaches for Autonomous Vehicles

Traditional autonomous vehicle perception subsystems that use onboard sensors have the drawbacks of high computational load and data duplication. Infrastructure-based sensors, which can provide high quality information without the computational burden and data duplication, are an alternative to traditional autonomous vehicle perception subsystems. However, these technologies are still in the early stages of development and have not been extensively evaluated for lane detection system performance. Therefore, there is a lack of quantitative data on their performance relative to traditional perception methods, especially during hazardous scenarios, such as lane line occlusion, sensor failure, and environmental obstructions. We address this need by evaluating the influence of hazards on the resilience of three different lane detection methods in simulation: (1) traditional camera detection using a U-Net algorithm, (2) radar detections using infrastructure-based radar retro-reflectors (RRs), and (3) direct communication of lane line information using chip-enabled raised pavement markers (CERPMs). The performance of each of these methods is assessed using resilience engineering metrics by simulating the individual methods for each sensor technology’s response to related hazards in the CARLA simulator. Using simulation techniques to replicate these methods and hazards acquires extensive datasets without lengthy time investments. Specifically, the resilience triangle was used to quantitatively measure the resilience of the lane detection system to obtain unique insights into each of the three lane detection methods; notably the infrastructure-based CERPMs and RRs had high resistance to hazards and were not as easily affected as the vision-based U-Net. However, while U-Net was able to recover the fastest from the disruption as compared to the other two methods, it also had the most performance loss. Overall, this study demonstrates that while infrastructure-based lane keeping technologies are still in early development, they have great potential as alternatives to traditional ones.

Patil, Pritesh↗

Resilience: Concepts and Measures

Inertia, the resistance of an ecosystem property to change under stress, is distinguished from resilience, which refers to the degree, manner. and pace of change or recovery in ecosystem properties following disturbance. In turn, these two terms are differentiated from 'stability'. which is used here to refer to the pattern of natural fluctuation in ecosystem properties in the absence of major exogenous disturbance. Four component attributes of resilience are reviewed in the context of Mediterranean-climate examples. The elasticity component concerns the rate of recovery of an ecosystem property following disturbance; amplitude, the threshold of stress beyond which recovery to the initial state does not occur; hysteresis, the degree to which the pattern of recovery after stress differs from that of deterioration under chronic stress, and malleability the ease with which the ecosystem can become permanently altered. Each ecosystem property will typically reveal a different level of resilience to a given stress and stressor. The degree of recovery should not be expected to be complete in any event, due to sample variability and stochastic events. In cyclicallystable ecosystems, the pattern of recovery should be measured in light of this periodicity, and short-term (within-cycle) recovery distinguished from long-term (between-cycle) recovery. The prediction of resilience properties of ecosystems can be approached through a knowledge of the modular structure of foodwebs, through knowledge of the autecological adaptations of key species to the stressor, or through cumulative experience of the response to disturbance at the community level. At present there is much room for investigation of each of these approaches in Mediterranean-climate ecosystems.

Westman, Walter E.↗

An Approach for the Assessment of System Upset Resilience

This report describes an approach for the assessment of upset resilience that is applicable to systems in general, including safety-critical, real-time systems. For this work, resilience is defined as the ability to preserve and restore service availability and integrity under stated conditions of configuration, functional inputs and environmental conditions. To enable a quantitative approach, we define novel system service degradation metrics and propose a new mathematical definition of resilience. These behavioral-level metrics are based on the fundamental service classification criteria of correctness, detectability, symmetry and persistence. This approach consists of a Monte-Carlo-based stimulus injection experiment, on a physical implementation or an error-propagation model of a system, to generate a system response set that can be characterized in terms of dimensional error metrics and integrated to form an overall measure of resilience. We expect this approach to be helpful in gaining insight into the error containment and repair capabilities of systems for a wide range of conditions.

Torres-Pomales, Wilfredo↗

Assessing and Promoting Functional Resilience in Flight Crews During Exploration Missions

The NASA Human Research Program works to mitigate risks to health and performance on extended missions. However, research should be directed not only to mitigating known risks, but also to providing crews with tools to assess and enhance resilience, as a group and individually. We can draw on ideas from complexity theory to assess resilience. The entire crew or the individual crewmember can be viewed as a complex system composed of subsystems; the interactions between subsystems are of crucial importance. Understanding the interactions can provide important information even in the absence of complete information on the component subsystems. Enabled by advances in noninvasive measurement of physiological and behavioral parameters, subsystem monitoring can be implemented within a mission and during training to establish baselines. Coupled with mathematical modeling, this can provide assessment of health and function. Since the web of physiological systems (and crewmembers) can be interpreted as a network in mathematical terms, we can draw on recent work that relates the structure of such networks to their resilience (ability to self-organize in the face of perturbation). Some of the many parameters and interactions to choose from include: sleep cycles, coordination of work and meal times, cardiorespiratory rhythms, circadian rhythms and body temperature, stress markers and cognition, sleep and performance, immune function and nutritional status. Tools for resilience are then the means to measure and analyze these parameters, incorporate them into models of normal variability and interconnectedness, and recognize when parameters or their couplings are outside of normal limits.

Shelhamer, M.↗

Considering Risk and Resilience in Decision-Making

This paper examines the concepts of decision-making, risk analysis, uncertainty and resilience analysis. The relation between risk, vulnerability, and resilience is analyzed. The paper describes how complexity, uncertainty, and ambiguity are the most critical factors in the definition of the approach and criteria for decision-making. Uncertainty in its various forms is what limits our ability to offer definitive answers to questions about the outcomes of alternatives in a decision-making process. It is shown that, although resilience-informed decision-making would seem fundamentally different from risk-informed decision-making, this is not the case as resilience-analysis can be easily incorporated within existing analytic-deliberative decision-making frameworks.

Torres-Pomales, Wilfredo↗

Self-Guided Multimedia Stress Management and Resilience Training for Flight Controllers

Stress and anxiety-related problems are among the most common and costly behavioral health problems in society, and for those working in operational environments (i.e. astronauts, flight controllers, military) this can seriously impact crew performance, safety, and wellbeing. Technology-based interventions are effective for treating behavioral health problems, and can significantly improve the delivery of evidence-based health care. This study is evaluating the effectiveness, usefulness, and usability of a self-guided multimedia stress management and resilience training program in a randomized controlled trial (RCT) with a sample of flight controllers at Johnson Space Center. The intervention, SMART-OP (Stress Management and Resilience Training for Optimal Performance), is a six-session, cognitive behavioral-based computer program that uses self-guided, interactive activities to teach skills that can help individuals build resilience and manage stress. In a prior RCT with a sample of stressed but otherwise healthy individuals, SMART-OP reduced perceived stress and increased perceived control over stress in comparison to an Attention Control (AC) group. SMART-OP was rated as "highly useful" and "excellent" in usability and acceptability. Based on α-amylase data, individuals in SMART-OP recovered quicker and more completely from a social stress test as compared to the AC group [1]. In the current study, flight controllers are randomized either to receive SMART-OP training, or to a 6-week waitlist control period (WLC) before beginning SMART-OP. Eligible participants include JSC flight controllers and instructors without any medical or psychiatric disorder, but who are stressed based on self-report. Flight controllers provide a valid analog sample to astronauts in that they work in an operational setting, use similar terminology to astronauts, are mission-focused, and work under the same broader work culture. The study began in December 2014, and to date 79 flight controllers and instructors have expressed interest in the study, 49 of those were cleared for participation, we have screened 44 for eligibility, and 23 have met inclusion criteria. Recruitment is ongoing and the study will continue until December 2016. Outcome measures include perceived stress, perceived control over stress, resilience, mood, personality, emotion regulation, sleep, health behaviors, and psychophysiological data such as 24-hour heart rate, alpha amylase, and urinary and salivary cortisol. We are also collecting user feedback such as usability, working alliance, usefulness, and treatment credibility.

Rose, R. D.↗

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↗

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↗

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.↗

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↗

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↗

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↗