REopt Lite Tutorial: Resilience Inputs
This tutorial gives an overview of a resilience modeling analysis in the REopt Lite™ web tool.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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REopt Lite Tutorial: Resilience Inputs
This tutorial gives an overview of a resilience modeling analysis in the REopt Lite™ web tool.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Structural dynamics of the renewable energy economy: A longitudinal input-output insights for a resilient transition
As countries accelerate their energy transitions, understanding how renewable energy (RE) systems structurally integrate into national economies is essential. This study presents a longitudinal economic input-output (EIO) analysis of the renewable energy sector in South Korea from 2016 to 2022. We develop a novel EIO-based framework that disaggregates the RE sector both by energy source (thermal, hydro, nuclear and renewable) and by industrial function (manufacturing, generation, and services), allowing for a detailed assessment of production dynamics, value-added creation, and import dependency. By quantifying backward and forward linkages and induced economic effects, the analysis reveals persistent structural vulnerabilities in renewable manufacturing and increasing sectoral interdependencies. Results reveal that while the renewable energy sector's production and value-added shares have increased, critical segments remain highly import-dependent, particularly in equipment manufacturing. The analysis highlights systemic gaps in domestic supply chain resilience and offers sector-specific insights for reducing vulnerability and enhancing energy security. Although applied to South Korea as a case study, the proposed framework is designed to be transferable to other national contexts where renewable energy planning requires economic structural insights. The findings offer policy-relevant guidance for enhancing domestic energy resilience and aligning industrial strategy with long-term decarbonization goals.
Economic linkage↗
Cell‐type‐specific transcriptomics uncovers spatial regulatory networks in bioenergy sorghum stems
SUMMARY Bioenergy sorghum is a low‐input, drought‐resilient, deep‐rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum's 4–5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about cell‐type gene expression and regulation in stems was available to enable engineering. To obtain this information, laser capture microdissection was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell‐type‐specific and cell‐preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell‐type‐specific gene regulatory networks (GRNs) revealed that unique transcription factor families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell‐specific transcriptome data was combined with known secondary cell wall (SCW) networks to identify the GRNs that differentially activate SCW formation in vascular sclerenchyma and epidermal cells. The spatial transcriptomic dataset provides a valuable source of information about the function of different sorghum cell types and GRNs that will enable the engineering of bioenergy sorghum stems, and an interactive web application developed during this project will allow easy access and exploration of the data ( https://mc‐lab.shinyapps.io/lcm‐dataset/ ).
09 BIOMASS FUELS↗
Gumby: Quantifying multi-modal model resiliency
With the rise of cheap data and sensors, more use cases are emerging for multi-input models. Research has shown that including multiple data modalities can improve performance, suggesting that deep learning models can successfully learn to leverage complementary information from different modalities. However, this improved predictive power comes with unanticipated costs: additional inputs change model resiliency and expand the threat space for adversarial attacks. We first provide theoretical underpinnings for how adversarial success scales with input dimension. We then characterize the performance of a suite of multispectral deep learning models with different fusion approaches, quantify their relative reliance on different input bands, and evaluate their robustness to naturalistic and adversarial image corruptions.
97 MATHEMATICS AND COMPUTING↗
Data for The Stem Cell-Type Transcriptome of Bioenergy Sorghum Reveals the Spatial Regulation of Secondary Cell Wall Networks
Bioenergy sorghum is a low-input, drought-resilient, deep-rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum’s 4-5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about stem cell-type gene expression and regulation was available to enable engineering. To obtain this information, Laser Capture Microdissection (LCM) was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell-type specific gene regulatory networks (GRNs) revealed that unique TF families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell-specific transcriptome data was combined with a stem developmental transcriptome dataset to identify the GRN that differentially activates the secondary cell wall (SCW) formation in stem xylem sclerenchyma and epidermal cells. The cell-type transcriptomic dataset provides a valuable source of information about the function of sorghum stem cell types and GRNs that will enable the engineering of bioenergy sorghum stems.
Software↗
Architecture for Quantum-in-the Loop Real-Time Simulations for Designing Resilient Smart Grids
With the power grid growing more complex every day with the inclusion of new sensors and regulatory approvals that enable end-users and small local developers to participate in the grid, it is becoming challenging for conventional smart grid simulation, emulation, and testing technologies to keep up. In this work, we propose that quantum-encoded real-time simulations can be helpful under the new paradigm and operational circumstances to solve optimization problems for power grids. By leveraging the principles of quantum mechanics, the proposed quantum-in-loop (QIL) framework will enable better and faster optimization solutions based on real-world, real-time data streams, facilitating the real-time planning and operations of electrical grids that rely on millions of distributed sensors and controllers. Furthermore, QIL will allow researchers and engineers to assist utilities in designing, developing, and de-risking algorithms to optimize power grid operation and resilience by considering inputs from millions of grid-connected devices. QIL framework is being developed to have a self-limiting triage mechanism, which will help engineers and practitioners identify fundamental physical limits on quantum processors, revealing what quantum algorithms can and cannot do in utility-specific use cases and must continue to count on classical high-performance computing infrastructure.
digital real-time simulation↗
A Systems Framework to Enhance the Potential of Camelina as Oilseed Crop (Final Report)
To alleviate the dependency of the United States on fossil fuels, particularly from foreign sources, the transition to biofuel crops has long been proposed as a crucial part of the long-term solution. Camelina sativa has emerged as one of the most promising oilseed crops for domestic biofuel and bioproduct production due to its low agronomic input requirements, natural resilience to a wide range of biotic and abiotic stresses, and the successful testing and approval of its oil-based blends for use in liquid transportation fuels.
09 BIOMASS FUELS↗
Increasing Battery Management System Resilience Following Identification of Sensor Anomalies Using Unknown Input Observer
Explore the source record for details and available documents.
Obrien, Victoria Ann↗
User Objectives and Design Approaches for Microgrids: Options for Delivering Reliability and Resilience, Clean Energy, Energy Savings, and Other Priorities
In fall 2019, the National Association of Regulatory Utility Commissioners (NARUC) and the National Association of State Energy Officials (NASEO) initiated a joint Microgrids State Working Group (MSWG), funded by the U.S. Department of Energy (DOE) Office of Electricity (OE). The MSWG aimed to bring together NARUC and NASEO members to explore the capabilities, costs, and benefits of microgrids; discuss barriers to microgrid development; and develop strategies to plan, finance, and deploy microgrids to improve resilience. Based on member input, the MSWG developed two companion briefing papers to answer key questions about microgrids: (1) User Objectives and Design Approaches for Microgrids: Options for Delivering Reliability and Resilience, Clean Energy, Energy Savings, and Other Priorities and (2) Private Sector, State, and Federal Funding and Financing Options to Enable Resilient, Affordable, and Clean Microgrids. Read together, these resources provide readers with an understanding of both why and how customers—whether an investor-owned, cooperative, or municipal utility; federal, state, or local government entity; individual or group of residential, commercial, and/or industrial customers; or other organization—select, design, and pay for microgrid projects.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A metric framework for evaluating the resilience contribution of hydropower to the grid
This paper will describe a proposed framework for expressing the resilience of hydropower generation and provide initial case studies for three classes of hydropower, run-of-river hydropower, hydropower with reservoirs, and pumped storage hydropower. Hydropower has great flexibility to provide support during and after natural and man-made events that can disrupt critical infrastructure functionality. The concept of the framework provides for consideration of policy and rules, constraints of the water shed and other allocations of water, storage and plant capabilities to produce real and reactive power, and the strength of the delivery network. The paper details a resilience response metric that has inputs of state of storage and plant level constraints on real and reactive power production. Using the definition of resilience, based on maintaining a minimally normal operations, we provide a qualitative assessment of hydropower’s ability to address the various time scales comprising the “R”s of resilience.
13 HYDRO ENERGY↗
Makah Tribe Climate Assessment, Adaptation, and Resilience Planning
Our aim was to develop a Climate Adaptation and Resilience Plan through gathering community input through personal interviews and individual surveys, building from our Climate Impacts Assessment work completed in 2018. This project has collected traditional, cultural, and local knowledge to support the ongoing multi-departmental environmental planning processes of the Makah Tribe. This information was then used to identify specific human wellbeing indicators to inform and enhance Makah tribal policy, management, and decision-making processes. Combined our tribal environmental planning to include the work of the Tribal Resilience Work Group (TRWG) and Oil Spill Work Group (OSWG), which relied on publicly available Western science-based data. While this information provided a strong basis for tribal environmental planning, it does not capture the unique traditional, cultural needs, and local knowledge and tribal voices of the Makah community.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Building Capacity: Solar Photovoltaics Site Assessment and Feasibility Study
While Bhutan is abundant with clean energy hydropower, there are dry months in winter when solar energy could reduce expensive power inputs and bolster Bhutan's energy resilience and independence. As the country explores solar photovoltaic (PV) development as an option to achieve that goal, grid planners and renewable energy experts are partnering with the South Asia Group for Energy (SAGE) to determine the benefits and challenges of building solar energy systems in Bhutan.
14 SOLAR ENERGY↗
Considerations for Fire Service Response to Residential Battery Energy Storage System Incidents
Renewable energy sources (e.g., rooftop photovoltaics, wind turbines) are capable of addressing our grid-level energy challenges by reducing environmental impacts, increasing resiliency, and increasing the supply of input energy. However, renewable energy sources alone are not a complete solution. The generation of power from major renewable energy sources fluctuates with the weather, creating significant challenges in matching electrical power generation to electrical power consumption. The value of renewable power generation sources is multiplied when paired with battery energy storage systems (ESS), which can store excess power generated from renewable energy sources when it is not consumed and deliver that power later when demand exceeds base power generation. Residential ESS units are frequently installed to support renewable energy initiatives by storing energy from intermittent sources such as photovoltaic panels. Residential ESS units also offer an alternative to gas-powered generators or other backup power means. Lithium-ion batteries are the most common residential ESS technology due to their affordability and energy density. Though lithium-ion systems come with benefits, there is also a risk of thermal runaway within this technology which can result in flammable gas release, fire, and explosion. As the installations of these products increase, the frequency of response to fire incidents involving these products will increase. In response to this new and evolving hazard, UL Solutions (ULS) and UL Fire Safety Research Institute (FSRI) have partnered with the International Association of Fire Fighters (IAFF) to conduct a series of large-scale tests sponsored by the US Department of Energy to characterize the challenges for fire fighters responding to fires involving residential energy storage systems. The project focuses on developing size-up and tactical considerations to support the fire service in navigating the evolving modern fireground.
25 ENERGY STORAGE↗
Energy Technology Innovation Partnership Project [Slides]
This presentation introduces the Energy Technology Innovation Partnership Project (ETIPP) and outlines proposed technical assistance to support St. Vincent's House in developing a resilient community hub in Galveston, Texas. The project explores opportunities for on-site energy solutions to ensure continuity of critical services during coastal hazards and grid disruptions. The session aims to gather stakeholder input to refine priorities and inform next steps for resilient, reliable, and cost-effective energy strategies.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Radiation-Induced Noise Resilience of Neuromorphic Architectures
Neuromorphic event-based networks use asynchronous time-dependent information to extract features from input data that can allow for edge-based distributed applications such as object recognition. The noise resilience properties of such networks, especially in the context of space applications, are yet to be explored. In this paper, we use the hierarchy of time surfaces (HOTS) algorithm, which is one of the neuromorphic algorithms, to understand the least and most resilient modules in a neuromorphic network. The HOTS algorithm relies on the computing of time surfaces that maps the temporal delays between neighboring pixels into normalized features that involve many computations that are also found in other neuromorphic networks such as exponential decays, distance computations, etcetera. We implemented HOTS on a Digilent PYNQ board with a Xilinx Zynq 7020 system on a chip, and we subjected the boards running the HOTS network inference to neutron radiation at the Los Alamos Neutron Science Center. Furthermore, we used simulation models from our previous similar experiments on the event-based sensor to create a neutron induced noise model to quantify the effect of this noise on the overall performance of the network. This experiment provides the preliminary measurements of the reliability of the HOTS algorithm and proposes methods to create a more reliable HOTS architecture in future spacecraft missions.
Engineering↗
Accessing and Understanding REopt's Federal Assumptions
REopt is a techno-economic analysis platform accessible as a user-friendly web tool that facilitates life cycle cost analysis of distributed energy resources. It is typically used for preliminary assessments to identify the least-cost technology mix, system sizing, and operations strategies towards agency cost savings and resilience goals. This guide identifies and explains REopt inputs for federal life cycle cost analyses, modified from their commercial default values. These federal input defaults are based on statutory requirements for life cycle cost analyses of energy conservation measures at federal facilities per 10 CFR 436 Subpart A.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Effect of realistic routing on the social burden metric
The distance people travel to reach critical services is a key input to the Social Burden metric used by Sandia’s Resilient Node Cluster Analysis Tool (ReNCAT) in the optimization’s objective function. By default, ReNCAT utilizes Euclidian distances between population blocks and critical facilities when calculating Social Burden. However, these straight-line distances do not reflect how most residents or goods would travel throughout the area. As distance is a vital input to the burden calculation, a more realistic distance calculation will yield more realistic burden values. This work uses real road networks and calculates the shortest distance path between population centers and critical facilities using a standard graph theory approach. These realistic route distances are then used to compute Social Burden for four areas of study. It was found that distances using real road routes are generally, but not always, longer than the Euclidean distance. The increased length increases the final Social Burden metric, however, the overall burden percent change ranged between 17% and 52%, which means the impact of realistic routes relies heavily upon the area’s road topology. It was found that rural locations within an area may have larger burden increases than urban areas as more dense road networks allow routes to more closely follow a straight-line path. Additionally, using the most straight forward routing algorithms requires high computational effort for areas with large road networks. While it is believed this process can be made more performant, that task is beyond this scope of work.
99 GENERAL AND MISCELLANEOUS↗