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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Gulf of Mexico Offshore Wind Transmission - Literature Review and Gaps Analysis: Environmental Considerations, Community Readiness, and Infrastructure

The ability to effectively and efficiently connect offshore wind energy resources to end users in the Gulf of Mexico, requires coordinated transmission planning to ensure that electric transmission facilities can adequately support future offshore development. The Gulf of Mexico has substantial wind resources in both shallow shelf waters and deeper waters off the shelf where fixed bottom and floating wind technologies would be most appropriate. Most interest in offshore wind development to date has been in the central and western portions of the Gulf of Mexico (Louisiana and Texas) in federal and state waters. As a companion study to other federal activities in the offshore wind transmission space, including the Atlantic Offshore Wind Transmission Literature Review and Gaps Analysis, the Atlantic Offshore Wind Transmission Study, the West Coast Offshore Wind Transmission Literature Review and Gaps Analysis, the West Coast Offshore Wind Transmission Study, and the Advancing Offshore Wind Energy in the United States: U. S. Department of Energy Strategic Contributions Toward 30 Gigawatts and Beyond Report, this literature review and gaps analysis for offshore wind transmission in the Gulf of Mexico builds off previous literature reviews and supports the role of federal leadership to facilitate offshore wind energy. The overarching goal of this document is to identify gaps and lay the groundwork to inform coordinated transmission planning, ocean co-use, existing energy infrastructure, and siting associated with offshore wind energy development in the Gulf of Mexico. There are unique regional considerations for offshore wind transmission, which are summarized herein based on a review and assessment of publicly available information.

08 HYDROGEN↗
DOE OSTI2024

7-8 GHz Point-to-Point Testing

Wireless spectrum is a limiting resource for continued economic growth in the United States. As discussed in the recent National Spectrum Strategy (NSS), wireless spectrum underpins several aspects of the U.S. economy and the demand for additional spectrum is driving the need for realizing spectrum sharing to enable continued development. At the same time, wireless spectrum is an essential foundation of critical energy infrastructure, including electric, oil, and natural gas resources. In particular, wireless point-to-point (P2P) links are the backbone of vast infrastructure networks that enable the flow of sensor and control information needed to manage critical energy sector infrastructure in the United States. These links will only become more important as the energy sector incorporates more diverse sensing and more efficient control mechanisms, which increases system complexity and data volume requiring more resilient communications. Therefore, the continued economic development of the U.S. depends on determining novel approaches to spectrum management that balance both broad access for advanced wireless technologies and resilience for critical infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Visualization Within the Department of Energy: NREL IEEE VIS Application Spotlight

This presentation highlights the role of advanced visualization techniques at the National Renewable Energy Laboratory (NREL) in supporting cutting-edge research across diverse energy domains. From immersive analytics and uncertainty visualization to high-resolution and real-time data analysis, NREL's visualization capabilities enable scientists to explore complex datasets more effectively. These tools are critical for advancing research in materials science, renewable energy technologies, biofuels, electric vehicle infrastructure, energy efficiency - from industrial processes to entire communities - and then bringing these innovations to practice through energy systems integration. NREL's visualization tools drive innovation across renewable energy and grid modernization efforts by providing deeper insights and improving decision-making.

grid modernization↗
DOE OSTI2026

An AI-driven framework for evaluating local and state authorities’ permitting processes

The demand for new energy infrastructure is increasing across the United States, but heterogenous permitting processes and embedded requirements across different local jurisdictions can cause project delays, increase “soft costs,” and hinder developer expansion. This study analyzes the variability in local permitting requirements across the U.S. and develops a quantitative approach to describe their clarity and effectiveness in enabling infrastructure project development. By using an Energy Language Model (ELM), a large language model (LLM) for energy technologies, we systematically gathered permitting information from nearly 300 state-, county-, and city-level documents, creating a structured dataset of requirements and procedures on an unprecedented scale and speed. Our analysis revealed that local (city and county) permitting requirement documents are underrepresented compared to state-level guidance documents, which can impede timely and cost-effective installation of new electric infrastructure. Our validation process showed that the final database has an accuracy of approximately 95%. We, further, created a new quantitative method to score permitting requirements for clarity and efficiency, with electric vehicle supply equipment as an initial use case. The average local permitting document scored a 1.8 out of 5, which we interpret as meaning that half of the requirements developers face when installing electric infrastructure are ambiguous, increasing both cost and time. We also created a “Generalized Permit Process”, highlighting common procedural steps and identifying specific opportunities for municipalities to improve their documentation. This research establishes a systematic and scalable framework for evaluating the complexities of local infrastructure permitting processes by combining LLM-powered data collection and quantitative scoring. The framework enables policymakers and developers to identify and mitigate procedural bottlenecks, with the expectation that these improvements can accelerate application review and approval, reduce project costs, and expedite connection to utility distribution grids. As a foundational approach for streamlining local project development processes, this study’s methods are intended to be extended to a wide range of energy applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Techno-Economic Assessment of Data Center Load Demand Powered by Small Modular Reactors and Distributed Energy Resources

The rapid increase in data center energy demand, driven by AI and large-scale data processing, poses significant challenges to global energy infrastructure. Data centers require substantial and reliable energy for continuous operations and high-performance computing. Current electrical grids face issues such as transmission bottlenecks and aging infrastructure, making it difficult to meet these demands. Integrating inverter-based-resources (IBRs) like solar and wind presents both opportunities and challenges due to their intermittent nature. Small Modular Reactors (SMRs) offer a promising solution with their enhanced safety, modularity, reliability, and scalability, providing consistent base load power ideal for data center operations. This study presents a comprehensive techno-economic assessment of powering data center load demand using a combination of SMRs and IBRs with grid-connected and islanded mode. This study utilized Idaho National Laboratory’s (INL) HPC data center hourly load profiles and Xendee microgrid optimization platform to conduct the analysis. In this configuration, SMRs serves as the primary base load power source, consistently providing a steady supply of electricity necessary to meet the minimum load demand of the data center with support from the IBRs. Key performance indicators such as Levelized Cost of Electricity (LCOE), Net Present Value (NPV) has been calculated to assess the economic feasibility. The findings from this research will underscore the strategic benefits of integrating SMR plant with DERs – particularly for critical infrastructure load such as data centers.

14 - SOLAR ENERGY↗
DOE OSTI2026

Dataset of Generative AI Workload Power Profiles

This dataset provides a collection of high-resolution (5/10 Hz or every 0.2/0.1 seconds) power consumption profiles for generative artificial intelligence (GenAI) workloads executed on NLR's High Performance Computing (HPC) platform Kestrel. The dataset also includes examples of representative whole-facility power profiles generated using a bottom-up, event-driven, data center energy model . This dataset is designed to support research in energy modeling, infrastructure planning, energy system integration, and sustainability analysis for AI-driven computing systems. The dataset captures time-resolved electrical power measurements across a diverse set of configurations, including variations in job type (inference vs. training), workload (LLM vs. image generation), datasets, and number of compute nodes. Power traces are provided in a standardized format and include both raw/instantaneous and aggregated files. Each profile is accompanied by metadata describing workload parameters, enabling reproducibility and cross-study comparison. The dataset is intended for use in applications such as data center infrastructure planning, energy modeling, demand response and grid impact studies, and development and validation of system-level simulation tools. By making these workload-specific power profiles publicly available, this dataset aims to address the current lack of open, empirical energy data for generative AI systems and to facilitate transparent, reproducible research on the energy and environmental impacts of large-scale AI deployment. If you use this dataset, please cite the associated publication: Vercellino et al., “Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning,” arXiv:2604.07345 (2026).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Resilient Communities, Maryland (RCM): A Framework for Community-Driven Energy Resilience (Final Technical Report)

The Resilient Communities, Maryland (RCM) project integrates community-based participatory research (CBPR) approaches into energy resilience planning. The combination of qualitative, community-driven data and quantitative utility data improves both the effectiveness and efficiency of assessing the impacts of disruptions to energy infrastructure. Centered around a metric of critical services access, RCM created a repeatable framework for evaluating and modeling energy resilience in communities and promoted community engagement, resulting in more equitable stakeholder participation and improved decision-making processes for siting infrastructure to improve community energy resilience.

14 SOLAR ENERGY↗
DOE OSTI2025

Master Services Agreement - Flexible Feeder/Distribution System Support: Cooperative Research and Development (Final Report)

PGE will engage NREL on a broad range of projects related to the integration of distributed energy resources (DERs) into the utility's operations. This portfolio of work could include projects focused on DER adoption models, advanced distribution management system (ADMS) and distributed energy management system (DERMS) design, DER dispatch strategy development, and DER valuation framework development. Additional topics could include long-term energy planning, renewable energy, energy efficiency and demand-side management. As well as technology evaluations and design guidance for building retrofits and new construction projects, energy and energy infrastructure planning, policies, and markets (and their analysis), energy storage, energy security and resilience (including energy system-related cybersecurity), transportation and mobility, technology integration analysis. Additionally, other assistance as requested by PGE consistent with NREL’s expertise.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Defense Resilience Technical Assistance Options - Initial Overview

The Defense Resilience Technical Assistance (TA) project, a collaboration between the DOE Grid Deployment Office and the DoD, aims to enhance energy infrastructure at military installations and utilities and the surrounding community. It focuses on improving energy system performance, addressing power infrastructure inadequacies, enhancing power quality, reducing cyber sabotage impacts, and strengthening digital supply chains. Defense Resilience Technical Assistance Options - Initial Overview. Intend to tailor to the pilot installation.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Securing Future Energy Supplies: From Renewables to Microreactors

This session will provide insight into how future energy deployments, critical to national-level programs focused on reducing carbon emissions, can be secured-by-design using lessons learned from current energy infrastructure. It will begin with an overview of current threats and risks associated with renewable energy assets and systems, primarily wind and solar, focusing on their control architecture and key system functions for both efficient and safe operations. This talk will then translate the key takeaways from current renewable infrastructure into applications for securing future energy systems, including microreactors and small modular reactors (SMRs), based on planned concepts of operations and control. Microreactors and SMRs are intended to be factory-assembled with commercially available components and deployed in more remote or distributed environments, necessitating centralized control centers, remote monitoring, and offsite maintenance and technical support. All of these factors lead these assets to a security posture and controls more similar to today's renewable energy assets than today's nuclear reactors, which represents a significant shift in mindset for the nuclear industry. This talk will provide justification for this shift as well as a path forward to motivate securing these groundbreaking technologies from the outset of their design and deployment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Fostering a Guiding Multiscale Model for the Development of Advanced MgB 2 Hydrogen Storage Materials (Final Technical Report)

Project Goal and Objective. The demand for energy and for an upgraded energy infrastructure has steadily grown, as have the needs for energy independence and alternatives to our reliance on petroleum. Hydrogen is considered the most viable fuels for wide-scale implementation in the near future as it is less-polluting, non-toxic, and has more stored energy than petroleum. It is envisioned that hydrogen can eventually become the prime energy carrier, integrating the transportation, grid, and chemical sectors in a way that improves resiliency, diversifies feedstocks, and affords new economic opportunities. A key remaining challenge is the development materials with enhanced gravimetric and volumetric hydrogen storage capacities that offer a higher performance than compressed gas. These materials would eliminate the need for large-scale compression, thereby dramatically reducing the footprint and cost of gas storage. The high gravimetric and volumetric hydrogen capacities of complex hydrides has prompted an intensive investigation of the potential of this class of materials as hydrogen storage media over the past 25 years. Among the many complex hydrides that have been explored, magnesium borohydride, Mg(BH 4 ) 2 , has been found to possess the best combination of practical thermodynamic properties. These include a gravimetric H 2 density of 14.9 wt% H 2 and thermodynamics for the dehydrogenation of Mg(BH 4 ) 2 to MgB 2 (equation 1) (ΔH° = 39 kJ/mol H 2 , ΔS = 112 J/K mol H 2 ) which lie in the narrow window required Mg(BH 4 ) 2 $\Leftrightarrow$ MgB 2 + 4 H 2 (1) for reversibility under moderate pressure and temperature. However, overcoming the extremely slow kinetics of the reversible release of hydrogen by this material in the solid state is a daunting challenge. At temperatures greater than 400 °C, the borohydride releases up to 14 wt% hydrogen giving MgB 2 . We discovered that the direct re-hydrogenation of MgB 2 to Mg(BH 4 ) 2 can be accomplished under 950 bar H 2 at 400 °C. While this demonstrated that complete reversibility can be achieved, the conditions employed are far too extreme for commercial hydrogen storage applications. More recently, we found through US DOE funded research projects (EERE HyMARC and HySCOR), that hydrogen cycling, can be accomplish at much milder conditions upon modification of the borohydride or boride. Guided by these discoveries these discoveries, the objective of this research project was to obtain key information that will enable the development of a model of reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 . The ultimate goal of our efforts is to attain a model of this transformation that can be utilized to accelerate development further advanced materials. This project directly follows on discoveries that were made over the course of a US DOE, EERE HyMARC project that was focused on improvement of the hydrogen cycling kinetics of modified MgB 2 . We found that that mechanical milling with graphene results the desired, pronounced kinetic enhancement. The dramatic lowering of the conditions required for the hydrogenation of MgB 2 is a significant step towards overcoming its chemical inertness allowing its development as a practical onboard hydrogen storage material. However, the exact nature of the modification(s) of MgB 2 that is responsible for its activation towards hydrogenation is completely unknown. This situation is not unique, as efforts to develop hydrogen storage materials typically have a narrow focus rather than a comprehensive approach that takes atomic level bonding and structure; molecular dynamics; long range, nano- and mesoscale-structure and their interconnection all into account. The goal of this project was the development of a comprehensive, multi-scale computational model of reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 that can be utilized for development of higher performance versions of the modified material. Development of the model requires determination of: 1) the bulk, nano-scale, and meso-scale structural changes occurring at elevated pressure following mechano-chemical modification of MgB 2 ; 2) the reaction pathway of the reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 ; 3) the effect of elevated pressure and mechano-chemical modification on the chemical reaction pathways; 4) the interactions at solid-gas interfaces; and particle surfaces; and 5) the kinetics and thermodynamic parameters associated with each step of the hydrogenation reaction pathway. This investigation required advanced techniques as preliminary, standard XRD, 11 B NMR, and FTIR analysis showed no signs of material modification. In order to gain this level of understanding of modified MgB 2 , required the teaming of a diverse group of experts and state-of-the art experimental capabilities at the University of Hawaii at Manoa (UHM) and collaborating National Laboratories: Craig Jensen , Department of Chemistry (PI and Project Director), solid state, solution, and high pressure NMR spectroscopy; solid-state synthesis; and high pressure hydrogenation (collaboration with SNL); Godwin Severa , Hawaii Natural Energy Institute (co-PI) calorimetry; infrared and Raman spectroscopy (collaboration with NREL); Dera , high pressure X-ray diffraction including in situ experiments (collaboration with ANL); Hope Ishii , Hawaii Institute of Geophysics electron microscopy investigations (collaboration with LBNL); and Joe Brown , Mechanical Engineering , material electronic structure and electric field effects.

08 HYDROGEN↗
NASA NTRSDate not supplied

Comparison Study of Machine Learning Techniques to Predict Flight Energy Consumption for Advanced Air Mobility

This paper addresses the need to predict the flight energy consumption of aerial vehicles in the presence of wind using machine learning techniques. The presented work is critical to achieving sustainable and efficient operations for Advanced Air Mobility (AAM) and to evaluating the readiness of the ground-supporting energy infrastructure, e.g., electric grid and AAM portals. The flight energy consumption is described using the "energy per meter" (EPM) metric. We present a comparison study of influential machine learning techniques in predicting EPM using real-world flight test data. We presented new results of using the Decision Tree, Random Forest, and linear regression techniques, along with our previous results using the Recurrent Neural Network and Feed Forward Neural Network techniques. The comparison results show that the Linear Regression method outperforms other methods on the basis of the Mean Squared Error and error variance.

Machine Learning↗
NASA NTRSDate not supplied

NASA Initiatives to Support Renewable Energy and Sustainable Infrastructure

Initiatives to build and manage climate-resilient infrastructure require spatially explicit environmental and climate information. NASA’s vantage point of Earth from space provides valuable observations that, in concert with additional information, can be used to inform both the design and operation of infrastructure that builds resilience to climate stressors. In this presentation, we provide an overview of how NASA Earth science is used to support decision-making associated with climate adaptation and mitigation, with a particular focus on renewable energy and sustainable infrastructure. Much of this work is currently delivered through NASA’s Prediction of Worldwide Energy Resources (POWER) project, which generates high quality solar and meteorological data products that are customized to the needs of user communities. Importantly, these products are delivered through a variety of web-based applications that make it easier for users to access relevant and timely information. We will highlight several examples of how the impact of POWER is scaled via a robust user community and discuss further plans to expand impact. Additionally, this presentation will highlight efforts of the NASA Earth Science Division’s Energy & Infrastructure Applications program to expand collaborative activities with researchers and practitioners that work on renewable energy and sustainable infrastructure.

Allison K Leidner↗
DOE OSTI2024

Multiscale approaches for optimizing the impact of strain on Na-ion battery cycle life

Abstract The high costs and geopolitical challenges inherent to the lithium-ion (Li-ion) battery supply chain have driven a rising interest in the development of sodium-ion (Na-ion) batteries as a potential alternative. Unfortunately, the larger ionic radius of Na limits the reversibility of cycling because of the extensive atomic rearrangements that accompany Na-ion insertion, which in turn limit diffusion and charging speed, and lead to rapid degradation of the electrodes. The Center for Strain Optimization for Renewable Energy (STORE) was established to address these challenges and develop new electrode materials for Na-ion cells. This article discusses the current state-of-the-art materials used in Na-ion cells and several directions that STORE believes are critical to understand and control the structural and volumetric changes during the reversible (de)insertion of large cations. Graphical abstract Highlights Understanding the fundamental way materials respond to localized strains at the atomic length-scale is a critical first step in the development of highly reversible, long cycle life, Na-ion insertion hosts. This perspective explores a variety of methods that can be employed to mitigate the detrimental effects of large strain. The insights gained from these investigations should help lay the foundation for the creation of more economical and sustainable batteries that could have immediate impact on global energy infrastructure. Discussion Although there is near universal agreement that electrochemical energy storage must be an integral part of a green-energy future, there is less agreement about how to reduce the cost of energy storage. Replacing high-cost lithium-ion cells with lower-cost sodium-ion batteries is one option frequently considered in future energy models, but the details of what can be achieve with optimized sodium cell performance remains unclear. Here we posit that developing methods to mitigating strain on the electrode particle length scale is a key factor for achieving long-cycle-life sodium-ion batteries. Mitigating strain on the atomic scale suppress electrode-level volume change. Allowing for fast cycling in materials without the problems of electrode cracking or delamination. We further posit that understanding volume change in sodium-ion electrodes at a fundamental level will lead to the designing new sodium-ion electrode materials that will allow for efficient, stable, lower-cost energy storage.

Brady, Michael J.↗
DOE OSTI2024

Criticality Analysis of Wind Turbine Components - Intern Poster [Poster]

Wind turbines are an important part of critical energy infrastructure, with wind farms generating more than 10% of US energy in 2023. The goal of this project is to identify and analyze major, common components of wind turbines to reach a preliminary understanding of which should be considered most critical in terms of turbine operation and attack surface. At the time of this project, minimal data was available regarding component costs and lead times, so a qualitative risk assessment approach was used. Components were given a score of 1-5 in four categories– cost to repair, operational downtime, ease of physical attack, and ease of cyber attack. An overall component criticality score was assigned based on the sum of those scores, with a higher score indicating higher criticality. The turbine control system was identified as the most critical component, closely followed by the blades, structural components, and gearbox. This is ongoing project, and further research on the supply chain for wind turbine components will allow for a deeper and more concrete understanding of component criticality.

17 WIND ENERGY↗
DOE OSTI2026

Public water supply infrastructure extensification and diversification in surface waters is insufficient to meet future demands in Texas

The data were developed to evaluate the capacity of existing and potential new surface water supply infrastructure to meet projected public water demands across districts in Texas under multiple future socioeconomic and climate scenarios. The database integrates hydrologic, water quality, infrastructure, energy, cost, demographic, and demand-projection information for candidate surface water supply locations. Candidate sites include stream reaches, waterbodies, reservoir surplus locations, and potential new reservoir sites. Water availability is characterized using historical and projected flow conditions, while site suitability is evaluated using five indicators: Water Availability Index (WAI), Water Quality Index (WQI), Energy Requirement Index (ERI), Water Treatment Cost (WTC), and Water Infrastructure Cost (WIC). The datasets include statewide candidate-site information, district-level demand projections under Shared Socioeconomic Pathways (SSPs), runoff-based allocation constraints, climate-stress metrics, and optimization outputs evaluating alternative infrastructure planning strategies. Optimization results compare Business-as-Usual (BAU) and All Surface Water (AllSW) demand-management approaches under both scaled and fixed cost-cap strategies. Associated validation datasets provide district-level feasibility assessments, infrastructure selection outcomes, cost-cap utilization, demand satisfaction metrics, and constraint diagnostics. Additional datasets quantify projected changes in storage and flow conditions as well as water availability stress for both existing and newly selected intake locations under the SSP5 scenario for mid-century and late-century climate conditions. Together, these datasets support assessment of the extent to which surface-water infrastructure expansion and diversification strategies can satisfy future public water demands while accounting for hydrologic, economic, and planning constraints across Texas. Dataset(s) Description Dataset_preoptimization.xlsx Comprehensive pre-optimization dataset containing candidate water-supply sites and associated hydrologic, water-quality, infrastructure, climate, demographic, runoff, and demand-projection variables used as inputs to the optimization analyses. Includes variable descriptions and the full statewide candidate-site database. District_level_site_selection.zip - Compressed archive containing all SSP-specific district-level optimization result files MESIO_ssp1_results.xlsx District-level site selection results for SSP1 (MESIO). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. MESID_ssp2_results.xlsx District-level site selection results for SSP2 (MESID). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. LCMRD_ssp3_results.xlsx District-level site selection results for SSP3 (LCMRD). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-Low_ssp4l_results.xlsx District-level site selection results for SSP4-Low (IRDev-Low). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-High_ssp4h_results.xlsx District-level site selection results for SSP4-High (IRDev-High). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. RSIM_ssp5_results.xlsx District-level site selection results for SSP5 (RSIM). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. tx_hydrological_stress.xlsx Hydrological stress dataset for existing and newly selected intake locations. Includes projected mid-century and late-century changes, gain/loss classifications, planning strategy information, and accompanying variable descriptions. Also includes water-stress metrics derived from historical and projected low-flow conditions.

Okoye, Perpetua I. (ORCID:0000000215545033)↗
NASA NTRS2017

NASA Earth Observations Informing Energy Management Decision Making

The Energy Sector is experiencing increasing impacts from severe weather and shifting climatic trends, as well as facing a changing political climate, adding uncertainty for stakeholders as they make short- and long-term planning investments. Climate changes such as prolonged extreme heat and drought (leading to wildfire spread, for example), sea level rise, and extreme storms are changing the ways that utilities operate. Energy infrastructure located in coastal or flood-prone areas faces inundation risks, such as damage to energy facilities. The use of renewable energy resources is increasing, requiring more information about their intermittency and spatial patterns. In light of these challenges, public and private stakeholders have collaborated to identify potential data sources, tools, and programmatic ideas. For example, utilities across the country are using cutting-edge technology and data to plan for and adapt to these changes. In the Federal Government, NASA has invested in preliminary work to identify needs and opportunities for satellite data in energy sector application, and the Department of Energy has similarly brought together stakeholders to understand the landscape of climate vulnerability and resilience for utilities and others. However, have these efforts improved community-scale resilience and adaptation efforts? Further, some communities are more vulnerable to climate change and infrastructure impacts than others. This session has two goals. First, panelists seek to share existing and ongoing efforts related to energy management. Second, the session seeks to engage with attendees via group knowledge exchange to connect national energy management efforts to local practice for increased community resilience.

Eckman, Richard↗