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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 OSTI2023

Distributed clean energy opportunities for US oil refinery operations

The oil and gas industry is increasingly seeking operational improvements to reduce costs and emissions while improving resilience. This study describes techno-economic analysis of opportunities for distributed energy resources that could be integrated to support oil and gas companies’ economic, environmental, and energy resiliency goals. Specifically, the analysis evaluates solar photovoltaics, wind turbines, battery energy storage, landfill gas, biomass, municipal solid waste-to-energy, solar steam for process heat, combined heat and power, and electrolyzers for hydrogen production at two hypothetical refineries, one located in Louisiana and the other in southern California. These technologies could reduce the sites’ consumption of grid electricity and/or natural gas and thus can help reduce emissions. This study employs the ReOPT tool and System Advisor Model to evaluate the techno-economic potential for clean energy technologies to support refineries in achieving energy goals, including energy cost savings, resiliency, and emissions reductions. Results indicate that the associated costs of emissions reductions via several distributed clean energy technologies are competitive with other emissions reduction strategies such as energy efficiency, reducing flaring, direct carbon capture and sequestration, and markets under certain conditions. There are also cost beneficial opportunities for the use of renewable energy for refining, especially for resilience, depending on local conditions such as resources and utility costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Parameterization of arctic hydrometeor physics using new precipitation measurement technologies: Final Report

Predictions of precipitation are highly sensitive to the accuracy of parameterized growth and sedimentation processes, especially in remote regions such as the Arctic where observations are scarce. The goal of this study was to combine measurements of meteorological conditions and retrievals from passive and active remote sensors to provide refined parameterizations of precipitation properties and processes with a particular focus on the Arctic. To accomplish the project goals, new instrumentation was used from the Oliktok Point Mobile Facility and the Utqiagvik (Barrow) North Slope of Alaska ARM site focusing in particular on Multi-Angle Snowflake Camera (MASC) data. The MASC is the first device able to automatically photograph precipitation particles in free-fall from multiple angles while simultaneously measuring their fall speed. The MASC installed at the ARM Oliktok Point and Utqiagvik facilities was used to examine the nature of Arctic precipitation, taking particular advantage of the unique suite of precipitation, meteorological, and remote sensing instrumentation that is available at the high latitude sites. Combined with radiometer data we were able to explore the relationship between precipitation particle characteristics and the clouds where the snow is created. Ground-based wind measurements provided detailed data on turbulence. Further theoretical work explored the physical mechanisms controlling precipitation size distributions, the physics determining hydrometeor fallspeed, and the existence of general solutions to the Navier-Stokes equations for falling particles. Outreach work introduced hydrometeor classification to classrooms across the United States.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Nuclear Waste Tank Emission Contributions to Particle Size Distribution

Pollutants from anthropogenic activities including industrial processes are ubiquitous to the environment. To understand the impact from industrial aerosol on climate and human health, industrial aerosol needs to be better characterized. Here, in this study, particle number concentrations were used as a proxy for atmospheric pollutants, which include both particles and gases. Particle concentration and size distribution were measured using a scanning mobility particle sizer (SMPS) approximately 4.5 km from primary industrial areas at the Savannah River Site in Aiken, SC. Industrial areas include numerous nuclear waste storage and processing tanks. The SMPS data were divided into two groups depending on the wind direction measured onsite to categorize transport from the industrial area or from elsewhere. Industrial contributions were found to have a higher concentration of particles with sizes less than 200 nm, 859 ± 564 cm -3 , in comparison to non-industrial attributed particles, 733 ± 495 cm -3 on average from March-July 2021. For sizes larger than 200 nm, industrial and non-industrial particles have a similar concentration, 89 ± 59 cm -3 and 99 ± 61 cm -3 , with non-industrial concentrations being slightly larger. To confirm that industrial particles could travel to the sampling location, air dispersion modeling was completed for specific case studies during the sampling period. The atmospheric dispersion modeling results confirmed that particles released at the industrial areas reached the sampling location when the wind direction was favorable for transport from the industrial areas. The greater concentration of smaller-sized particles in industrial emissions has implications for typical particulate measurements (PM2.5), heath impacts, and climatological influences.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Turbulent Flux Measurements of the Near‐Surface and Residual‐Layer Small Particle Events

Abstract According to recent field studies, almost half of the New Particle Formation (NPF) events occur aloft, in a residual layer, near the top of the boundary layer. Therefore, measurements of the meteorological parameters, precursor gas concentrations, and aerosol loadings conducted at the ground level are often not representative of the conditions where the NPFs take place. This paper presents new measurements obtained during the Turbulent Flux Measurements of the Residual Layer Nucleation Particles, conducted at the Southern Great Plains research site. Vertical turbulent fluxes of 3–10 nm‐sized particles were measured using a sonic anemometer and two condensation particle counters with nominal cutoff diameters of 3 nm and 10 nm mounted at the top of the 10‐m telescoping tower. Aerosol number size distribution (5–300 nm) was determined through the ground‐based Scanning Mobility Particle Sizers. The size selected (15–50 nm) particle hygroscopicity was derived with the Humidified Tandem Differential Mobility Analyzer. The ground level observations were supplemented by vertically‐resolved measurements of horizontal and vertical wind speeds and aerosol backscatter. The data analysis suggests that (a) turbulent flux measurements of 3–10 nm particles can distinguish between near‐surface and residual‐layer small particle events; (b) sub‐50 nm particles had a hygroscopicity value of 0.2, suggesting that organic compounds dominate atmospheric nanoparticle chemical composition at the site; and (c) current methodologies are inadequate for estimating the dry deposition velocity of sub‐10 nm particles because it is not feasible to measure particle concentration very near the surface, in the diffusion sublayer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Long-Term Photovoltaic System Performance in Cold, Snowy Climates

As countries around the world transition towards renewable energy, there is increasing interest in using photovoltaic (PV) technologies to help decarbonize northern and alpine communities due to their scalability and affordability. However, a barrier to large-scale adoption of PV in cold climates is long-term performance uncertainty under snowfall, freeze-thaw cycles, low temperatures, and high winds. In this work, we provide a comprehensive review of published silicon degradation rates in cold Koppen-Geiger climate classifications of Dfb (humid continental), Dfc (subarctic), and ET (tundra). We first analyze the system degradation rates of three subarctic ground-mounted photovoltaic sites in North America using the RdTools year-on-year method: an Al-BSF double-axis tracking site in Fairbanks, Alaska (65degrees N); a PERC and silicon heterojunction bifacial vertical and south-tilted site in Fairbanks, Alaska; and a PERC south-facing fixed-tilt site in Fort Simpson, Northwest Territories (62degrees N). Degradation rates of these newly analyzed sites vary between -0.4%/year and -1.5%/year. Combining these data with previously reported cold climate degradation rates, we show that the distribution of cold climate degradation peaks at -0.1%/year to -0.2%/year but has a large tail with rates above -0.5%/year. The average reported cold climate degradation rate is -0.45%/year, whereas the median value is -0.33%/year. These results suggest that despite frequent freeze-thaw cycles and potential exposure to high wind and snow loads, PV systems in cold climates tend to degrade slower than PV systems in warmer climates. The limited sample size of reported degradation rates in cold climates (27) motivates the need for further data acquisition and monitoring efforts as new technologies are deployed.

14 SOLAR ENERGY↗
DOE OSTI2021

A novel network-based approach to determining measurement representation error for model evaluation of aerosol microphysical properties

Atmospheric aerosol size and abundance influence radiative effects and climate change. To date, efforts to constrain global climate models’ radiative forcing with in situ aerosol observations have been hamstrung by uncertainty. One source of error, the regional “representation error,” arises when accurate but sparse single-point measurements of atmospheric aerosol distributions are compared with a model value, assuming that the single-point measurement is representative of the model domain. The Portable Optical Particle Spectrometer network in the Southern Great Plains (POPSnet-SGP) campaign has demonstrated that a network of nearly autonomous aerosol instruments operating at ambient temperature and relative humidity (with low measurement error) may be used to quantify measurement representation error and investigate the factors introducing heterogeneity in aerosol distributions across a rural, continental background region. Measurements were made using Portable Optical Particle Spectrometer (POPS) instruments at several sites for five months across the Department of Energy’s Aerosol Radiation Measurement Southern Great Plains (ARM-SGP) User Facility in the central USA. Measurement representation error decreased with longer averaging periods (20-40 % between 1 sec and 1 day), varied between sites by 10 – 20 % for aerosol concentration 140 – 2500 nm in diameter (N_140), and was higher for aerosols > 400 nm in diameter (N_400). Our measurements also show the influence of local meteorology on aerosol surface area (A_140) and size distributions: A_140 is positively correlated with wind speed and relative humidity, negatively correlated with precipitation, and lower given westerly winds. Based on this study, we conclude that the POPSnet approach provides considerably more insight into the spatial variability in the aerosol population that can be used to constrain climate models than would be available from similar networks of PM 2.5 monitors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Solar PV, Wind Generation, and Load Forecasting Dataset for ERCOT 2018: Performance-Based Energy Resource Feedback, Optimization, and Risk Management (P.E.R.F.O.R.M.)

This report describes the Advanced Research Projects Agency-Energy Performance-Based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) Electric Reliability Council of Texas (ERCOT) dataset consisting of load, solar, and wind deterministic and probabilistic forecasts at three timescales. This dataset consists of 1 year of time-coincident load, wind, and solar actuals and probabilistic forecasts for a region similar to ERCOT. All the data are stored in Hierarchical Data Format 5 (HDF5) files and have been uploaded to an Amazon Web Services repository. The ERCOT data set has 2 years (2017, 2018) of actuals and 1 year (2018) of probabilistic forecasts. These data are provided at various spatial (i.e., site-level, zone-level, and system-level) and temporal scales (i.e., day-ahead, intraday, and intra-hour). Specifically, data are provided for 125 existing wind sites, 22 existing solar sites, 139 proposed wind sites, and 204 proposed solar sites.

14 SOLAR ENERGY↗
DOE OSTI2024

Spatially resolved land and grid model of carbon neutrality in China

China has committed to achieve net carbon neutrality by 2060 to combat global climate change, which will require unprecedented deployment of negative emissions technologies, renewable energies (RE), and complementary infrastructure. At terawatt-scale deployment, land use limitations interact with operational and economic features of power systems. To address this, we developed a spatially resolved resource assessment and power systems planning optimization that models a full year of power system operations, sub-provincial RE siting criteria, and transmission connections. Our modeling results show that wind and solar must be expanded to 2,000 to 3,900 GW each, with one plausible pathway leading to 300 GW/yr combined annual additions in 2046 to 2060, a three-fold increase from today. Over 80% of solar and 55% of wind is constructed within 100 km of major load centers when accounting for current policies regarding land use. Large-scale low-carbon systems must balance key trade-offs in land use, RE resource quality, grid integration, and costs. Under more restrictive RE siting policies, at least 740 GW of distributed solar would become economically feasible in regions with high demand, where utility-scale deployment is limited by competition with agricultural land. Effective planning and policy formulation are necessary to achieve China’s climate goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Evaluating opportunity for distributed wind energy in rural and agricultural areas

Wind energy is among the most mature renewable energy technologies, accounting for 11% of the current US electricity generation in 2024, with the lowest average levelized cost. While it is known that substantial opportunity exists for further development, a key question has been where wind energy is best suited compared to other technologies. This study leverages an immense dataset of parcel-resolved technoeconomic potential for the contiguous United States, focusing on distributed wind (DW) energy—a configuration where one or more turbines, typically 30–60 m in height are used to satisfy nearby energy needs. The analysis is conducted at multiple spatial scales and considers land use, crop land, census, and incentive program data to determine the most opportune areas for market development. The results show that rural, agricultural and residential areas are most suited to DW. Connection type (in front of, or behind the meter) and regulations determine the best application, while siting constraints, economics, demand and the wind resource determines the optimal size of turbine.

17 WIND ENERGY↗
DOE OSTI2023

Onsite Energy Techno-Economic Analysis Using REopt

Since 2019, the National Renewable Energy Laboratory (NREL) has collaborated with IEDO's Combined Heat and Power (CHP) Deployment Program and the CHP Technical Assistance Partnerships (TAPs) to expand the capabilities of NREL's publicly available REopt® tool for techno-economic analysis of on-site energy. As a result, capabilities to analyze heating and cooling loads and serve those loads with CHP were added to the REopt tool in 2021. Currently, NREL is using REopt to evaluate the economics and feasibility of deploying distributed energy resources at sites of 3-5 manufacturers. The analysis is based on location, site-specific load data, customized utility bill analysis, and other criteria such as resilience needs and decarbonization targets. The objectives of the current effort are to (1) assist manufacturers with analyzing on-site energy options, including CHP, solar photovoltaics (PV), wind, and battery storage, (2) validate the capabilities and use of REopt to provide technical assistance to manufacturers, and (3) publish case studies showcasing the engagement, key takeaways, and lessons learned. Future work is expected to include additional REopt capabilities for evaluating other technologies to reduce scope 1 emissions, such as electrifying process heating loads, using carbon-free fuels, and other clean heat strategies.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Predicting Wind Loading and Instability in Solar Tracking PV Arrays

Wind loading and the fluctuating pressure loads it creates on PV panel surfaces are associated with multiple degradation mechanisms and failures. Modest wind speeds create reversing loads that can initiate cell cracks and weather cracked cells. Stronger wind speeds and extreme weather events can lead to larger scale forces and the aerodynamic instability known as torsional galloping. All these effects are dependent on the complex coupling between wind speed, panel orientation, and a myriad of other hardware and site-specific factors. In this work, we present the latest developments from our work to build an open-source, high-performance computing (HPC) fluid dynamics solver to predict and mitigate these effects. This simulation package allows users to easily specify different array layouts, solar-tracking angles, panel geometries, and weather conditions before automatically generating a refined computational mesh and solving for the unsteady loading on each panel surface. Small domains (e.g., a single panel row in isolation) can be solved on a modern laptop, while larger domains or very high-fidelity studies can be solved on distributed or HPC resources with minimal modifications to the underlying problem specification. We present preliminary case studies obtained using this simulation package and highlight how increased wind speeds combined with sub-optimal tracking angles can exacerbate degradation drivers.

aerodynamics↗
DOE OSTI2023

Wind RD&T: On Site Wind for Rural Load Centers

This presentation will provide an overview of the "On Site Wind for Rural Load Center" project for an FY23 research, development, and technology review with other Wind Energy Technologies Office researchers and DOE program managers. This copy of slides is appropriate for public release.

17 WIND ENERGY↗
DOE OSTI2023

Building the Case for Hybrid Energy Developments: Webinar Recording Day 2

INL, PNNL, and NREL, with support from our academic and industry partners, hosted a 2-day webinar to learn more about the benefits of hybrid energy systems, considerations for designing the right system for communities, and practical tools that can help with the design and development process. In Day 2 of this webinar, the focus was on tools that can be used to help inform design decisions for hybrid systems, including resource analysis, siting, resilience, valuation, and resource optimization. Day 2 also highlighted funding opportunities for hybrid systems.

14 SOLAR ENERGY↗
DOE OSTI2023

Building the Case for Hybrid Energy Developments: Webinar Recording Day 2

INL, PNNL, and NREL, with support from our academic and industry partners, hosted a 2-day webinar to learn more about the benefits of hybrid energy systems, considerations for designing the right system for communities, and practical tools that can help with the design and development process. In Day 2 of this webinar, the focus was on tools that can be used to help inform design decisions for hybrid systems, including resource analysis, siting, resilience, valuation, and resource optimization. Day 2 also highlighted funding opportunities for hybrid systems.

14 SOLAR ENERGY↗
DOE OSTI2024

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Concurrent Cooling Effects of Dynamic Line Ratings on Wind Plant Gen-Tie Lines

This report was prepared for the Wind Energy Technology Office for the FY 2022, quarter 2 deliverable. This details the use of dynamic line rating technology to rate a series of gen tie lines connecting wind plants to the regional transmission lines. This consists of two primary study regions, the first on the desert west of Idaho Falls, and the second in the region east of the Cascades along the Columbia River Gorge. The TREAD program that was developed at INL was used to create generated gen-tie lines based on nearby regional transmission line connections. The capacity availability of the gen tie lines are compared with the power production of the wind farms. Overall, the INL Site location shows a much greater capacity for the gen-tie lines due to the higher wind speeds. Across both locations, the HRRR data shows higher wind speeds than observed at the observational weather stations. For both the Columbia Gorge and Idaho areas, the sites show that a statically rate gen-tie could carry additional capacity far above the rated during periods of high wind due to the concurrent cooling effects.

17 WIND ENERGY↗