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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

2022 Standard Scenarios Report: A U.S. Electricity Sector Outlook

This report documents the eighth edition of the annual Standard Scenarios. It summarizes 70 forward-looking scenarios of the U.S. electricity sector that have been designed to capture a wide range of possible futures. In August 2022, the United States Congress passed the Inflation Reduction Act (IRA), a law aimed at accelerating U.S. decarbonization, clean energy manufacturing, and deployment of new power and end-use technologies. This year’s scenarios include representations of the main electricity-sector provisions from IRA and the potential impact on electricity demand. The Standard Scenarios are simulated using the Regional Energy Deployment System (ReEDS) model, which projects utility-scale electricity sector evolution for the contiguous United States using a system-wide, least-cost approach subject to policy and operational constraints. A subset of the scenarios are simulated in the PLEXOS production cost model to obtain a broader suite of metrics at the hourly resolution, which are made available through the National Renewable Energy Laboratory’s (NREL’s) annual Cambium data sets. The scenarios can be viewed and downloaded from NREL’s Scenario Viewer. Annual results are available for the full suite of scenarios in the Standard Scenarios projects in the viewer, whereas the Cambium projects contain hourly data for a subset of scenarios. The Standard Scenarios includes a scenario called the Mid-case, which has central or median values for core inputs such as technology costs and fuel prices, moderately paced demand growth averaging 1.3% per year, and electricity sector policies as they existed in September 2022 (including IRA). The remaining 69 scenarios are created by varying inputs such as technology and fuel prices, resource availability, demand growth, whether nascent generation technologies are allowed, and by introducing national decarbonization constraints.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Harvesting effects on wild bee communities in bioenergy grasslands depend on nesting guild

Conversion of annual crops to native perennial grasslands for bioenergy production may help conserve wild bees by enhancing nest and food resources. However, bee response to the disturbance of biomass harvesting may depend on their nesting location, thus their vulnerability to nest destruction, and the response of the forb community on which they forage. Moreover, because bees have long foraging ranges, effects of local harvesting may depend on the amount of natural habitat in the surrounding landscape. We performed a large-scale one- and two-year experiment in Michigan and Wisconsin, USA, respectively, to examine how grassland harvesting, landscape context, and study year affect the forb community, above- and belowground-nesting bee species richness, community composition, trap nest emergence, and visitation rate. In Wisconsin, harvesting increased forb richness, cover, and evenness compared to unharvested control sites. Harvesting negatively affected aboveground-nesting bee richness and emergence from trap nests, possibly because of nest destruction during the previous harvest. By contrast, harvesting positively affected belowground-nesting bee richness, possibly because of the greater food resource availability and reduced thatch allowing greater access to nesting sites in the soil. Harvesting also affected bee community composition, reflecting the increase in belowground-nesting species at harvested sites. Despite harvesting effects on forb and bee communities, there was no effect on flower visitation rate, indicating little effect on pollination function. We did not find a harvest by landscape context interaction, which, in combination with the negative harvesting effect on trap nest emergence, suggests that harvesting can affect local population growth rather than simply affecting forager aggregation in different resource environments. For bees, there was no harvest by study year interaction, indicating a consistent response over a short timescale. Similarly, in Michigan, belowground-nesting species also responded positively to harvesting, which was more pronounced in sandier soils that are preferred for nesting. However, other components of the Michigan bee and forb communities were not significantly affected by biomass harvesting. Overall, our study demonstrates that harvesting grasslands can positively affect the ~80% of bee species that nest belowground by enhancing nest and/or forage resources, but that conserving aboveground nesters may require leaving some area unharvested.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Data from: Harvesting effects on wild bee communities in bioenergy grasslands depend on nesting guild

Conversion of annual crops to native perennial grasslands for bioenergy production may help conserve wild bees by enhancing nest and food resources. However, bee response to the disturbance of biomass harvesting may depend on their nesting location, thus their vulnerability to nest destruction, and the response of the forb community on which they forage. Moreover, because bees have long foraging ranges, effects of local harvesting may depend on the amount of natural habitat in the surrounding landscape. We performed a large-scale one- and two-year experiment in Michigan and Wisconsin, USA, respectively, to examine how grassland harvesting, landscape context, and study year affect the forb community, above- and belowground-nesting bee species richness, community composition, trap nest emergence, and visitation rate. In Wisconsin, harvesting increased forb richness, cover, and evenness compared to unharvested control sites. Harvesting negatively affected aboveground-nesting bee richness and emergence from trap nests, possibly because of nest destruction during the previous harvest. By contrast, harvesting positively affected belowground-nesting bee richness, possibly because of the greater food resource availability and reduced thatch allowing greater access to nesting sites in the soil. Harvesting also affected bee community composition, reflecting the increase in belowground-nesting species at harvested sites. Despite harvesting effects on forb and bee communities, there was no effect on flower visitation rate, indicating little effect on pollination function. We did not find a harvest by landscape context interaction, which, in combination with the negative harvesting effect on trap nest emergence, suggests that harvesting can affect local population growth rather than simply affecting forager aggregation in different resource environments. For bees, there was no harvest by study year interaction, indicating a consistent response over a short timescale. Similarly, in Michigan, belowground-nesting species also responded positively to harvesting, which was more pronounced in sandier soils that are preferred for nesting. However, other components of the Michigan bee and forb communities were not significantly affected by biomass harvesting. Overall, our study demonstrates that harvesting grasslands can positively affect the 80% of bee species that nest belowground by enhancing nest and/or forage resources, but that conserving aboveground-nesters may require leaving some area unharvested.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Can We Constrain Uncertainty in Hydrologic Cycle Projections?

Abstract Climate change intensifies the Earth's hydrologic cycle, which has far‐reaching consequences including water availability, agricultural production, and electric power generation. The rate of intensification projected by state‐of‐the‐art global climate models (GCMs) with increasing greenhouse gas emissions, however, is highly uncertain. Thackeray et al. (2018, https://doi.org/10.1029/2018GL079698 ) show that these uncertainties are related to how GCMs distribute future precipitation by either strongly increasing extreme precipitation at the cost of nonextreme events or by increasing nonextreme precipitation at the cost of extreme precipitation events. These results could help to constrain uncertainties in future hydrologic cycle intensification, thereby improving our understanding of future water resource availability and extreme hydrologic events.

Prein, Andreas F.↗
DOE OSTI2020

TeraChem Cloud: A High-Performance Computing Service for Scalable Distributed GPU-Accelerated Electronic Structure Calculations

The encapsulation and commoditization of electronic structure arise naturally as interoperability, and the use of nontraditional compute resources (e.g., new hardware accelerators, cloud computing) remains important for the computational chemistry community. Here, we present TERACHEM CLOUD, a high-performance computing service (HPCS) that offers on-demand electronic structure calculations on both traditional HPC clusters and cloud-based hardware. The framework is designed using off-the-shelf web technologies and containerization to be extremely scalable and portable. Within the HPCS model, users can quickly develop new methods and algorithms in an interactive environment on their laptop while allowing TERACHEM CLOUD to distribute ab initio calculations across all available resources. This approach greatly increases the accessibility of hardware accelerators such as graphics processing units (GPUs) and flexibility for the development of new methods as additional electronic structure packages are integrated into the framework as alternative backends. Cost-performance analysis indicates that traditional nodes are the most cost-effective long-term solution, but commercial cloud providers offer cutting-edge hardware with competitive rates for short-term large-scale calculations. We demonstrate the power of the TERACHEM CLOUD framework by carrying out several showcase calculations, including the generation of 300,000 density functional theory energy and gradient evaluations on medium-sized organic molecules and reproducing 300 fs of nonadiabatic dynamics on the B800-B850 antenna complex in LH2, with the latter demonstration using over 50 Tesla V100 GPUs in a commercial cloud environment in 8 h for approximately $1250.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

ATLAS Data Carousel

The ATLAS experiment at CERN's LHC stores detector and simulation data in raw and derived data formats across more than 150 Grid sites world-wide, currently in total about 200PB on disk and 250PB on tape. Data have different access characteristics due to various computational workflows, and can be accessed from different media, such as remote I/O, disk cache on hard disk drives or SSDs. Also, larger data centers provide the majority of offline storage capability via tape systems. For the High-Luminosity LHC (HL-LHC), the estimated data storage requirements are several factors bigger than the present forecast of available resources, based on a flat budget assumption. On the computing side, ATLAS Distributed Computing was very successful in the last years with high performance and high throughput computing integration and in using opportunistic computing resources for the Monte Carlo simulation. On the other hand, equivalent opportunistic storage does not exist. ATLAS started the "Data Carousel" project to increase the usage of less expensive storage, i.e. tapes or even commercial storage, so it is not limited to tape technologies exclusively. Data Carousel orchestrates data processing between workload management, data management, and storage services with the bulk data resident on offline storage. The processing is executed by staging and promptly processing a sliding window of inputs onto faster buffer storage, such that only a small percentage of input data are available at any one time. With this project, we aim to demonstrate that this is the natural way to dramatically reduce our storage cost. The first phase of the project was started in the fall of 2018 and was related to I/O tests of the sites archiving systems. Phase II now requires a tight integration of the workload and data management systems. Additionally, the Data Carousel studies the feasibility to run multiple computing workflows from tape. The project is progressing very well and the results presented in this document will be used before the LHC Run 3.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Coordinated Collaboration between Heterogeneous Distributed Energy Resources

A power distribution feeder, where a heterogeneous set of distributed energy resources is deployed, is examined by simulation. The energy resources include PV, battery storage, natural gas GenSet, fuel cells, and active thermal storage for commercial buildings. The resource scenario considered is one that may exist in a not too distant future. Two cases of interaction between different resources are examined. One interaction involves a GenSet used to partially offset the duty cycle of a smoothing battery connected to a large PV system. The other example involves the coordination of twenty thermal storage devices, each associated with a commercial building. Storage devices are intended to provide maximum benefit to the building, but it is shown that this can have a deleterious effect on the overall system, unless the action of the individual storage devices is coordinated. A network based approach is also introduced to calculate some type of effectiveness metric to all available resources which take part in coordinated operation. The main finding is that it is possible to achieve synergy between DERs on a system; however this required a unified strategy to coordinate the action of all devices in a decentralized way.

Abdollahy, Shahin↗
DOE OSTI2024

Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States (2023 Edition)

Estimates of the potential of renewable energy are essential for understanding how we can decarbonize our electric grid and economy. They provide key data for policymakers, land managers, and energy modelers by defining the quantity, quality, and cost of renewable resources. However, estimating renewable energy potential is challenging and requires frequent updates because of rapid advances in technology, cost reductions, and uncertainty about developable land that are due to social, regulatory, and environmental factors. Additionally, the complex processes involved in renewable energy development require regular reviews of methods and assumptions, which can also impact our understanding of renewable potential. In this, the 2023 edition of this annual report, we present new estimates of the technical potential for land-based wind and solar photovoltaics (PV) for the contiguous United States (CONUS). We also provide cost estimates for the available resources, presenting representative supply curves that can be used in downstream modeling and analysis. Additionally, we introduce the new methodologies used to estimate wind capacity, wind energy losses, transmission cost and representation, updated technology cost and design, and scenarios of siting constraints designed to help bound the uncertainty of renewable potential.

14 SOLAR ENERGY↗
DOE OSTI2024

A Novel Framework to Evaluate the Costs and Potential of Bioenergy in Decarbonization of the U.S. Economy

The long-term strategy of the United States targets reaching economy-wide net-zero emissions by 2050 and a carbon-neutral electricity grid by 2035 (U.S. Department of State and U.S. Executive Office of the President, 2021). Meeting these targets would require considerable changes to the energy system. Some key characteristics of illustrative net-zero energy systems include increased penetration of renewable energy and carbon sources, use of CO2 capture and storage (CCS) in hard-to-abate sectors, and a greater role for energy carriers such as electricity and hydrogen (Davis et al, 2018). Another common feature of such energy systems is the need for carbon dioxide removal (CDR) approaches (Horowitz et al, 2022). Across all these characteristics of net-zero energy systems, bioenergy and biomass feedstock is anticipated to play an important role. Biomass feedstock serves as a renewable carbon source. This can enable conversion of such feedstock into fuels and energy carriers for hard-to-abate sectors such as aviation. Indeed, the U.S. Government has a target to meet all jet fuel demand by 2050 from sustainable aviation fuel (SAF), where biofuel pathways are likely to have an important role (EERE, 2020). Bioenergy is also highly versatile with the possibility to convert feedstock into electricity, hydrogen, liquid fuels, heat or high-value products, based on biomass type, demand and technology availability (Clarke et al, 2022). Combination of bioenergy with CCS can also nominally deliver CDR (Fuhrman et al, 2023). As such, the share of bioenergy is expected to grow by at least five time across scenarios studied for the long-term strategy of the U.S. between 2020 and 2050 (Horowitz et al, 2022). Notwithstanding the role of bioenergy in the energy systems, its deployment, costs and scalability are influenced by a number of factors. Some of these factors pertain to policy interventions such as imposition of a binding decarbonization target either at an economy-wide level or the sectoral level. Resource availability and type of biomass feedstock also varies considerably across regions. From a technological perspective, the readiness of bioenergy conversion pathways is subject to high variability. This influences the costs of deployment. Moreover, the sourcing of feedstock, grid carbon intensity, and co-product handling approaches all affect the life cycle efficacy of bioenergy. The latter, in turn, is particularly important in determining the extent to which bioenergy with CCS or BECCS can effectively deliver CDR (Fajardy and Mac Dowell, 2017).

air emission↗
DOE OSTI2016

Dynamic performance analysis of two regional Nuclear Hybrid Energy Systems

In support of more efficient utilization of clean energy generation sources, including renewable and nuclear options, hybrid energy systems (HES) can be designed and operated as flexible energy resources (FER) to meet both electrical and thermal energy needs in the electric grid and industrial sectors. These conceptual systems could effectively and economically be utilized, for example, to manage the increasing levels of dynamic variability and uncertainty introduced by variable energy resources (VER) such as renewable sources (e.g., wind, solar), distributed energy resources, demand response schemes, and modern energy demands (e.g., electric vehicles) with their ever changing usage patterns. HES typically integrate multiple energy inputs (e.g., nuclear and renewable generation) and multiple energy outputs (e.g., electricity, gasoline, fresh water) using complementary energy conversion processes. This work reports a preliminary dynamic analysis of two realistic HES including a nuclear reactor as the main baseload heat generator and to assess the local (e.g., HES owners) and system (e.g., the electric grid) benefits attainable by their application in scenarios with multiple commodity production and high renewable penetration. It is performed for regional cases - not generic examples - based on available resources, existing infrastructure, and markets within the selected regions. This study also briefly addresses the computational capabilities developed to conduct such analyses.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

The Value of Storage and Demand Response for Renewble Integration

Increased contributions from wind and solar power resources are necessary to meet California’s goal to use 33 percent renewable energy by 2020. Using these renewable resources, however, will substantially increase the variability and uncertainty in electricity generation resources available to California’s electricity grid operators. Automated demand response and energy storage systems can help reduce this variability and uncertainty through energy buying and selling (arbitrage) in day-ahead markets that would levelize loads and prices throughout the day. They could also provide load-following capability through bids in the real-time market and system management (or regulation) services to the system operator. The project identified policies, technologies (energy storage), and control methods (demand response) that could reduce the cost and improve the reliability of electric power for California ratepayers. Data and assumptions describing energy storage and demand response resources were provided by the Electric Power Research Institute, the California Energy Storage Alliance, and the Demand Response Research Center. The California Independent System Operator provided the production simulation model and supporting data.

14 SOLAR ENERGY↗
DOE OSTI2018

Supporting the Nation's Electric Interconnections through Integration of Water into their Long-Term Transmission Planning.

Water is a critical resource in the production of electric power. The purpose of this plan is to extend support to the nation's three electric interconnections toward integrating water issues into their long-range transmission planning. This continued support is at the request of the interconnections. The proposed program leverages prior support as well as that of other similarly focused efforts funded across the Department of Energy (DOE). The effort will utilize a project team lead by Sandia National Laboratories and supported by Argonne National Laboratory, National Renewable Energy Laboratory, and Pacific Northwest National Laboratory. The activities recorded here are meant to provide a menu of potential projects that could be implemented as available resources permit.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

ARSK1 activates TORC1 signaling to adjust growth to phosphate availability in Arabidopsis

Nutrient sensing and signaling are essential for adjusting growth and development to available resources. Deprivation of the essential mineral phosphorus (P) inhibits root growth. The molecular processes that sense P limitation to trigger early root growth inhibition are not known yet. Target of rapamycin (TOR) kinase is a central regulatory hub in eukaryotes to adapt growth to internal and external nutritional cues. How nutritional signals are transduced to TOR to control plant growth remains unclear. Here, we identify Arabidopsis-root-specific kinase 1 (ARSK1), which attenuates initial root growth inhibition in response to P limitation. We demonstrate that ARSK1 phosphorylates and stabilizes the regulatory-associated protein of TOR 1B (RAPTOR1B), a component of the TOR complex 1, to adjust root growth to P availability. Finally, these findings uncover signaling components acting upstream of TOR to balance growth to P availability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Direct prediction of inelastic neutron scattering spectra from the crystal structure*

Abstract Inelastic neutron scattering (INS) is a powerful technique to study vibrational dynamics of materials with several unique advantages. However, analysis and interpretation of INS spectra often require advanced modeling that needs specialized computing resources and relevant expertise. This difficulty is compounded by the limited experimental resources available to perform INS measurements. In this work, we develop a machine-learning based predictive framework which is capable of directly predicting both one-dimensional INS spectra and two-dimensional INS spectra with additional momentum resolution. By integrating symmetry-aware neural networks with autoencoders, and using a large scale synthetic INS database, high-dimensional spectral data are compressed into a latent-space representation, and a high-quality spectra prediction is achieved by using only atomic coordinates as input. Our work offers an efficient approach to predict complex multi-dimensional neutron spectra directly from simple input; it allows for improved efficiency in using the limited INS measurement resources, and sheds light on building structure-property relationships in a variety of on-the-fly experimental data analysis scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Extreme Weather and Climate Vulnerabilities of the Electric Grid: A Summary of Environmental Sensitivity Quantification Methods

Climate hazards and extreme weather affect all components of the electric grid system, from generation to end use. Increasing temperatures, decreasing water availability, more intense storm events, and sea level rise affect the ability of the electric grid to produce and transmit electricity from fossil, nuclear, and existing and emerging renewable energy sources. Most electricity infrastructure is built for past or current climate conditions. Due to long lifetimes, electricity systems are likely to be exposed more frequently to more extreme climate conditions than those for which they were designed, and may not operate as intended under changing climate conditions. Utilities, regulators, state energy offices, and other electricity system planners are beginning to conduct environmental risk assessments, develop climate resilience plans, and incorporate changing climate conditions into long-term planning processes. Here, we highlight the analytical resources available for sensitivity assessment of electrical grid components under extreme weather and climate, and identify gaps in the literature on quantitative methods available for assessment of component vulnerability.

Dumas, Melissa↗
DOE OSTI2019

Using facility-level emissions data to estimate the technical potential of alternative thermal sources to meet industrial heat demand

Industry is frequently highlighted as the world's largest energy-using end-use sector. More specifically, the demand for heat drives much of the demand for energy and fossil fuels in the industrial sector. We conduct a top-down analysis to characterize historical energy and fossil fuel use in 14 top-GHG-emitting industries in the United States, their heat demand requirements, and the potential to substitute heat from geothermal, solar thermal (including concentrating technologies), and small modular nuclear reactors to meet these needs while reducing fossil-fuel use and greenhouse gas (GHG) emissions. We base this analysis on publicly-available facility-level GHG emissions and fuel-combustion data, in addition to assumed requirements for process temperature, to demonstrate the potential value to industry energy analysts of the U.S. Environmental Protection Agency's Greenhouse Gas Reporting Program data. We estimate on a county level that the adoption of these alternative heat sources could have reduced 2015 fossil-fuel use by approximately 31% and combustion GHG emissions by approximately 24%. The most extensive substitution opportunities are in the ethyl alcohol manufacturing and wet corn-milling industries; petroleum refining represents the largest absolute emissions mitigation potential. This initial top-down analysis of substitution potential does not consider more detailed technical factors, including resource availability that will influence the actual deployment of alternative energy technologies. The analysis also does not consider the economic or market factors, including the expected cost to build and operate these generators. We do assume process byproducts that are extensively used for combustion fuels would not be good candidates for substitution for alternative energy generators. Based on these caveats, our analysis could be considered a top-range estimate for this mix of heat generators and industry heat demands. Any subsequent analysis of these alternate energy sources should increase the level of technical, economic, and policy detail.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Environmental issues elimination through circular economy

Environmental efforts of European Union are currently going towards circular economy. Tools like Extended Producer Responsibility and Eco-design were established. The circular economy deals with resources availability issue on one hand and waste management on the other hand. There are few pioneering companies all over the world with some kind of circular economy practice. Generally the concept is not very wide-spread. The paper aims to evaluate possibility of transition towards circular economy in Slovak industrial companies. They need to have an active approach to material treatment of their products after usage stage. Innovation is another important pre-condition for the transition. Main problem of current cradle to grave system is landfilling of valuable materials after one cycle of usage. Their potential value for next manufacturing cycles is lost. Companies may do not see connection between waste management and material resource prices and volatility of supplies. Municipalities are responsible for municipal waste collection and treatment in Slovakia. The circular economy operates by cradle to cradle principle. Company manages material flow until the material comes back to the beginning of manufacturing process by itself or by another partners. Stable material supplies with quite low costs are provided this way. It is necessary to deal with environmental problems in phase of product design. Questionnaire survey results show on one hand low involvement of industrial companies in waste management area, however on the other hand they are open to environmental innovations in future.

54 ENVIRONMENTAL SCIENCES↗