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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Heterogeneous graphics processing unit for scheduling thread groups for execution on variable width SIMD units

A compute unit configured to execute multiple threads in parallel is presented. The compute unit includes one or more single instruction multiple data (SIMD) units and a fetch and decode logic. The SIMD units have differing numbers of arithmetic logic units (ALUs), such that each SIMD unit can execute a different number of threads. The fetch and decode logic is in communication with each of the SIMD units, and is configured to assign the threads to the SIMD units for execution based on such differing numbers of ALUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

HydroBio: Hydropower Capacity and Freshwater Biodiversity in Conterminous United States Sub-basins

This dataset summarizes existing and potential hydropower capacity and freshwater biodiversity at the sub-basin level throughout the conterminous United States (CONUS). It contains descriptive information regarding each sub-basin (e.g., 8-digit hydrologic unit code identifier, name, states, and size) along with sub-basin-level summaries of: 1) existing hydropower capacity (MW), 2) potential nominal non-powered dam (NPD) capacity (MW), 3) potential capacity of new stream reach development (NSD) (MW), and 4) freshwater biodiversity, including the total richness of fish, crayfish, and mussels and metrics that account for how rare and threatened those species tend to be. Hydropower data were obtained from Oak Ridge National Laboratory data resources (Existing Hydropower Assets, Non-Powered Dam Technical Potential, and New Stream Reach Development). Freshwater biodiversity data were obtained from NatureServe. Sub-basin characteristic information was obtained from the United States Geological Survey. Additionally, long data that provide lists of unique elements within each sub-basin for each constituent data resource (e.g., NatureServe, Existing Hydropower Assets) are provided to enhance dataset utility for users. The dataset provides, for the first time, a national-level assessment of existing and potential hydropower capacity in the context of freshwater biodiversity and is a valuable resource for stakeholders tasked with providing affordable, reliable energy to the American public while maintaining or enhancing invaluable freshwater resources. The dataset contains six data files in comma separated (*.csv) format that are within a zipped file.

Bozeman, Bryan [Oak Ridge National Laboratory (ORN↗
DOE OSTI2020

Aquifer Hydraulic Testing and Characterization Plan for the Ringold Formation Unit A in the Hanford 200-ZP-1 Groundwater Operable Unit and Vicinity

This document presents a plan for testing and characterizing the hydraulic properties of the Ringold Formation, member of Wooded Island – unit A (Rwia) in the 200-ZP groundwater operable unit. The testing approach includes multiple field methods and associated analyses designed to investigate and understand aquifer hydraulic properties over a range of scales. Testing was designed to achieve specific testing objectives identified previously in the 200 ZP-1 Groundwater Operable Unit Ringold Formation Unit A Characterization Sampling and Analysis Plan (Ringold A SAP). The test plan provides necessary technical and operational detail for writing subsequent field test instruction documents specific to each testing location. Hydraulic characterization activities will proceed in a phased manner focusing on areas identified to have knowledge gaps and also critical for remedy modifications and/or selection. These activities are designed to minimize impact to pump-and-treat (P&T) operations and to use existing P&T injection and extraction wells as stress wells, and include use of the new Rwia monitoring wells installed for Ringold A SAP activities. ZP-1 hydraulic testing will include slug testing in new Rwia wells, shutdown-recovery tests in multiple Rwia and composite Ringold Formation member of Wooded Island – unit E (Rwie)-Rwia aquifer test locations, installation of new Automated Water Level Network stations in Rwia monitoring wells, characterization of P&T and barometric responses, identifying the vertical distribution of hydraulic conductivity in the Rwia and Rwie units using electromagnetic borehole flowmeter tests, and single-well tracer testing in select Rwia monitoring wells. Slug testing to be conducted during drilling is described under the Ringold A SAP. The remaining testing activities are to be conducted after well drilling and completion and are described in this test plan.

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

Notable impact of wildfires in the western United States on weather hazards in the central United States

Increased wildfire events constitute a significant threat to life and property in the United States. Wildfire impact on severe storms and weather hazards is another pathway that threatens society, and our understanding of which is very limited. Here, we use unique modeling developments to explore the effects of wildfires in the western US (mainly California and Oregon) on precipitation and hail in the central US. We find that the western US wildfires notably increase the occurrences of heavy precipitation rates by 38% and significant severe hail (≥2 in.) by 34% in the central United States. Both heat and aerosols from wildfires play an important role. By enhancing surface high pressure and increasing westerly and southwesterly winds, wildfires in the western United States produce ( 1 ) stronger moisture and aerosol transport to the central United States and ( 2 ) larger wind shear and storm-relative helicity in the central United States. Both the meteorological environment more conducive to severe convective storms and increased aerosols contribute to the enhancements of heavy precipitation rates and large hail. Moreover, the local wildfires in the central US also enhance the severity of storms, but their impact is notably smaller than the impact of remote wildfires in California and Oregon because of the lessened severity of the local wildfires. As wildfires are projected to be more frequent and severe in a warmer climate, the influence of wildfires on severe weather in downwind regions may become increasingly important.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Solving Unit Commitment Problems with Demand Responsive Loads

This work focuses on using variations of the Frank-Wolfe (FW) algorithm for solving unit commitment problems with high volumes of demand responsive loads on the power grid. We present a formulation of the unit commitment problem with demand responsive loads. We then show through reformulation and relaxations of the problem that variations of the Frank-Wolfe algorithm can be used to determine the time series decisions for the demand responsive loads. We show through computational experiments on the IEEE Reliability Test System that the timeseries of demand responsive load decisions obtained through our approach are near optimal and describe how large-scale parallel implementations of our approach can be highly computationally efficient.

demand response↗
DOE OSTI2024

Geospatial characterization of low-temperature heating and cooling demand in residential, commercial, manufacturing, agricultural, and data center sectors for potential geothermal applications in the United States

Thermal demand for heating and cooling has been predominantly supplied by fossil fuel combustion in the United States, although low-carbon alternatives are extensively available including geothermal, solar thermal, and waste heat. Here, this study analyzed end-use energy consumption, fuel expenditure, and data center commissioned power data to geospatially characterize the U.S. low-temperature heating and cooling demand at the county level in residential, commercial, manufacturing, agricultural, and data center sectors and understand potential opportunities for geothermal applications. In the analysis, the regional-scale energy consumption data was incorporated with system efficiencies to address actual demand and was then disaggregated with weighting factors to the county level. The results indicated that total low-temperature heating and cooling demand is 16.7 EJ, combining heating demand of 10.8 EJ and cooling demand of 5.9 EJ. Overall, 59.9 % (10 EJ) of the low-temperature heating and cooling demand occurred in the residential sector. The heating and cooling demand visualized in maps represented that the geospatial distribution of heating and cooling demand in the residential and commercial sectors is governed by the number of housing units and climate zone designations, while heating and cooling demand in the manufacturing, agricultural, and data center sectors is dependent on the number and location of facilities. The results also demonstrated that geothermal heat pumps are broadly used in the residential and commercial sectors for heating and cooling in the U.S. Midwest, South, and Northeast regions but are limited in the West, implying great decarbonization potential in the future.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Desert-Urban SysTem IntegratEd AtmospherIc Monsoon (DUSTIEAIM) in the Southwestern United States

Phoenix, Arizona, is the fifth-largest city in the United States with about 1.6 million residents. It is also considered to be the hottest major city in the country, having set a record of 31 consecutive days with temperatures above 110 F (43 C) in summer 2023. Phoenix depends on the Colorado River for over a third of its water supply, but there are questions about how much water will eventually be available to serve the rapidly growing metropolitan area, especially in such extreme heat. Current earth system models struggle to accurately capture precipitation in the Southwestern United States, especially in relation to the summertime North American Monsoon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment

Nonlinear power flow constraints render a variety of power system optimization problems computationally intractable. Emerging research shows, however, that the nonlinear AC power flow equations can be successfully modeled using neural networks. These neural networks can be exactly transformed into mixed integer linear programs and embedded inside challenging optimization problems, thus replacing nonlinearities that are intractable for many applications with tractable piecewise linear approximations. Such approaches, though, suffer from an explosion of the number of binary variables needed to represent the neural network. Accordingly, this paper develops a technique for training an "optimally compact'' neural network, i.e., one that can represent the power flow equations with a sufficiently high degree of accuracy while still maintaining a tractable number of binary variables. We demonstrate the use of this neural network as an approximator of the nonlinear power flow equations by embedding it in the AC unit commitment problem, transforming the problem from a mixed integer nonlinear program into a more manageable mixed integer linear program. We use the 14-, 57-, and 89-bus networks as test cases and compare the AC-feasibility of commitment decisions resulting from the neural network, DC, and linearized power flow approximations. Our results show that the neural network model outperforms both the DC and linearized power flow approximations when embedded in the unit commitment problem. The neural network formulation most often selects a feasible unit commitment schedule, and furthermore, it only s

AC power flow↗
DOE OSTI2024

Measuring Economy-Wide Circularity of the United States: An Input-Output Model in Mass Units

The ideal of creating closed material cycles by transforming the way we make, use and repurpose goods has become known as the circular economy. Besides its visionary appeal, material efficiency strategies central to circular economy can allow us to meet decarbonization goals that are otherwise out of reach. Production of basic materials such as cement, iron and steel and petrochemicals is one of the largest drivers of greenhouse gas emissions. Measuring circularity, and understanding its relationship with other sustainability metrics, however, is still difficult due to lack of data in mass units covering the entire economic system. Input-output (I-O) tables were originally created as a means of tracking the monetary flows that represent exchanges of goods and services within an economy, but have found additional uses in life cycle assessment and material flow accounts. In the traditional approach of environmentally extended I-O tables, emissions and energy data augment monetary flows. This approach can lead to price effects that distort physical quantities. Also, circular economy strategies and their goals relate to mass, not monetary flows. Therefore, it is best to simulate them using physical quantities. With these issues in mind, we have developed I-O tables in mass units to measure the flow of goods in the U.S. economy. This allows us to better measure how circular the economy really is, and how policy changes to affect this circularity may also affect decarbonization goals. Improving knowledge of these linkages could allow manufacturers to make changes in their production to achieve their sustainability and decarbonization targets. Our tool also provides a standard approach and public repository for data in physical units, making such data more available, useful, and meaningful. Following an established set of material flow metrics used by the European Union, we have used our tool to calculate material footprints over time differentiated by oil and gas versus other extractive industries. This approach also shows the relative trade balances of the U.S. in materials. We have developed a case study for the iron and steel sector, showing how different decarbonization scenarios affect not only economy-wide greenhouse gas emissions, but also total material use.

circular economy↗
DOE OSTI2024

Near-Optimal Solutions for Day-Ahead Unit Commitment

Given the difficulty and the time pressure of solving unit commitment problems, near -optimal solutions (those with 0.1 or 0.001% optimality gaps) are often used in practice. The choice in which of the near -optimal solutions is used, however, is random. We investigate the impact of solution choice on the revenues obtained by generator owners across a variety of pricing schemes and problem instances.

market-clearing↗
DOE OSTI2024

Battery Degradation Modeling in Hybrid Power Plants: An Island System Unit Commitment Study: Preprint

As hybrid power plants (HPPs), such as photovoltaic (PV) and battery combinations, become increasingly important in power systems with high renewable energy penetration to address PV variability and ensure grid stability. This paper focuses on the urgent need to model the coordination between PV and battery systems in HPPs while accounting for battery degradation. We present a generation scheduling model that explicitly incorporates PV-battery hybridization in the unit commitment problem. Moreover, the cost function of the HPP scheduling problem endogenously considers battery degradation with adjustable weights to strike a balance between minimizing production costs and prolonging battery life, particularly when providing energy arbitrage and ancillary services. Using a realistic island system simulation, we demonstrate that accounting for battery degradation in the scheduling problem can significantly extend battery life with only minor additional production costs.

battery degradation↗
DOE OSTI2021

A Flexible and Generic Functional Mock-up Unit Based Threat Injection Framework for Grid-interactive Efficient Buildings: A Case Study in Modelica

Grid-interactive efficient buildings (GEBs) have been considered as an important asset to support the power grid reliability by utilizing the demand flexibility offered by GEBs. GEBs are enabled by advances in sensors and controls, and the communication between building equipment, whole buildings, and the grid. The integration of different building technologies and network-based communication system makes GEBs vulnerable to passive threats such as equipment failure and active threats such as cyber-attacks. Modeling and simulation is an effective way to evaluate the impact of threats on the system performance. This paper proposes a generic and flexible threat injection framework for commonly-used building energy simulators such as EnergyPlus and Modelica to support threat modeling and evaluation. This framework leverages functional mock-up unit (FMU) to develop a general modeling interface for threat injection and simulation. A numerical case study using Modelica as a building energy simulator is conducted to demonstrate the capability of the framework for supporting single/multiple-order threat modeling and simulation of a GEB. Four threats and their combinations are injected on a Modelica-based threat-free building energy and control system, including operating supply fan at its full speed, remotely cycling the chiller on and off, blocking the chiller from receiving the chilled water supply temperature setpoints, and hijacking the global zone air temperature setpoint. Simulation results show that the cyber-attack that leads to short-term signal blocking has small effects on the system operation due to the "self-healing" feature of the heating, ventilation, and air-conditioning (HVAC) interactive control system. The threat that takes control of resetting the global zone air temperature setpoints has the most adverse impact on the system energy use, peak power demand, thermal comfort and the provision of demand flexibility. The combination of four threats have aggregative effects on the system but the effects are less than the additive effects of the individual threat.

Fu, Yanyang↗
DOE OSTI2020

Patience is a virtue: A data-driven analysis of rooftop solar PV permitting timelines in the United States

© 2020 The Authors Local permitting can ensure the safe installation and operation of rooftop solar photovoltaic (PV) systems. At the same time, burdensome local permitting processes and local variation in requirements may pose challenges to PV deployment. In this article, we explore new data on the durations between key steps in the PV permitting process in the United States. The data suggest that a typical customer can expect to wait around 25–100 days from permit application until an installed system passes inspection. Permit durations vary significantly across jurisdictions, due in part to differences in local permitting policies. However, permit durations vary as significantly within jurisdictions as across them, in part due to significant variation across installers, suggesting that installer strategies and practices play an important role in permitting timelines. Permit durations have declined over time, reflecting progress from permit streamlining policies and jurisdiction learning-by-doing, though durations have stabilized in recent years. The data suggest that typical PV customers still face long and uncertain permitting timelines in the United States.

O'Shaughnessy, E↗