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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The HST See Change Program. I. Survey Design, Pipeline, and Supernova Discoveries*

The See Change survey was designed to make z > 1 cosmological measurements by efficiently discovering high-redshift Type Ia supernovae (SNe Ia) and improving cluster mass measurements through weak lensing. This survey observed twelve galaxy clusters with the Hubble Space Telescope (HST) spanning the redshift range z = 1.13–1.75, discovering 57 likely transients and 27 likely SNe Ia at z ~ 0.8–2.3. As in similar previous surveys, this proved to be a highly efficient use of HST for supernova observations; the See Change survey additionally tested the feasibility of maintaining, or further increasing, the efficiency at yet higher redshifts, where we have less detailed information on the expected cluster masses and star formation rates. Furthermore, we find that the resulting number of SNe Ia per orbit is a factor of ~8 higher than for a field search, and 45% of our orbits contained an active SN Ia within 22 rest-frame days of peak, with one of the clusters by itself yielding 6 of the SNe Ia. We present the survey design, pipeline, and supernova discoveries. Novel features include fully blinded supernova searches, the first random forest candidate classifier for undersampled IR data (with a 50% detection threshold within 0.05 mag of human searchers), real-time forward-modeling photometry of candidates, and semi-automated photometric classifications and follow-up forecasts. We also describe the spectroscopic follow-up, instrumental in measuring host galaxy redshifts. The cosmology analysis of our sample will be presented in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

LONG-TERM STEWARDSHIP AT DOE HANFORD SITE - 12575

The U.S. Department of Energy's (DOE) Hanford Site is located in southeast Washington and consists of 1,518 square kilometers (586 square miles) of land. Established in 1943 as part of the Manhattan Project, Hanford workers produced plutonium for our nation's nuclear defense program until the mid 1980's. Since then, the site has been in cleanup mode that is being accomplished in phases. As we achieve remedial objectives and complete active cleanup, DOE will manage Hanford land under the Long-Term Stewardship (LTS) Program until completion of cleanup and the site becomes ready for transfer to the post cleanup landlord - currently planned for DOE's Office of Legacy Management (LM). We define Hanford's LTS Program in the ''Hanford Long-Term Stewardship Program Plan,'' (DOE/RL-201 0-35)[1], which describes the scope including the relationship between the cleanup projects and the LTS Program. DOE designed the LTS Program to manage and provide surveillance and maintenance (S&M) of institutional controls and associated monitoring of closed waste sites to ensure the protection of human health and the environment. DOE's Richland Operations Office (DOE-RL) and Hanford cleanup and operations contractors collaboratively developed this program over several years. The program's scope also includes 15 key activities that are identified in the DOE Program Plan (DOE/RL-2010-35). The LTS Program will transition 14 land segments through 2016. The combined land mass is approximately 570 square kilometers (220 square miles), with over 1,300 active and inactive waste sites and 3,363 wells. Land segments vary from buffer zone property with no known contamination to cocooned reactor buildings, demolished support facilities, and remediated cribs and trenches. DOE-RL will transition land management responsibilities from cleanup contractors to the Mission Support Contract (MSC), who will then administer the LTS Program for DOE-RL. This process requires an environment of cooperation between the contractors and DOE-RL. Information Management (IM) is a key part of the LTS program. The IM Program identifies, locates, stores, protects and makes accessible Hanford LTS records and data to support the transfer of property ultimately to LM. As such, DOE-RL manages the Hanford LTS Program in a manner consistent with LM's goals, policies, and procedures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

National Renewable Energy Laboratory Renewable Energy Opportunity Assessment for USAID Mexico

The United States Agency for International Development (USAID) Enhancing Capacity for Low Emission Development Strategies (EC-LEDS) program is designing its second phase of assistance to the Government of Mexico (GOM). In preparation for program design, USAID has asked the National Renewable Energy Laboratory (NREL) to assist in identifying options for enabling renewable energy in Mexico and reducing greenhouse gas (GHG) emissions in the energy sector. The NREL team conducted a literature review and consulted with over 20 Mexican agencies and organizations during a two-week temporary duty assignment (TDY) to Mexico to identify gaps, opportunities, and program theme areas for Mexico.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Overview of Canada's Plan for the Long-Term Management of Used Nuclear Fuel - 19537

In June 2007, the Government of Canada approved the Nuclear Waste Management Organisation's (NWMO) recommended Adaptive Phased Management (APM) approach for the long-term management of Canada's used nuclear fuel. As per this approach, used nuclear fuel will be isolated and contained in a centralized Deep Geological Repository (DGR) located in a stable crystalline or sedimentary rock formation at a nominal depth of 500 metres below ground surface. The DGR concept contains multiple barriers to safely contain and isolate the used nuclear fuel over the long-term. The used nuclear fuel bundles will be encapsulated in a copper-coated steel Used Fuel Container (UFC) and pre-packaged in a bentonite clay buffer box above ground. The UFC and bentonite clay buffer box assemblies will then be emplaced in excavated tunnel openings and sealed with clay-based backfill material and room seals, which completes the primary Engineered Barrier System (EBS). Since 2011, the NWMO has executed a design-development program to validate the design and manufacturing technologies for the EBS. Currently, the NWMO are executing a proof test program for the EBS for the purpose of demonstrating serial production. As the prototypes are produced, they will be subject to full-scale in-room emplacement trials within a custom-built above-ground mock emplacement room. The proof test program will be executed using APM reference designs, materials, processes, and procedures. An overview of this program is discussed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Community Toolkit for Designing and Implementing a Contractor Accelerator Program

This toolkit is designed to provide communities with an overview of the methodology and approach to designing, developing, and implementing contractor development programs. These programs support small businesses from historically under-represented communities so that they can better compete and become leaders in the clean energy marketplace. The toolkit was developed by Elevate and NREL for the Communities LEAP program.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Multidimensional sum-up rounding for integer programming in optimal experimental design

Here we present a numerical method for approximating the solution of convex integer programs stemming from optimal experimental design. The statistical setup consists of a Bayesian framework for linear inverse problems for which the direct relationship is described by a discretized integral equation. Specifically, we aim to find the optimal sensor placement from a set of candidate locations where data are collected with measurement error. The convex objective function is a measure of the uncertainty, described here by the trace or log-determinant of the posterior covariance matrix, for the discretized linear inverse problem solution. The resulting convex integer program is relaxed, producing a lower bound. An upper bound is obtained by extending the sum-up rounding approach to multiple dimensions. For this extension, we analyze its accuracy as a function of the discretization mesh size for a rectangular domain. We show asymptotic optimality of the integer solution defining the upper bound for different experimental design criteria (A- and D-optimal), by proving the convergence to zero of the gap between the upper and lower bounds as the mesh size goes to zero. The technique is illustrated on a two-dimensional gravity surveying problem for both A-optimal and D-optimal sensor placement where our designs yield better results compared with a thresholding rounding approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Customer enrollment and participation in building demand management programs: A review of key factors

Increasing the efficiency and flexibility of electricity demand is necessary for ensuring a cost-effective and reliable transition to zero-carbon electricity systems. Such demand-side management (DSM) resources have been procured by utilities for decades via energy efficiency and demand response programs; however, the key drivers of program enrollment and customer participation levels remain poorly understood — even as governments and grid planners seek to scale up the deployment of DSM assets to meet climate targets. Here we systematically review the evidence on multiple factors that may influence customer enrollment and participation in building DSM programs, focusing primarily on residential and commercial buildings. We examine the contexts in which relationships between DSM factors and outcomes are most often explored and with which methods; we also score the strength, direction, and internal consistency of each factor's reported impact on the enrollment and participation outcomes. We find that studies most commonly assess the effects of economic incentives for load flexibility on program participation levels, often using simulation-based methods in lieu of measured data. Few studies focus on program enrollment outcomes or regulatory drivers of either enrollment or participation, and gaps are also evident in the coverage of emerging DSM opportunities like load electrification. Removal of structural barriers (e.g., the lack of controls infrastructure) and the use of third party services (e.g., load aggregators) are the factors with the largest positive impacts on DSM outcomes, but no single factor emerges as clearly most impactful. For a given factor, the range of reported impacts typically varies widely across the relevant studies reviewed. Our findings provide a snapshot of the state of knowledge about building DSM and customer decision-making, and they expose key gaps in understanding that must be filled if building DSM is to expand as a critical resource for operating clean power grids.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Demographic Information Incorporated Household Energy Consumption Analysis

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗
DOE OSTI2023

Demographic Information Incorporated Household Energy Consumption Analysis: Preprint

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗
DOE OSTI2023

Demographic Information Incorporated Household Energy Consumption Analysis

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗
DOE OSTI2023

IM3 GO WEST Parameter Search Dataset

GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It is developed to address weather and water dynamics, and associated vulnerabilities in this bulk power system. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. Therefore, GO WEST can help researchers to strike a balance between model fidelity (i.e. accuracy) and computational complexity (i.e. runtime). This dataset includes model inputs and outputs from 600 model versions for each 2019, 2020, and 2021. The folder naming convention is as follows: Exp{Number of Nodes}_{Mathematical Formulation}_{Transmission Line Limit Scaling Factor in MW}_{Hurdle Rate Scaling Factor in %}_{Year}. Linear programming is designated with "simple" label whereas mixed-integer linear programming is designated with "coal" label. For example, "Exp100_simple_1000_50_2019" folder contains inputs and outputs from 2019 model version with 100 nodes, linear programming, +1000 MW transmission line limit scaling factor, and +50% hurdle rate scaling factor. GO WEST GitHub repository hosts all raw datasets, processing scripts, and model scripts. Please refer to the README file for a detailed description of the included files.

Economics↗
DOE OSTI2017

Community Solar Value Project

The Community Solar Value Project (CSVP) is designed to assist electric utilities in designing better community solar programs. Better programs seek new sources of value to promote “win-win” solutions between utilities and their customers. The CSVP focused on five “challenge areas” in identifying new sources of value: - Strategic solar design for community solar projects (including technology choices, siting, orientation, and related issues) - Market research and targeted marketing approaches (for program design and for customer recruitment) - Procurement and financing (for establishing best practices that can bring economies of scale and economies of expertise) - Integration of “companion measures” (such as storage and demand-response options that can benefit customer and utility net load shapes) - Pricing in program design (including best practices for integration of identified value in program prices or credits) The CSVP directly engaged the Sacramento Municipal Utility District (SMUD), the Public Service Company of New Mexico (PNM), and more than a dozen other utilities to develop improved community solar program designs. The outcomes include a plan at SMUD for over 100 MW or more of community and shared solar and support for new or expanded programs at 15 other utilities so far. Resulting best-practice solutions have not only informed program applications, but also have generated discussion among experts and industry associations about the new opportunities and challenges CSVP has brought forth. In these ways, the CSVP has impacted community solar programs and DER plans, competitive innovations and policies nationwide. The CSVP team has been led by Extensible Energy under John Powers, President and CEO. Jill Cliburn, of Santa Fe, NM-based Cliburn and Associates, has served as Principal Investigator. The team also benefitted from expertise from Navigant, Olivine Inc. and Millennium Energy, LLC, in addition to the collaborative and cost-sharing contributions of its utility partners. The CSVP team participated fully in the Solar Market Pathways Program, which was initiated under the U.S. Department of Energy SunShot program and reports to the U.S. Department of Energy Solar Energy Technologies Office. This report summarizes a multi-disciplinary project that took place over 33 months from January, 2015 through September, 2017.

14 SOLAR ENERGY↗