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All sourcesNASA NTRSDOE OSTI
DOE OSTI2010

Save Energy Now Assessments Results 2008 Detailed Report

In October 2005, U.S. Department of Energy Secretary Bodman launched his Easy Ways to Save Energy campaign with a promise to provide energy assessments to 200 of the largest U.S. manufacturing plants. DOE's Industrial Technologies Program (ITP) responded to the Secretary's campaign with its Save Energy Now initiative, featuring a new and highly cost-effective form of energy savings assessment. The approach for these assessments drew heavily on the existing resources of ITP's technology delivery component. Over the years, ITP Technology Delivery has worked with industry partners to assemble a suite of respected software tools, proven assessment protocols, training curricula, certified energy experts, and strong partnerships for deployment. The Save Energy Now assessments conducted in calendar year 2006 focused on natural gas savings and targeted many of the nation's largest manufacturing plants - those that consume at least 1 TBtu of energy annually. The 2006 Save Energy Now assessments focused primarily on assessments of steam and process heating systems, which account for an estimated 74% of all natural gas use by U.S. manufacturing plants. Because of the success of the Save Energy Now assessments conducted in 2006 and 2007, the program was expanded and enhanced in two major ways in 2008: (1) a new goal was set to perform at least 260 assessments; and (2) the assessment focus was expanded to include pumping, compressed air, and fan systems in addition to steam and process heating. DOE ITP also has developed software tools to assess energy efficiency improvement opportunities in pumping, compressed air, and fan systems. The Save Energy Now assessments integrate a strong training component designed to teach industrial plant personnel how to use DOE's opportunity assessment software tools. This approach has the advantages of promoting strong buy-in of plant personnel for the assessment and its outcomes and preparing them better to independently replicate the assessment process at the company's other facilities. Another important element of the Save Energy Now assessment process is the follow-up process used to identify how many of the recommended savings opportunities from individual assessments have been implemented in the industrial plants. Plant personnel involved with the Save Energy Now assessments are contacted 6 months, 12 months, and 24 months after individual assessments are completed to determine implementation results. A total of 260 Save Energy Now assessments were successfully completed in calendar year 2008. This means that a total of 718 assessments were completed in 2006, 2007, and 2008. As of July 2009, we have received a total of 239 summary reports from the ESAs that were conducted in year 2008. Hence, at the time that this report was prepared, 680 final assessment reports were completed (200 from year 2006, 241 from year 2007, and 239 from year 2008). The total identified potential cost savings from these 680 assessments is $1.1 billion per year, including natural gas savings of about 98 TBtu per year. These results, if fully implemented, could reduce CO{sub 2} emissions by about 8.9 million metric tons annually. When this report was prepared, data on implementation of recommended energy and cost savings measures from 488 Save Energy Now assessments were available. For these 488 plants, measures saving a total of $147 million per year have been implemented, measures that will save $169 million per year are in the process of being implemented, and plants are planning implementation of measures that will save another $239 million per year. The implemented recommendations are already achieving total CO{sub 2} reductions of about 1.8 million metric tons per year. This report provides a summary of the key results for the Save Energy Now assessments completed in 2008; details of the 6-month, 12-month, and 24-month implementation results obtained to date; and an evaluation of these implementation results. This report also summarizes key accomplishments, findings, and lessons learned from all the Save Energy Now assessments completed to date. A separate report (Wright et al. 2010) provides more detailed information on key results for all of the 2008 assessments of steam, process heating, pumping, compressed air, and fan systems. Two prior reports (Wright et al. 2007 and Wright et al. 2009) detail the results from the 2006 and 2007 assessments and discuss the major components of the assessment process and improvements in the process made in 2007.

03 NATURAL GAS↗
DOE OSTI2014

Impacts Analyses Supporting the National Environmental Policy Act Environmental Assessment for the Resumption of Transient Testing Program

This document contains the analysis details and summary of analyses conducted to evaluate the environmental impacts for the Resumption of Transient Fuel and Materials Testing Program. It provides an assessment of the impacts for the two action alternatives being evaluated in the environmental assessment. These alternatives are (1) resumption of transient testing using the Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) and (2) conducting transient testing using the Annular Core Research Reactor (ACRR) at Sandia National Laboratory in New Mexico (SNL/NM). Analyses are provided for radiologic emissions, other air emissions, soil contamination, and groundwater contamination that could occur (1) during normal operations, (2) as a result of accidents in one of the facilities, and (3) during transport. It does not include an assessment of the biotic, cultural resources, waste generation, or other impacts that could result from the resumption of transient testing. Analyses were conducted by technical professionals at INL and SNL/NM as noted throughout this report. The analyses are based on bounding radionuclide inventories, with the same inventories used for test materials by both alternatives and different inventories for the TREAT Reactor and ACRR. An upper value on the number of tests was assumed, with a test frequency determined by the realistic turn-around times required between experiments. The estimates provided for impacts during normal operations are based on historical emission rates and projected usage rates; therefore, they are bounding. Estimated doses for members of the public, collocated workers, and facility workers that could be incurred as a result of an accident are very conservative. They do not credit safety systems or administrative procedures (such as evacuation plans or use of personal protective equipment) that could be used to limit worker doses. Doses estimated for transportation are conservative and are based on transport of the bounding radiologic inventory that will be contained in any given test. The transportation analysis assumes all transports will contain the bounding inventory.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Integration of Experimental Hydroprocessing and FCC Data with Process (Aspen Plus) and Refinery Optimization (Aspen PIMS) Models

NREL's Economic, Sustainability, and Market Analysis (ESMA) team develops process models in Aspen Plus to support techno-economic analysis (TEA) and life-cycle assessment (LCA) of conversion pathways from renewable and circular resources to fuels and chemicals. These tools are being applied to assess probable operational constraints or bottlenecks associated with refinery co-processing and repurposing opportunities. The team also utilizes optimizable refinery models to quantify opportunities for biofuel and bioproduct pathways through integration with existing refining infrastructure. The goals of analysis are to model the transition of refineries to renewable and circular feedstocks and quantify the costs production and CO2 abatement through utilization of existing refineries. At the core of the ESMA team's work is the process data derived from conversion experiments on hydroprocessing and fluid catalytic cracking performed at NREL. The objective of this presentation is to highlight new analysis approaches and capabilities in pathway analysis and refinery optimization modeling with specific emphasis on integration of experimental data.

BIOMASS FUELS,ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Influence of Groundwater Extraction Costs and Resource Depletion Limits on Simulated Global Nonrenewable Water Withdrawals Over the Twenty‐First Century

Abstract Future rates of global groundwater depletion will depend on the economic and environmental viability of extracting water from increasingly stressed aquifers. Here we analyze global groundwater depletion by considering these factors explicitly. Global gridded groundwater availability and extraction cost data are aggregated to produce nonrenewable resource supply curves for 235 major river basins and geopolitical regions. These resources are then exposed to dynamically generated demands for water in a fully coupled, multisectoral, global simulation. As groundwater head levels drop, imposing greater capital and operating costs to bring water to the surface, modeled water use sectors are able to deploy a range of supply‐ and demand‐driven adaptive responses. Results demonstrate large sensitivity in global groundwater depletion rates to adjustments in resource exploitability. Extraction costs moderate demands for nonrenewable water substantially, resulting in the onset of a decline in global groundwater depletion rates within the twenty‐first century. New groundwater depletion hot spots may emerge as crop producers abandon overexploited basins and expand croplands in regions with cheaper, more plentiful water resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Hierarchical Framework for CO2 Storage Capacity in Deep Saline Aquifer Formations

Carbon dioxide (CO 2 ) storage in deep saline aquifers is a vital option for CO 2 mitigation at a large scale. Determining storage capacity is one of the crucial steps toward large-scale deployment of CO 2 storage. Results of capacity assessments tend toward a consensus that sufficient resources are available in saline aquifers in many parts of the world. However, current CO 2 capacity assessments involve significant inconsistencies and uncertainties caused by various technical assumptions, storage mechanisms considered, algorithms, and data types and resolutions. Furthermore, other constraint factors (such as techno-economic features, site suitability, risk, regulation, social-economic situation, and policies) significantly affect the storage capacity assessment results. Consequently, a consensus capacity classification system and assessment method should be capable of classifying the capacity type or even more related uncertainties. We present a hierarchical framework of CO 2 capacity to define the capacity types based on the various factors, algorithms, and datasets. Finally, a review of onshore CO 2 aquifer storage capacity assessments in China is presented as examples to illustrate the feasibility of the proposed hierarchical framework.

58 GEOSCIENCES↗
DOE OSTI2023

Hardware-in-the-loop Testing of Network Protectors for Low-Voltage Networks with Distributed Energy Resources

In this report, we developed and validated a network protector relay digital twin model and interfaced a commonly used network protector relay hardware with our real-time simulation system. Hardware-in-the-loop protection studies are performed to assess the impact of distributed energy resources (DER) and benchmark a rate-of-change-based mitigation strategy. Simulation results suggest that the network protector reverse trip and auto-reclose functions are negatively impacted by the high distributed energy resource penetration. To accommodate DER backfeed while remaining secure and reliable for faults on primary feeders, we recommend options for a rate-of-change-based blocking scheme and a protection setting change. Finally, future mitigation ideas and standard revisions are discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

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

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

14 - SOLAR ENERGY↗
DOE OSTI2025

Evaluating the combined effects of light and water availability on the early growth and physiology of Tamarindus indica : Implications for restoration

Abstract Premise The tamarind tree (Tamarindus indica) is a species of significant cultural, economic, and ecological value, with a pantropical distribution. However, the tamarind is experiencing a decline in wild populations in its native range, but the reasons for its decline remain unknown. Methods We examined the critical early life‐history stages for tamarind establishment to understand how varying levels of light and water availability and watering frequency affect its regeneration. Through three greenhouse experiments, we assessed the impact of these resources on the germination, survival, growth, and physiological responses of tamarind seedlings and saplings. Results Water availability was critical for seed germination, but not light levels or pre‐germination treatments. Light was the primary limiting factor for seedling growth. Tamarinds in high light availability grew taller, had more biomass and larger diameter, but the effect of light was modulated by water availability, indicating that there was an interaction between both resources. Water and light affected specific leaf area and leaf dry matter content but not biomass allocation, root‐to‐shoot ratio, or stomatal conductance. Water availability influenced sapling growth, but watering frequency did not, indicating a resilience of tamarind saplings to changes in rainfall periodicity but a sensitivity to total rainfall amounts. Conclusions Our study underscores the importance of considering both light and water availability in tamarind restoration efforts and contribute to understanding plant responses and trade‐offs under different levels of critical resources. Our findings will inform conservation strategies to support the regeneration and long‐term survival ofTamarindus indicain its native habitats.

Plant Sciences↗
DOE OSTI2022

Quantifying the effect of multiple load flexibility strategies on commercial building electricity demand and services via surrogate modeling

The expansion of commercial building demand response as a demand-side management resource for the electric grid necessitates new decision support resources for customers seeking to assess the benefit–risk tradeoffs of possible strategies for energy flexible building operations. To address this need, we, in this study, develop surrogate models that predict the impacts of several load flexibility strategies on commercial building electricity demand and indoor temperature, focusing on offices and retail buildings at multiple scales. The surrogate models are fit to a synthetic database generated via whole building simulations, which establish the relationships between the key operational features of a given strategy and potential changes in building demand and temperature across a variety of contexts. The surrogate models are translated to a Bayesian framework to allow straightforward communication of uncertainty and parameter updating given new evidence. We find strong predictive performance across the suite of models, underscoring the usefulness of the approach in guiding decisions about implementing load flexibility strategies under a particular set of operational and environmental conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Simulators for quantum network modeling: A comprehensive review

Quantum network research is exploring new networking protocols, physics-based hardware and novel experiments to demonstrate how quantum distribution will work over large distances. Current work explores much of these concepts in simulations, that are developed to understand how quantum networking will be set up and researchers can experiment virtually. Exposing flaws in network designs, like unsustainable topologies, or develop protocols that efficiently utilize network resources, simulators can also help assess whether workloads are balanced across virtual machines in the network. However, much of these simulation models come without reliable verification methods, for testing performance in real deployments. Here, in this paper, we present a review of, to the best of our knowledge, currently used toolkits for modeling quantum networks. With these toolkits and standardized validation techniques, we can lay down the foundations for more accurate and reliable quantum network simulators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Dynamic logistic regression and variable selection: Forecasting and contextualizing civil unrest

Civil unrest can range from peaceful protest to violent furor, and researchers are working to monitor, forecast, and assess such events to allocate resources better. Twitter has become a real-time data source for forecasting civil unrest because millions of people use the platform as a social outlet. Additionally, daily word counts are used as model features, and predictive terms contextualize the reasons for the protest. To forecast civil unrest and infer the reasons for the protest, we consider the problem of Bayesian variable selection for the dynamic logistic regression model and propose using penalized credible regions to select parameters of the updated state vector. This method avoids the need for shrinkage priors, is scalable to high-dimensional dynamic data, and allows the importance of variables to vary in time as new information becomes available. A substantial improvement in both precision and F1-score using this approach is demonstrated through simulation. Finally, we apply the proposed model fitting and variable selection methodology to the problem of forecasting civil unrest in Latin America. Our dynamic logistic regression approach shows improved accuracy compared to the static approach currently used in event prediction and feature selection.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A quantitative analysis of hydraulic interaction processes in stream-aquifer systems

The hydraulic relationship between the stream and aquifer can be altered from hydraulic connection to disconnection when the pumping rate exceeds the maximum seepage flux of the streambed. This study proposes to quantitatively analyze the physical processes of stream-aquifer systems from connection to disconnection. A free water table equation is adopted to clarify under what conditions a stream starts to separate hydraulically from an aquifer. Both the theoretical analysis and laboratory tests have demonstrated that the hydraulic connectedness of the stream-aquifer system can reach a critical disconnection state when the horizontal hydraulic gradient at the free water surface is equal to zero and the vertical is equal to 1. A boundary-value problem for movement of the critical point of disconnection is established for an analytical solution of the inverted water table movement beneath the stream. The result indicates that the maximum distance or thickness of the inverted water table is equal to the water depth in the stream, and at a steady state of disconnection, the maximum hydraulic gradient at the streambed center is 2. In conclusion, this study helps us to understand the hydraulic phenomena of water flow near streams and accurately assess surface water and groundwater resources.

42 ENGINEERING↗
DOE OSTI2024

Projected regional changes in mean and extreme precipitation over Africa in CMIP6 models

Precipitation plays a crucial role in Africa's agriculture, water resources, and economic stability, and assessing its potential changes under future warming is important. In this study, we demonstrate that the latest generation of coupled climate models (CMIP6) robustly project substantial wetting over western, central, and eastern Africa. In contrast, southern Africa and Madagascar tend toward future drying. Under shared socioeconomic pathways (defined by Shared Socioeconomic Pathways SSP2-4.5 and SSP5-8.5), our results suggest that most parts of Africa, except for southern Africa and Madagascar, will experience very wet years five times more often in 2050–2100, according to the multi-model median. Conversely, southern Africa and Madagascar will experience very dry years twice as often by the end of the 21st century. Furthermore, we find that the increasing risk of extreme annual rainfall is accompanied by a shift toward days with heavier rainfall. Our findings provide important insights into inter-hemispheric changes in precipitation characteristics under future warming and underscore the need for serious mitigation and adaptation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

efam: an e xpanded, metaproteome-supported HMM profile database of viral protein fam ilies

Viruses infect, reprogram and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases. Here, we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240 311 HMM profiles, each with at least 2 protein sequences, making efam >7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from ‘conservative’ to ‘eXtremely Conservative’ resulted in 37 841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ~24% on average (up to ~42%) and especially improved the recovery of often-missed shorter contigs (<5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Grid-Forming Inverters for Stability Improvements in Bulk Power Systems with High Inverter-Based Resources Penetration

The grid-forming inverter (GFM) has been considered recently as a means to enhance grid stability in areas with Inverter-based Resources (IBRs) concentration. This paper assesses the potential improvements the GFM can bring to Bulk-power Systems (BPS) through two distinct studies. The first study was conducted on West Texas in ERCOT with presence of more than 35GW of IBRs, the Grid-Following (GFL) batteries were replaced with GFM batteries. The results demonstrate that the GFM significantly improved the voltage profile and active power injection during and after a fault. The second study focused on a local area within ERCOT grid. In this case, a battery operating as GFL within the local study area was replaced with a GFM battery. The findings clearly illustrate that GFM can strengthen the area and allow a higher IBRs power generation and a higher power export from the local study area.

Quedan, Amro↗
DOE OSTI2020

Validation of Synthetic U.S. Electric Power Distribution System Data Sets

There is a strong need for synthetic yet realistic distribution system test data sets that are as diverse, large, and complex to solve as real systems. Such data sets can facilitate the development of advanced algorithms and the assessment of emerging distributed energy resources while avoiding the need to acquire proprietary critical infrastructure or private data. Such synthetic data sets, however, are useful only if they are realistic enough to look and behave similarly to actual systems. This paper presents a comprehensive framework for validating synthetic distribution data sets using a three-pronged statistical, operational, and expert validation approach. Furthermore, it also presents a set of statistical and operational metric targets for achieving realistic data sets based on detailed characterization of more than 10,000 real U.S. utility feeders. The paper demonstrates the use of the proposed validation approach to validate three large-scale synthetic data sets developed by the authors representing Santa Fe, New Mexico; Greensboro, North Carolina; and the San Francisco Bay Area, California.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2011

A survey of Existing V&V, UQ and M&S Data and Knowledge Bases in Support of the Nuclear Energy - Knowledge base for Advanced Modeling and Simulation (NE-KAMS)

The Nuclear Energy - Knowledge base for Advanced Modeling and Simulation (NE-KAMS) is being developed at the Idaho National Laboratory in conjunction with Bettis Laboratory, Sandia National Laboratories, Argonne National Laboratory, Oak Ridge National Laboratory, Utah State University and others. The objective of this consortium is to establish a comprehensive knowledge base to provide Verification and Validation (V&V) and Uncertainty Quantification (UQ) and other resources for advanced modeling and simulation (M&S) in nuclear reactor design and analysis. NE-KAMS will become a valuable resource for the nuclear industry, the national laboratories, the U.S. NRC and the public to help ensure the safe operation of existing and future nuclear reactors. A survey and evaluation of the state-of-the-art of existing V&V and M&S databases, including the Department of Energy and commercial databases, has been performed to ensure that the NE-KAMS effort will not be duplicating existing resources and capabilities and to assess the scope of the effort required to develop and implement NE-KAMS. The survey and evaluation have indeed highlighted the unique set of value-added functionality and services that NE-KAMS will provide to its users. Additionally, the survey has helped develop a better understanding of the architecture and functionality of these data and knowledge bases that can be used to leverage the development of NE-KAMS.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗