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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Analysis of Solar Census Remote Solar Access Value Calculation Methodology

The costs of photovoltaic (PV) system hardware (PV panels, inverters, racking, etc.) have fallen dramatically over the past few years. Nonhardware (soft) costs, however, have failed to keep pace with the decrease in hardware costs, and soft costs have become a major driver of U.S. PV system prices. Upfront or 'sunken' customer acquisition costs make up a portion of an installation's soft costs and can be addressed through software solutions that aim to streamline sales and system design aspects of customer acquisition. One of the key soft costs associated with sales and system design is collecting information on solar access for a particular site. Solar access, reported in solar access values (SAVs), is a measurement of the available clear sky over a site and is used to characterize the impacts of local shading objects. Historically, onsite shading studies have been required to characterize the SAV of the proposed array and determine the potential energy production of a photovoltaic system.

14 SOLAR ENERGY↗
DOE OSTI2017

Cloud Type Classification (cldtype) Value-Added Product

The Cloud Type (cldtype) value-added product (VAP) provides an automated cloud type classification based on macrophysical quantities derived from vertically pointing lidar and radar. Up to 10 layers of clouds are classified into seven cloud types based on predetermined and site-specific thresholds of cloud top, base and thickness. Examples of thresholds for selected U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility sites are provided in Tables 1 and 2. Inputs for the cldtype VAP include lidar and radar cloud boundaries obtained from the Active Remotely Sensed Cloud Location (ARSCL) and Surface Meteorological Systems (MET) data. Rain rates from MET are used to determine when radar signal attenuation precludes accurate cloud detection. Temporal resolution and vertical resolution for cldtype are 1 minute and 30 m respectively and match the resolution of ARSCL. The cldtype classification is an initial step for further categorization of clouds. It was developed for use by the Shallow Cumulus VAP to identify potential periods of interest to the LASSO model and is intended to find clouds of interest for a variety of users.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Estimating the Value of Improved Distributed Photovoltaic Adoption Forecasts for Utility Resource Planning

Misforecasting the adoption of customer-owned distributed photovoltaics (DPV) can have operational and financial implications for utilities - forecasting capabilities can be improved, but generally at a cost. This paper informs this decision-space by quantifying the costs of misforecasting across a wide range of DPV growth rates and misforecast severities. Using a simplified probabilistic method presented within, an analyst can make a first-order estimate of the financial benefit of improving a utility's forecasting capabilities, and thus be better informed about whether to make such an investment. For example, we show that a utility with 10 TWh per year of retail electric sales who initially estimates that the increase in DPV's contribution to total generation could range from 2 to 7.5 percent over the next 15 years could expect total present-value savings of approximately 4 million dollars if they could keep the severity of successive five-year misforecasts within plus or minus 25 percent. We also have more general discussions about how misforecasting DPV impacts the buildout and operation of the bulk power system - for example, we observed that misforecasting DPV most strongly influenced the amount of utility-scale PV that gets built, due to the similarity in the energy and capacity services offered by the two solar technologies.

14 SOLAR ENERGY↗
DOE OSTI2018

Shallow Cumulus (SHALLOWCUMULUS) Value-Added Product Report

Periods of shallow cumulus clouds are identified automatically at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory in order to help determine times of interest for Large-Eddy Simulation (LES) and Observation (LASSO) modeling efforts. This value-added data product (VAP) uses input from the Cloud Type (CLDTYPE) VAP (with cloud types determined from Active Remotely Sensed Cloud Locations [ARSCL] VAP cloud boundaries), the ceilometer, and the total sky imager (TSI). The data set uses an hourly temporal resolution and only classifies events as shallow cumulus when low clouds are detected for at least 1.5 hours and meet specified criteria for cloud occurrence and cloud fraction. In addition to time periods that contain just shallow cumulus, cases with overlying cirrus and a number of transitional cases (transitions to/from cirrus, stratus, and altocumulus/altostratus) are also identified.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Estimating the Value of Improved Distributed Photovoltaic Adoption Forecasts for Utility Resource Planning

Misforecasting the adoption of customer-owned distributed photovoltaics (DPV) can have operational and financial implications for utilities - forecasting capabilities can be improved, but generally at a cost.This paper informs this decision-space by quantifying the costs of misforecasting across a wide range of DPV growth rates and misforecast severities. Using a simplified probabilistic method presented within, an analyst can make a first-order estimate of the financial benefit of improving a utility's forecasting capabilities, and thus be better informed about whether to make such an investment. For example, we show that a utility with 10 TWh per year of retail electric sales who initially estimates that the increase in DPV's contribution to total generation could range from 2 percent to 7.5 percent over the next 15 years could expect total present-value savings of approximately 4 million if they could keep the severity of successive five-year misforecasts within +/- 25 percent. We also have more general discussions about how misforecasting DPV impacts the buildout and operation of the bulk power system - for example, we observed that misforecasting DPV most strongly influenced the amount of utility-scale PV that gets built, due to the similarity in the energy and capacity services offered by the two solar technologies.

14 SOLAR ENERGY↗
DOE OSTI2018

Value Streams from Distribution Grid Support Using Utility-Scale Vanadium Redox Flow Battery: NREL-Sumitomo Electric Battery Demonstration Project

The National Renewable Energy Laboratory (NREL) collaborated with Sumitomo Electric to provide research support in modeling and optimally dispatching a utility-scale vanadium redox flow battery (VRFB) energy storage. The objective of the project was to identify value streams from using utility-scale VRFB for local grid support use-cases, including voltage regulation (droop), capacity firming, peak shaving and valley filling, and energy arbitrage. This project was also supported by San Diego Gas and Electric (SDGandE). SDGandE provided data and approval to operate their VRFB energy storage system on an SDGandE distribution feeder. NREL worked with Sumitomo Electric to evaluate optimal dispatch strategies to VRFB, analyze the technical impacts, and calculate the associated cost-benefit ratio of substation-level energy storage on an SDG&E distribution feeder. To support this research, NREL evaluated the impacts of the battery use cases suggested by Sumitomo on the SDGandE host feeder. In addition to evaluating the battery use case, this effort identified possible ways to monetize the benefits from distribution feeder support.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Optimizing the Energy Usage and Cognitive Value of Extreme-Scale Data-Analysis Approaches

This report serves as a record that we have successfully completed work on the proposal Optimizing the Energy Usage and Cognitive Value of Extreme Scale Analysis Approaches, or, more succinctly, ECX. This includes successful completion of all three phases of the project, findings as summarized below, strong publications across the fields represented in the proposal, and a set of artifacts (code, websites, and other documentation) available to the public. In total, the results of this project represent significant findings in each domain, and a toolkit that will allow the community to engage with this work, advancing it and contributing to it in the years ahead. They also form the basis for a successfully funded follow-on project.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

The QCECOR Value-Added Product: Quality-Controlled Eddy Correlation Flux Measurements

Eddy correlation flux (ECOR) measurement system stations are used by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility to provide surface turbulence flux measurements. In recent years, ARM has significantly enhanced its ECOR systems and made them available at all its primary research observatories and mobile facilities. However, the original ECOR data were not corrected through common eddy correlation corrections and still contain suspicious data due to instrument and measurement uncertainties. Such uncertainties in the ECOR surface turbulence fluxes hampered their uses by the user community. To improve the ECOR data, we develop a value-added product (VAP) —the Quality-Controlled Eddy Correlation Flux (QCECOR) — by applying the following necessary corrections and quality control (QC) procedures: Eddy correlation corrections. Determination of the quality-controlled energy fluxes from the corrected ECOR fluxes. Stringent QC checks. Flagging possible incorrect fluxes due to hydrometeor impacts using the collocated surface energy balance system (SEBS) wetness measurements. The QCECOR VAP currently contains two variables: surface latent heat flux (LH) and sensible heat flux (SH), together with their QC flags. When SEBS are collocated with ECOR, the wetness measurements from SEBS are used to flag the LH that may be incorrect due to hydrometeors such as precipitation, dew, or frost. An indeterminate flag is given to those that fail the wetness test. The QCECOR data are currently available at the Southern Great Plains (SGP) atmospheric observatory for the ARM extended facilities of E1, E3, E5, E6, E10, E14, E16, E21, E24, E31, E33, E37, E38, E39, and E41 updated to 2018. The data are also available at the following AMF sites: PYE (Point Reyes, 2005), NIM (Niamey, Niger, 2006), FKB (Black Forest, Germany, 2007), HFE (Shouxian, China, 2008), GRW (Azores, 2009 to 2010), and MAO (Manacapuru, Brazil, 2014-2015). The algorithm is now in the process of moving to production mode. After that, QCECOR will run automatically for all available ARM sites.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Quantifying Rooftop Solar Benefits: A State-Level Value of Solar Analysis for India

Analyses that quantify the costs and benefits associated with rooftop solar (RTS) adoption and operation can inform decision-makers in the development and evaluation of RTS policies. One such analysis is a Value of Solar (VOS) study, which quantifies select costs and benefits surrounding RTS based on the electricity system context. These studies can drive changes to existing policies towards fairer, more cost-reflective RTS compensation or alternatively can provide confidence for the decision-maker to stay the course and largely maintain existing policies. This report provides a VOS analysis for two states in India: Gujarat and Jharkhand and provides details related to the methodology and key findings.

14 SOLAR ENERGY↗
DOE OSTI2022

Framework for Quantitative Evaluation of Resilience Solutions: An Approach to Determine the Value of Resilience for a Particular Site

The paper provides the approach to providing a benefit cost analysis of energy and water alternatives to provide resilience to extreme events. The approach estimates the costs and returns of providing greater resilience of water and energy infrastructure. Extreme events are defined as high impact, low-frequency events such as, but not limited to, hurricanes, floods, storm surges and earthquakes. The provides justification for hardening water and energy infrastructure. Resilience is defined as “the ability to prepare for and to withstand an extreme event with little or no damage, or to recover more quickly from an extreme event.” The approach can be summarized as follows. The approach requires the development of a baseline with which to compare alternatives. The baseline is used to evaluate the baseline’s resilience to hazards through the probability of the hazard(s), the likelihood of damage from that the hazard through a vulnerability analysis, and the consequence to calculate a cost of the damage. The approach then evaluates proposed mitigation alternatives that would improve the resilience of the system. Each alternative is evaluated based on probability of the hazard, probability of vulnerability and consequence to determine the reduced damage that each alternative presents. The approach includes any monetary and non-monetary benefits that can quantified for each of the alternatives. Non-quantifiable benefits are evaluated based on the relative importance of each alternative to the criteria used to determine how well the alternative meets the goals and objectives of the site/facility. Then, a life cycle cost analysis should be conducted for the baseline and alternatives. Finally, the results of the life cycle analysis should be presented in a decision matrix with cost, net present value, benefit/cost ratios, and any non-monetary criteria ranked to show how well the alternatives met the criteria, weighted with the decision maker’s weights and the results presented.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

High Precision Penning Trap Measurements of beta-decay Q-values for Neutrino Physics

The 2015 Nobel Prize in physics was awarded to Takaaki Kajita and Arthur B. McDonald “for the discovery of neutrino oscillations, which shows that neutrinos have mass”. This fact has wide reaching implications for the standard model of particle physics, nuclear physics, and cosmology. However, important fundamental questions remain: What is the absolute neutrino mass scale? Is the neutrino a Majorana or a Dirac particle? A number of large-scale experiments are underway or are being developed to attempt to answer these questions. Two classes of experiments are direct neutrino mass determination experiments, and searches for neutrinoless double betadecay. This work aimed to aid these experiments via high-precision Q value determinations for the relevant isotopes using Penning trap mass spectrometry (PTMS).

42 ENGINEERING↗
DOE OSTI2022

Combined Sugarcane Pretreatment for the Generation of Ethanol and Value-Added Products

In this work, we have tested individual and combination of applications of ozonolysis and liquid hot water (LHW) to pretreat sugarcane bagasse (SCB) for the removal of enzyme and/or microbial inhibitors and generation of potential value-added chemicals. A solid content with 80% cellulose and a liquid phase (liquor) rich in phenolic derived compounds (3 g . L −1 ) from lignin, sugars (>20 g . L −1 ), and other compounds, such as furfural and hydroxymethylfurfural (HMF), were generated. Maximal (59%) glucan conversion occurred in the presence of double-pretreated bagasse, which had 32–50% more glucan available than the samples that were individually LHW or ozone-pretreated, resulting in maximal ethanol production (92% after 42 h) from double-pretreated SCB enzyme hydrolyzate. In summary, this work showed that ozone reacts effectively with lignin without the use of any other chemical reagent, and LHW pretreatment, followed by a washing step, was effective in solubilizing and cleaning up the fiber enzyme and microbial inhibitory compounds with ozone being effective against phenolics. Moreover, the generated cellulose-rich substrate is readily fermentable. The acidic liquor fraction removed by sequential washings and containing mainly sugars and phenolic compounds may be evaluated for use in green chemistry bioconversions processes.

09 BIOMASS FUELS↗
DOE OSTI2024

OctoFAS: A Two-Level Fair Scheduler That Increases Fairness in Network-Based Key-Value Storage

We identified a fairness problem in a network-based key-value storage system using Intel Storage Performance Development Kit (SPDK) in a multitenant environment. In such an environment, each tenant’s I/O service rate is not fairly guaranteed compared to that of other tenants. To address the fairness problem, we propose OctoFAS, a two-level fair scheduler designed to improve overall throughput and fairness among tenants. The two-level scheduler of OctoFAS consists of (i) inter-core scheduling and (ii) intra-core scheduling. Through inter-core scheduling, OctoFAS addresses the load imbalance problem that is inherent in SPDK on the storage server by dynamically migrating I/O requests from overloaded cores to underloaded cores, thereby increasing overall throughput. Intra-core scheduling prioritizes handling requests from starving tenants over well-fed tenants within core-specific event queues to ensure fair I/O services among multiple tenants. OctoFAS is deployed on a Linux cluster with SPDK. Through extensive evaluations, we found that OctoFAS ensures that the total system throughput remains high and balanced, while enhancing fairness by approximately 10% compared to the baseline, when both scheduling levels operate in a hybrid fashion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Improving Prediction of Peroxide Value of Edible Oils Using Regularized Regression Models

We present four unique prediction techniques, combined with multiple data pre-processing methods, utilizing a wide range of both oil types and oil peroxide values (PV) as well as incorporating natural aging for peroxide creation. Samples were PV assayed using a standard starch titration method, AOCS Method Cd 8-53, and used as a verified reference method for PV determination. Near-infrared (NIR) spectra were collected from each sample in two unique optical pathlengths (OPLs), 2 and 24 mm, then fused into a third distinct set. All three sets were used in partial least squares (PLS) regression, ridge regression, LASSO regression, and elastic net regression model calculation. While no individual regression model was established as the best, global models for each regression type and pre-processing method show good agreement between all regression types when performed in their optimal scenarios. Furthermore, small spectral window size boxcar averaging shows prediction accuracy improvements for edible oil PVs. Best-performing models for each regression type are: PLS regression, 25 point boxcar window fused OPL spectral information RMSEP = 2.50; ridge regression, 5 point boxcar window, 24 mm OPL, RMSEP = 2.20; LASSO raw spectral information, 24 mm OPL, RMSEP = 1.80; and elastic net, 10 point boxcar window, 24 mm OPL, RMSEP = 1.91. The results show promising advancements in the development of a full global model for PV determination of edible oils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Sun's Series via Cyclotomic Multiple Zeta Values

We prove and generalize several recent conjectures of Z.-W. Sun surrounding binomial coefficients and harmonic numbers. We show that Sun's series and their analogs can be represented as cyclotomic multiple zeta values of levels N ϵ {4,8,12,16,24} , namely Goncharov's multiple polylogarithms evaluated at N -th roots of unity.

97 MATHEMATICS AND COMPUTING↗