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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 739 records · Page 41

PV Fleet Performance Data Initiative: Performance Index-Based Analysis

In this analysis, we report on 250 PV systems throughout the US, comprising 157 MWdc of system capacity and over 10,000 monthly PI values based on high-frequency (subhourly) energy data and satellite-based resource data. The distribution of PI values is analyzed, and multiple causes of underperformance are assessed, including first-year startup issues, snowfall and inverter downtime. An initial distribution of raw monthly PI values was collected with mean measured / modeled performance of PI = 0.935. After correcting for the three identifiable loss factors mentioned above, an average monthly performance of PI = 0.994 was obtained, with a distribution closely following a Gumbel Extreme Value distribution. In particular, inverter availability was found to contribute a system energy loss of 2.3% on average, except in the first six months of operation when availability losses are closer to 8%. Other startup issues beyond inverter downtime such as partial string outage contributed an additional 5% underperformance in the first year of operation across the fleet. Winter performance was also found to be 5%-10% below summer performance on average, likely due to snowfall. A simple linear relationship was found between snow loss and monthly snowfall accumulation in cm, indicating between 6% - 40% loss in months with nonzero snowfall, depending on climate.

14 SOLAR ENERGY↗

Pressure sensing of the atmosphere by solar occultation - An application to remote sensing of atmospheric minor gases

The simultaneous inference of pressure and gas concentration in a remote-sensing experiment will increase the accuracy of inverted gas concentrations and minimize the dependence of the experiment on pressure or mass-path error resulting from use of climatological pressure data, satellite ephemeris, and instrument pointing accuracy. A technique for obtaining tangent-point pressure information needed for inversion of gas concentration in an IR solar occultation experiment is described. By measuring IR absorption in bands of atmospheric CO2 (e.g., 2.0, 2.7, or 4.3 microns) pressure values for each layer (2 km or less in the vertical) of the atmosphere can be obtained with rms errors of less than 3%.

Park, J. H.↗

Road load simulator tests of the Gould phase 1 functional model silicon controlled rectifier ac motor controller for electric vehicles

The test results for a functional model ac motor controller for electric vehicles and a three-phase induction motor which were dynamically tested on the Lewis Research Center road load simulator are presented. Results show that the controller has the capability to meet the SAE-J227a D cycle test schedule and to accelerate a 1576-kg (3456-lb) simulated vehicle to a cruise speed of 88.5 km/hr (55 mph). Combined motor controller efficiency is 72 percent and the power inverter efficiency alone is 89 percent for the cruise region of the D cycle. Steady state test results for motoring, regeneration, and thermal data obtained by operating the simulator as a conventional dynamometer are in agreement with the contractor's previously reported data. The regeneration test results indicate that a reduction in energy requirements for urban driving cycles is attainable with regenerative braking. Test results and data in this report serve as a data base for further development of ac motor controllers and propulsion systems for electric vehicles. The controller uses state-of-the-art silicon controlled rectifier (SCR) power semiconductors and microprocessor-based logic and control circuitry. The controller was developed by Gould Laboratories under a Lewis contract for the Department of Energy's Electric and Hybrid Vehicle program.

Gourash, F.↗

Reflectance Modeling

The main thrust of the work conducted is in the modeling of spectral responses of discontinuous conifer forest canopies, considered as collections of conical forms that are illuminated at an angle and cast shadows on contracting background. The three first-year objectives are: (1) modification of the variance-driven model to incorporate overlapping of shadows and crowns; (2) collection and analysis of photographic data to calibrate tree-spacing functions; and (3) collection of field data to determine height, spacing, and shape of conifers in open and closed stands in the Goosenest (California) test area. Modification of the invertible model uses a linear approximation to correct for the reduction in shadow and canopy area that occurs when shadows fall on crowns or tree crowns intersect. Comparison of the results of the approximation with a series of Monte Carlo simulations shows that the mean area covered by crowns or shadows is approximated quite accurately, but the variance calculated departs significantly from simulated values. The analysis of tree spacing patterns using air photos showed that spacing tended to be somewhat regular at a scale approximately equal to the average distance between trees, but at larger distance scales counts of trees in cells could be approximated acceptably by a Poisson (random) function.

Strahler, A. H.↗

Buoyancy Effects upon Vapor Flame and Explosion Processes

The objective of this microgravity project is to develop an experimental and theoretical analyses critical to the understanding of the coupling of buoyancy and turbulence generation and its effect on fuel-air mixing, flame intensity and flame propagation in jet diffusion flames. The experiment is designed to examine certain effects of buoyancy acting on a diffusion flame in which the flame is directed either upward or downward. This change from negative to positive g is observed to significantly alter the flame shape although all other operating conditions are the same for both configurations. However, to perform this experiment a significant coaxial secondary air flow is needed in order to prevent flow reversal when the flame is inverted. The theoretical analysis that has been developed handles the secondary air flow and the extreme change in gravity vector direction. Thus the data will provide a measure of credibility of the analysis which will then be used to assist in the design of the actual zero-g experiment.

Edelman, R. B.↗

Experimental measurement of solutal and thermal layers in unidirectional solidification

An experimental study to evaluate and characterize the effects and causes of convection in the directional solidification of metal alloys is described. The temporal history of the inverted density layers in front of a dendritic interface for directionally solidified ammonium chloride-(72 wt pct) water is presented based on photographic data taken using a laser schlieren system. Data are given for both 1-g and low-g solidification runs, and the stability of the layer is discussed. The reduction of buoyancy effects is shown to be significant, and the possible impact of reducing gravity level on freckling in metal alloys is considered.

Mccay, M. H.↗

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities: Preprint

Increased penetration of distributed variable re-newable generation may cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But due to the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network is needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69 node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Recent Photovoltaic Performance Data in the USA (Presentation)

This paper presents performance data from nearly 50,000 Photovoltaic systems totaling 1.7 Gigawatts installed capacity in the USA from 2009 to 2012. 90% of the systems performed to within 10% or better of expected performance. Only 2-4% of the data indicate issues significantly affecting the system performance. Special causes of underperformance and their impacts are delineated by reliability category. Delays and interconnections dominate project-related issues particularly in the first year, but total less than 0.5% of all systems. Hardware-related issues are dominated by inverter problems totaling less than 0.4% and underperforming modules to less than 0.1%.

14 SOLAR ENERGY↗

Machine learning reveals strong grid-scale dependence in the satellite N d –LWP relationship

The relationship between cloud droplet number concentration ( N d ) and liquid water path (LWP) is highly uncertain yet crucial for determining the impact of aerosol-cloud interactions (ACI) on Earth's radiation budget. The N d -LWP relationship is examined using a machine learning (ML) random forest model applied to five years of satellite data at grid resolutions ranging from 10° to 0.05° in 12 distinct regions. In the subtropics, the shape of the N d -LWP relationship switches from an inverted-V at 1° grid-resolution to an “M” shape at 0.1° resolution with decreased $\frac{\textrm{dln⁡LWP}}{\textrm{dln⁡}N_d}$ sensitivity. Tropical and midlatitude regions generally show a more positive sensitivity. Cloud sampling and filtering also influence this slope, wherein the exclusion of thin clouds, as commonly performed to reduce retrieval uncertainty, leads to strongly negative sensitivity across all regions. Precipitation is primarily responsible for driving the strength of the sensitivity, with strong positive slopes in raining clouds and negative and/or neutral responses found in non-raining clouds. A new method to compute radiative forcing from the ML model shows a robust Twomey radiative forcing across all regions and grid resolutions. However, LWP and cloud fraction adjustments to the radiative forcing, which are ∼50 % or smaller than the Twomey effect, decrease to negligible values with higher spatial resolution data. As Earth system models move toward higher spatial resolutions in the future, evaluating the LWP and CF adjustment contributions to the radiative forcing budget at these finer resolutions will be essential for evaluation and model development.

Aerosol-Cloud Interactions↗

Towards real-time monitoring: data assimilated time-lapse full waveform inversion for seismic velocity and uncertainty estimation

SUMMARY Rapid development of time-lapse seismic monitoring instrumentations has made it possible to collect dense time-lapse data for tomographically retrieving time-lapse (even continuous) images of subsurface changes. While traditional time-lapse full waveform inversion (TLFWI) algorithms are designed for sparse time-lapse surveys, they lack of effective temporal constraint on time-lapse data, and, more importantly, lack of the uncertainty estimation of the TLFWI results that is critical for further interpretation. Here, we propose a new data assimilation TLFWI method, using hierarchical matrix powered extended Kalman filter (HiEKF) to quantify the image uncertainty. Compared to existing Kalman filter algorithms, HiEKF allows to store and update a data-sparse representation of the cross-covariance matrices and propagate model errors without expensive operations involving covariance matrices. Hence, HiEKF is computationally efficient and applicable to 3-D TLFWI problems. Then, we reformulate TLFWI in the framework of HiEKF (termed hereafter as TLFWI-HiEKF) to predict time-lapse images of subsurface spatiotemporal velocity changes and simultaneously quantify the uncertainty of the inverted velocity changes over time. We demonstrate the validity and applicability of TLFWI–HiEKF with two realistic CO2 monitoring models derived from Frio-II and Cranfield CO2 injection sites, respectively. In both 2-D and 3-D examples, the inverted high-resolution time-lapse velocity results clearly reveal a continuous velocity reduction due to the injection of CO2. Moreover, the accuracy of the model is increasing over time by assimilating more time-lapse data while the standard deviation is decreasing over lapsed time. We expect TLFWI-HiEKF to be equipped with real-time seismic monitoring systems for continuously imaging the distribution of subsurface gas and fluids in the future large-scale CO2 sequestration experiments and reservoir management.

58 GEOSCIENCES↗

Analysis techniques for background rejection at the MAJORANA DEMONSTRATOR

The MAJORANA Collaboration is constructing the MAJORANA DEMONSTRATOR, an ultra-low background, 40- kg modular HPGe detector array to search for neutrinoless double beta decay in {sup 76}Ge. In view of the next generation of tonne-scale Ge-based 0νβ β-decay searches that will probe the neutrino mass scale in the inverted-hierarchy region, a major goal of the MAJORANA DEMONSTRATOR is to demonstrate a path forward to achieving a background rate at or below 1 count/tonne/year in the 4 keV region of interest around the Q-value at 2039 keV. The background rejection techniques to be applied to the data include cuts based on data reduction, pulse shape analysis, event coincidences, and time correlations. The Point Contact design of the DEMONSTRATOR’s germanium detectors allows for significant reduction of gamma background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Method for Assessing the Quality of Model-Based Estimates of Ground Temperature and Atmospheric Moisture Using Satellite Data

A method is developed for validating model-based estimates of atmospheric moisture and ground temperature using satellite data. The approach relates errors in estimates of clear-sky longwave fluxes at the top of the Earth-atmosphere system to errors in geophysical parameters. The fluxes include clear-sky outgoing longwave radiation (CLR) and radiative flux in the window region between 8 and 12 microns (RadWn). The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data, and multiple global four-dimensional data assimilation (4-DDA) products. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic clear-sky longwave fluxes from two different 4-DDA data sets. Simple linear regression is used to relate the clear-sky longwave flux discrepancies to discrepancies in ground temperature ((delta)T(sub g)) and broad-layer integrated atmospheric precipitable water ((delta)pw). The slopes of the regression lines define sensitivity parameters which can be exploited to help interpret mismatches between satellite observations and model-based estimates of clear-sky longwave fluxes. For illustration we analyze the discrepancies in the clear-sky longwave fluxes between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS2) and a recent operational version of the European Centre for Medium-Range Weather Forecasts data assimilation system. The analysis of the synthetic clear-sky flux data shows that simple linear regression employing (delta)T(sub g)) and broad layer (delta)pw provides a good approximation to the full radiative transfer calculations, typically explaining more thin 90% of the 6 hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters, Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for (delta)T(sub g) to approx. 20% for the lower tropospheric moisture between 500 hPa and surface. The regression relationships developed from the synthetic flux data, together with CLR and RadWn observed with the Clouds and Earth Radiant Energy System instrument, ire used to assess the quality of the GEOS2 T(sub g) and pw. Results showed that the GEOS2 T(sub g) is too cold over land, and pw in upper layers is too high over the tropical oceans and too low in the lower atmosphere.

Wu, Man Li C.↗

The Stratospheric Aerosol and Gas Experiment II (SAGE II) design and in-orbit performance

The design and in-orbit performance data are presented for the Stratospheric Aerosol and Gas Experiment II (SAGE II) instrument which was launched by Shuttle on the Earth Radiation Budget Satellite. SAGE II is a sun photometer that measures the extinction of solar radiation caused by the earth's atmosphere in seven spectral channels ranging in center wavelength from 0.385 to 1.02 micrometers. These measurements, which occur twice each orbit during satellite sunrise and sunset, are inverted to yield vertical distributions of stratospheric aerosols, ozone, water vapor, and nitrogen dioxide. The SAGE II instrument consists of a Cassegrain telescope with a two axis gimbal mounting, a grating spectrometer, and a 12 bit data system. The instrument tracks the solar centroid in the azimuth plane and vertically scans the instrument's instantaneous field of view across the sun for tangent altitudes ranging from the earth's horizon to 150 km. SAGE II is a third generation instrument following the highly successful Stratospheric Aerosol Measurement II (SAM II) and SAGE I programs.

Mauldin, L. E., III↗

Steep-sided domes on Venus - Characteristics, geologic setting, and eruption conditions from Magellan data

A survey of more than 95 percent of the Venus surface reveals 145 steep-sided domes which can be subdivided into a variety of morphologic forms, the most common being shaped like inverted bowls or flat-topped domes. Results of a preliminary analysis of the distribution and geologic setting of the domes are presented. The relation of the domes to analogous terrestrial features is examined, and possible models for their mode of emplacement are outlined.

Pavri, Betina↗

NREL/SCE High-Penetration PV Integration Project: Report on Field Demonstration of Advanced Inverter Functionality in Fontana, CA

The National Renewable Energy Laboratory/Southern California Edison High-Penetration PV Integration Project is (1) researching the distribution system level impacts of high-penetration photovoltaic (PV) integration, (2) determining mitigation methods to reduce or eliminate those impacts, and (3) seeking to demonstrate these mitigation methods on actual high-penetration PV distribution circuits. This report describes a field demonstration completed during the fall of 2013 on the Fontana, California, study circuit, which includes a total of 4.5 MW of interconnected utility-scale rooftop PV systems. The demonstration included operating a 2-MW PV system at an off-unity power factor that had been determined during previously completed distribution system modeling and PV impact assessment analyses. Data on the distribution circuit and PV system operations were collected during the 2-week demonstration period. This demonstration reinforces the findings of previous laboratory testing that showed that utility-scale PV inverters are capable of operating at off-unity power factor to mitigate PV impacts; however, because of difficulties setting and retaining PV inverter power factor set points during the field demonstration, it was not possible to demonstrate the effectiveness of off-unity power factor operation to mitigate the voltage impacts of high-penetration PV integration. Lessons learned from this field demonstration are presented to inform future field demonstration efforts.

14 SOLAR ENERGY↗

Detection and Diagnosis of Data Integrity Attacks in Solar Farms Based on Multilayer Long Short-Term Memory Network

Photovoltaic (PV) systems are becoming more vulnerable to cyber threats. In response to this emerging concern, developing cyber-secure power electronics converters has received increased attention from the IEEE Power Electronics Society that recently launched a cyber-physical-security initiative. Here this letter proposes a deep sequence learning based diagnosis solution for data integrity attacks on PV systems in smart grids, including dc–dc and dc–ac converters. The multilayer long short-term memory networks are used to leverage time-series electric waveform data from current and voltage sensors in PV systems. The proposed method has been evaluated in a PV smart grid benchmark model with extensive quantitative analysis. As a comparison, we have evaluated classic data-driven methods, including K-nearest neighbor, decision tree, support vector machine, artificial neural network, and convolutional neural network. Comparison results verify performances of the proposed method for detection and diagnosis of various data integrity attacks on PV systems.

42 ENGINEERING↗

Integration and Validation of Multi-Layer Mitigation Strategies for Cyber Physical Systems Resilience (RD2C Capstone I Project) (Technical Report)

This project demonstrated the effectiveness of RD2C-developed, resilience-driven control strategies on high-fidelity system models with high penetrations of inverter-based resources, under the impacts of unexpected natural events and cyber-physical attacks. Controller performance and overall system resilience were quantified using data from a comprehensive suite of scenarios, and provided a clear understanding on how to operate and deploy these mitigation strategies.

42 ENGINEERING↗

Evaluation of a Reduced-Order Model for IBR Fault Response Representation via OEM Blackbox Models

This paper presents a fully implemented inverter reduced-order-model (ROM) in an EMT simulation (PSCAD) library component for direct user utilization in protection studies. The developed inverter ROM has the following features: Equivalent to a full inverter-based resource (IBR) inverter model with positive- and negative-sequence current formulation and representation. A Python script is developed to fully automate this process, including training data generation, ROM parameter training, updating parameters, and model verification and validation. The ROM is validated using both IEEE 2800-compliant and non-compliant OEM modes in a real-world system, building confidence of its usability by protection engineers.

24 POWER TRANSMISSION AND DISTRIBUTION↗