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DOE OSTI2014

Full-wavefield inversion of surface waves for mapping embedded low-velocity zones in permafrost

Surface waves are advantageous for mapping seismic structures of permafrost, in which irregular velocity gradients are common and thus the effectiveness of refraction methods are limited. Nevertheless, the complex velocity structures that are common in permafrost environments often yield unusual dispersion spectra, in which higher-order and leaky modes are dominant. Such unusual dispersion spectra were prevalent in the multichannel surface-wave data acquired from our permafrost study site at Barrow, Alaska. Owing to the difficulties in picking and identifying dispersion curves from these dispersion spectra, conventional surface-wave inversion methods become problematic to apply. Here, to overcome these difficulties, we adopted a full-wavefield method to invert for velocity models that can best fit the dispersion spectra instead of the dispersion curves. The inferred velocity models were consistent with collocated electric resistivity results and with subsequent confirmation cores, which indicated the reliability of the recovered seismic structures. The results revealed embedded low-velocity zones underlying the ice-rich permafrost at our study site — an unexpected feature considering the low ground temperatures of - 10 ° C to - 8 ° C . The low velocities in these zones ( ~ 70 % – 80 % lower than the overlying ice-rich permafrost) were most likely caused by saline pore-waters that prevent the ground from freezing, and the resultant velocity structures are vivid examples of complex subsurface properties in permafrost terrain. Finally, we determined that full-wavefield inversion of surface waves, although carrying higher computational costs than conventional methods, can be an effective tool for delineating the seismic structures of permafrost.

58 GEOSCIENCES↗

DOE OSTI2024

On the connection between least squares, regularization, and classical shadows

Classical shadows (CS) offer a resource-efficient means to estimate quantum observables, circumventing the need for exhaustive state tomography. Here, we clarify and explore the connection between CS techniques and least squares (LS) and regularized least squares (RLS) methods commonly used in machine learning and data analysis. By formal identification of LS and RLS ``shadows'' completely analogous to those in CS---namely, point estimators calculated from the empirical frequencies of single measurements---we show that both RLS and CS can be viewed as regularizers for the underdetermined regime, replacing the pseudoinverse with invertible alternatives. Through numerical simulations, we evaluate RLS and CS from three distinct angles: the tradeoff in bias and variance, mismatch between the expected and actual measurement distributions, and the interplay between the number of measurements and number of shots per measurement. Compared to CS, RLS attains lower variance at the expense of bias, is robust to distribution mismatch, and is more sensitive to the number of shots for a fixed number of state copies---differences that can be understood from the distinct approaches taken to regularization. Conceptually, our integration of LS, RLS, and CS under a unifying ``shadow'' umbrella aids in advancing the overall picture of CS techniques, while practically our results highlight the tradeoffs intrinsic to these measurement approaches, illuminating the circumstances under which either RLS or CS would be preferred, such as unverified randomness for the former or unbiased estimation for the latter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2024

Opinion: Aerosol Remote Sensing Over the Next Twenty Years

More than two decades ago, aerosol remote sensing underwent a revolution with the launch of the Terra and Aqua satellites. Advancement continued via additional launches carrying new passive and active sensors. Capable of retrieving parameters characterizing aerosol loading, rudimentary particle properties and in some cases aerosol layer height, the satellite view of Earth’s aerosol system came into focus.The modeling communities have made similar advances. Now the efforts have continued long enough that we can see developing trends in both remote sensing and modeling communities, allowing us to speculate about the future and how the community will approach aerosol remote sensing twenty years from now. We anticipate technology that will replace today’s standard multi-wavelength radiometers with hyperspectral and/or polarimetry all viewing in multiple angles.These will be supported by advanced active sensors with the ability to measure profiles of aerosol extinction in addition to backscatter. The result will be greater insight into aerosol particle properties. Algorithms will move from being primarily physically-based to include an increasing degree of Machine Learning methods, but physically-based techniques will not go extinct. However, the practice of applying algorithms to a single sensor will be in decline. Retrieval algorithms will encompass multiple sensors and all available ground measurements into a unifying framework, and these inverted products will be ingested directly into assimilation systems, becoming “cyborgs”: half observations, half model. In twenty years we will see a true democratization in space with nations large and small, private organizations and commercial entities of all sizes launching space sensors. With this increasing amount of data and aerosol products available, there will be a lot of bad data. User communities will organize to set standards and the large national space agencies will lead the effort to maintain quality by deploying and maintaining validation ground networks and focused field experiments. Through it all, interest will remain high in the global aerosol system and how that system affects climate, clouds, precipitation and dynamics, air quality, the environment and public health, transport of pathogens and fertilization of ecosystems, and how these processes are adapting to a changing climate.

aerosol remote sensing↗

DOE OSTI2020

Real-Time Distributed Control of Smart Inverters for Network-level Optimization

The limitations of centralized optimization methods in managing electric power distribution systems operations have led to the distributed paradigm of computing and decision-making. Unfortunately, the existing distributed optimization algorithms are limited in their applicability to managing fast varying phenomena such as those resulting from highly variable Distributed Energy Resource (DER) generation patterns. They require a large number of communication rounds (in the order of 10 2 to 10 3 ) among the computing agents to solve one instance of the optimization problem. Related real-time distributed control methods are equally limited in their applications to power distribution systems with fast-changing DER generation; they require hundreds of rounds of communication and thus are slow in tracking the network-level optimal solutions. In this paper, we propose a novel distributed voltage controller that provides a fast-tracking of rapidly varying DER generation profiles while simultaneously converging to network-level optimal solutions within a few communication rounds. The proposed control algorithm leverages the radial topology of the system, which reduces the required communication rounds to reach the network-level optimum solution by order of magnitude. The novelty lies in carefully reducing the electrical network model from the perspective of each distributed controller and enabling appropriate data sharing among upstream and downstream nodes to achieve fast convergence. The simulation results demonstrate the effectiveness of the proposed approach in minimizing the feeder losses while maintaining the node voltage within the pre-specified limits.

voltage control, optimization, reactive power, inv↗

NASA NTRS2015

Consistency of CERES Radiances and Fluxes from Aqua and Suomi-NPP

The Clouds and Earth's Radiant Energy System (CERES) instruments on board Terra, Aqua, and Suomi-NPP have been providing data products critical to advancing our understanding of the effects of clouds and aerosols on radiative energy within the Earth-atmosphere system. The CERES instrument consists of a threechannel broadband scanning radiometer. The scanning radiometer measures radiances in shortwave (SW, 0.3-5 micron), window (WN, 8-12 micron), and total (0.3-200 micron) channels. The longwave (LW) component is derived as the difference between total and SW channels. These measured radiances at a given sun-Earthsatellite geometry are converted to outgoing reflected solar and emitted thermal TOA radiative fluxes by using CERES scene-type dependent angular distribution models (ADMs). The CERES instruments must remain radiometrically stable and correctly inter-calibrated to accurately capture changes in Earth"s radiation budget from interannual to decadal timescales. This presentation will focus on comparisons between collocated radiance measurements from CERES instruments on Aqua and on Suomi-NPP. As we do not have a set of ADMs that is constructed specifically for the CERES instrument on Suomi-NPP, CERES Aqua ADMs are used to invert fluxes from radiance measurements on Suomi-NPP. But the CERES Aqua footprint size is smaller than the CERES Suomi-NPP footprint size and the scene identifications provided by MODIS and VIIRS can also be different from each other. Will using Aqua ADMs for Suomi-NPP flux inversion increase the flux uncertainty? We will examine the deseasonalized flux anomaly time series using Aqua data alone and using combined Aqua and Suomi-NPP data. We will also present a simulation study to assess the Suomi-NPP flux uncertainty from using Aqua ADMs for the flux inversion.

Su, Wenying↗

NASA NTRS1984

Continental and oceanic crustal magnetization modelling

Inversion of magnetic data from the MAGSAT satellite, to arrive at intensities of magnetization of the Earth's crust, was performed by two different methods. The first method uses a spherical harmonic model of the magnetic field. The coefficients believed to represent sources in the Earth's crust can then be inverted to arrive at vertical dipole moments per unit area at the Earth's surface. The spherical harmonic models contain coefficients of degrees of harmonics up to 23. The dipole moment per unit area for a surface element can then be determined by summing the contribution for each individual degree of harmonic. The magnetic moments were calculated for continental and oceanic areas separately as well as over certain latitudinal segments. Of primary concern was to determine whether there are any differences between continental and oceanic areas. The second analysis with magnetization intensities was made using narrower ranges of degrees of harmonics, assuming that higher degrees are present in the core field signal.

Harrison, C. G. A.↗

NASA NTRS2001

Comparison of Profiling Microwave Radiometer, Aircraft, and Radiosonde Measurements From the Alliance Icing Research Study (AIRS)

Measurements from a profiling microwave radiometer are compared to measurements from a research aircraft and radiosondes. Data compared is temperature, water vapor, and liquid water profiles. Data was gathered at the Alliance Icing Research Study (AIRS) at Mirabel Airport outside Montreal, Canada during December 1999 and January 2000. All radiometer measurements were found to lose accuracy when the radome was wet. When the radome was not wetted, the radiometer was seen to indicate an inverted distribution of liquid water within a cloud. When the radiometer measurements were made at 15 deg. instead of the standard zenith, the measurements were less accurate.

Reehorst, Andrew L.↗

DOE OSTI2017

Instrumental Response Model and Detrending for the Dark Energy Camera

We describe the model for mapping from sky brightness to the digital output of the Dark Energy Camera (DECam) and the algorithms adopted by the Dark Energy Survey (DES) for inverting this model to obtain photometric measures of celestial objects from the raw camera output. This calibration aims for fluxes that are uniform across the camera field of view and across the full angular and temporal span of the DES observations, approaching the accuracy limits set by shot noise for the full dynamic range of DES observations. The DES pipeline incorporates several substantive advances over standard detrending techniques, including principal-components-based sky and fringe subtraction; correction of the "brighter-fatter" nonlinearity; use of internal consistency in on-sky observations to disentangle the influences of quantum efficiency, pixel-size variations, and scattered light in the dome flats; and pixel-by-pixel characterization of instrument spectral response, through combination of internal-consistency constraints with auxiliary calibration data. This article provides conceptual derivations of the detrending/calibration steps, and the procedures for obtaining the necessary calibration data. Other publications will describe the implementation of these concepts for the DES operational pipeline, the detailed methods, and the validation that the techniques can bring DECam photometry and astrometry within $\approx 2$ mmag and $\approx 3$ mas, respectively, of fundamental atmospheric and statistical limits. In conclusion, the DES techniques should be broadly applicable to wide-field imagers.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Predicting Reactor Antineutrino Emissions Using New Precision Beta Spectroscopy

Neutrino experiments at nuclear reactors are currently vital to the study of neutrino oscillations. The observed antineutrino rates at reactors are typically lower than model expectations. This observed deficit is called the “reactor neutrino anomaly”. A new understanding of neutrino physics may be required to explain this deficit, though model estimation uncertainties may also play a role in the apparent discrepancy. PNNL is currently investigating an experimental technique that promises reduced uncertainties for measured data to support these hypotheses and interpret reactor antineutrino measurements. The experimental approach is to 1) direct a proton accelerator beam on a metal target to produce a source of neutrons, 2) use spectral tailoring to modify the neutron spectrum to closely simulate the energy distribution of a power reactor neutron spectrum, 3) irradiate isotopic fission foils (235U, 238U, 239Pu, 241Pu) in this neutron spectrum so that fissions occur at energies representative of a reactor, 4) transport the beta particles released by the fission products in the foils to a beta spectrometer, 5) measure the beta energy spectrum, and 6) invert the measured beta energy spectrum to an antineutrino energy spectrum. A similar technique using a beta spectrometer and isotopic fission foils was pioneered in the 1980’s at the ILL thermal reactor. Those measurements have been the basis for interpreting all subsequent antineutrino measurements at reactors. A basic constraint in efforts to reduce uncertainties in predicting the antineutrino emission from reactor cores is any underlying limitation of the original measurements. This may include beta spectrum energy resolution, the absolute normalization of beta emission to number of fission, statistical counting uncertainties, lack of 238U data, the purely thermal nature of the IIL reactor neutrons used, etc. An accelerator-based neutron source that can be tailored to match various reactor neutron spectra provides an advantage for control in studying how changes in the neutron spectra (i.e. "in the reactor core") affects the resulting fission product beta spectrum. Furthermore, the 238U antineutrino spectrum, which has not been measured, can be studied directly because of the enhanced 1 MeV fast neutron flux available at the accelerator source. A facility such as the Project X Injector Experiment (PXIE) 30 MeV proton linear accelerator at Fermilab is being considered for this experiment. The hypothesis is that a new approach utilizing the flexibility of an accelerator neutron source with spectral tailoring coupled with a careful design of an isotopic fission target and beta spectrometer and the inversion of the beta spectrum to the neutrino spectrum will allow further reduction in the uncertainties associated with prediction of the reactor antineutrino spectrum.

Asner, David M.↗

DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗

DOE OSTI2023

Spatial-Temporal Recurrent Graph Neural Networks for Fault Diagnostics in Power Distribution Systems

Fault diagnostics are extremely important to decide proper actions toward fault isolation and system restoration. The growing integration of inverter-based distributed energy resources imposes strong influences on fault detection using traditional overcurrent relays. This paper utilizes emerging graph learning techniques to build new temporal recurrent graph neural network models for fault diagnostics. The temporal recurrent graph neural network structures can extract the spatial-temporal features from data of voltage measurement units installed at the critical buses. From these features, fault event detection, fault type/phase classification, and fault location are performed. Compared with previous works, the proposed temporal recurrent graph neural networks provide a better generalization for fault diagnostics. Moreover, the proposed scheme retrieves the voltage signals instead of current signals so that there is no need to install relays at all lines of the distribution system. Therefore, the proposed scheme is generalizable and not limited by the number of relays installed. The effectiveness of the proposed method is comprehensively evaluated on the Potsdam microgrid and IEEE 123-node system in comparison with other neural network structures.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1992

Inverse sequential detection of parameter changes in developing time series

Progressive values of two probabilities are obtained for parameter estimates derived from an existing set of values and from the same set enlarged by one or more new values, respectively. One probability is that of erroneously preferring the second of these estimates for the existing data ('type 1 error'), while the second probability is that of erroneously accepting their estimates for the enlarged test ('type 2 error'). A more stable combined 'no change' probability which always falls between 0.5 and 0 is derived from the (logarithmic) width of the uncertainty region of an equivalent 'inverted' sequential probability ratio test (SPRT, Wald 1945) in which the error probabilities are calculated rather than prescribed. A parameter change is indicated when the compound probability undergoes a progressive decrease. The test is explicitly formulated and exemplified for Gaussian samples.

Radok, Uwe↗

NASA NTRS2013

Innovations for ISS Plug-In Plan (IPiP) Operations

Limited resources and increasing requirements will continue to influence decisions on ISS. The ISS Plug-In Plan (IPiP) supports power and data for utilization, systems, and daily operations through the Electrical Power System (EPS) Secondary Power/Data Subsystem. Given the fluid launch schedule, the focus of the Plug-In Plan has evolved to anticipate future requirements by judicious development and delivery of power supplies, power strips, Alternating Current (AC) power inverters, along with innovative deployment strategies. A partnership of ISS Program Office, Engineering Directorate, Mission Operations, and International Partners poses unique solutions with existing on-board equipment and resources.

Moore, Kevin D.↗

NASA NTRS2013

The Multi-Stage History of Mt. Sharp

The Curiosity rover is exploring Gale crater and Mt. Sharp, Gale's 5‐km high central mound. We are investigating the history of alteration and erosion of Mt. Sharp using orbital imagery, spectroscopy and rover observations. Our results suggest a significant time gap between emplacement of the upper and lower sections of the mound. Crater counts show that the lower mound was formed soon after Gale itself, and that it contains distinct units ranging in altitude from approximately ‐4,500 to ‐1,800 m. Spectral data suggest that many units contain phyllosilicates. We found that these clay‐bearing rocks occur in distinct layers concentrated below ‐2,900 m. Parts of the lower mound exhibit a transition from clays to sulfates with increasing altitude. The lower mound shows evidence of flowing water, including canyons and inverted channels. Wind erosion produced km‐scale yardangs and scalloped cliffs. Our mapping shows that many yardangs in the lower mound are clay‐bearing, with a predominant orientation of around N‐S. Curiosity's ground‐level images show myriad fine‐scale, mainly horizontal layers in the lower mound. The rover has found stream beds and conglomerates, indicating that water once flowed on the crater floor. Drilling near the deepest point in Gale produced abundant clay, providing additional evidence of aqueous alteration. Upper mound units range in altitude from ‐2,100 m to +500 m, and mantle the lower mound above an angular unconformity. Most upper mound units are composed of layers. The formation age of the upper mound is unknown, since few craters are preserved. Clay‐bearing layers are detectable in several locations, mainly at altitudes near ‐2,000 m. There is no evidence of water flow, but wind erosion has scalloped the surfaces and edges of layers, and fine‐scale yardangs are common. Correlations between yardangs and clay spectra are apparent only in the lowermost units of the upper mound. Yardang orientations vary, and include N‐S, NW‐SE, and NE‐SW. Upper mound units resemble the planet‐wide Medusae Fossae formation, dated as Hesperian and argued to be composed of ignimbrites. Medusae Fossae layers are easily eroded by wind, and our mapping demonstrates their resemblance to upper mound fine‐scale yardangs. The history of Mt. Sharp started with deposition and lithification of sediments shortly after crater formation. Some lower mound layers were partially altered to clays and sulfates, and water formed streams and canyons. Wind erosion of the lower mound produced large‐scale yardangs, particularly in clay‐rich layers, oriented generally N‐S. Upper mound units were emplaced following a considerable period of wind erosion. The absence of water flow on the upper mound suggests that these units were emplaced after atmospheric loss rendered water unstable at the surface. The shift in dominant wind direction, as indicated by yardang orientations, also argues for a time gap between erosion of the lower and upper mound. These observations are consistent with upper mound units being related to the Hesperian Medusae Fossae formation. During 2014 Curiosity is expected to reach the foot of Mt. Sharp and ascend through the clay‐rich layers, into the sulfate‐rich layers, and possibly past the interface with the upper mound. This will be a unique opportunity to field check geologic models on the surface of Mars.

Allen, C.↗

DOE OSTI2019

Rate versus Free Energy Change for Attaching Highly Mobile Electrons to Molecules in Nonpolar Liquids

The inverted region of the Marcus theory, usually absent for bimolecular electron transfer reactions, is clearly observed for electron attachment reactions to molecules in nonpolar fluids. Application of pressure increased the energies of the solvated electron reactants letting us continuously adjust the free energy change. Inverted behavior is enabled by the very high mobilities of the solvated electrons which raise the diffusion-controlled encounter rates so high that they do not limit the reaction rates. The nonpolar media used in these experiments reduce reorganization energies, enhancing inverted behavior. Still, for every case showing an inverted region, the presence of low-lying excited states in the product radical anions led to regions of increasing rate constants that began at the energies of excited states of –0.54 to –1.2 eV. Here, while continuum models predict no solvent reorganization energy in nonpolar liquids, fits to the data found solvent reorganization energies of 0.05–0.4 eV supporting ideas advanced in theories of Matyushov.

14 SOLAR ENERGY↗

DOE OSTI2012

Partial Shade Evaluation of Distributed Power Electronics for Photovoltaic Systems: Preprint

Site survey data for several residential installations are provided, showing the extent and frequency of shade throughout the year. This background information is used to design a representative shading test that is conducted on two side-by-side 8-kW photovoltaic (PV) installations. One system is equipped with a standard string inverter, while the other is equipped with microinverters on eachsolar panel. Partial shade is applied to both systems in a comprehensive range of shading conditions, simulating one of three shade extents. Under light shading conditions, the microinverter system produced the equivalent of 4% annual performance improvement, relative to the string inverter system. Under moderate shading conditions, the microinverter system outperformed the string invertersystem by 8%, and under heavy shading the microinverter increased relative performance by 12%. In all three cases, the percentage of performance loss that is recovered by the use of distributed power electronics is 40%-50%. Additionally, it was found that certain shading conditions can lead to additional losses in string inverters due to peak-power tracking errors and voltage limitations.

14 SOLAR ENERGY↗

DOE OSTI2022

Quasielastic least-squares reverse time migration of PS reflections

Conventional analysis of amplitude variation with offset for elastic PS reflections is based on analytical reflection coefficients in a layered medium, and wave-equation-based PS migration is mainly used to produce a structural image. To overcome this problem, we have developed a least-squares reverse time migration (LSRTM) method for elastic PS reflections based on a quasielastic wave equation. Here, the quasielastic wave equation can accurately model PS reflections with elastic amplitudes under the first-order Born approximation. Our LSRTM method inverts for perturbations of the S-wave velocity and density by minimizing the L 2 norm of the difference between recorded and predicted PS reflections modeled using a quasielastic wave equation. We refer to our new method as quasielastic LSRTM of PS reflections. Numerical tests on synthetic and field data indicate that our method can properly handle the amplitudes of elastic PS reflections and provides an accurate estimate of the perturbations of S-wave velocity and density. Extending the method to the 3D case is not straightforward and might require incorporating certain PS data processing techniques into the inversion itself.

58 GEOSCIENCES↗

DOE OSTI2020

HEMP Transformer Defense Through Power Electronics

High altitude electromagnetic pulses and geo-magnetic disturbances have the potential to severely impact the electric power grid by damaging large power transformers and causing severe power quality issues. This impact comes as a result of a quasi-static bias induced on transmission lines by geomagnetically induced currents which saturate magnetic components in the electric power system. This paper introduces the concept of utilizing a h-bridge inverter on the neutral of a LPT to inject a DC bias equivalent voltage onto the neutral side of the transformer windings. This biasing floats the transformer windings, eliminating the effect of the DC current and keeping the transformer from saturating. Schematic diagrams will be presented, along with simulation model data using Typhoon and PLECS, and finally test results from a benchtop hardware test.

24 POWER TRANSMISSION AND DISTRIBUTION↗