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DATA-DRIVEN ALGORITHMS FOR DISTRIBUTION SYSTEM OPERATION AND CONTROL

Transactive energy systems are an alternative solution for the problems that distribution system operators face due to an increase in the use of distributed energy resources(DERs) and resulting much required scalability in managing active distribution system. To meet the reliability, sustainability and security requirement, ecient management and control of DERs including distributed generators, energy storage systems, and demand response is necessary. DERs can provide services such as reactive power compensation, voltage control, energy balancing, peak load reduction. These edge resources can also be used for system restoration after the extreme events within regulatory bound and enabling resiliency of the electric grid. While there are numbers of related work focused on solving these problems, availability of additional data resources has not been utilized to its potential to enable the reliable, sustainable and resilient electric grid. In order to address these challenges, data-driven algorithms have been proposed in this dissertation, including a) Volt/Var control, b) activity aware demand response and c) estimation of behind the meter distributed energy resources. Results indicate satisfactory performance of the developed algorithms.

ZHANG, YUE↗

Mind the Gap: Exploring the Underground of the NASA Space Cancer Risk Model

The REID quantifies the lifetime risk of death from radiation-induced cancer in an exposed astronaut. The NASA Space Cancer Risk (NSCR) 2012 mode incorporates elements from physics, biology, epidemiology, and statistics to generate the REID distribution. The current model quantifies the space radiation environment, radiation quality, and dose-rate effects to estimate a NASA-weighted dose. This weighted dose is mapped to the excess risk of radiation-induced cancer mortality from acute exposures to gamma rays and then transferred to an astronaut population. Finally, the REID is determined by integrating this risk over the individual's lifetime. The calculated upper 95% confidence limit of the REID is used to restrict an astronaut's permissible mission duration (PMD) for a proposed mission. As a statistical quantity characterized by broad, subjective uncertainties, REID estimates for space missions result in wide distributions. Currently, the upper 95% confidence level is over 350% larger than the mean REID value, which can severely limit an astronaut's PMD. The model incorporates inputs from multiple scientific disciplines in the risk estimation process. Physics and particle transport models calculate how radiation moves through space, penetrates spacecraft, and makes its way to the human beings onboard. Epidemiological studies of exposures from atomic bombings, medical treatments, and power plants are used to quantify health risks from acute and chronic low linear energy transfer (LET) ionizing radiation. Biological studies in cellular and animal models using radiation at various LETs and energies inform quality metrics for ions present in space radiation. Statistical methodologies unite these elements, controlling for mathematical and scientific uncertainty and variability. Despite current progress, these research platforms contain knowledge gaps contributing to the large uncertainties still present in the model. The NASA Space Radiation Program Element (SRPE) defines the knowledge gaps that impact our understanding of the cancer risks. These gaps are outlined in NASA's Human Research Roadmap [4], which identifies the research questions and actions recommended for reducing the uncertainty in the current NSCR model and for formulation of future models. The greatest contributors to uncertainty in the current model include radiation quality, dose rate effects, and the transfer of exposure-based risk from other populations to an astronaut population. Future formulations of the risk model may benefit from including other potential sources of uncertainty such as space dosimetry, errors in human epidemiology data, and the impact of microgravity and other spaceflight stressors. Here, we discuss the current capabilities of the NSCR-2012 model and several immediate research needs, highlighting areas expected to have an operational impact on the current model schema. The following subway-style route map outlines the NSCR-2012 model (Green Line), emphasizing the research gaps in the Human Research Roadmap for risk of radiation-induced carcinogenesis (Stops on Dashed Lines). The map diagrams how these research gaps feed specific portions of the model.

Chappell, L. J.↗

The effect of temperature and pressure on the distribution of iron group elements between metal and olivine phases in the process of differentiation of protoplanetary material

The distribution patterns of Ni, Co, Mn, and Cr were studied in olivines of various origins: from meteorites (chondrites, achondrites, pallasites), which are likely analogs of the protoplanetary material, to peridotite inclusions in kimberlite pipes, which are analogs of mantle material. According to X-ray microanalysis data, nickel is concentrated in peridotite olivines, while manganese is concentrated in meteoritic olivines. The maximum chromium content was found in ureilites, which were formed under reducing conditions. Experiments at pressures of 20 to 70 kbar and temperatures of 1100 to 2000 C have shown that in a mixture of olivine and Ni metal or NiO, nickel enters the silicate phase, displacing Fe into the metallic phase. Equilibrium temperatures were estimated from the Fe, Ni distribution coefficients between the metal and olivine: 1500 K for pallasites, 1600 K for olivine-bronzite H6 chondrites, 1200 K for olivine-hypersthene L6, 900 K for LL6, and 1900 K for ureilites (at P = 1 atm). The equilibrium conditions of peridotites are close to T = 1800 K and P over 100 kbar. It is concluded that there is a sharp difference between the conditions of differentiation of the protoplanetary material at the time meteorites were formed and the conditions of differentiation of the planets into concentric layers.

Vinogradov, A. P.↗

Comprehensive Analysis of Model Parameter Uncertainty Influence on Evaluation of HVAC Operation to Mitigate Indoor Virus: A Case Study for an Office Building in a Cold and Dry Climate

Simulation-based studies of HVAC operation to mitigate indoor virus have been conducted to understand tradeoffs between indoor air quality (IAQ) and energy consumption. However, the influence of model parameter uncertainty in these studies has not been systematically quantified, which is critical when providing guidance to building operators. To address this gap, we identify 20 model parameters for a typical medium office building system in a cold and dry climate that can influence IAQ and energy consumption for indoor virus scenarios. Next, the distributions of the parameter values are estimated from literature and a set of simulation samples for three representative days is generated that simultaneously sample all of the parameters from their distributions. Two HVAC virus mitigation strategies are studied: increased filtration using MERV 13 filters and increased ventilation, via supply of 100% outdoor air into buildings. The model parameter uncertainty leads to significant variability in the results, particularly for the IAQ because of the highly uncertain virus generation rate. Use of 100% outdoor air can be beneficial for some uncertain scenarios on the hot day, but shows less IAQ improvement and/or significant energy increases on the other days. The virus removal efficiency and pressure drop of the HVAC filter, fan efficiency, and internal heat gain are the most important parameters to determining the tradeoffs of the two strategies. Our results demonstrate how this model parameter uncertainty analysis methodology can provide practical guidance to building operators.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Probabalistic Modeling of Minibangs and Megabands (Final Report)

This project was original proposed as a fundamental advance in the treatment of probabilistic modeling as it applies to nuclear fission calculations of nuclear database inputs and produced particle distributions in heavy-ion collisions. However, funding decisions made within LLNL and the DOE Office of Science led to the project proceeding through three distinct stages. The first two, probabilistic calculations of the fission and jet energy loss relate follow directly from the proposed research. The fission task led to the development of a proof-of-principle Gaussian Process Emulator for time-dependent generator coordinate method (TDGCM) calculation for the fission of Pu-240. To study energy loss in heavy-ion collisions with a probabilistic model, we generated a training data set using the Pythia event generator superimposed on a heavy-ion background with a single quench-factor parameter. We then used kernel density estimation (KDE) to recover the distribution of quench-factors for a calibration data set. In the third stage, we proceeded to work through collaborations, collecting new data within the ATLAS experiment at the Large Hadron Collider (LHC), and further developing bayesian methodology within the Jet Energy-loss Tomography with a Statistically and Computationally Advanced Program Envelope (JETSCAPE) Collaboration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Protection of Distribution Circuits with High Penetration of Solar PV: Distance, Learning, and Estimation-Based Methods

The results of DOE Solar Energy Technologies Office project 34233 are presented. The newest version of IEEE Standard 1547 enables photovoltaic inverters to ride through voltage disturbances, improving bulk system reliability, at the expense of removing undervoltage trip as a fast method of de facto fault detection in high PV adoption scenarios. The project explored new methods of fault detection that don't rely on communication systems and could be available quickly, including distance-based schemes, focused directional relays, and two different data-driven schemes. The schemes were evaluated with fast-phasor simulation, electromagnetic transient simulation, and field data collection at partner utilities Chattanooga Electric Power Board and Dominion Energy Virginia. Accomplishments and possible paths forward are summarized.

14 SOLAR ENERGY↗

Microwave scatter and sea state estimation - Two-scale ocean wave models

The efficient estimation of ocean wave-structure parameters with a remote, narrow-beam, pulsed, microwave radar at intermediate incidence angles is discussed. The sea surface is described as the sum of random small- and large-scale structures (waves), the latter the sum of a sinusoid and a random field. It is shown that the small-scale structure is responsible for scattering and that the scatter depends parametrically on the large-scale structure. For the estimation problem it is assumed, reasonably, that the received signal is normally distributed: a relatively simple processor which will efficiently estimate parameters of the sinusoidal structure is illustrated and its performance discussed. A brief comparison is made with a normal incidence system with which the variance of the large-scale random roughness can be estimated.

Harger, R. O.↗

Distribution of SLS Integrated Load Uncertainty to Surface Pressures and Sectional Loads

Aerodynamic loads that are important to launch vehicle programs such as NASA’s Space Launch System (SLS) include both integrated loads such as the force & moment on the entire vehicle and distributed loads. In this work two examples of distributed loads are considered: the pressure field on the surface of the vehicle and sectional loads, which are one-dimensional distributions along the axis of the launch vehicle. In some modern flight programs, the integrated loads, such as lift and drag, used to design the guidance and control laws for the vehicle come from wind tunnel testing, while distributed loads are produced using Computational Fluid Dynamics(CFD). The first task that is addressed in this paper, then, is to provide a formal method to adjust the distributed loads so that integrating them matches the prescribed integrated load. In addition, the integrated loads in a launch vehicle typically include an uncertainty estimate. The second task is to distribute this prescribed integrated uncertainty to each point in a distributed load. Both tasks are addressed using the same technique, which is to create distributed load profiles that isolate adjustments to one integrated load while leaving the others unaffected. These adjustments are informed by Proper Orthogonal Decomposition (POD) of the entire CFD-based distributed load database. Once applied, the adjusted distributed loads can be used to evaluate any scalar quantity of interest that might be needed by downstream users such as structural analysis or trajectory modelers.

SLS↗

Distributed parameter modeling of the structural dynamics of the Solar Array Flight Experiment

A distributed-parameter model of the structural dynamics of the space-shuttle-deployed Solar Array Flight Experiment is developed and used to produce estimates of the modal frequencies and mode shapes. A lumped parameter version of the distributed model is used to estimate model characteristics by analyzing the measured responses of 32 targets. To make the modeling more tenable, a distributed parameter system is used to reduce the number of unknown parameters, a modified Newton-Raphson technique is used for rapid convergence, and a parallel processing supercomputer is used for more efficient computation. The performances of computers with a high-speed serial processor and with a high-speed parallel processor are compared. The best results are obtained with the modeling approach in which maximum likelihood estimation is applied to distributed parameter models.

Taylor, L. W., Jr.↗

Facile alignment estimation in carbon nanotube films using image processing

Whether a macroscopic assembly of carbon nanotubes can exhibit the one-dimensional properties expected from individual nanotubes critically depends on how well the nanotubes are aligned inside the assembly. Therefore, a simple and accurate method for assessing the degree of alignment is desired for the rapid characterization of carbon nanotube films and fibers. Here, we present an end-to-end solution for determining the global and local spatial orientation of carbon nanotubes in films within a short amount of time using a fast, precise, and economical approach based on an image processing method applied to scanning electron microscopy images. Further, we first use Laplacian edge enhancement filtering for improving the appearance of edge regions, which is followed by image partitioning into multiple blocks to capture the nanoscale orientation characteristics and total variation-based image decomposition of these image blocks. We then perform a 2D-fast Fourier transform on the image decomposed textural components of these edge-enhanced image blocks to determine the orientation distribution, which is utilized to estimate the 2D nematic order parameter. To show the effectiveness of our method, we corroborated our results against results obtained with other state-of-the-art image processing and experimental techniques.

2D-FFT↗

MO-FG-CAMPUS-JeP1-03: Luminescence Imaging of Water During Proton Beam Irradiation for Range Estimation

Purpose: Since proton therapy has the ability to selectively deliver a dose to a target tumor, the dose distribution should be accurately measured. A precise and efficient method to evaluate the dose distribution is desired. We found that luminescence was emitted from water during proton irradiation and thought this phenomenon could be used for estimating the dose distribution. Methods: For this purpose, we placed water phantoms set on a table with a spot-scanning proton-therapy system, and luminescence images of these phantoms were measured with a high-sensitivity cooled charge coupled device (CCD) camera during proton-beam irradiation. We also conducted the imaging of phantoms of pure-water, fluorescein solution and acrylic block. We made three dimensional images from the projection data. Results: The luminescence images of water phantoms during the proton-beam irradiations showed clear Bragg peaks, and the measured proton ranges from the images were almost the same as those obtained with an ionization chamber. The image of the pure-water phantom also showed almost the same distribution as the tap-water phantom, indicating that the luminescence image was not related to impurities in the water. The luminescence image of fluorescein solution had ∼3 times higher intensity than water, with the same proton range as that of water. The luminescence image of the acrylic phantom had 14.5% shorter proton range than that of water; the proton range in the acrylic phantom was relatively matched with the calculated value. The luminescence images of the tap-water phantom during proton irradiation could be obtained in less than 2 sec. Three dimensional images were successfully obtained which have more quantitative information. Conclusion: Luminescence imaging during proton-beam irradiation has the potential to be a new method for range estimations in proton therapy.

60 APPLIED LIFE SCIENCES↗

Comparison of fiber-optic distributed temperature sensing and high-sensitivity sensor spatial surveying of stream temperature

Measuring surface water temperature spatial variability is needed to estimate the interaction between surface water and groundwater, evaluate fish habitat and thermal inertia, and to estimate streamflow frequency and duration. Fiber optic distributed temperature sensing (FO-DTS) has been used in rivers and lakes, providing high-resolution and sensitive temperature monitoring over large temporal and spatial scales. However, in streams with cobbly or bedrock-lined streambeds and variable bathymetry, use of FO-DTS to measure temperature close to the surface water and groundwater interface can be challenging if even feasible. FO-DTS can also be costly, involve difficult installations, and require an advanced understanding of the technology, calibration, and data processing. In this study, we compared FO-DTS stream temperature survey results to an alternative temperature survey method employing a towed transect of high-resolution temperature loggers spaced at 1-m and transported in the stream along the study reach, to measure the spatial distribution of stream-water temperature in East Fork Poplar Creek near Oak Ridge, Tennessee, USA. We assessed the applicability and limitations of the two methods, and quantitatively compared in-situ temperature survey results measured simultaneously with each method. Regression results showed strong temporal and spatial correlation between the two methods. Differences were only elevated near the stream banks in areas that were coincident with correlation slope deviations from unity, which was attributed to shallower water and lower data density. Kriging standard errors were also low at channel center with minor increases near the stream banks. Furthermore, the results suggested that the array of the individual temperature sensors can provide a practical alternative to FO-DTS for thermal characterization of surface water, providing slightly lower spatial and temporal resolution, but with higher accuracy of temperature measurement, with greater simplicity, and with a broader range of conditions where it may be applied.

54 ENVIRONMENTAL SCIENCES↗

Spatial distribution of melt-season cloud radiative effects over Greenland: Evaluating satellite observations, reanalyses, and model simulations against in situ measurements

Arctic clouds can profoundly influence surface radiation and thus surface melt. Over Greenland, these cloud radiative effects (CRE) vary greatly with the diverse topography. To investigate the ability of assorted platforms to reproduce heterogeneous CRE, we evaluate CRE spatial distributions from a satellite product, reanalyses, and a global climate model against estimates from 21 automatic weather stations (AWS). Net CRE estimated from AWS generally decreases with elevation, forming a “warm center” distribution. CRE areal averages from the five large–scale data sets we analyze are all around 10 W/m 2 . Modern–Era Retrospective Analysis for Research and Applications version 2 (MERRA–2), ERA–Interim, and Clouds and the Earth's Radiant Energy System (CERES) CRE estimates agree with AWS and reproduce the warm center distribution. However, the National Center for Atmospheric Research Arctic System Reanalysis (ASR) and the Community Earth System Model Large ENSemble Community Project (LENS) show strong warming in the south and northwest, forming a warm L–shape distribution. Discrepancies are mainly caused by longwave CRE in the accumulation zone. MERRA–2, ERA–Interim, and CERES successfully reproduce cloud fraction and its dominant positive influence on longwave CRE in this region. On the other hand, longwave CRE from ASR and LENS correlates strongly with ice water path instead of with cloud fraction or liquid water path. Moreover, ASR overestimates cloud fraction and LENS underestimates liquid water path substantially, both with limited spatial variability. MERRA–2 best captures the observed interstation changes, captures most of the observed cloud–radiation physics, and largely reproduces both albedo and cloud properties. Furthermore, the warm center CRE spatial distribution indicates that clouds enhance surface melt in the higher accumulation zone and reduce surface melt in the lower ablation zone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Online Model-Free DER Dispatch Via Adaptive Voltage Sensitivity Estimation and Chance Constrained Programming

This paper proposes an online data-driven distributed energy resource management system (DERMS) for distribution system optimal DER dispatch as well as voltage regulation. Here, the key innovation is to leverage the Local Sensitivity Factor (LSF) for transforming the DER control into a computationally efficient linear programming (LP) problem. By taking real-time measurements, the estimation of LSF eliminates the need for an accurate distribution system model as well as full nodal load information, which is difficult to achieve in practice. A robust recursive least squares method is also developed to ensure the robust estimation of LSF, which is initialized using reasonable values from model-derived LSFs. This allows the system to adapt to changing operational conditions effectively. A scenario-based, chance-constrained framework is further employed to ensure voltage remains within acceptable limits in the presence of measurement and estimation uncertainties. Test results on a real-world, 759-node distribution network located in western Colorado, U.S., validate the effectiveness and robustness of the proposed control approach and demonstrate its superior performance as compared to alternative methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Herschel's "Cold Debris Disks": Background Galaxies or Quiescent Rims of Planetary Systems?

Infrared excesses associated with debris disk host stars detected so far peak at wavelengths around approx, 100 micron or shorter. However, 6 out of 31 excess sources studied in the Herschel Open Time Key Programme, DUNES, have been seen to show significant-and in some cases extended-excess emission at 160 micron, which is larger than the 100 micron excess. This excess emission has been attributed to circumstellar dust and has been suggested to stem from debris disks colder than those known previously. Since the excess emission of the cold disk candidates is extremely weak, challenging even the unrivaled sensitivity of Herschel, it is prudent to carefully consider whether some or even all of them may represent unrelated galactic or extragalactic emission, or even instrumental noise. We re-address these issues using several distinct methods and conclude that it is highly unlikely that none of the candidates represents a true circumstellar disk. For true disks, both the dust temperatures inferred from the spectral energy distributions and the disk radii estimated from the images suggest that the dust is nearly as cold as a blackbody. This requires the grains to be larger than approx. 100 micron, even if they are rich in ices or are composed of any other material with a low absorption in the visible. The dearth of small grains is puzzling, since collisional models of debris disks predict that grains of all sizes down to several times the radiation pressure blowout limit should be present. We explore several conceivable scenarios: transport-dominated disks, disks of low dynamical excitation, and disks of unstirred primordial macroscopic grains. Our qualitative analysis and collisional simulations rule out the first two of these scenarios, but show the feasibility of the third one. We show that such disks can indeed survive for gigayears, largely preserving the primordial size distribution. They should be composed of macroscopic solids larger than millimeters, but smaller than a few kilometers in size. If larger planetesimals were present, then they would stir the disk, triggering a collisional cascade and thus causing production of small debris, which is not seen. Thus, planetesimal formation, at least in the outer regions of the systems, has stopped before "cometary" or "asteroidal" sizes were reached.

Herschel↗