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DOE OSTI2017

Collimated thermal radiation transfer via half Maxwell's fish-eye lens for thermophotovoltaics

Thermophotovoltaics (TPV) convert heat into electricity by capturing thermal radiation with a photovoltaic (PV) cell, ideally at efficiencies of 50% or more. However, excess heating of the PV cell from close proximity to the emitter substantially reduces the system efficiency. In this paper, we theoretically develop and numerically demonstrate an approach to fundamentally improving TPV systems that allow for a much greater separation of an emitter and a receiver. Thus, we solve the excess heating dilemma, required for achieving theoretically high efficiencies. It consists of a spherically graded index lens known as Maxwell's Fish-Eye (MFE) structure, capable of collimating hemispherical emission into a much narrower range of angles, close to the normal direction. To fully characterize the power radiation profile of the MFE, we perform finite-difference time-domain simulations for a quarter MFE and then map it onto a Gaussian beam approximation. The modeled beam properties are subsequently used to study a half MFE. In an optimized half MFE design, 90% of all thermal photons reach a receiver at a distance of 100 λ; by comparison, only 15.6% of a blackbody emitter reach a receiver in the same geometry. It is also shown that the emission achieved by a half MFE can lead to a photon recycling rate above 95% for below bandgap photons at an emitter-receiver separation of 100 λ. Finally, by applying a half MFE, the absolute TPV efficiency can be improved from 5.74% to 37.15%, which represents a significant step forward in realizing high-efficiency TPV systems.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2020

Fast strength model characterization using Bayesian statistics

A variety of flow stress models exist with new models constantly being developed. These models aim to approximate the strength of materials in a variety of regimes from quasistatic loading through shock scenarios. All models contain an array of parameters which need to be tuned to the material under study. Some models perform well under limited conditions, requiring adjustment of the parameters when venturing outside of those predefined ranges. Other models perform well over a wide range of conditions with a set of parameters, but may be outperformed by other models optimized on a tighter range of conditions. Recent research by Los Alamos demonstrated the ability to optimize the Johnson Cook (JC) model using a set of 3 plate-impact experiments on Aluminum. They utilized Bayesian statistics and emulation to determine optimal parameters for the model with a quantification of parameter uncertainty. We present an extension of this capability to incorporate velocimetry from plate-impact tests, stress-strain data from split Hopkinson pressure bar and quasistatic compression tests, plus profiles from Taylor cylinders in a unified fashion. Statistically robust comparisons of the performance and uncertainty of different realizations of the JC flow stress model were carried out based on calibration to several possible combinations of these three different experiment types.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Probing elemental diffusion and radiation tolerance of perovskite solar cells via non-destructive Rutherford backscattering spectrometry

Mixed organic–inorganic halide perovskite-based solar cells have attracted interest in recent years due to their potential for both terrestrial and space applications. Analysis of interfaces is critical to predicting device behavior and optimizing device architectures. Most advanced tools to study buried interfaces are destructive in nature and can induce further degradation. Ion beam techniques, such as Rutherford backscattering spectrometry (RBS), is a useful non-destructive method to probe an elemental depth profile of multilayered perovskite solar cells (PSCs) as well as to study the inter-diffusion of various elemental species across interfaces. Additionally, PSCs are becoming viable candidates for space photovoltaic applications, and it is critical to investigate their radiation-induced degradation. RBS can be simultaneously utilized to analyze the radiation effects induced by He+ beam on the device, given their presence in space orbits. In the present work, a 2 MeV He+ beam was used to probe the evidence of elemental diffusion across PSC interfaces with architecture glass/ITO/SnO2/Cs0.05(MA0.17FA0.83)0.95Pb(I0.83Br0.17)3/spiro-OMeTAD/MoO3/Au. During the analysis, the device active area was exposed to an irradiation equivalent of up to 1.62 × 1015 He+/cm2, and yet, no measurable evidence (with a depth resolution ∼1 nm) of beam-induced ion migration was observed, implying high radiation tolerance of PSCs. On the other hand, aged PSCs exhibited indications of the movement of diverse elemental species, such as Au, Pb, In, Sn, Br, and I, in the active area of the device, which was quantified with the help of RBS.

14 SOLAR ENERGY↗

DOE OSTI2018

Privacy-Preserving Aggregation of Controllable Loads to Compensate Fluctuations in Solar Power

Cybersecurity and privacy are of the utmost importance for safe, reliable operation of the electric grid. It is well known that the increased connectivity/interoperability between all stakeholders (e.g., utilities, suppliers, and consumers) will enable personal information collection. Significant advanced metering infrastructure (AMI) deployment and demand response (DR) programs across the country, while enable enhanced automation, also generate energy data on individual consumers that can potentially be used for exploiting privacy. Inspired by existing works which consider DR, battery-based perturbation, and differential privacy noise adding, we novelly consider the aggregator (cluster) level privacy issue in the DR framework of solar photovoltaic (PV) generation following. Different from most of the existing works which mainly rely on the charging/discharging scheduling of rechargeable batteries, we utilize controllable building loads to serve as virtual storage devices to absorb a large portion of the PV genertaion while delicately keeping desired noisy terms to satisfy the differential privacy for the raw load profiles at the aggregator level. This not only ensures differential privacy, but also improves the DR efficiency in load following since part of the noisy signal in solar PV generation has been filtered out. In particular, a mixed integer quadratic optimization problem is formulated to optimally dispatch a population of on/off controllable loads to achieve this privacy-preserving DR service.

Dong, Jin↗

DOE OSTI2022

Throughput Analytics of Cloud Networks

A network of virtual machines at cloud server sites connected over virtual IO connections is a flexible, easily deployable, and cost-effective alternative to a physical network infrastructure with dedicated servers connected over leased fiber lines. We study the throughput performance of such a cloud network by collecting measurements over Google Cloud infrastructure spanning multiple continents. To study its ideal performance and impact of packet losses, we utilize its emulation using dedicated servers and connection hardware emulation devices. We compare the measurements over the cloud network to those over its emulation on a testbed. We examine the throughput profiles of both networks as a function of the round trip time and their utilization-concavity coefficients, estimated using measurements for common TCP versions. The throughput profile's concave-convex shape and its coefficient are critical indicators of the network performance, qualitatively and quantitatively, respectively. The results indicate their overall agreement between the production cloud network and its emulation using dedicated connections, and a near optimal throughput performance of the former except for a few under-performing connections. Also, the number of parallel flows is found to be a dominant factor in optimizing the throughput across various conditions and TCP versions.

Phanekham, Derek↗

DOE OSTI2016

Coordinated Optimization of Distributed Energy Resources and Smart Loads in Distribution Systems

Distributed energy resources (DERs) and smart loads have the potential to provide flexibility to the distribution system operation. A coordinated optimization approach is proposed in this paper to actively manage DERs and smart loads in distribution systems to achieve the optimal operation status. A three-phase unbalanced Optimal Power Flow (OPF) problem is developed to determine the output from DERs and smart loads with respect to the system operator's control objective. This paper focuses on coordinating PV systems and smart loads to improve the overall voltage profile in distribution systems. Simulations have been carried out in a 12-bus distribution feeder and results illustrate the superior control performance of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

EMOS (Energy Management Optimization System) [SWR-21-46]

EMOS software performs a real-time hierarchal optimal control for energy systems like multi-port electric vehicles charging site with distributed energy resources (DERs) and energy storage systems (ESSs). It gathers information in real-time from electric vehicles, power grid, and DERs, solves a multi-objective energy management optimization problem, and output setpoint for chargers, ESS converters, DERs converters, and grid converters. The software incorporates a novel integration of two control tasks: a) An Energy Management Optimization (EMO), which is the brain of EMOS controller that gathers information in real-time from EVs [e.g., battery size, state-of-charge (SOC), desired SOC, and charge acceptance curve], grid (e.g., electricity price, allowed feeder capacity, ramp rate limit, and reactive power), and DERs (e.g., prediction for solar generation for PV systems). It solves a control optimization problem in real-time to find optimal setpoint for ESSs power dispatch, EVs charging rate, and grid inverters. The objectives are to (1) minimize the charging cost considering grid energy, demand charges, and battery energy, (2) minimize charging time to meet fast charging criterion, (3) keep high energy level on ESSs at the end of an operating period, while satisfying constraints related to grid, EVs, and power converters. b) Real-Time Energy Management System (RT-EMS) is a rule-based algorithm that has faster response than EMO. It receives optimal setpoint from EMO and actual measurements from the system and modify the setpoint to compensate for any fast disturbance in the system, until a new optimum solution is received. Fast disturbances may include vehicle connect/disconnect, unpredicted variation in DERs profiles, variation in grid voltage, errors in PV generation prediction, and others. In addition, RT-EMS regulates voltage at point of common coupling (PCC) by managing reactive power of grid converters.

Mohamed, Ahmed↗

DOE OSTI2016

Oak ridge national laboratory automated clean chemistry for bulk analysis of environmental swipe samples

To shorten the lengthy and costly manual chemical purification procedures, sample preparation methods for mass spectrometry are being automated using commercial-off-the-shelf (COTS) equipment. This addresses a serious need in the nuclear safeguards community to debottleneck the separation of U and Pu in environmental samples—currently performed by overburdened chemists—with a method that allows unattended, overnight operation. In collaboration with Elemental Scientific Inc., the prepFAST-MC2 was designed based on current COTS equipment that was modified for U/Pu separations utilizing Eichrom™ TEVA and UTEVA resins. Initial verification of individual columns yielded small elution volumes with consistent elution profiles and good recovery. Combined column calibration demonstrated ample separation without crosscontamination of the eluent. Automated packing and unpacking of the built-in columns initially showed >15% deviation in resin loading by weight, which can lead to inconsistent separations. Optimization of the packing and unpacking methods led to a reduction in the variability of the packed resin to less than 5% daily. The reproducibility of the automated system was tested with samples containing 30 ng U and 15 pg Pu, which were separated in a series with alternating reagent blanks. These experiments showed very good washout of both the resin and the sample from the columns as evidenced by low blank values. Analysis of the major and minor isotope ratios for U and Pu provided values well within data quality limits for the International Atomic Energy Agency. Additionally, system process blanks spiked with 233U and 244Pu tracers were separated using the automated system after it was moved outside of a clean room and yielded levels equivalent to clean room blanks, confirming that the system can produce high quality results without the need for expensive clean room infrastructure. Comparison of the amount of personnel time necessary for successful manual vs. automated chemical separations showed a significant decrease in hands-on time from 9.8 hours to 35 minutes for seven samples, respectively. This documented time savings and reduced labor translates to a significant cost savings per sample. Overall, the system will enable faster sample reporting times at reduced costs by limiting personnel hours dedicated to the chemical separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Automated Clean Chemistry for Bulk Analysis of Environmental Swipe Samples – Final Report

Sample preparation methods for mass spectrometry are being automated using commercial-off-the-shelf (COTS) equipment to shorten lengthy and costly manual chemical purification procedures. This development addresses a serious need in the International Atomic Energy Agency’s (IAEA) Network of Analytical Laboratories (NWAL) to increase efficiency in the Bulk Analysis of Environmental Samples for Safeguards program with a method that allows unattended, overnight operation. In collaboration with Elemental Scientific Inc. (ESI), the prepFAST-MC2 was designed based on COTS equipment. It was modified for uranium/plutonium separations using renewable columns packed with Eichrom TEVA® and UTEVA® resins, with a chemical separation method based on the Oak Ridge National Laboratory (ORNL) NWAL chemical procedure. Initial verification of individual columns yielded small elution volumes with consistent elution profiles and good recovery. Combined column calibration demonstrated ample separation without crosscontamination of the eluent. Automated packing and unpacking of the built-in columns initially showed >15% deviation in resin loading by weight, which can lead to inconsistent separations. Optimization of the packing and unpacking methods led to a reduction in the variability of the packed resin to less than 5% daily. Based on the initial experience at ORNL with the prepFAST-MC2, a second-generation model, the prepFAST-SR, was built by ESI. The newly designed prepFAST-SR has several upgrades compared with the original prepFAST-MC2. The upgrades largely addressed issues with the reliability of unpacking the Eichrom columns and with ventilation to ensure adequate removal of acid vapors. Both systems are currently installed in the Ultra-Trace Forensics Science Center at ORNL. Separations of mixed uranium and plutonium samples containing certified reference materials were analyzed by multi-collector inductively coupled plasma mass spectrometry and yielded good results. Current efforts have demonstrated a wider applicability of the prepFAST system. Near-quantitative removal of metal interferences was achieved with the system in both uranium and plutonium separated fractions. Successful system validation was completed with several archived samples. Isotopic results from archived samples and certified reference materials were well within data quality limits for the IAEA NWAL. Additional COTS equipment has been evaluated for its potential to aid the prepFAST-SR system in reducing the time allotments and cleanroom infrastructure requirements for accurate separations. Overall, these efforts help ensure continued efficient and effective operation of the NWAL. Comparison of the amount of personnel time necessary for successful manual vs. automated chemical separations showed a significant decrease in hands-on time from 9.8 hours to 35 minutes for seven samples, respectively. This documented time savings and reduced labor translates to a significant cost savings per sample. Overall, the system will enable faster sample reporting times at reduced cost by limiting personnel hours dedicated to the chemical separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Coordinated Optimization of Distributed Energy Resources and Smart Loads in Distribution Systems: Preprint

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Machine Learning-Based PV Reserve Determination Strategy for Frequency Control on the WECC System

This paper proposes a machine learning based strategy, that is suitable for real-time operation, to determine the optimal photovoltaic (PV) power plants reserve for frequency control. The proposed machine learning algorithm is trained and tested on 1,987 offline simulations of a 60% renewable penetration Western Electricity Coordinating Council (WECC) system. On a realistic 1-day operation profile of the WECC system, the ML model demonstrates a savings of more than 40% PV headroom compared to a conservative approach.

14 SOLAR ENERGY↗

DOE OSTI2019

Elemental Characterization of Neutron-Irradiated Tungsten Using the GD-OES Technique

In reactor-relevant fusion divertor conditions, tungsten (W) will be used as an armor material due to its excellent thermal properties. It will be exposed to impurities from numerous sources, including ion implantation and mixing, neutron transmutation, low-Z plasma-facing-component (PFC) redeposition and codeposition of deuterium and tritium fuel, and trapped helium bubbles. The impurity plasma material–interaction effects are a concern because they can cause gradual degradation of the material and of plasma performance due to dust formation, fuel retention, and even changes to the thermal and mechanical properties of the W armor. It is crucial to measure the amount of impurities in W, and the glow discharge–optical emission spectroscopy (GD-OES) technique is exceptionally well suited for analysis of irradiated samples. GD-OES can measure a sample’s elemental composition by sputtering the surface of the sample, ionizing the eroded material, and measuring the optical emission of the excited atoms. In order for the GD-OES technique to be applied to neutron-irradiated tungsten samples, a mounting system for miniature samples was designed. The sample mounting and centering procedure was successful in measuring the depth distribution of control W and W alloy sample elemental concentrations. These control depth spectra will be used as elemental references for postirradiated samples. The residence time of surface layers was measured, a comparison of signals from different anodes was completed, and the influence of initial surface roughness or nonuniformity was understood. The depth distribution of an arc-welded W-0.4% rhenium (Re) alloy was measured to have a stable Re signal that was distributed evenly in the W matrix. Here, the methods developed here will allow for quantification of impurities and transmutation amounts in neutron-irradiated W. GD-OES is a powerful tool but requires calibration and careful optimization of the parameters to obtain meaningful results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Growth optimization and characterization of GaN epilayers on multifaceted (111) surfaces etched on Si(100) substrates

The four nearest Si(111) multifaceted sidewalls were exposed inside an array of 3 μm-wide square holes patterned on an Si(100) substrate, and this patterned Si(100) substrate was used as a substrate for the deposition of a gallium nitride (GaN) epilayer. Subsequently the effect that the growth pressure, the etched-hole profiles, and the etched-hole arrangement had upon the quality of the as-grown GaN was investigated. The coalescence of the as-grown GaN epilayer on the exposed Si(111) facets was observed to be enhanced with reduced growth pressure from 120 to 90 Torr. A larger Si(001) plane area at the bottom of the etched holes resulted in bidirectional GaN domains, which resulted in poor material quality. The bidirectional GaN domains were observed as two sets of six peaks via a high-resolution x-ray diffraction phi scan of the GaN(10-11) reflection. It was also shown that a triangular array of etched holes was more desirable than square arrays of etched holes for the growth high-quality and continuous GaN films.

42 ENGINEERING↗

DOE OSTI2018

A genetic meta-algorithm-assisted inversion approach: hydrogeological study for the determination of volumetric rock properties and matrix and fluid parameters in unsaturated formations

An evolutionary inversion approach is suggested for the interpretation of nuclear and resistivity logs measured by direct-push tools in shallow unsaturated sediments. The efficiency of formation evaluation is improved by estimating simultaneously (1) the petrophysical properties that vary rapidly along a drill hole with depth and (2) the zone parameters that can be treated as constant, in one inversion procedure. In the workflow, the fractional volumes of water, air, matrix and clay are estimated in adjacent depths by linearized inversion, whereas the clay and matrix properties are updated using a float-encoded genetic meta-algorithm. The proposed inversion method provides an objective estimate of the zone parameters that appear in the tool response equations applied to solve the forward problem, which can significantly increase the reliability of the petrophysical model as opposed to setting these parameters arbitrarily. The global optimization meta-algorithm not only assures the best fit between the measured and calculated data but also gives a reliable solution, practically independent of the initial model, as laboratory data are unnecessary in the inversion procedure. The feasibility test uses engineering geophysical sounding logs observed in an unsaturated loessy-sandy formation in Hungary. The multi-borehole extension of the inversion technique is developed to determine the petrophysical properties and their estimation errors along a profile of drill holes. The genetic meta-algorithmic inversion method is recommended for hydrogeophysical logging applications of various kinds to automatically extract the volumetric ratios of rock and fluid constituents as well as the most important zone parameters in a reliable inversion procedure.

58 GEOSCIENCES↗

DOE OSTI2019

Modelling a Transition-Edge Sensor X-Ray Microcalorimeter Linear Array for Compton Profile Measurements and Energy Dispersive Diffraction

Transition-edge sensors (TES) are a type of superconducting detector that offers high energy resolution based on their sharp resistance-temperature feature in the superconducting-to-normal transition. TES X-ray microcalorimeters have typically been designed and used for spectroscopic applications. In this work, we present a design optimization for a TES X-ray microcalorimeter array for high-energy scattering and diffraction measurements. Specifically, Compton scattering provides information about the electron momentum distribution, while energy dispersive diffraction provides structural information about dense engineering materials. Compton scattering and energy dispersive diffraction experiments must be conducted in the very hard X-ray regime (~100 keV), demanding a high X-ray stopping power in the detector; therefore, an absorber with a large heat capacity is needed in conjunction with the TES. In addition, both applications would benefit from an array composed of parallel strips. We propose a design for a TES X-ray microcalorimeter optimized for such applications. In particular, we model the longitudinal position dependence due to the finite thermal diffusion time in the absorber.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Delay-resolved spectroscopy in terahertz photonic circuits

Photonic integrated circuits incorporating intersubband transitions are ideal for mid-infrared and terahertz nanophotonics. However, the design of epitaxies has long been inhibited by two factors: the modest predictivity of ab initio theory and the absence of absolute intersubband gain and loss measurements under operating conditions. Existing measurements either yield inaccurate gain profiles or do not accurately assess dependence on frequency, bias, and temperature. Here, we present a delay-resolved absolute-referencing method for accurate gain evaluation without these limitations, addressing a long-standing challenge. By creating a photonic circuit that allows broadband pulses to traverse different lengths of a gain medium, we measure the absolute transmission of intersubband structures. Gain profiles match theoretical predictions at lower temperatures, with gain and dispersion clamping after lasing, and faster-than-expected degradation occurs at higher temperatures. Our approach provides a precise experimental evaluation of temperature-dependent gain performance and gives insight into optimizing temperature performance and frequency comb designs.

Optical spectroscopy↗

DOE OSTI2021

Distribution System State Estimation With High Penetration of Demand Response Enabled Loads

Demand-side operations incentivize utility customers to take part in various grid services. A demand response enabled load (DREL) is a flexible grid asset that schedules electricity consumption in response to a time-of-use (TOU) energy price. Consequently, its energy profile differs from that of a conventional load that is insensitive to price. This difference may cause new challenges for distribution system state estimation (DSSE). It is well known that DSSE often needs to use pseudo-measurements based on historic load profiles to increase system observability. However, historic profiles of conventional loads are not representative of DREL behaviors. Additionally, the inaccuracy impacts DSSE results and other DSSE-dependent operations. In this paper, we propose an online pseudo-measurement generation approach for DSSE with DRELs. We formulate an optimization model to represent DRELs self-adjusting actions. Sampling-based stochastic optimization techniques are proposed to account for uncertainties in DRELs. A set of representative DREL behavior data corresponding to the samples are used to characterize DREL pseudo-measurements. Case studies with modified IEEE 123-bus test system verify the validity of the proposed work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

A Stochastic Charging Station Deployment Model for Electrified Taxi Fleets in Coupled Urban Transportation and Power Distribution Networks

Metropolitansworldwide are increasingly adopting electric taxis (ET) to address concerns about transportation-related emissions. However, the widespread deployment of electric taxis presents challenges in terms of increased electricity demand and changing demand profiles. This transition impacts both the urban transportation network (TN) and the electricity power distribution network (PDN), highlighting the interdependence between these two systems. Here, in this paper, we propose a two-stage stochastic programming planning model that aims to optimize both the TN and PDN, enabling efficient deployment of charging stations and grid upgrades. Our model seeks to strike a balance between meeting ET drivers' charging preferences, minimizing the costs associated with infrastructure deployment and grid expansion, and harmonizing the coordination between the TN and PDN. Additionally, we explore the potential benefits of utilizing an autonomous ET fleet to enhance overall system performance.

33 ADVANCED PROPULSION SYSTEMS↗