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At least 1,351 records · Page 75

Critical Current Distributions of Recent Bi-2212 Round Wires

Bi 2 Sr 2 CaCu 2 O 8+x (Bi-2212) is the only high-field, high-temperature superconductor (HTS) capable of reaching a critical current density J c (16 T, 4.2 K) of 6500 A·mm –2 in the highly desirable round wire (RW) form. However, state-of-the-art Bi-2212 conductors still have a critical current density (J c ) to depairing current density (J d ) ratio around 20 to 30 times lower than that of state-of-the-art Nb–Ti or REBCO. Previously, we have shown that recent improvements in Bi-2212 RW J c are due to improved connectivity associated with optimization of the heat treatment process, and most recently due to a transition to a finer and more uniform powder manufactured by Engi-Mat. One quantitative measure of connectivity may be the critical current (I c ) distribution, since the local I c in a wire can vary along the length due to variable vortex-microstructure interactions and to factors such as filament shape variations, grain-to-grain connectivity variations and blocking secondary phase distributions. Modeling the experimental V-I transition measured on a low resistance shunt as a complex sum of voltage contributions of individual filament and wire sub-sections allows a numerical extraction of the I c distribution from the d 2 V/dI 2 treatment of the V-I curves. Here we compare ~0.1 m length I c distributions of Bi-2212 RWs with recent state-of-the-art very high-J c Engi-Mat powder and lower J c and older Nexans granulate powder. We do find that the I c spread for Bi-2212 wires is about twice the relative standard of high-J c Nb–Ti well below H irr . We do not yet see any obvious contribution of the Bi-2212 anisotropy to the I c distribution and are rather encouraged that these Bi-2212 round wires show relative I c distributions not too far from high-J c Nb–Ti wires.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Joint Management and Optimization of Residential Natural Gas and Electricity Distribution Networks Coupled via Fuel Cells

The interesting properties of natural gas as well as the growing electric power demand worldwide have led to increasing attention to natural-gas-based distributed generation applications in electric distribution systems. This paper goes over the interdependency between a residential natural gas network and an electric distribution network that are coupled via fuel cells. The modeling of the gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the gas and electric distribution networks, subject to their model constraints. In addition to this, in order to capture the probabilistic nature of the optimization problem under study, the K-means clustering algorithm is applied to the gas and electricity demands to determine hourly load states and their corresponding probabilities. Furthermore, simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution feeder and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Voltage Calculations in Secondary Distribution Networks via Physics-Inspired Neural Network Using Smart Meter Data

The increasing penetration of distributed energy resources (DERs) leads to voltage issues across distribution networks, necessitating voltage calculations by utilities. Electric model-free voltage calculation offers an enticing solution. However, most researches mainly focus on primary distribution networks ignoring secondary distribution networks and commonly overlook extreme voltage case calculations, which require the model’s extrapolation abilities. Here, in addressing the gaps, this paper presents a customized physics-inspired neural network (PINN) model, the structure of which is inspired by the derived coupled power flow model of primary-secondary distribution networks. To ensure precision and rapid convergence, a crafted training framework for the PINN model is proposed. The PINN’s “structure-mimetic” design enables superior extrapolation for unseen scenarios and enhances physical information awareness. We demonstrate this through two applications: hosting capacity analysis and customer-transformer connectivity. The effectiveness and advantages of the proposed PINN model are validated on two public testing systems and one utility distribution feeder model.

Distribution network↗

Development of XFCT imaging strategy for monitoring the spatial distribution of platinum-based chemodrugs: Instrumentation and phantom validation

Purpose: Developing an imaging method to directly monitor the spatial distribution of platinum-based (Pt) drugs at the tumor region is of critical importance for early assessment of treatment efficacy and personalized treatment. In this study, the authors investigated the feasibility of imaging platinum (Pt)-based drug distribution using x-ray fluorescence (XRF, a.k.a. characteristic x ray) CT (XFCT). Methods: A 5-mm-diameter pencil beam produced by a polychromatic x-ray source equipped with a tungsten anode was used to stimulate emission of XRF photons from Pt drug embedded within a water phantom. The phantom was translated and rotated relative to the stationary pencil beam in a first-generation CT geometry. The x-ray energy spectrum was collected for 18 s at each position using a cadmium telluride detector. The spectra were then used for the K-shell XRF peak isolation and sinogram generation for Pt. The distribution and concentration of Pt were reconstructed with an iterative maximum likelihood expectation maximization algorithm. The capability of XFCT to multiplexed imaging of Pt, gadolinium (Gd), and iodine (I) within a water phantom was also investigated. Results: Measured XRF spectrum showed a sharp peak characteristic of Pt with a narrow full-width at half-maximum (FWHM) (FWHM{sub K{alpha}1}= 1.138 keV, FWHM{sub K{alpha}2}= 1.052 keV). The distribution of Pt drug in the water phantom was clearly identifiable on the reconstructed XRF images. Our results showed a linear relationship between the XRF intensity of Pt and its concentrations (R{sup 2}= 0.995), suggesting that XFCT is capable of quantitative imaging. A transmission CT image was also obtained to show the potential of the approach for providing attenuation correction and morphological information. Finally, the distribution of Pt, Gd, and I in the water phantom was clearly identifiable in the reconstructed images from XFCT multiplexed imaging. Conclusions: XFCT is a promising modality for monitoring the spatial distribution of Pt drugs. The technique may be useful in tailoring tumor treatment regimen in the future.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-E-T-243: MonteCarlo Simulation Study of Polymer and Radiochromic Gel for Three-Dimensional Proton Dose Distribution

Purpose: To estimate the three dimensional dose distributions in a polymer gel and a radiochromic gel by comparing with the virtual water phantom exposed to proton beams by applying Monte Carlo simulation. Methods: The polymer gel dosimeter is the compositeness material of gelatin, methacrylic acid, hydroquinone, tetrakis, and distilled water. The radiochromic gel is PRESAGE product. The densities of polymer and radiochromic gel were 1.040 and 1.0005 g/cm3, respectively. The shape of water phantom was a hexahedron with the size of 13 × 13 × 15 cm3. The proton beam energies of 72 and 116 MeV were used in the simulation. Proton beam was directed to the top of the phantom with Z-axis and the shape of beam was quadrangle with 10 × 10 cm2 dimension. The Percent depth dose and the dose distribution were evaluated for estimating the dose distribution of proton particle in two gel dosimeters, and compared with the virtual water phantom. Results: The Bragg-peak for proton particles in two gel dosimeters was similar to the virtual water phantom. Bragg-peak regions of polymer gel, radiochromic gel, and virtual water phantom were represented in the identical region (4.3 cm) for 72 MeV proton beam. For 116 MeV proton beam, the Bragg-peak regions of polymer gel, radiochromic gel, and virtual water phantom were represented in 9.9, 9.9 and 9.7 cm, respectively. The dose distribution of proton particles in polymer gel, radiochromic gel, and virtual water phantom was approximately identical in the case of 72 and 116 MeV energies. The errors for the simulation were under 10%. Conclusion: This work indicates the evaluation of three dimensional dose distributions by exposing proton particles to polymer and radiochromic gel dosimeter by comparing with the water phantom. The polymer gel and the radiochromic gel dosimeter show similar dose distributions for the proton beams.

07 ISOTOPE AND RADIATION SOURCES↗

High resolution Cerenkov light imaging of induced positron distribution in proton therapy

Purpose: In proton therapy, imaging of the positron distribution produced by fragmentation during or soon after proton irradiation is a useful method to monitor the proton range. Although positron emission tomography (PET) is typically used for this imaging, its spatial resolution is limited. Cerenkov light imaging is a new molecular imaging technology that detects the visible photons that are produced from high-speed electrons using a high sensitivity optical camera. Because its inherent spatial resolution is much higher than PET, the authors can measure more precise information of the proton-induced positron distribution with Cerenkov light imaging technology. For this purpose, they conducted Cerenkov light imaging of induced positron distribution in proton therapy. Methods: First, the authors evaluated the spatial resolution of our Cerenkov light imaging system with a {sup 22}Na point source for the actual imaging setup. Then the transparent acrylic phantoms (100 × 100 × 100 mm{sup 3}) were irradiated with two different proton energies using a spot scanning proton therapy system. Cerenkov light imaging of each phantom was conducted using a high sensitivity electron multiplied charge coupled device (EM-CCD) camera. Results: The Cerenkov light’s spatial resolution for the setup was 0.76 ± 0.6 mm FWHM. They obtained high resolution Cerenkov light images of the positron distributions in the phantoms for two different proton energies and made fused images of the reference images and the Cerenkov light images. The depths of the positron distribution in the phantoms from the Cerenkov light images were almost identical to the simulation results. The decay curves derived from the region-of-interests (ROIs) set on the Cerenkov light images revealed that Cerenkov light images can be used for estimating the half-life of the radionuclide components of positrons. Conclusions: High resolution Cerenkov light imaging of proton-induced positron distribution was possible. The authors conclude that Cerenkov light imaging of proton-induced positron is promising for proton therapy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-E-T-89: Accuracy of Absolute Three-Dimensional Dose Distribution Measurement Using the Delta4

Purpose: In this study, we investigated the accuracy of the absolute dose distribution measurement using the Delta4 phantom compared to the measurements using a ionization chamber and EDR2 film Methods: Several conventional and intensity-modulated radiation therapy plans were used to compare the dose distribution measured using the Delta4 phantom to the absolute point dose using the chamber and the relative two-dimensional dose distribution using the EDR2 film. For the absolute dose distribution evaluation, the measurements using the Delta4, the chamber and the film were performed in similar measurement geometry. For point dose measurement using the chamber, an acrylic slab phantom with the PTW Semiflex chamber was inserted into the Delta4 phantom, alternative to the Delta4 main unit. Similarly, for dose distribution measurement using the film, the EDR2 film sandwiched with two acrylic slab phantoms were inserted to the phantom. Dose difference and gamma analysis were done for point dose and relative dose distribution comparisons, respectively. Results: The point dose measurements show slight negative systematic dose difference of −0.5 ± 0.1% and −1.0 ± 0.4% in the conventional and the IMRT plans, respectively. The additional measurement for direction dependency for Delta4 shows similar negative systematic dose difference even the phantom analysis software consider the directional dependency. The pass rate of the gamma evaluation was 77.7 ± 5.8% and 88.8±3.3% in the conventional and the IMRT plans, respectively. Conclusions: The Delta4 phantom shows a 1%-systematic dose difference derived from directional dependency and lower resolution compared to the film. Thus it is necessary to comprehensively evaluate the phantom to verify the IMRT/VMAT plans. Especially, the dosimetry tool is needed to have high resolution and high measurement accuracy in IMRT/VMAT-SBRT plan with small fields using intensity modulation in which the analysis area is limited and the higher correspondence between calculation and measurement is needed.

60 APPLIED LIFE SCIENCES↗

SU-E-T-753: Three-Dimensional Dose Distributions of Incident Proton Particle in the Polymer Gel Dosimeter and the Radiochromic Gel Dosimeter: A Simulation Study with MCNP Code

Purpose: The purpose of this study is to estimate the three-dimensional dose distributions in the polymer and the radiochromic gel dosimeter, and to identify the detectability of both gel dosimeters by comparing with the water phantom in case of irradiating the proton particles. Methods: The normoxic polymer gel and the LCV micelle radiochromic gel were used in this study. The densities of polymer and the radiochromic gel dosimeter were 1.024 and 1.005 g/cm{sup 3}, respectively. The dose distributions of protons in the polymer and radiochromic gel were simulated using Monte Carlo radiation transport code (MCNPX, Los Alamos National Laboratory). The shape of phantom irradiated by proton particles was a hexahedron with the dimension of 12.4 × 12.4 × 15.0 cm{sup 3}. The energies of proton beam were 50, 80, and 140 MeV energies were directed to top of the surface of phantom. The cross-sectional view of proton dose distribution in both gel dosimeters was estimated with the water phantom and evaluated by the gamma evaluation method. In addition, the absorbed dose(Gy) was also calculated for evaluating the proton detectability. Results: The evaluation results show that dose distributions in both gel dosimeters at intermediated section and Bragg-peak region are similar with that of the water phantom. At entrance section, however, inconsistencies of dose distribution are represented, compared with water. The relative absorbed doses in radiochromic and polymer gel dosimeter were represented to be 0.47 % and 2.26 % difference, respectively. These results show that the radiochromic gel dosimeter was better matched than the water phantom in the absorbed dose evaluation. Conclusion: The polymer and the radiochromic gel dosimeter show similar characteristics in dose distributions for the proton beams at intermediate section and Bragg-peak region. Moreover the calculated absorbed dose in both gel dosimeters represents similar tendency by comparing with that in water phantom.

60 APPLIED LIFE SCIENCES↗

SU-F-BRD-04: Robustness Analysis of Proton Breast Treatments Using An Alpha-Stable Distribution Parameterization

Purpose: Currently, planning systems allow robustness calculations to be performed, but a generalized assessment methodology is not yet available. We introduce and evaluate a methodology to quantify the robustness of a plan on an individual patient basis. Methods: We introduce the notion of characterizing a treatment instance (i.e. one single fraction delivery) by describing the dose distribution within an organ as an alpha-stable distribution. The parameters of the distribution (shape(α), scale(γ), position(δ), and symmetry(β)), will vary continuously (in a mathematical sense) as the distributions change with the different positions. The rate of change of the parameters provides a measure of the robustness of the treatment. The methodology is tested in a planning study of 25 patients with known residual errors at each fraction. Each patient was planned using Eclipse with an IBA-proton beam model. The residual error space for every patient was sampled 30 times, yielding 31 treatment plans for each patient and dose distributions in 5 organs. The parameters’ change rate as a function of Euclidean distance from the original plan was analyzed. Results: More than 1,000 dose distributions were analyzed. For 4 of the 25 patients the change in scale rate (γ) was considerably higher than the lowest change rate, indicating a lack of robustness. The sign of the shape change rate (α) also seemed indicative but the experiment lacked the power to prove significance. Conclusion: There are indications that this robustness measure is a valuable tool to allow a more patient individualized approach to the determination of margins. In a further study we will also evaluate this robustness measure using photon treatments, and evaluate the impact of using breath hold techniques, and the a Monte Carlo based dose deposition calculation. A principle component analysis is also planned.

60 APPLIED LIFE SCIENCES↗

MO-FG-204-08: Optimization-Based Image Reconstruction From Unevenly Distributed Sparse Projection Views

Purpose: Optimization-based reconstruction has been proposed and investigated for reconstructing CT images from sparse views, as such the radiation dose can be substantially reduced while maintaining acceptable image quality. The investigation has so far focused on reconstruction from evenly distributed sparse views. Recognizing the clinical situations wherein only unevenly sparse views are available, e.g., image guided radiation therapy, CT perfusion and multi-cycle cardiovascular imaging, we investigate the performance of optimization-based image reconstruction from unevenly sparse projection views in this work. Methods: The investigation is carried out using the FORBILD and an anthropomorphic head phantoms. In the study, 82 views, which are evenly sorted out from a full (360°) axial CT scan consisting of 984 views, form sub-scan I. Another 82 views are sorted out in a similar manner to form sub-scan II. As such, a CT scan with sparse (164) views at 1:6 ratio are formed. By shifting the two sub-scans relatively in view angulation, a CT scan with unevenly distributed sparse (164) views at 1:6 ratio are formed. An optimization-based method is implemented to reconstruct images from the unevenly distributed views. By taking the FBP reconstruction from the full scan (984 views) as the reference, the root mean square (RMS) between the reference and the optimization-based reconstruction is used to evaluate the performance quantitatively. Results: In visual inspection, the optimization-based method outperforms the FBP substantially in the reconstruction from unevenly distributed, which are quantitatively verified by the RMS gauged globally and in ROIs in both the FORBILD and anthropomorphic head phantoms. The RMS increases with increasing severity in the uneven angular distribution, especially in the case of anthropomorphic head phantom. Conclusion: The optimization-based image reconstruction can save radiation dose up to 12-fold while providing acceptable image quality for advanced clinical applications wherein only unevenly distributed sparse views are available. Research Grants: W81XWH-12-1-0138 (DoD), Sinovision Technologies.

60 APPLIED LIFE SCIENCES↗

Practical dose point-based methods to characterize dose distribution in a stationary elliptical body phantom for a cone-beam C-arm CT system

Purpose: To propose new dose point measurement-based metrics to characterize the dose distributions and the mean dose from a single partial rotation of an automatic exposure control-enabled, C-arm-based, wide cone angle computed tomography system over a stationary, large, body-shaped phantom. Methods: A small 0.6 cm{sup 3} ion chamber (IC) was used to measure the radiation dose in an elliptical body-shaped phantom made of tissue-equivalent material. The IC was placed at 23 well-distributed holes in the central and peripheral regions of the phantom and dose was recorded for six acquisition protocols with different combinations of minimum kVp (109 and 125 kVp) and z-collimator aperture (full: 22.2 cm; medium: 14.0 cm; small: 8.4 cm). Monte Carlo (MC) simulations were carried out to generate complete 2D dose distributions in the central plane (z = 0). The MC model was validated at the 23 dose points against IC experimental data. The planar dose distributions were then estimated using subsets of the point dose measurements using two proposed methods: (1) the proximity-based weighting method (method 1) and (2) the dose point surface fitting method (method 2). Twenty-eight different dose point distributions with six different point number cases (4, 5, 6, 7, 14, and 23 dose points) were evaluated to determine the optimal number of dose points and their placement in the phantom. The performances of the methods were determined by comparing their results with those of the validated MC simulations. The performances of the methods in the presence of measurement uncertainties were evaluated. Results: The 5-, 6-, and 7-point cases had differences below 2%, ranging from 1.0% to 1.7% for both methods, which is a performance comparable to that of the methods with a relatively large number of points, i.e., the 14- and 23-point cases. However, with the 4-point case, the performances of the two methods decreased sharply. Among the 4-, 5-, 6-, and 7-point cases, the 7-point case (1.0% [±0.6%] difference) and the 6-point case (0.7% [±0.6%] difference) performed best for method 1 and method 2, respectively. Moreover, method 2 demonstrated high-fidelity surface reconstruction with as few as 5 points, showing pixelwise absolute differences of 3.80 mGy (±0.32 mGy). Although the performance was shown to be sensitive to the phantom displacement from the isocenter, the performance changed by less than 2% for shifts up to 2 cm in the x- and y-axes in the central phantom plane. Conclusions: With as few as five points, method 1 and method 2 were able to compute the mean dose with reasonable accuracy, demonstrating differences of 1.7% (±1.2%) and 1.3% (±1.0%), respectively. A larger number of points do not necessarily guarantee better performance of the methods; optimal choice of point placement is necessary. The performance of the methods is sensitive to the alignment of the center of the body phantom relative to the isocenter. In body applications where dose distributions are important, method 2 is a better choice than method 1, as it reconstructs the dose surface with high fidelity, using as few as five points.

60 APPLIED LIFE SCIENCES↗

SU-F-T-159: Monte Carlo Simulation Studies of Three-Dimensional Dose Distribution for Polymer Gel Dosimeter and Radiochromic Gel Dosimeter in a Proton Beam

Purpose: The purpose of this simulation study is to evaluate the proton detectability of gel dosimeters, and estimate the three-dimensional dose distribution of protons in the radiochromic gel and polymer gel dosimeter compared with the dose distribution in water. Methods: The commercial composition ratios of normoxic polymer gel and LCV micelle radiochromic gel were included in this simulation study. The densities of polymer and radiochromic gel were 1.024 and 1.005 g/cm3, respectively. The 50, 80 and 140 MeV proton beam energies were selected. The dose distributions of protons in the polymer and radiochromic gel were simulated using Monte Carlo radiation transport code (MCNPX 2.7.0, Los Alamos Laboratory). The water equivalent depth profiles and the dose distributions of two gel dosimeters were compared for the water. Results: In case of irradiating 50, 80 and 140 MeV proton beam to water phantom, the reference Bragg-peak depths are represented at 2.22, 5.18 and 13.98 cm, respectively. The difference in the water equivalent depth is represented to about 0.17 and 0.37 cm in the radiochromic gel and polymer gel dosimeter, respectively. The proton absorbed doses in the radiochromic gel dosimeter are calculated to 2.41, 3.92 and 6.90 Gy with increment of incident proton energies. In the polymer gel dosimeter, the absorbed doses are calculated to 2.37, 3.85 and 6.78 Gy with increment of incident proton energies. The relative absorbed dose in radiochromic gel (about 0.47 %) is similar to that of water than the relative absorbed dose of polymer gel (about 2.26 %). In evaluating the proton dose distribution, we found that the dose distribution of both gel dosimeters matched that of water in most cases. Conclusion: As the dosimetry device, the radiochromic gel dosimeter has the potential particle detectability and is feasible to use for quality assurance of proton beam therapy beam.

07 ISOTOPE AND RADIATION SOURCES↗

Why Do Electricity Policy and Competitive Markets Fail to Use Advanced PV Systems to Improve Distribution Power Quality?

The increasing pressure for network operators to meet distribution network power quality standards with increasing peak loads, renewable energy targets, and advances in automated distributed power electronics and communications is forcing policy-makers to understand new means to distribute costs and benefits within electricity markets. Discussions surrounding how distributed generation (DG) exhibits active voltage regulation and power factor/reactive power control and other power quality capabilities are complicated by uncertainties of baseline local distribution network power quality and to whom and how costs and benefits of improved electricity infrastructure will be allocated. DG providing ancillary services that dynamically respond to the network characteristics could lead to major network improvements. With proper market structures renewable energy systems could greatly improve power quality on distribution systems with nearly no additional cost to the grid operators. Renewable DG does have variability challenges, though this issue can be overcome with energy storage, forecasting, and advanced inverter functionality. This paper presents real data from a large-scale grid-connected PV array with large-scale storage and explores effective mitigation measures for PV system variability. We discuss useful inverter technical knowledge for policy-makers to mitigate ongoing inflation of electricity network tariff components by new DG interconnection requirements or electricity markets which value power quality and control.

14 SOLAR ENERGY↗

Unveiling Current Guanaco Distribution in Chile Based upon Niche Structure of Phylogeographic Lineages: Andean Puna to Subpolar Forests

Niche description and differentiation at broad geographic scales have been recent major topics in ecology and evolution. Describing the environmental niche structure of sister taxa with known evolutionary trajectories stands out as a useful exercise in understanding niche requirements. Here we model the environmental niche structure and distribution of the recently resolved phylogeography of guanaco (Lama guanicoe) lineages on the western slope of the southern Andes. Using a maximum entropy framework, field data, and information on climate, topography, human density, and vegetation cover, we identify differences between the two subspecies (L.g.cacsilensis, L.g.guanicoe) and their intermediate-hybrid lineage, that most likely determine the distribution of this species. While aridity seems to be a major factor influencing the distribution at the species-level (annual precipitation ,900 mm), we also document important differences in niche specificity for each subspecies, where distribution of Northern lineage is explained mainly by elevation (mean = 3,413 m) and precipitation seasonality (mean = 161 mm), hybrid lineage by annual precipitation (mean = 139 mm), and Southern subspecies by annual precipitation (mean = 553 mm), precipitation seasonality (mean = 21 mm) and grass cover (mean = 8.2%). Among lineages, we detected low levels of niche overlap: I (Similarity Index) = 0.06 and D (Schoener’s Similarity Index) = 0.01; and higher levels when comparing Northern and Southern subspecies with hybrids lineage (I = 0.32-0.10 and D = 0.12-0.03, respectively). This suggests that important ecological and/or evolutionary processes are shaping the niche of guanacos in Chile, producing discrepancies when comparing range distribution at the species-level (81,756 km 2 ) with lineages-level (65,321 km 2 ). The subspecies-specific description of niche structure is provided here based upon detailed spatial distribution of the lineages of guanacos in Chile. Such description provides a scientific tool to further develop large scale plans for habitat conservation and preservation of intraspecific genetic variability for this far ranging South American camelid, which inhabits a diversity of ecoregion types from Andean puna to subpolar forests.

59 BASIC BIOLOGICAL SCIENCES↗

Final Technical Report Power through Policy: "Best Practices" for Cost-Effective Distributed Wind

Power through Policy: 'Best Practices' for Cost-Effective Distributed Wind is a U.S. Department of Energy (DOE)-funded project to identify distributed wind technology policy best practices and to help policymakers, utilities, advocates, and consumers examine their effectiveness using a pro forma model. Incorporating a customized feed from the Database of State Incentives for Renewables and Efficiency (DSIRE), the Web-based Distributed Wind Policy Comparison Tool (Policy Tool) is designed to assist state, local, and utility officials in understanding the financial impacts of different policy options to help reduce the cost of distributed wind technologies. The project's final products include the Distributed Wind Policy Comparison Tool, found at www.windpolicytool.org, and its accompanying documentation: Distributed Wind Policy Comparison Tool Guidebook: User Instructions, Assumptions, and Case Studies.

16 TIDAL AND WAVE POWER↗

An update to the computation of the Goudsmit-Saunderson distribution in MCNP® version 6.2

To demonstrate how the number of terms used to compute the Goudsmit- Saunderson distribution impacts results, we study a thin foil problem where the outgoing angular distribution is observed for 20-MeV electrons. The foil thickness is roughly 1.5 times the default substep size for a 20-MeV electron in gold ( 2.8e -3 cm). Therefore, for the default substep size, electrons are guaranteed to undergo at least one collision before encountering a boundary (at which point an approximation is applied). In theory, one can improve the accuracy of the MCNP6.2 electron transport method by reducing the substep size. However, one must assume that the underlying data are valid. We show that when a user reduces the substep size, the angular distribution observed is different than expected, the primary reason being that the underlying data were not computed using a sufficient number of terms. We also show that the distribution is recovered when the number of terms is increased from hundreds to thousands. Here, we showed that stabilizing the underlying angular deflection distributions used in transport improves simulation results, particularly when default parameters are adjusted such that the substep size is reduced. Stabilization is achieved by adding more terms when computing the Goudsmit-Sanderson distribution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Integrated Multi-Scale Data Analytics and Machine Learning for the Distribution Grid and Building-to-Grid Interface

This white paper introduces the application of advanced data analytics to the modernized grid. In particular, we consider the field of machine learning and where it is both useful, and not useful, for the particular field of the distribution grid and buildings interface. While analytics, in general, is a growing field of interest, and often seen as the golden goose in the burgeoning distribution grid industry, its application is often limited by communications infrastructure, or lack of a focused technical application. Overall, the linkage of analytics to purposeful application in the grid space has been limited. In this paper we consider the field of machine learning as a subset of analytical techniques, and discuss its ability and limitations to enable the future distribution grid and the building-to-grid interface. To that end, we also consider the potential for mixing distributed and centralized analytics and the pros and cons of these approaches. Machine learning is a subfield of computer science that studies and constructs algorithms that can learn from data and make predictions and improve forecasts. Incorporation of machine learning in grid monitoring and analysis tools may have the potential to solve data and operational challenges that result from increasing penetration of distributed and behind-the-meter energy resources. There is an exponentially expanding volume of measured data being generated on the distribution grid, which, with appropriate application of analytics, may be transformed into intelligible, actionable information that can be provided to the right actors – such as grid and building operators, at the appropriate time to enhance grid or building resilience, efficiency, and operations against various metrics or goals – such as total carbon reduction or other economic benefit to customers. While some basic analysis into these data streams can provide a wealth of information, computational and human boundaries on performing the analysis are becoming significant, with more data and multi-objective concerns. Efficient applications of analysis and the machine learning field are being considered in the loop.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Incentive-Based Control and Coordination of Distributed Energy Resources. Final Report

The rapid growth of low-inertia renewable energy resources represents an immense opportunity for the U.S. to minimize its carbon footprint, while presenting a challenge for system operators as traditional “spinning” generation resources are displaced. This transformation requires solutions to robustly and cost-effectively manage dynamic changes on the grid while ensuring quality of service. There is growing recognition that distributed energy resources (DERs – loads, distributed generation, storage, electric vehicles, etc.) represent a great potential to perform this function. This report details a scalable hierarchical control strategy for coordinating thousands of heterogeneous DERs in order to provide three ancillary gird services: 1) frequency response, a rapid (within 2 seconds) service used to maintain the grid at 60 Hz; 2) regulation response, a larger response used to balance on-going differences in supply and demand on the grid; and, 3) ramping reserve, used to bring on capacity to replace lost generation. The developed control architecture consists of 1) a Distribution Reliability Coordinator (DRC), 2) aggregator controllers, and finally, 3) DER controllers. The DRC coordinates all the flexible loads and distributed energy resources on the distribution system and bids the aggregate flexibility into the wholesale market. The DRC also performs resource allocation (deciding how the flexible devices on the distribution system will be dispatched) to meet the requirements for each of the three ancillary services. The aggregators control a collection of devices that are geographically co-located and provide a platform to aggregate their flexibility and mitigate uncertainty associated with a single flexible load by managing a large aggregation of similar loads (so that any stochastic effects average out). Finally, DER controllers (for example, thermostats for air conditioners, chargers for electric vehicles) adjust the power consumption of individual devices to ensure accurate and reliable delivery of the requested grid services. Evaluation and validation of this approach was conducted with a mixture of simulation and hardware testing for a range of DERs in residential (air conditioners and water heaters), commercial HVAC (ventilation fans and central chiller plants), and micro-grids (battery energy storage, solar PV etc.). This culminated in DER hardware and simulation models operating in conjunction with grid simulations as part of a large scale federated test-bed demonstration. Simulations of over 10,000 controllable residential devices (a combination of air conditioners, water heaters, batteries, and electric vehicles) demonstrated that this advanced control approach could simultaneously meet all three grid services. Furthermore, hardware-in-the-loop testing was performed with operational micro-grid and commercial building HVAC equipment. The micro-grid equipment (representing PV, battery storage, and back-up generators) demonstrated the ability to meet all frequency response requirements (except ramping time). The commercial building HVAC ventilation equipment successfully provided the regulating response service. An Industry Advisory Board (IAB) was formed and engaged throughout the project to get feed-back on project risks and potential commercialization barriers. Their input was invaluable in identify key risks stemming from regulatory and market access challenges, financial risks from under-performance, and competitive threats from utility-scale solutions such as integrated storage. A phased commercialization plan was developed that addresses continued risk reduction (value proposition refinement and performance uncertainty assessments), piloting through field demonstrations with key stakeholders, and finally, deployment as an emerging standard for DER control.

24 POWER TRANSMISSION AND DISTRIBUTION↗