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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Keyless Infrastructure Security Solution (KISS) (Technology Landscape Analysis Report)

The following landscape analysis explores blockchain or distributed ledger technologies application to securing electricity infrastructure. The exploration of how distributed ledger technologies can be used to increase the trustworthiness and integrity of the grid’s edge is imperative to the economic, security and well-being of all modern societies that rely on electricity. Blockchain technology’s ability to secure, track and optimize complex data transactions provides an exciting value proposition to securing and optimizing the U.S. power grid. An energy delivery system (EDS) operating at the grid’s edge requires unprecedented levels of security and trustworthiness to verify integrity of data and manage complex transactive and distributed Energy Resources (DERs) exchanges. Moreover, grid-edge devices lack visibility, control and security to conduct real-time energy transactions with the required security, speed and scale. The U.S. power grid is a complex system of systems that requires secure, reliable and trustworthy EDSs. Grid modernization has increased the speed and size of data sets exchanged on these systems (Gordes and Mylrea 2014). Exasperating the challenge is these systems are increasingly distributed creating new data fidelity and interoperability challenges for grid operators struggling to balance and incorporate DERs. Blockchain technology provides an atomically verifiable cryptographic signature to help increase the trustworthiness of EDSs at the grid’s edge. This feature is especially important at distribution level since EDSs and field devices have increasing operational and security requirements that are often diametrically opposed. For example, as data, speed and analytic requirements increase, security and functionality requirements increase. Further, as the grid’s edge incorporate DERs and transacts in real time, availability is prioritized over the integrity and confidentially of that data. Blockchain presents the prospect of solving some of these complex challenges related to grid security and modernization. However, there are more questions about blockchain applicability than answers. There are number of theoretical blockchain applications to the energy sector, but few energy utilities have actually applied, implemented or even experimented with the underlying distributed ledger technology and consensus algorithms that enable blockchain to exchange data more efficiently and securely.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

TH-AB-209-03: Overcoming Resolution Limitations of Diffuse Optical Signals in X-Ray Induced Luminescence (XIL) Imaging Via Selective Plane Illumination and 2D Deconvolution

Purpose: To evaluate the resolution and sensitivity of XIL imaging using a surface radiance simulation based on optical diffusion and maximum likelihood expectation maximization (MLEM) image reconstruction. XIL imaging seeks to determine the distribution of luminescent nanophosphors, which could be used as nanodosimeters or radiosensitizers. Methods: The XIL simulation generated a homogeneous slab with optical properties similar to tissue. X-ray activated nanophosphors were placed at 1.0 cm depth in the tissue in concentrations of 10{sup −4} g/mL in two volumes of 10 mm{sup 3} with varying separations between each other. An analytical optical diffusion model determined the surface radiance from the photon distributions generated at depth in the tissue by the nanophosphors. The simulation then determined the detected luminescent signal collected with a f/1.0 aperture lens and back-illuminated EMCCD camera. The surface radiance was deconvolved using a MLEM algorithm to estimate the nanophosphors distribution and the resolution. To account for both Poisson and Gaussian noise, a shifted Poisson imaging model was used in the deconvolution. The deconvolved distributions were fitted to a Gaussian after radial averaging to measure the full width at half maximum (FWHM) and the peak to peak distance between distributions was measured to determine the resolving power. Results: Simulated surface radiances for doses from 1mGy to 100 cGy were computed. Each image was deconvolved using 1000 iterations. At 1mGy, deconvolution reduced the FWHM of the nanophosphors distribution by 65% and had a resolving power is 3.84 mm. Decreasing the dose from 100 cGy to 1 mGy increased the FWHM by 22% but allowed for a dose reduction of a factor of 1000. Conclusion: Deconvolving the detected surface radiance allows for dose reduction while maintaining the resolution of the nanophosphors. It proves to be a useful technique in overcoming the resolution limitations of diffuse optical imaging in tissue. C. S. acknowledges support from the NIH National Institute of General Medical Sciences (Award number R25GM109439, Project Title: University of Chicago Initiative for Maximizing Student Development, IMSD). B. Q. and P. L. acknowledge support from NIH grant R01EB017293.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Multiscale modeling of polyisoprene on graphite

The local dynamics and the conformational properties of polyisoprene next to a smooth graphite surface constructed by graphene layers are studied by a multiscale methodology. First, fully atomistic molecular dynamics simulations of oligomers next to the surface are performed. Subsequently, Monte Carlo simulations of a systematically derived coarse-grained model generate numerous uncorrelated structures for polymer systems. A new reverse backmapping strategy is presented that reintroduces atomistic detail. Finally, multiple extensive fully atomistic simulations with large systems of long macromolecules are employed to examine local dynamics in proximity to graphite. Polyisoprene repeat units arrange close to a parallel configuration with chains exhibiting a distribution of contact lengths. Efficient Monte Carlo algorithms with the coarse-grain model are capable of sampling these distributions for any molecular weight in quantitative agreement with predictions from atomistic models. Furthermore, molecular dynamics simulations with well-equilibrated systems at all length-scales support an increased dynamic heterogeneity that is emerging from both intermolecular interactions with the flat surface and intramolecular cooperativity. This study provides a detailed comprehensive picture of polyisoprene on a flat surface and consists of an effort to characterize such systems in atomistic detail.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-E-T-517: Analytic Formalism to Compute in Real Time Dose Distributions Delivered by HDR Units

Purpose: Develop an analytical algorithm to compute the dose delivered by Ir-192 dwell positions with high accuracy using the 3-dimensional (3D) dose distribution of an HDR source. Using our analytical function, the dose delivered by an HDR unit as treatment progresses can be determined using the actual delivered temporal and positional data of each individual dwell. Consequently, true delivered dose can be computed when each catheter becomes active. We hypothesize that the knowledge of such analytical formulation will allow developing HDR systems with a real time treatment evaluation tool to avoid mistreatments. Methods: In our analytic formulation, the dose is computed by using the full anisotropic function data of the TG 43 formalism with 3D ellipsoidal function. The discrepancy between the planned dose and the delivered dose is computed using an analytic perturbation method over the initial dose distribution. This methodology speeds up the computation because only changes in dose discrepancies originated by spatial and temporal deviations are computed. A dose difference map at the point of interest is obtained from these functions and this difference can be shown during treatment in real time to examine the treatment accuracy. Results: We determine the analytical solution and a perturbation function for the 3 translational 3 rotational, and 1D temporal errors in source distributions. The analytic formulation is a sequence of simple equations that can be processed in any modern computer in few seconds. Because computations are based in an analytical solution, small deviations of the dose when sub-millimeter positional changes occur can be detected. Conclusions: We formulated an analytical method to compute 4D dose distributions and dose differences based on an analytical solution and perturbations to the original dose. This method is highly accurate and can be.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Bus Clustering for Distribution Grid Topology Identification

Recovering the distribution grid topology is essential to perform several distribution system operator functions. Many algorithms that address the topology recovery problem have already been proposed in the literature. Most are based on a priori information regarding which buses are fed by which substation; however, this information might not be available because frequent grid reconfigurations change the distribution grid portion connected to each substation. This paper addresses the problem of assigning every substation the set of buses that it is feeding, given field data. First, the aforementioned task is cast as a nonconvex optimization problem. Second, a relaxed version of the optimization problem is solved via the alternating direction method of multipliers. Finally, the performance of our approach is validated through numerical simulations of realistic scenarios using a standard IEEE benchmark feeder.

bus clustering↗
DOE OSTI2020

Repair and Resource Scheduling in Unbalanced Distribution Systems Using Neighborhood Search

—This paper proposes an optimization strategy to assist utility operators to recover power distribution systems after large outages. Specifically, a mixed-integer linear programming (MILP) model is developed for co-optimizing crews, resources, and network operations. The MILP model coordinates damage isolation, network reconfiguration, distributed generator re-dispatch, and crew/resource logistics. In addition, a framework for integrating different types of photovoltaic (PV) systems in the restoration process is developed. We consider two different types of crews, namely, line crews for damage repair and tree crews for obstacle removal. We also model the repair resource logistic constraints. Furthermore, a new algorithm is developed for solving the distribution system repair and restoration problem (DSRRP). The algorithm starts by solving DSRRP using an assignmentbased method, then a neighborhood search method is designed to iteratively improve the solution. The proposed method is validated on modified IEEE 123- and 8500-bus distribution test systems.

Outage management↗
DOE OSTI2014

Independent calculation of dose distributions for helical tomotherapy using a conventional treatment planning system

Purpose: The dosimetric verification of treatment plans in helical tomotherapy usually is carried out via verification measurements. In this study, a method for independent dose calculation of tomotherapy treatment plans is presented, that uses a conventional treatment planning system with a pencil kernel dose calculation algorithm for generation of verification dose distributions based on patient CT data. Methods: A pencil beam algorithm that directly uses measured beam data was configured for dose calculation for a tomotherapy machine. Tomotherapy treatment plans were converted into a format readable by an in-house treatment planning system by assigning each projection to one static treatment field and shifting the calculation isocenter for each field in order to account for the couch movement. The modulation of the fluence for each projection is read out of the delivery sinogram, and with the kernel-based dose calculation, this information can directly be used for dose calculation without the need for decomposition of the sinogram. The sinogram values are only corrected for leaf output and leaf latency. Using the converted treatment plans, dose was recalculated with the independent treatment planning system. Multiple treatment plans ranging from simple static fields to real patient treatment plans were calculated using the new approach and either compared to actual measurements or the 3D dose distribution calculated by the tomotherapy treatment planning system. In addition, dose–volume histograms were calculated for the patient plans. Results: Except for minor deviations at the maximum field size, the pencil beam dose calculation for static beams agreed with measurements in a water tank within 2%/2 mm. A mean deviation to point dose measurements in the cheese phantom of 0.89% ± 0.81% was found for unmodulated helical plans. A mean voxel-based deviation of −0.67% ± 1.11% for all voxels in the respective high dose region (dose values >80%), and a mean local voxel-based deviation of −2.41% ± 0.75% for all voxels with dose values >20% were found for 11 modulated plans in the cheese phantom. Averaged over nine patient plans, the deviations amounted to −0.14% ± 1.97% (voxels >80%) and −0.95% ± 2.27% (>20%, local deviations). For a lung case, mean voxel-based deviations of more than 4% were found, while for all other patient plans, all mean voxel-based deviations were within ±2.4%. Conclusions: The presented method is suitable for independent dose calculation for helical tomotherapy within the known limitations of the pencil beam algorithm. It can serve as verification of the primary dose calculation and thereby reduce the need for time-consuming measurements. By using the patient anatomy and generating full 3D dose data, and combined with measurements of additional machine parameters, it can substantially contribute to overall patient safety.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Neutron tomography of axially symmetric objects using 14 MeV neutrons from a portable neutron generator

In nuclear boiling water reactor cores, the distribution of water and steam (void) is essential for both safety and efficiency reasons. In order to enhance predictive capabilities, void distribution assessment is performed in two-phase test-loops under reactor-relevant conditions. This article proposes the novel technique of fast-neutron tomography using a portable deuterium-tritium neutron generator to determine the time-averaged void distribution in these loops. Fast neutrons have the advantage of high transmission through the metallic structures and pipes typically concealing a thermal-hydraulic test loop, while still being fairly sensitive to the water/void content. However, commercially available fast-neutron generators also have the disadvantage of a relatively low yield and fast-neutron detection also suffers from relatively low detection efficiency. Fortunately, some loops are axially symmetric, a property which can be exploited to reduce the amount of data needed for tomographic measurement, thus limiting the interrogation time needed. In this article, three axially symmetric test objects depicting a thermal-hydraulic test loop have been examined; steel pipes with outer diameter 24 mm, thickness 1.5 mm, and with three different distributions of the plastic material POM inside the pipes. Data recorded with the FANTOM fast-neutron tomography instrument have been used to perform tomographic reconstructions to assess their radial material distribution. Here, a dedicated tomographic algorithm that exploits the symmetry of these objects has been applied, which is described in the paper. Results are demonstrated in 20 rixel (radial pixel) reconstructions of the interior constitution and 2D visualization of the pipe interior is demonstrated. The local POM attenuation coefficients in the rixels were measured with errors (RMS) of 0.025, 0.020, and 0.022 cm{sup −1}, solid POM attenuation coefficient. The accuracy and precision is high enough to provide a useful indication on the flow mode, and a visualization of the radial material distribution can be obtained. A benefit of this system is its potential to be mounted at any axial height of a two-phase test section without requirements for pre-fabricated entrances or windows. This could mean a significant increase in flexibility of the void distribution assessment capability at many existing two-phase test loops.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Small-Noise Analysis and Symmetrization of Implicit Monte Carlo Samplers

Implicit samplers are algorithms for producing independent, weighted samples from multivariate probability distributions. These are often applied in Bayesian data assimilation algorithms. We use Laplace asymptotic expansions to analyze two implicit samplers in the small noise regime. Our analysis suggests a symmetrization of the algorithms that leads to improved implicit sampling schemes at a relatively small additional cost. Here, computational experiments confirm the theory and show that symmetrization is effective for small noise sampling problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-I-45: An Automated Technique to Measure Image Contrast in Clinical CT Images

Purpose: To develop and validate an automated technique for measuring image contrast in chest computed tomography (CT) exams. Methods: An automated computer algorithm was developed to measure the distribution of Hounsfield units (HUs) inside four major organs: the lungs, liver, aorta, and bones. These organs were first segmented or identified using computer vision and image processing techniques. Regions of interest (ROIs) were automatically placed inside the lungs, liver, and aorta and histograms of the HUs inside the ROIs were constructed. The mean and standard deviation of each histogram were computed for each CT dataset. Comparison of the mean and standard deviation of the HUs in the different organs provides different contrast values. The ROI for the bones is simply the segmentation mask of the bones. Since the histogram for bones does not follow a Gaussian distribution, the 25th and 75th percentile were computed instead of the mean. The sensitivity and accuracy of the algorithm was investigated by comparing the automated measurements with manual measurements. Fifteen contrast enhanced and fifteen non-contrast enhanced chest CT clinical datasets were examined in the validation procedure. Results: The algorithm successfully measured the histograms of the four organs in both contrast and non-contrast enhanced chest CT exams. The automated measurements were in agreement with manual measurements. The algorithm has sufficient sensitivity as indicated by the near unity slope of the automated versus manual measurement plots. Furthermore, the algorithm has sufficient accuracy as indicated by the high coefficient of determination, R2, values ranging from 0.879 to 0.998. Conclusion: Patient-specific image contrast can be measured from clinical datasets. The algorithm can be run on both contrast enhanced and non-enhanced clinical datasets. The method can be applied to automatically assess the contrast characteristics of clinical chest CT images and quantify dependencies that may not be captured in phantom data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Sparse Recovery for Scientific Data

We have built build and analyzed fundamental mathematical tools that enable sparse recovery of scientific data for high performance computing, experimental facilities and sensor measurement. The proposed work will impact many areas of research across the DOE. We have designed, developed and analyzed fast scalable algorithms for the sparse recovery of scientific data sets that may be extremely large, generated very quickly and distributed across multiple storage devices. The algorithms we developed will be used to process the copious amounts of scientific data generated by the DOE supercomputer simulations and by DOE experimental and observational facilities. They leverage the fact that while the amount of data produced can be extremely large, the actual quantities of interest (QoI's) are often sparse, either in space time, or in some feature space. Mathematically, notions of compressive sensing, including l1 regularized and total variation regularized optimization have played an important part in this effort.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Decentralized Low-Rank State Estimation for Power Distribution Systems

This article considers the low-observability state estimation problem in power distribution networks and develops a decentralized state estimation algorithm leveraging the matrix completion methodology. Matrix completion has been shown to be an effective technique in state estimation that exploits the low dimensionality of the power system measurements to recover missing information. This technique can utilize an approximate (linear) load flow model, or it can be used with no physical models in a network where no information about the topology or line admittance is available. The direct application of matrix completion algorithms requires solving a semi-definite programming (SDP) problem, which becomes computationally challenging for large networks. We therefore develop a decentralized algorithm that capitalizes on the popular proximal alternating direction method of multipliers (proximal ADMM). The method allows us to distribute the computation among different areas of the network, leading to a scalable algorithm. By doing all computations at individual control areas and only communicating with neighboring areas, the algorithm eliminates the need for data to be sent to a central processing unit and thus increases efficiency and contributes to the goal of autonomous control of distribution networks. We illustrate the advantages of the proposed algorithm numerically using standard IEEE test cases.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2023

Distributed approximate minimal Steiner trees with millions of seed vertices on billion-edge graphs

In this report, we present a parallel 2-approximation Steiner minimal tree algorithm and its MPI-based distributed implementation. In place of expensive distance computations between all pairs of seed vertices, the solution we employ exploits a cheaper Voronoi cell computation. Our design leverages asynchronous processing and message prioritization to accelerate convergence of distance computations, and harnesses vertex and edge centric processing to offer fast time-to-solution. We demonstrate scalability and performance using real-world graphs with up to 128 billion edges and 512 compute nodes, and show the ability to find Steiner trees with up to one million seed vertices. Using 12 data instances, we present comparison with the state-of-the-art exact solver, SCIP-Jack, and two sequential 2-approximate algorithms. We empirically show that, on average, the total distance of the Steiner tree identified by our solution is 1.1290 times greater than the Steiner minimal tree – well within the theoretical approximation bound of 2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

The Effective Number Density of Galaxies for Weak Lensing Measurements in the LSST Project

Future weak lensing surveys potentially hold the highest statistical power for constrain ing cosmological parameters compared to other cosmological probes. The statistical power of a weak lensing survey is determined by the sky coverage, the inverse of the noise in shear measurements, and the galaxy number density. The combination of the latter two factors is often expressed in terms of n eff – the “effective number density of galaxies used for weak lensing measurements”. In this work, we estimate n eff for the Large Synoptic Survey Telescope (LSST) project, the most powerful ground-based lensing survey planned for the next two decades. We investigate how the following factors affect the resulting n eff of the survey with detailed simulations: (1) survey time, (2) shear measurement algorithm, (3) algorithm for combining multiple exposures, (4) inclusion of data from multiple filter bands, (5) redshift distribution of the galaxies, and (6) masking and blending. For the first time, we quantify in a general weak lensing analysis pipeline the sensitivity of n eff to the above factors. We find that with current weak lensing algorithms, expected distributions of observing parameters, and all lensing data (r- and i-band, covering 18,000 degree 2 of sky) for LSST, n eff ≈ 37 arcmin -2 before considering blending and masking, n eff ≈ 31 arcmin -2 when rejecting seriously blended galaxies and n eff ≈ 26 arcmin -2 when considering an additional 15% loss of galaxies due to masking. With future improvements in weak lensing algorithms, these values could be expected to increase by up to 20%. Throughout the paper, we also stress the ways in which n eff depends on our ability to understand and control systematic effects in the measurements.

Astrophysics↗
DOE OSTI2014

TU-C-BRE-11: 3D EPID-Based in Vivo Dosimetry: A Major Step Forward Towards Optimal Quality and Safety in Radiation Oncology Practice

Purpose: To develop a 3D in vivo dosimetry method that is able to substitute pre-treatment verification in an efficient way, and to terminate treatment delivery if the online measured 3D dose distribution deviates too much from the predicted dose distribution. Methods: A back-projection algorithm has been further developed and implemented to enable automatic 3D in vivo dose verification of IMRT/VMAT treatments using a-Si EPIDs. New software tools were clinically introduced to allow automated image acquisition, to periodically inspect the record-and-verify database, and to automatically run the EPID dosimetry software. The comparison of the EPID-reconstructed and planned dose distribution is done offline to raise automatically alerts and to schedule actions when deviations are detected. Furthermore, a software package for online dose reconstruction was also developed. The RMS of the difference between the cumulative planned and reconstructed 3D dose distributions was used for triggering a halt of a linac. Results: The implementation of fully automated 3D EPID-based in vivo dosimetry was able to replace pre-treatment verification for more than 90% of the patient treatments. The process has been fully automated and integrated in our clinical workflow where over 3,500 IMRT/VMAT treatments are verified each year. By optimizing the dose reconstruction algorithm and the I/O performance, the delivered 3D dose distribution is verified in less than 200 ms per portal image, which includes the comparison between the reconstructed and planned dose distribution. In this way it was possible to generate a trigger that can stop the irradiation at less than 20 cGy after introducing large delivery errors. Conclusion: The automatic offline solution facilitated the large scale clinical implementation of 3D EPID-based in vivo dose verification of IMRT/VMAT treatments; the online approach has been successfully tested for various severe delivery errors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Dosimetric comparison of lung stereotactic body radiotherapy treatment plans using averaged computed tomography and end-exhalation computed tomography images: Evaluation of the effect of different dose-calculation algorithms and prescription methods

The purpose of this article is to quantitatively evaluate differences in dose distributions calculated using various computed tomography (CT) datasets, dose-calculation algorithms, and prescription methods in stereotactic body radiotherapy (SBRT) for patients with early-stage lung cancer. Data on 29 patients with early-stage lung cancer treated with SBRT were retrospectively analyzed. Averaged CT (Ave-CT) and expiratory CT (Ex-CT) images were reconstructed for each patient using 4-dimensional CT data. Dose distributions were initially calculated using the Ave-CT images and recalculated (in the same monitor units [MUs]) by employing Ex-CT images with the same beam arrangements. The dose-volume parameters, including D{sub 95}, D{sub 90}, D{sub 50}, and D{sub 2} of the planning target volume (PTV), were compared between the 2 image sets. To explore the influence of dose-calculation algorithms and prescription methods on the differences in dose distributions evident between Ave-CT and Ex-CT images, we calculated dose distributions using the following 3 different algorithms: x-ray Voxel Monte Carlo (XVMC), Acuros XB (AXB), and the anisotropic analytical algorithm (AAA). We also used 2 different dose-prescription methods; the isocenter prescription and the PTV periphery prescription methods. All differences in PTV dose-volume parameters calculated using Ave-CT and Ex-CT data were within 3 percentage points (%pts) employing the isocenter prescription method, and within 1.5%pts using the PTV periphery prescription method, irrespective of which of the 3 algorithms (XVMC, AXB, and AAA) was employed. The frequencies of dose-volume parameters differing by >1%pt when the XVMC and AXB were used were greater than those associated with the use of the AAA, regardless of the dose-prescription method employed. All differences in PTV dose-volume parameters calculated using Ave-CT and Ex-CT data on patients who underwent lung SBRT were within 3%pts, regardless of the dose-calculation algorithm or the dose-prescription method employed.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

SU-E-J-240: The Impact On Clinical Dose-Distributions When Using MR-Images Registered with Stereotactic CT-Images in Gamma Knife Radiosurgery

Purpose: Most Gamma knife treatments are based solely on MR-images. However, for fractionated treatments and to implement TPS dose calculations that require electron densities, CT image data is essential. The purpose of this work is to assess the dosimetric effects of using MR-images registered with stereotactic CT-images in Gamma knife treatments. Methods: Twelve patients treated for vestibular schwannoma with Gamma Knife Perfexion (Elekta Instruments, Sweden) were selected for this study. The prescribed doses (12 Gy to periphery) were delivered based on the conventional approach of using stereotactic MR-images only. These plans were imported into stereotactic CT-images (by registering MR-images with stereotactic CT-images using the Leksell gamma plan registration software). The dose plans, for each patient, are identical in both cases except for potential rotations and translations resulting from the registration. The impact of the registrations was assessed by an algorithm written in Matlab. The algorithm compares the dose-distributions voxel-by-voxel between the two plans, calculates the full dose coverage of the target (treated in the conventional approach) achieved by the CT-based plan, and calculates the minimum dose delivered to the target (treated in the conventional approach) achieved by the CT-based plan. Results: The mean dose difference between the plans was 0.2 Gy to 0.4 Gy (max 4.5 Gy) whereas between 89% and 97% of the target (treated in the conventional approach) received the prescribed dose, by the CT-plan. The minimum dose to the target (treated in the conventional approach) given by the CT-based plan was between 7.9 Gy and 10.7 Gy (compared to 12 Gy in the conventional treatment). Conclusion: The impact of using MR-images registered with stereotactic CT-images has successfully been compared to conventionally delivered dose plans showing significant differences between the two. Although CTimages have been implemented clinically; the effect of the registration has not been fully investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Optimal Power Flow Pursuit

Past works that focused on addressing power-quality and reliability concerns related to renewable energy resources (RESs) operating with business-as-usual practices have looked at the design of Volt/VAr and Volt/Watt strategies to regulate real or reactive powers based on local voltage measurements, so that terminal voltages are within acceptable levels. These control strategies have the potential of operating at the same time scale of distribution-system dynamics, and can therefore mitigate disturbances precipitated fast time-varying loads and ambient conditions; however, they do not necessarily guarantee system-level optimality, and stability claims are mainly based on empirical evidences. On a different time scale, centralized and distributed optimal power flow (OPF) algorithms have been proposed to compute optimal steady-state inverter setpoints, so that power losses and voltage deviations are minimized and economic benefits to end-users providing ancillary services are maximized. However, traditional OPF schemes may offer decision making capabilities that do not match the dynamics of distribution systems. Particularly, during the time required to collect data from all the nodes of the network (e.g., loads), solve the OPF, and subsequently dispatch setpoints, the underlying load, ambient, and network conditions may have already changed; in this case, the DER output powers would be consistently regulated around outdated setpoints, leading to suboptimal system operation and violation of relevant electrical limits. The present work focuses on the synthesis of distributed RES-inverter controllers that leverage the opportunities for fast feedback offered by power-electronics interfaced RESs. The overarching objective is to bridge the temporal gap between long-term system optimization and real-time control, to enable seamless RES integration in large scale with stability and efficiency guarantees, while congruently pursuing system-level optimization objectives. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. The proposed controllers enable an update of the power outputs at a time scale that is compatible with the underlying dynamics of loads and ambient conditions, and continuously drive the system operation towards OPF-based solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗