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At least 613 records · Page 34

Dynamic Building Load Control to Facilitate High Penetration of Solar Photovoltaic Generation (Final Technical Report)

Solar photovoltaic (PV) resources are the most common form of distributed generation in residential and commercial customer premises within electric distribution networks. A higher penetration of PV generation in distribution circuits will impose challenges on maintaining service voltages within the range of industry standards, power quality, and power flow. Buildings consume 74% of the electricity produced in the United States, and a significant portion of the building load is dispatchable, making them responsive to electrical grid needs. Oak Ridge National Laboratory—in collaboration with Southern Company; the University of Tennessee, Knoxville; and the Georgia Institute of Technology—is examining the PV integration issues in distribution-level electrical grids and developing integrated demand-side control and communication systems to enable responsive loads. The proposed responsive loads mechanism performs renewable generation following to increase the penetration of solar PV within each feeder. The specific objectives of this project are to (1) examine distribution-level PV integration scenarios to understand requirements, (2) undertake an end-to-end simulation-based design of a distributed control strategy of loads geographically near the PV generation asset to minimize the effect on the distribution feeder, (3) deploy and demonstrate the control technology developed in partnership with utilities, and (4) perform a scalability analysis at the utility scale. This 3-year integrated project aims to develop, demonstrate, and validate demand-side control technology to enable increased the penetration of renewables while mitigating challenges that arise due to their intermittency. Activities in Budget Period (BP) 1 focused on a literature review and the formal design of a control system for integrating local distribution with generation and loads. The team used modeling and simulation to evaluate the impact of varying buildings loads, variable PV generation, and power flow dynamics on the distribution circuit. The dynamic models developed in BP 1 were used in BP 2 to develop a model-based control design and a test bed. The test bed has enabled the simulation-based testing and comparison of different control designs and formulations applied to different configurations of the distribution grid, PVs, and building loads. The control approaches developed in BP 2 were implemented in BP 3 in the form of hardware deployed at the Central Baptist Church (CBC) in Knoxville, Tennessee, for testing and evaluation. The outcome of this project was the development and demonstration of open-source, low-cost, low-touch sensing and control retrofits to distributed PV generation and building loads that, in a coordinated fashion, provide the load-shaping response needed to integrate high levels of renewable penetration. This research addresses the target metrics by dynamically controlling a load with solar generation variability to minimize the extent of two-way power flow, enhance reliability, facilitate high PV penetration (>100% of peak load in a line segment), and generate scalable software and hardware solutions adaptable to any penetration levels. The research and development activities are focused and designed to be impactful within the relevant 2020 targets time frame.An accurate open-source integration simulation framework for end-to-end control design was developed and deployed at the CBC facility for testing and evaluation. This final report provides a detailed review of the technical results achieved during this 3-year integrated project. A novel spectral analysis of PV data is demonstrated to derive the requirements of the control design. A detailed simulation-based analysis of PV integration at increasing penetration levels is presented using 1 year of PV data to demonstrate the impact on the distribution circuits. Two different control strategies were developed and demonstrated via simulation to track variable PV generation with adaptive load dispatch. The report concludes with a summary of accomplishments and recommendations for a path forward.

14 SOLAR ENERGY↗

Drought Impacts on Hydroelectric Power Generation in the Western United States

The Western United States experiences large fluctuations in rain and snowfall from year to year, affecting river flows and reservoir levels throughout the region. This interannual variability in water resources leaves a strong signature on total annual energy generated by the region’s fleet of hydroelectric dams. In a wet year, like 2011, hydroelectric power can meet 30 percent of annual western electricity demand. That contribution can drop below 20 percent during severe drought years. Characterizing the contribution of hydroelectric power to the western generation portfolio during drought is crucial to understanding the resilience of the hydropower sector to climate-related risk, both now and in the future. This report analyzes the impacts of historical western droughts on hydroelectric power production by combining two decades’ worth of annual generation—recorded at more than 600 hydroelectric power plants—with historical climate data developed for distinct hydropower subregions of the West. The most extreme impacts of drought on hydroelectric power are found at individual dams where reservoir levels are so low that released water and thus generation becomes severely restricted. These isolated cases often receive widespread media attention, leading to a common misconception that hydroelectric power is an unreliable technology whose role will diminish over time as the western climate produces longer and more severe droughts. Yet, when aggregated to the scale of the West, the observational records of hydropower generation reveal a different story. Even during the most severe droughts experienced since the turn of the century, the western hydropower fleet sustained more than 80% of its typical annual generation. Observational data indicate that drought in 2021 led to the worst year for hydropower generation in the West since 2001, with total generation approximately 16 percent below the 21st century two-decade average. The year 2021 was particularly severe in California (second worst hydro year of last two decades, ~48 percent below average) and Oregon (worst hydro year of last two decades), while generation in Washington and Idaho was affected to a lesser degree (~12 percent below average for combined region). The year 2001 remains the year of lowest western hydropower generation of the twenty-first century so far, owing to extreme drought in the Pacific Northwest, where about two-thirds of western hydropower capacity is located. The primary reason for this relative stability is the diversity of weather across the West; drought rarely impairs hydroelectric power across all river basins at the same time.

13 HYDRO ENERGY↗

Impact of Emergency Diesel Generator Reliability on Microgrids and Building-Tied Systems

Microgrids are an emerging alternative as an energy backup system for critical electric loads and have improved performance compared to the traditional architecture where a single emergency diesel generator is tied to an individual building. Both architectures are dependent on the reliability of their individual generators and a quantitative and realistic comparison of the overall system reliability of the two architectures is lacking. Using recently published work on emergency diesel generator finite reliability, a quantitative methodology is presented to compare the reliability of a microgrid architecture based on centralized emergency diesel generators to the traditional approach of generators tied to individual buildings. Three system reliability performance metrics are calculated as a function of outage duration: (1) probability to meet 100% of the critical load; (2) expected fraction of lost load; and (3) probability to meet the highest priority critical loads. It is shown that stand-alone building-tied emergency diesel generators systems, even when two emergency diesel generators are used per building, cannot provide the reliability required to sustain critical loads for a grid outage lasting multiple days. Due to their network configuration and ability to share load, diesel generator-based microgrid configurations are estimated to have = 93% probability of powering all buildings for a 2-week outage there the individual building-tied emergency diesel generator architecture has a =20% probability. Microgrids do present other susceptibilities that are site specific and should be considered including vulnerabilities associated with the on-campus distribution system and cybersecurity.

backup power↗

Stochastic correlation analysis to rank the impact of intermittent wind generation on unreliability margins of power systems

Power systems are vulnerable to extreme contingencies (like an outage of a major generating substation or transmission line) that can cause significant generation and load loss and can lead to further cascading outages of other transmission facilities and generators in the system. Power systems operators take time-ahead actions (real time to day ahead) actions based on forecasted data as well as telemetry. However, there is a probability of extreme swings in wind generation that can push the power system that is already close to system boundaries into unreliable states. Increasing penetration on wind generation and uncertainties in short term forecast can move the system into operational states that can violate N-1 reliability criteria. While the power system planning accounts for worst case analyses to mitigate such emergencies, it is necessary to understand the spatial and temporal correlation of load buses with intermittent wind generation. The ranking of wind generators based on stochastic correlation to unreliability margins of load buses provides an insight of system vulnerabilities that can be corrected by appropriate emergency controls. A Monte-Carlo simulation of wind uncertainty forecast is performed to identify the probability distributions of unreliability margins. Ranking of wind generators is performed based on stochastic correlation analysis of the wind power generated and the load losses at the buses. This helps in not only identifying weak buses in the power system but also in identifying the vulnerable wind locations to plan for system reinforcements. Power system modeling and hybrid simulation to calculate unreliability margins are performed using DCAT and demonstrated on the 32-bus Nordic test system.

generators, wind forecasting, wind power generatio↗

Western Wind and Solar Integration Study Phase 3A: Low Levels of Synchronous Generation

The stability of the North American electric power grids under conditions of high penetrations of wind and solar is a significant concern and possible impediment to reaching renewable energy goals. The 33% wind and solar annual energy penetration considered in this study results in substantial changes to the characteristics of the bulk power system. This includes different power flow patterns, different commitment and dispatch of existing synchronous generation, and different dynamic behavior from wind and solar generation. The Western Wind and Solar Integration Study (WWSIS), sponsored by the U.S. Department of Energy, is one of the largest regional solar and wind integration studies to date. In multiple phases, it has explored different aspects of the question: Can we integrate large amounts of wind and solar energy into the electric power system of the West? The work reported here focused on the impact of low levels of synchronous generation on the transient stability performance in one part of the region in which wind generation has displaced synchronous thermal generation under highly stressed, weak system conditions. It is essentially an extension of WWSIS-3. Transient stability, the ability of the power system to maintain synchronism among all elements following disturbances, is a major constraint on operations in many grids, including the western U.S. and Texas systems. These constraints primarily concern the performance of the large-scale bulk power system. But grid-wide stability concerns with high penetrations of wind and solar are still not thoroughly understood. This work focuses on 'traditional' fundamental frequency stability issues, such as maintaining synchronism, frequency, and voltage. The objectives of this study are to better understand the implications of low levels of synchronous generation and a weak grid on overall system performance by: 1) Investigating the Western Interconnection under conditions of both high renewable generation (e.g., wind and solar) and low synchronous generation (e.g., significant coal power plant decommitment or retirement); and 2) Analyzing both the large-scale stability of the Western Interconnection and regional stability issues driven by more geographically dispersed renewable generation interacting with a transmission grid that evolved with large, central station plants at key nodes. As noted above, the work reported here is an extension of the research performed in WWSIS-3.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High yield neutron generators using the DD reaction

A product line of high yield neutron generators has been developed at Adelphi technology inc. The generators use the D-D fusion reaction and are driven by an ion beam supplied by a microwave ion source. Yields of up to 5 Multiplication-Sign 10{sup 9} n/s have been achieved, which are comparable to those obtained using the more efficient D-T reaction. The microwave-driven plasma uses the electron cyclotron resonance (ECR) to produce a high plasma density for high current and high atomic ion species. These generators have an actively pumped vacuum system that allows operation at reduced pressure in the target chamber, increasing the overall system reliability. Since no radioactive tritium is used, the generators can be easily serviced, and components can be easily replaced, providing essentially an unlimited lifetime. Fast neutron source size can be adjusted by selecting the aperture and target geometries according to customer specifications. Pulsed and continuous operation has been demonstrated. Minimum pulse lengths of 50 {mu}s have been achieved. Since the generators are easily serviceable, they offer a long lifetime neutron generator for laboratories and commercial systems requiring continuous operation. Several of the generators have been enclosed in radiation shielding/moderator structures designed for customer specifications. These generators have been proven to be useful for prompt gamma neutron activation analysis (PGNAA), neutron activation analysis (NAA) and fast neutron radiography. Thus these generators make excellent fast, epithermal and thermal neutron sources for laboratories and industrial applications that require neutrons with safe operation, small footprint, low cost and small regulatory burden.

43 PARTICLE ACCELERATORS↗

Engineering a modular 44 Ti/ 44 Sc generator: eluate evaluation in preclinical models and estimation of human radiation dosimetry

Background: 44 Sc/ 47 Sc is an attractive theranostic pair for targeted in vivo positron emission tomographic (PET) imaging and beta-particle treatment of cancer. The 44 Ti/ 44 Sc generator allows daily onsite production of this diagnostic isotope, which may provide an attractive alternative for PET facilities that lack in-house irradiation capabilities. Early animal and patient studies have demonstrated the utility of 44 Sc. In our current study, we built and evaluated a novel clinical-scale 44 Ti/ 44 Sc generator, explored the pharmacokinetic profiles of 44 ScCl 3 , [ 44 Sc]-citrate and [ 44 Sc]-NODAGA (1,4,7-triazacyclononane,1-glutaric acid-4,7-acetic acid) in naïve mice, and estimated the radiation burden of 44 ScCl 3 in humans. Methods: 44 Ti/ 44 Sc (101.2 MBq) in 6 M HCl solution was utilized to assemble a modular ZR resin containing generator. After assembly, 44 Sc was eluted with 0.05 M HCl for further PET imaging and biodistribution studies in female Swiss Webster mice. Based on the biodistribution data, absorbed doses of 44 / 47 ScCl 3 in human adults were calculated for 18 organs and tissues using the IDAC-Dose software. Results: 44 Ti in 6 M HCl was loaded onto the organic resin generator with a yield of 99.97%. After loading and initial stabilization, 44 ScCl 3 was eluted with 0.05 M HCl in typical yields of 82.9 ± 5.3% (N = 16), which was normalized to the estimated generator capacity. Estimated generator capacity was computed based on elution time interval and the total amount of 44 Ti loaded on the generator. Run in forward and reverse directions, the 44 Sc/ 44 Ti ratio from a primary column was significantly improved from 1038 ± 440 to 3557 ± 680 (Bq/Bq) when a secondary, replaceable, ZR resin cartridge was employed at the flow outlet. In vivo imaging and ex vivo distribution studies of the reversible modular generator for 44 ScCl 3 , [ 44 Sc]-citrate and [ 44 Sc]-NODAGA show that free 44 Sc remained in the circulation significantly longer than the chelated 44 Sc. The dose estimation of 44 ScCl 3 reveals that the radiation burden is 0.146 mSv/MBq for a 70 kg adult male and 0.179 mSv/MBq for a 57 kg adult female. Liver, spleen and heart wall will receive the highest absorbed dose: 0.524, 0.502, and 0.303 mGy/MBq, respectively, for the adult male. Conclusions: A clinical-scale 44 Ti/ 44 Sc generator system with a modular design was developed to supply 44 ScCl 3 in 0.05 M HCl, which is suitable for further radiolabeling and in vivo use. Our data demonstrated that free 44 ScCl 3 remained in the circulation for extended periods, which resulted in approximately 10 times greater radiation burden than stably chelated 44 Sc. Stable 44 Sc/ 47 Sc-complexation will be more favorable for in vivo use and for clinical utility.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation

Here, we present a supervised learning framework of training generative models for density estimation. Generative models, including generative adversarial networks (GANs), normalizing flows, and variational auto-encoders (VAEs), are usually considered as unsupervised learning models, because labeled data are usually unavailable for training. Despite the success of the generative models, there are several issues with the unsupervised training, e.g., requirement of reversible architectures, vanishing gradients, and training instability. To enable supervised learning in generative models, we utilize the score-based diffusion model to generate labeled data. Unlike existing diffusion models that train neural networks to learn the score function, we develop a training-free score estimation method. This approach uses mini-batch-based Monte Carlo estimators to directly approximate the score function at any spatial-temporal location in solving an ordinary differential equation (ODE), corresponding to the reverse-time stochastic differential equation (SDE). This approach can offer both high accuracy and substantial time savings in neural network training. Once the labeled data are generated, we can train a simple, fully connected neural network to learn the generative model in the supervised manner. Compared with existing normalizing flow models, our method does not require the use of reversible neural networks and avoids the computation of the Jacobian matrix. Compared with existing diffusion models, our method does not need to solve the reverse-time SDE to generate new samples. As a result, the sampling efficiency is significantly improved. We demonstrate the performance of our method by applying it to a set of 2D datasets as well as real data from the University of California Irvine (UCI) repository.

97 MATHEMATICS AND COMPUTING↗

Online Monitoring Technical Basis and Analysis Framework for Emergency Diesel Generators - Interim Report for FY 2013

The Light Water Reactor Sustainability program at Idaho National Laboratory is actively conducting research to develop and demonstrate online monitoring capabilities for active components in existing nuclear power plants. Idaho National Laboratory and the Electric Power Research Institute are working jointly to implement a pilot project to apply these capabilities to emergency diesel generators and generator step-up transformers. The Electric Power Research Institute Fleet-Wide Prognostic and Health Management Software Suite will be used to implement monitoring in conjunction with utility partners: Braidwood Generating Station (owned by Exelon Corporation) for emergency diesel generators, and Shearon Harris Nuclear Generating Station (owned by Duke Energy Progress) for generator step-up transformers. This report presents monitoring techniques, fault signatures, and diagnostic and prognostic models for emergency diesel generators. Emergency diesel generators provide backup power to the nuclear power plant, allowing operation of essential equipment such as pumps in the emergency core coolant system during catastrophic events, including loss of offsite power. Technical experts from Braidwood are assisting Idaho National Laboratory and Electric Power Research Institute in identifying critical faults and defining fault signatures associated with each fault. The resulting diagnostic models will be implemented in the Fleet-Wide Prognostic and Health Management Software Suite and tested using data from Braidwood. Parallel research on generator step-up transformers was summarized in an interim report during the fourth quarter of fiscal year 2012.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

New Generator Technology

New generator technology project is driven by the need to be able to remotely deploy generator technology where it is needed, when it is needed. Both the military and aid programs that provide assistance after disasters could use the ability to deploy energy generation that fits the needs of the situation. Currently, pre-specified generators are deployed, sometime more than half way around the world to provide electricity. Through our Phase-I to Phase III DARPA grant, we will provide a mechanism where a 3d print station and raw materials could be shipped to a deployment site and remotely deployed personnel. These remote personnel can collaborate with engineers at a home location where 3d print plans can be optimized for the remote purpose. The plans can then be sent electronically to the remote location for printing, much like NASA sent the plans for a socket wrench to the International Space Station for printing in . If multiple generators need to be deployed at different remote locations, within miles of each other the printer rig can be moved to print the generators where they are needed. 3d printing is growing in the field of manufacturing. 3d printing has matured to the point where many types of materials are now available for many types of manufacturing. Both magnetic and electrically conductive material materials have recently been developed which can now lead to 3d printing of engines and generators. Our project will provide a successful printer rig that can be remotely deployed, to print a generator design in the field as well as provide a process for deploying the printed generator as well. This Systems Engineering Management Plan(SEMP) will provide the planning required for a Phase I DARPA grant that may also include goals for Phase II and Phase II grants. The SEMP provides a proposed project schedule, references, system engineering processes, specialty engineering system deployment and product support sections. Each section will state how our company will provide the necessary services to make this project succeed.

3D printing, manufacturing, generator technology, ↗

MultiLoad-GAN: A GAN-Based Synthetic Load Group Generation Method Considering Spatial-Temporal Correlations

This paper presents a deep-learning framework, Multi-load Generative Adversarial Network (MultiLoad-GAN), for generating a group of synthetic load profiles (SLPs) simultaneously. The main contribution of MultiLoad-GAN is the capture of spatial-temporal correlations among a group of loads that are served by the same distribution transformer. This enables the generation of a large amount of correlated SLPs required for microgrid and distribution system studies. Here, the novelty and uniqueness of the MultiLoad-GAN framework are three-fold. First, to the best of our knowledge, this is the first method for generating a group of load profiles bearing realistic spatial- temporal correlations simultaneously. Second, two complementary realisticness metrics for evaluating generated load profiles are developed: computing statistics based on domain knowledge and comparing high-level features via a deep-learning classifier. Third, to tackle data scarcity, a novel iterative data augmentation mechanism is developed to generate training samples for enhancing the training of both the classifier and the MultiLoad-GAN model. Simulation results show that MultiLoad- GAN can generate more realistic load profiles than existing approaches, especially in group level characteristics. With little finetuning, MultiLoad-GAN can be readily extended to generate a group of load or PV profiles for a feeder or a service area.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Submersible Generator for Marine Hydrokinetics

A submersible generator was designed as a distinct and critical subassembly of marine hydrokinetics systems, specifically tidal and stream energy conversion. The generator is designed to work with both vertical and horizontal axis turbines. The final product is a high-pole-count, radial-flux, permanent magnet, rim mounted generator, initially rated at twenty kilowatts in a two-meter-per-second flow, and designed to leverage established and simple manufacturing processes. The generator was designed to work with a 3 meter by 7 meter Gorlov Helical Turbine or a marine hydrokinetic version of the FloDesign wind turbine. The team consisted of experienced motor/generator design engineers with cooperation from major US component suppliers (magnetics, coil winding and electrical steel laminations). Support for this effort was provided by Lucid Energy Technologies and FloDesign, Inc. The following tasks were completed: Identified the conditions and requirements for MHK generators. Defined a methodology for sizing and rating MHK systems. Selected an MHK generator topology and form factor. Completed electromechanical design of submersible generator capable of coupling to multiple turbine styles. Investigated MHK generator manufacturing requirements. Reviewed cost implications and financial viability. Completed final reporting and deliverables

13 HYDRO ENERGY↗

3D-Scaffold: A Deep Learning Framework to Generate 3D Coordinates of Drug-like Molecules with Desired Scaffolds

The prerequisite of therapeutic drug design is to identify novel molecules with desired biophysical and biochemical properties. Deep generative models have demonstrated their ability to find such molecules by exploring a huge chemical space efficiently. An effective way to obtain molecules with desired target properties is the preservation of critical scaffolds in the generation process. To this end, we propose a domain aware generative framework called 3D-Scaffold that takes 3D coordinates of a desired scaffold as an input and generates 3D coordinates of novel therapeutic candidates as an output while always preserving the desired scaffolds in generated structures. We show that our framework generates predominantly valid, unique, novel, and experimentally synthesizable molecules that have drug-like properties similar to the molecules in the training set. Using domain specific datasets, we generate covalent and non-covalent antiviral inhibitors. Therefore, to measure the success of our framework in generating therapeutic candidates, generated structures were subjected to high throughput virtual screening via docking simulations, which shows favorable interaction against SARS-CoV-2 main protease and non-structural protein endoribonuclease (NSP15) targets. Most importantly, our model performs well with relatively small volumes of training data and generalizes to new scaffolds, making it applicable to other domain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A comparative numerical analysis of linear and nonlinear aerodynamic sound generation by vortex disturbances in homentropic constant shear flows

Aerodynamic sound generation in shear flows is investigated in the light of the breakthrough in hydrodynamics stability theory in the 1990s, where generic phenomena of non-normal shear flow systems were understood. By applying the thereby emerged short-time/non-modal approach, the sole linear mechanism of wave generation by vortices in shear flows was captured [G. D. Chagelishvili, A. Tevzadze, G. Bodo, and S. S. Moiseev, “Linear mechanism of wave emergence from vortices in smooth shear flows,” Phys. Rev. Lett. 79, 3178-3181 (1997); B. F. Farrell and P. J. Ioannou, “Transient and asymptotic growth of two-dimensional perturbations in viscous compressible shear flow,” Phys. Fluids 12, 3021-3028 (2000); N. A. Bakas, “Mechanism underlying transient growth of planar perturbations in unbounded compressible shear flow,” J. Fluid Mech. 639, 479-507 (2009); and G. Favraud and V. Pagneux, “Superadiabatic evolution of acoustic and vorticity perturbations in Couette flow,” Phys. Rev. E 89, 033012 (2014)]. Its source is the non-normality induced linear mode-coupling, which becomes efficient at moderate Mach numbers that is defined for each perturbation harmonic as the ratio of the shear rate to its characteristic frequency. Based on the results by the non-modal approach, we investigate a two-dimensional homentropic constant shear flow and focus on the dynamical characteristics in the wavenumber plane. This allows to separate from each other the participants of the dynamical processes — vortex and wave modes — and to estimate the efficacy of the process of linear wave-generation. This process is analyzed and visualized on the example of a packet of vortex modes, localized in both, spectral and physical, planes. Further, by employing direct numerical simulations, the wave generation by chaotically distributed vortex modes is analyzed and the involved linear and nonlinear processes are identified. The generated acoustic field is anisotropic in the wavenumber plane, which results in highly directional linear sound radiation, whereas the nonlinearly generated waves are almost omni-directional. As part of this analysis, we compare the effectiveness of the linear and nonlinear mechanisms of wave generation within the range of validity of the rapid distortion theory and show the dominance of the linear aerodynamic sound generation. Finally, topological differences between the linear source term of the acoustic analogy equation and of the anisotropic non-normality induced linear mechanism of wave generation are found.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Generation of EM radiations using intense electron beam produced in vacuum

The results of a pulse power generator driving an axial virtual cathode oscillator are being presented in this paper as a source of high power microwave (HPM) radiations. The electron beam generator is also modified to attain the intense X-ray burst. The pulse power generator used for these applications is common and is having 10 ohms as its characteristic impedance with 50nS of pulse width. The peak charging voltage of the pulse forming line is 450 kV and hence 225 kV and 22.5 kA is peak voltage and peak current delivery capabilities respectively for the pulse power generator. The peak electrical power of the generator is 5GW for a matched load. The charging power supply for the pulse forming line consists of a high voltage generator made by pulse transformer and charging the pulse forming line in the first cycle of the charging pulse. To utilize the energy of the primary capacitive storage efficiently the pulse transformer is having 0.8 coupling coefficient between its primary and the secondary. The axial vircator chamber is evacuated to attain the vacuum of 2 x 10{sup -4} torr for the HPM application. In the case of modified electron beam chamber for the generation of X-rays the vacuum of same order is used. The pulse forming line is made using equal lengths of high voltage transmission lines, each having a length of 10 meters, connected in the parallel to give a net source impedance of 10 ohm. The pulse power generator can operate in repetitive mode and hence the HPM as well as X-rays may be generated in the repetitive burst. (author)

43 PARTICLE ACCELERATORS↗

An Operational Resilience Metric to Evaluate Inertia and Inverter-based Generation on the Grid

In an effort to reduce carbon emissions and curtail the effects of climate change there has been considerable effort to increase the penetration of inverter-based renewable energy sources. The adoption of renewable generation over conventional inertia-based generation sources is forming considerable challenges for the operation and stability of the power system. The power system has been designed around generation units characterized by high inertia and primary frequency response (PFR), allowing them to respond to disturbances such as faults or generators tripping off line. In contrast, the modern inverter-based assets are characterized by no contribution to inertia and they typically provide stochastic generation at their maximum output, thus having no contribution to PFR during low-frequency disturbance events. Because of this, inertia in power systems is reducing, resulting in a faster rate of frequency change after a disturbance occurs. As more inverter-based generation units are added to the grid it is important to understand the stability of the system and the size of disturbance a system is capable of withstanding. This paper presents a resilience metric that evaluates the maximum size of disturbance a systems can withstand based on the system inertia and the primary frequency control of inverter and inertia-based generation. The results are shown visually and are based on the real-time operation of generation units and their characteristics such as latency, ramp rates, and energy constraints. It is demonstrated that the real-time positioning or bias of the generating units has an effect of the size of disturbance that a system can withstand, i.e. its resilience. It is expected that this type of analysis can help operators increase the resilience of power systems in the future.

13 HYDRO ENERGY↗

An Investigation of Potential Intermittency Induced Outage Modes for Wind Generation

In a deterministic contingency analysis (DCA), renewable generation such as wind is modeled similar to a conventional generator. In the current practices of a probabilistic contingency analysis (PCA), the outage parameters for a renewable generator reflect only failures of its parts. Intermittency due to wind speed changes or cloud cover may cause renewable generation to ramp up or down within a short time period and, after the transient is finished, stay at a certain generation level before a new ramp starts. A fast ramp-down transient can last for some time and thus, have an effect similar to a failure or de-rated generation of a conventional generator. This paper investigates potential outage modes that are induced by the intermittency of renewable generation, as well as the modeling and parameterization of such outage modes in the PCA framework. Historical time-series wind generation data are used in this study to extract different types of transients and perform statistical analyses to obtain input data such that the intermittency induced outages (IIOs) can be included in PCA.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Disaggregating Customer-Level Behind-the-Meter PV Generation Using Smart Meter Data and Solar Exemplars

Customer-level rooftop photovoltaic (PV) has been widely integrated into distribution systems. In most cases, PVs are installed behind-the-meter (BTM), and only the net demand is recorded. Therefore, the native demand and PV generation are unknown to utilities. Separating native demand and solar generation from net demand is critical for improving grid-edge observability. In this paper, a novel approach is proposed for disaggregating customer-level BTM PV generation using low-resolution but widely available hourly smart meter data. The proposed approach exploits the strong correlation between monthly nocturnal and diurnal native demands and the high similarity among PV generation profiles. First, a joint probability density function (PDF) of monthly nocturnal and diurnal native demands is constructed for customers without PVs, using Gaussian mixture modeling (GMM). Deviation from the constructed PDF is utilized to probabilistically assess the monthly solar generation of customers with PVs. Then, to identify hourly BTM solar generation for these customers, their estimated monthly solar generation is decomposed into an hourly timescale; to do this, we have proposed a maximum likelihood estimation (MLE)-based technique that utilizes hourly typical solar exemplars. Leveraging the strong monthly native demand correlation and high PV generation similarity enhances our approach's robustness against the volatility of customers’ hourly load and enables highly-accurate disaggregation. Furthermore, the proposed approach has been verified using real native demand and PV generation data.

14 SOLAR ENERGY↗