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At least 1,063 records · Page 59

Cooperative Model Predictive Control Scheme for Dispersed Smart Inverters at the Grid Edge

Growing number of distributed energy resources (DERs) requires cutting-edge control schemes to ensure uniform but not identical involvement of DERs to address rapid fluctuations on voltage of the grid clusters. Designing such control schemes for a grid with high penetration of DERs connected various clusters is complex and depends on physical configuration of the clusters themselves. This paper proposes a two-layered cooperative model predictive control scheme for fleet of dispersed smart inverters connected to a three-phase grid cluster located at the edge of a grid cluster. The upper layer of the controller ensures cooperative operation of fleet of smart inverters to perform voltage regulation and address voltage fluctuations in the grid cluster; while the lower level controller guarantees each individual inverter obeys the dictated references for active/reactive powers by the upper layer controller. In addition, the proposed twolayered controller has low voltage ride through (LVRT) capability to support the grid clusters during voltage sags. By employing the proposed control approach, the smart inverters will inject desired active/reactive powers based on circumstance of the entire cluster while guaranteeing proper power curtailment among the generation units. The control scheme is verified by simulation.

Fard, Amin Y.↗

Robust Restoration From Cyber-Physical Attacks in Active Distribution Grids With Grid-Edge IBRs

The inverter-based resources (IBRs) have enabled the integration of renewable energy at the grid edge with enhanced control capabilities to support the reliable operation of power grids. Different control frameworks, such as hierarchical or distributed architecture, have been proposed with the expansion of cyber networks for real-time monitoring and control. This evolution of critical infrastructure into cyber-physical systems also brings more vulnerabilities for the broadened attack surfaces, and significantly increases the possibility of physical system failures or outages caused by cyberattacks. Among tremendous efforts in the defense-in-depth approach, it remains challenging to provide prompt detection and accurate location of attack entry points or paths. Therefore, the prevailing restoration framework may struggle to fully consider the cyber-physical interdependence, successfully isolate the compromised cyber and physical components, and safely recover the systems without the potential risks leading to secondary outages. This paper is motivated to develop a cyber-physical restoration framework for distribution grids to recover from cyber attacks by harnessing grid-edge IBRs. The framework is first built on the operational guidelines of IBRs considering the compromised cyber layer. Then, an ambiguity set is established to represent the uncertainty of attack scenarios and their possibility levels. Next, a distributionally robust optimization model is developed to provide the optimal load restoration strategy across all scenarios. The effectiveness of the proposed model is demonstrated through various use cases on the modified IEEE 13-node and 123-node test systems. Finally, simulation results demonstrate the effectiveness and advancement of developed post-attack restoration strategies.

Cybersecurity↗

An Edge-Cloud Integrated Solution for Buildings Demand Response Using Reinforcement Learning

Buildings, as major energy consumers, can provide great untapped demand response (DR) resources for grid services. However, their participation remains low in real-life. One major impediment for popularizing DR in buildings is the lack of cost-effective automation systems that can be widely adopted. Existing optimization-based smart building control algorithms suffer from high costs on both building-specific modeling and on-demand computing resources. To tackle these issues, this paper proposes a cost-effective edge-cloud integrated solution using reinforcement learning (RL). Beside RL’s ability to solve sequential optimal decision-making problems, its adaptability to easy-to-obtain building models and the off-line learning feature are likely to reduce the controller’s implementation cost. Using a surrogate building model learned automatically from building operation data, an RL agent learns an optimal control policy on cloud infrastructure, and the policy is then distributed to edge devices for execution. Simulation results demonstrate the control efficacy and the learning efficiency in buildings of different sizes. A preliminary cost analysis on a 4-zone commercial building shows the annual cost for optimal policy training is only 2.25% of the DR incentive received. Results of this study show a possible approach with higher return on investment for buildings to participate in DR programs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Smart Meter Pinging and Reading Through AMI Two-Way Communication Networks to Monitor Grid Edge Devices and DERs

Today’s power distribution system is changing to a power-electronics-enabled distribution system, especially with the increasing penetration of distributed energy resources (DERs). To monitor and manage those electronic devices and DERs at the grid edge, the advanced metering infrastructure (AMI) with two-way communications presents great potential. At present, extensive research explores the upstream communication from smart meters to electric utilities (e.g., meter reading) but few examine the downstream communication from the utilities to smart meters (e.g., meter pinging). This article discusses the AMI two-way communication and its recent industrial practice in the U.S., especially for applying the smart meter pinging functionality to monitor grid-edge devices and DERs. This paper then develops the two-way communication model and the network calculus method to quantify the impact of the two-way communication on the AMI network. In the end, the proposed method is validated with ns-3 simulation using the modified 13-node test feeder and real-world feeder systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reliable edge machine learning hardware for scientific applications

Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementations of ML algorithms: enabling bit-accurate functional simulations for performance validation in experimental software frameworks, verifying those ML models are robust under extreme quantization and pruning, and enabling ultra-fine-grained model inspection for efficient fault tolerance. We discuss approaches to developing and validating reliable algorithms at the scientific edge under such strict latency, resource, power, and area requirements in extreme experimental environments. We study metrics for developing robust algorithms, present preliminary results and mitigation strategies, and conclude with an outlook of these and future directions of research towards the longer-term goal of developing autonomous scientific experimentation methods for accelerated scientific discovery.

Baldi, Tommaso↗

Dynamics of filaments during the edge-localized mode crash on NSTX

Edge localized modes (ELMs) are routinely observed in H-mode plasma regimes of the National Spherical Torus Experiment (NSTX). Due to the explosive nature of the instability, only diagnostics with high temporal and spatial resolution could provide a detailed insight into the dynamics associated with the ELMs. Gas-puff imaging (GPI) at NSTX provides 2D measurements of the magnetic field aligned fluctuations (e.g. ELM filaments) in the scrape-off layer and the at the plasma edge with 2.5 us temporal and 10 mm optical resolution.A novel analysis technique was developed to estimate the frame-by-frame velocities and the spatial parameters of the dominant structures associated with the ELMs. The analysis was applied to single ELM events to characterize the ELM crash dynamics, and then extended to a database of 169 ELM events.Statistical analysis was performed in order to find the characterizing dynamics of the ELM crash. The results show that on average an ELM crash consists of a filament with a circular cross-section which is propelled outwards with a characterizing peak radial velocity of ~3.3 km/s. The radial velocity was found to be linearly dependent on the distance of the filament from the separatrix, which has never been seen before. The ELM filament is characterized by propagation in the ion-diamagnetic direction poloidally with a peak velocity of 11.4 km/s. The ELM crash lasts for approximately 100us until the radial propulsion settles back to the pre-ELM level. The experimental findings were compared with analytical theory. Two possible mechanisms were identified for explaining the observations: the curvature interchange model and the current-filament interaction model.

correlation↗

Source noise suppression in attosecond transient absorption spectroscopy by edge-pixel referencing

Attosecond transient absorption spectroscopy (ATAS) is used to observe photoexcited dynamics with outstanding time resolution. The main experimental challenge of this technique is that high-harmonic generation sources show significant instabilities, resulting in sub-par sensitivity when compared to other techniques. This paper proposes edge-pixel referencing as a means to suppress this noise. Two approaches are introduced: the first is deterministic and uses a correlation analysis, while the second relies on singular value decomposition. Each method is demonstrated and quantified on a noisy measurement taken on WS 2 and results in a fivefold increase in sensitivity. The combination of the two methods ensures the fidelity of the procedure and can be implemented on live data collection but also on existing datasets. The results show that edge-referencing methods bring the sensitivity of ATAS near the detector noise floor. An implementation of the post-processing code is provided to the reader.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bragg edge imaging (BEI) of B12W and M8N socket sections of the Arecibo telescope

From neutron user principal investigator: We kindly request the public release of three neutron imaging datasets through ONCat. All datasets were collected from two forensic specimens, B12W and M8N, sectioned from zinc-filled steel-wire sockets recovered from the collapsed Arecibo Telescope. The dataset titled “Neutron radiographs of B12W and M8N socket sections of the Arecibo telescope” contains normalized two-dimensional (2D) neutron radiographs of the specimens, showing the geometry and spatial distribution of the steel wires embedded within the zinc matrix, as well as internal features such as voids and cracks. The dataset titled “Neutron computed tomography of B12W and M8N socket sections of the Arecibo telescope” contains normalized 2D neutron projection images acquired over a range of specimen rotation angles for one selected region of each specimen. These projection images were used to reconstruct three-dimensional (3D) tomographic volumes that reveal the embedded-wire geometry and internal defects. The dataset titled “Bragg edge imaging (BEI) of B12W and M8N socket sections of the Arecibo telescope” contains six time-of-flight (TOF) neutron imaging datasets, three from each specimen, acquired at regions of interest selected based on the radiographs. The spatially resolved 2D TOF images show the zinc matrix and embedded steel wires, and the wavelength-dependent neutron transmission data were used to characterize crystallographic texture within the zinc. All components and their condition are in the public domain as they are the property of the National Science Foundation (NSF). The neutron imaging data, part geometries, and detailed forensic information have been widely published in the Arecibo Telescope Collapse Forensic Report by Thornton Tomasetti Engineers and others (NASA report and NASEM report).

Bilheux, Hassina↗

Data from: "Moisture rivals temperature in limiting photosynthesis by trees establishing beyond their cold-edge range limit under ambient and warmed conditions"

This archive contains data files that were used to draw conclusions in “Moisture rivals temperature in limiting photosynthesis by trees establishing beyond their cold-edge range limit under ambient and warmed conditions”, by Moyes et al., 2015. All field research was completed in common garden plots set up as part of the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA.There are two main data file formats in this archive: comma-separated values (.csv), and Microsoft Excel (.xls and .xlsx). .xlsx files can be read using Microsoft Excel and Google Sheets, and .csv files can be read using any simple text editor program, such as TextEdit (Mac) and Notepad (Windows). This .pdf data user’s guide can be read using Adobe Acrobat Reader, or any other compatible software. Seedling photographs and their corresponding leaf area-processed images are available in .jpg/.JPG image format, and can be opened using Preview (Mac) and Photos (Windows). To provide additional spatial context, two types of geospatial files are also published in this data package: ESRI shapefiles (.shp) and .kml files. Shapefiles are compatible with any GIS software able to read the file type (such as QGIS or ESRI’s ArcGIS suite), and .kml files can be opened with Google Earth or Google Maps. Figures 3 and 4 in the publication contain data from Moyes et al. 2013. This publication is cited in the References section in this archive, and data files can be accessed via the Alpine Treeline Warming Experiment project portal on ESS-DIVE. ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Climate change is altering plant species distributions globally, and warming is expected to promote uphill shifts in mountain trees. However, at many cold-edge range limits, such as alpine treelines in the western United States, tree establishment may be colimited by low temperature and low moisture, making recruitment patterns with warming difficult to predict.- We measured response functions linking carbon (C) assimilation and temperature- and moisture-related microclimatic factors for limber pine (Pinus flexilis) seedlings growing in a heating × watering experiment within and above the alpine treeline. We then extrapolated these response functions using observed microclimate conditions to estimate the net effects of warming and associated soil drying on C assimilation across an entire growing season.- Moisture and temperature limitations were each estimated to reduce potential growing season C gain from a theoretical upper limit by 15–30% (c. 50% combined). Warming above current treeline conditions provided relatively little benefit to modeled net assimilation, whereas assimilation was sensitive to either wetter or drier conditions.- Summer precipitation may be at least as important as temperature in constraining C gain by establishing subalpine trees at and above current alpine treelines as seasonally dry subalpine and alpine ecosystems continue to warm.

54 ENVIRONMENTAL SCIENCES↗

Two lectures on Yang-Lee edge singularity and analytic structure of QCD equation of state

These lecture notes, prepared for the 2024 XQCD PhD, provide an introduction to the analytic structure of an equation of state near a second-order phase transition and its most prominent landmark: the Yang-Lee edge singularity. In addition to discussing general properties, the notes review recent theoretical progress in locating the QCD critical point by tracking the trajectory of the Yang-Lee edge singularity.

Skokov, Vladimir (ORCID:0000000176191796)↗

Summary of 2020 edge-plasma modeling for FNSFand plans for 2021

This year, following the study of liquid-wall options, our edge-plasma modeling has returned to analyzing issues associated with a solid tungsten-wall, Fusion Nuclear Science Facility (FNSF)-size device, primarily using the 2D UEDGE plasma/neutral transport code. The focus is to predict plasma/neutral heat and particle fluxes to various wall components and determine the concentration of injected and wall-sputtered impurities that reach the core plasma region. Our models have been advanced in a number of areas compared to the initial modeling done in the 2017 timeframe: this year we include each individual charge-state of impurity ions instead of assuming a fixed concentration of impurities relative to the deuterium-tritium (DT) fuel plasma, including the interaction between inner and outer divertor legs. Here edge fueling of the impurity and pumping in the private-flux region is incorporated. Increasingly detailed atomic-physics rate files for impurity radiation have been compared, as well as the role of molecules. The impact of spatial variation of the turbulence-driven radial plasma transport is considered to contribute to the understanding of the heat-flux-limit effects of choosing a double-null or single-null divertor configuration. Detailed plasma/neutral wall fluxes, densities, and temperatures have been provided to the ERO group for their more detailed studies of wall sputtering and near-surface impurity transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Soft X-ray measurements of transport and MHD activity in the core and edge NSTX plasma (Final Technical Report)

A comprehensive suite of innovative diagnostic instrumentation and techniques has been developed by the Johns Hopkins collaboration for measurements of transport and MHD activity in the core and edge of the National Spherical Torus Experiment (NSTX) at the Princeton Plasma Physics Laboratory (PPPL). These include ultrafast multi-energy poloidal soft X-ray arrays, high spatial resolution multi-energy tangential soft X-ray arrays, high spectral resolution transmission grating imaging VUV spectrometers and ultrafast bolometric arrays, which measure over a broad range of spatial, spectral, and temporal scales the emission from ohmic, RF, and beam driven NSTX plasmas. The instrumentation was designed to fulfill the specific measurement needs of the Spherical Torus (ST) magnetic fusion concept and is accompanied by a comprehensive set of numerical tools for data analysis and modeling, aimed at determining as many as possible plasma parameters and at extracting as much as possible physics information from NSTX experiments. The Johns Hopkins diagnostics have been and continue to be instrumental for essentially all the NSTX experiments. In addition, our own research and experiments using these diagnostics has led over the years to fundamental conclusions for the ST fusion physics, such as the establishment of near neoclassical impurity transport in the NSTX core and edge plasma, and the critical role of the Global Alfven Eigenmode (GAE) MHD activity for the ST core electron thermal transport. The Johns Hopkins Diagnostics continue to be operational on the upgraded NSTX-U and will provide key plasma information in its upcoming high field, current and power experimental campaigns. The present report summarizes the main technical characteristics and measurement capabilities of the diagnostic instrumentation and methods developed within our research and describes a key physics result achieved during this research. Success in our research was made possible also by the excellent support and cooperation of the NSTX research team and of PPPL researchers, who are warmly acknowledged here.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Eddy Current Power Dissipation at the Edge of a Thin Conductive Layer

A method used to solve the problem of water waves on a sloping beach is applied to a thin conducting half plane described by a thin layer impedance boundary condition. The solution for the electric field behavior near the edge is obtained and a simple fit for this behavior is given. This field is used to determine the correction to the impedance per unit length of a conductor due to a sharp edge. The results are applied to the strip conductor. The final appendix also discusses the solution to the dual-sided (impedance surface & perfect conductor surface) half plane problem.

42 ENGINEERING↗

Application of Hybrid K-Edge Densitometry in Reprocessing Facilities

During reprocessing operations, accurately determining the elemental concentrations of uranium and plutonium is critical for nuclear security. Reprocessing facilities processes hundreds of tons of nuclear material annually, requiring accurate measurements to ensure effective nuclear material control and accountability. Hybrid K-edge densitometry (HKED) system combines K-edge absorption densitometry with x-ray fluorescence to measure actinide elemental concentrations with a low uncertainty. This system uses high-purity germanium gamma-ray detectors and advanced signal processing equipment to detect x-ray accurately. This document provides guidance on how to achieve effective performance from an HKED system for measuring uranium and plutonium concentrations in reprocessing facilities. It includes best practices for the setup and operation of an HKED system, while highlighting factors influencing uncertainties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Leading Edge Erosion Classification System

The leading edge erosion of wind turbine blades is a common issue that can have a range of implications for the operation and maintenance of the turbine. A variety of methods have attempted to determine the severity of erosion damage, applied in different academic, testing and in-situ settings. This paper describes the current state of the art in categorization, and the individual drivers in assessment. From this foundation, the IEA Wind Task 46 WP3 group collated key considerations from the process of categorizing erosion damage and a proposed erosion classification system was put forward. Trial assessments were performed using the initial system, which led to adjustments to the original proposition. The refined system defines discrete severity levels that concern the wind turbine blade: (1) Visual Condition (concerning blades with/without leading edge protection); (2) Mass Loss; (3) Aerodynamic Performance; and (4) Structural Integrity. The classification system presented is not intended to be a fixed entity. The Task 46 group has already identified specific challenges and opportunities that are applicable to individual use and the overall wind energy industry. The intention is for the system to evolve as improvements are identified, technology improves, and work progresses through other Task 46 activities. Several considerations and recommendations are discussed that could be applicable for future implementation of the system.

17 WIND ENERGY↗

Development of an L-Edge X-ray Absorbance Spectrometer for Monitoring Dissolver Solutions in H-Canyon

Savannah River National Laboratory has developed a monitor to measure plutonium and uranium concentrations in solutions of dissolved nuclear fuel. The monitor will be installed in the sample aisle location for the 6.3D Dissolver in the Savannah River Site’s H-Canyon and used in support of the electrolytic dissolution such as Fast Critical Assembly fuel. The monitor is based on the atomic absorbance of x-rays. Elements are differentiated by the appearance of absorbance features at specific energies of the x-ray spectrum that correspond to L-edge transitions of inner core electrons. Hence, the technique is called L-Edge X-Ray Absorbance Spectroscopy (L-XRAS). The technique is suitable for nuclear fuel processing due to its relative insensitivity to other components of the dissolver solution, such as nitric acid, transition metals (Fe, Cr, Ni, Mn) such as those from stainless steel, particulates, and catalysts and additives. The instrumentation consists of a commercially available x-ray source and detector, a sample cell designed to interface with the airlift sampler associated with H-Canyon Tank 6.3D, and a stainless steel enclosure. SRNL wrote instrument control software and developed chemometric models to interpret x-ray intensity spectra and estimate analyte concentrations and uncertainties in real time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Architecting the Grid Edge: Ensuring Reliability and Resilience

Changes in technology, customer expectations, and business and regulatory environments are rapidly evolving causing fundamental changes in the nation’s electrical infrastructure. Nowhere is this more apparent that at the “grid edge”, where there is an increasing number of new devices and systems, as well as complex new interactions between them. This is leading to the traditional relationship between the end-use customers and their utilities being expanded by an increasing number of stakeholders, each with their own operational and financial objectives, governed by regulatory policy. While there are concerns about the rapidly increasing complexity negatively impacting reliable and resilience of the electrical infrastructure, these changes are also bringing new resources and opportunities that hold great potential if they can be properly coordinated. This white paper outlines the considerations for the coordination of multi-stakeholder objectives with electric utility requirements using the concept of grid services. Describing a framework that enables new stakeholders to achieve their local technical and economic objectives, while simultaneously delivering operational benefits to the electrical infrastructure. The concepts of grid architecture are presented as a tool to evaluate how stakeholders might participate in, and benefit from, services, and how utilities can make decision on the reliance on services to ensure reliability and resilience, translating abstract concepts into actionable information for utilities and grid edge stakeholders. The end result of proper coordination, informed by grid architecture, will be a range of new devices and systems, operated by new stakeholders, achieving their local objectives while also increasing the reliability, resilience, security, and affordability of the nation’s critical electrical infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Architecting the Grid Edge: Ensuring Reliability and Resilience

Changes in technology, customer expectations, and business and regulatory environments are rapidly evolving causing fundamental changes in the nation’s electrical infrastructure. Nowhere is this more apparent that at the “grid edge”, where there is an increasing number of new devices and systems, as well as complex new interactions between them. This is leading to the traditional relationship between the end-use customers and their utilities being expanded by an increasing number of stakeholders, each with their own operational and financial objectives, governed by regulatory policy. While there are concerns about the rapidly increasing complexity negatively impacting reliable and resilience of the electrical infrastructure, these changes are also bringing new resources and opportunities that hold great potential if they can be properly coordinated. This white paper outlines the considerations for the coordination of multi-stakeholder objectives with electric utility requirements using the concept of grid services. Describing a framework that enables new stakeholders to achieve their local technical and economic objectives, while simultaneously delivering operational benefits to the electrical infrastructure. The concepts of grid architecture are presented as a tool to evaluate how stakeholders might participate in, and benefit from, services, and how utilities can make decision on the reliance on services to ensure reliability and resilience, translating abstract concepts into actionable information for utilities and grid edge stakeholders. The end result of proper coordination, informed by grid architecture, will be a range of new devices and systems, operated by new stakeholders, achieving their local objectives while also increasing the reliability, resilience, security, and affordability of the nation’s critical electrical infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗