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At least 1,639 records · Page 91

Experimental Evaluation of PV Inverter Anti-Islanding with Grid Support Functions in Multi-Inverter Island Scenarios

As PV and other DER systems are connected to the grid at increased penetration levels, island detection may become more challenging for two reasons: 1.) In islands containing many DERs, active inverter-based anti-islanding methods may have more difficulty detecting islands because each individual inverter's efforts to detect the island may be interfered with by the other inverters in the island. 2.) The increasing numbers of DERs are leading to new requirements that DERs ride through grid disturbances and even actively try to regulate grid voltage and frequency back towards nominal operating conditions. These new grid support requirements may directly or indirectly interfere with anti-islanding controls. This report describes a series of tests designed to examine the impacts of both grid support functions and multi-inverter islands on anti-islanding effectiveness. Crucially, the multi-inverter anti-islanding tests described in this report examine scenarios with multiple inverters connected to multiple different points on the grid. While this so-called 'solar subdivision' scenario has been examined to some extent through simulation, this is the first known work to test it using hardware inverters. This was accomplished through the use of power hardware-in-the-loop (PHIL) simulation, which allows the hardware inverters to be connected to a real-time transient simulation of an electric power system that can be easily reconfigured to test various distribution circuit scenarios. The anti-islanding test design was a modified version of the unintentional islanding test in IEEE Standard 1547.1, which creates a balanced, resonant island with the intent of creating a highly challenging condition for island detection. Three common, commercially available single-phase PV inverters from three different manufacturers were tested. The first part of this work examined each inverter individually using a series of pure hardware resistive-inductive-capacitive (RLC) resonant load based anti-islanding tests to determine the worst-case configuration of grid support functions for each inverter. A grid support function is a function an inverter performs to help stabilize the grid or drive the grid back towards its nominal operating point. The four grid support functions examined here were voltage ride-through, frequency ride-through, Volt-VAr control, and frequency-Watt control. The worst-case grid support configuration was defined as the configuration that led to the maximum island duration (or run-on time, ROT) out of 50 tests of each inverter. For each of the three inverters, it was observed that maximum ROT increased when voltage and frequency ride-through were activated. No conclusive evidence was found that Volt-VAr control or frequency-Watt control increased maximum ROT. Over all single-inverter test cases, the maximum ROT was 711 ms, well below the two-second limit currently imposed by IEEE Standard 1547-2003. A subsequent series of 244 experiments tested all three inverters simultaneously in the same island. These tests again used a procedure based on the IEEE 1547.1 unintentional islanding test to create a difficult-to-detect island condition. For these tests, which used the two worst-case grid support function configurations from the single-inverter tests, the inverters were connected to a variety of island circuit topologies designed to represent the variety of multiple-inverter islands that may occur on real distribution circuits. The interconnecting circuits and the resonant island load itself were represented in the real-time PHIL model. PHIL techniques similar to those employed here have been previously used and validated for anti-islanding tests, and the PHIL resonant load model used in this test was successfully validated by comparing single-inverter PHIL tests to conventional tests using an RLC load bank.

24 POWER TRANSMISSION AND DISTRIBUTION↗

End-Use Savings Shapes Measure Documentation: LED Lighting

Building on the successfully completed effort to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models over the past three years, the objective of this work is to produce national data sets that empower analysts working for federal, state, utility, city, and manufacturer stakeholders to answer a broad range of analysis questions. The goal of this work is to develop energy efficiency, electrification, and demand flexibility end-use load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) measures. "Measures" refers to energy efficiency variables that can be applied to buildings during modeling. An end-use savings shape is the difference in energy consumption between a baseline building and a building with an energy efficiency, electrification, or demand flexibility measure applied. It results in a timeseries profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each timestep. ComStock is a highly granular, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The baseline model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology and results of the baseline model are discussed in the final technical report of the End-Use Load Profiles project. This documentation focuses on a single end-use savings shape measure - LED lighting. The LED lighting measure replaces interior lights with LEDs where applicable. The measure resulted in 1.25 TBtu energy savings across the building stock, with the majority of savings occurring in retail and warehouse buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Field Test Report Neutron Scintillator Array Dry Storage Cask Scanner FY2024

During two weeks of Field Testing at the Idaho National Laboratory INTEC Cask Farm in July and August 2024, the LLNL Dry Storage Cask Scanner Array was lifted on top of an MC-10 dry storage fuel cask and operated to acquire neutron and gamma-ray data from the 24 fuel bundle positions. Neutron and gamma-ray data acquisition scans across the top of the cask of varying dwell times were performed July 15-18, 2024 and August 19-22, 2024 to evaluate the ability of the scanner data to reveal asymmetries in the fuel positions that reflect asymmetries in the MC-10 cask fuel bundle loading. The MC-10 cask 24 position fuel bundle loading at the INTEC Cask Farm is well documented, including the locations of six empty fuel bundle positions. This loading presents an opportunity to test the ability of the scanner system to detect diversion of spent fuel bundles as well as to validate the MC-10 cask MCNP modeling. The cask scanner array consists of six Stilbene crystal scintillator detectors and a linear actuator frame that moves the six detectors across the MC-10 dry storage cask to obtain data above each of the 24 fuel bundle positions. The detectors are connected to a pulse-shape discrimination data acquisition system capable of generating separate neutron and gamma-ray spectra for each detector and for each scan position. From the prior single detector Field Test in 2021 and iteration with MCNP modeling, the neutron and gamma-ray data were analyzed in multiple energy regions to identify an analysis method that would provide the strongest and most consistent signature of the asymmetric MC-10 cask fuel loading1 . From both the 2021 Field Test and the current Field Test results, the neutron capture gamma-ray count rate around 2.2 MeV provides the strongest signature of the asymmetric MC-10 cask fuel loading and has qualitative agreement with MCNP calculations. Counting all gamma-rays produces a similar signature. Neutrons emerging from the cask top are moderated and captured by the hydrogen in the polyethylene moderator and scintillator detector, producing a 2.2 MeV gamma ray which is seen in the scintillator gamma-ray spectrum. The count rate in the 2.2 MeV gamma-ray region is ~50 c/s, which is ~1000x higher than the ~0.05 n/s rate in the > 4MeV neutron region, and ~50x greater than the ~1 n/s rate in the neutrons > 500 keV region. Analysis of the 2.2 MeV neutron-capture Compton-scattered gamma-rays produces a statistically significant signature of the INTEC Cask Farm MC-10 asymmetric fuel loading. MCNP simulations indicate that the average neutron energy spectrum offers the potential to detect a large asymmetry from several missing bundles as well as individual missing fuel bundles. Testing this feature will require measurements on a cask with single missing elements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

3D–Integrated, Multi–Functional Carbon Fibers for Stable, High–Areal–Capacity Batteries

Increasing lithium-ion batteries' (LIBs) electrode areal capacity can boost energy density and lower manufacturing costs, but faces challenges in manufacturing, rate performance, and cycling stability. A conductive framework made of commercial micro-sized carbon fibers (Cfs) is presented that serves as a host for both the LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC 532) cathode and Cfs anode. The Cf framework has multiple functions that offer high electronic conductivity (270 mS cm –1 ), low tortuosity (1.7), low Li + diffusion resistance (22 Ω), and high thermal conductivity (200 W mK –1 ). Additionally, the Cf-integrated electrodes can have an extremely high mass loading of NMC 532 (70 mg cm –2 ) with a theoretical capacity of 14 mAh cm –2 . Thus, the practical full cells assembled with the Cfs-enabled electrodes exhibit an initial areal capacity of 4.1 mAh cm –2 and capacity retention of 90.4% at 500 cycles at a cycling rate of C/3, 1.5 mA cm –2 . Data collected from the operando isothermal microcalorimetry suggest that full cells utilizing the Cf anode experience less heat release from side reactions compared to cells utilizing a conventional graphite anode. Finally, this present approach is scalable and cost-effective and can fabricate practical LIBs that boast high areal capacity, rate performance, and a lengthy cycling lifetime.

25 ENERGY STORAGE↗

A practical extension of the recursive multi-fidelity model for the emulation of hole closure experiments

We report in regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three-dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi-fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi-fidelity model to employ low-fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization.

36 MATERIALS SCIENCE↗

Machine learning approaches for crystallographic classification from synthetic 2D X-ray diffraction data

Crystallographic structure identification is crucial for understanding material properties; however, current methodologies often depend on labor-intensive and time-consuming analyses of 2D X-ray diffraction (XRD) patterns. To address these limitations, this study employs synthetic 2D XRD patterns combined with deep learning (DL) techniques to enable automated and high-throughput classification of the seven crystal systems and 230 space groups. We introduce the novel Auto Diffraction Pipeline, designed to generate synthetic 2D XRD spot patterns from crystallographic information files under diverse conditions, including varying zone axes, atomic substitution, atomic depletion and mechanical loading. These conditions enhance the realism of synthetic data, mitigating the scarcity of experimental datasets and enabling the creation of large representative training sets. Convolutional neural networks were trained and validated on these synthetic datasets to classify crystallographic structures across multiple scenarios. Our results demonstrate that integrating synthetic 2D XRD patterns with DL facilitates rapid, accurate and automated crystallographic classification, promoting the wider adoption of data-driven approaches in materials science.

Shahnazari, Ayoub [Univ. of Rochester, NY (United ↗

Dynamic Shaping of Grid Response of Multi-Machine Multi-Inverter Systems Through Grid-Forming IBRs

We consider the problem of controlling the frequency response of weakly-coupled multi-machine multi-inverter low-inertia power systems via grid-forming inverter-based resources (IBRs). In contrast to existing methods, our approach relies on dividing the larger system into multiple strongly-coupled subsystems, without ignoring either the underlying network or approximating the subsystem response as an aggregate harmonic mean model. Rather, through a structured clustering and recursive dynamic shaping approach, the frequency response of the overall system to load perturbations is shaped appropriately. We demonstrate the proposed approach for a three-node triangular configuration and a small-scale radial network. Furthermore, previous synchronization analysis for heterogeneous systems requires the machines to satisfy certain proportionality property. In our approach, the effective transfer functions for each cluster can be tuned by the IBRs to satisfy such property, enabling us to apply the shaping control to systems with a wider range of heterogeneous machines.

frequency-shaping control↗

Distributed Load Shedding Application Architecture and Bi-Level Predictive Estimator Algorithm

Increasing penetrations of distributed renewables are decreasing the effectiveness of traditional decentralized under-frequency load shedding (UFLS) schemes. As more distribution circuits begin to back-feed the transmission system, operation of traditional UFLS may exacerbate frequency instability. This paper presents the conceptual framework for a data-rich environment to coordinate UFLS across multiple distribution providers based on the laminar coordination framework in order to ensure optimal adaptive setting of UFLS relays. Communication and control are enabled through a distributed implementation of the IEC 61968-1 Common Information Model message bus structure. In addition to the proposed architecture, a novel adaptive UFLS scheme informed by a bi-level state estimator to create optimal relay setpoints is introduced. Initial simulation results are presented for the IEEE 14-bus test system on scenarios leading to mis-operation of traditional UFLS.

Anderson, Alexander A.↗

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncer- tainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗

Real-Time Federated Cyber-Transmission-Distribution Testbed Architecture for the Resiliency Analysis

With the ongoing automation driven by the push toward the smart electric grid and the advancement in associated cyber infrastructure, the interaction between physical [electric transmission and distribution (T&D) systems], cyber (communication, automation, and control), and human (grid operators and decision-makers) is increasingly becoming more complex. This creates the requirement of analyzing the effect of the transmission system on the distribution system and vice versa with consideration of the additional complexity of the cyber infrastructure. Such an integrated testbed will also help with resiliency analysis, where resiliency refers to the ability of the system to continue serving energy to the critical loads even with limited extreme contingencies. Interaction of the physical power grid with the cyber layer can be effectively modeled using real-time (RT) simulator for developing and validating various operational and control algorithms. Testbeds using RT simulators with multiple capabilities have been developed at different institutions. Still, no single existing testbed can offer full scalability while simultaneously meeting high fidelity requirements for resiliency experimentation. Co-simulating federated testbed assets can provide a scalable experimentation platform that can be leveraged for verification and validation. In this article, an architecture is developed for federated cyber-physical testbed. A local federation with two real-time simulators is developed: real-time digital simulator (RTDS) and OPAL-RT have been interfaced using VILLAS framework for end-to-end testing. Also, a real-time linear predictor is developed and integrated here to address the communication latency impact on geographically allocated federated RT simulation. Finally, resiliency analysis tools are formulated and utilized for T&D systems. Finally as an illustrative use case, the resiliency of a T&D test system is simulated, and the results are analyzed. A 179-bus Western Electricity Coordinating Council (WECC) transmission system is developed using OPAL-RT/ HYPERSIM, and a modified IEEE 13 node feeder system is modeled in RTDS/RSCAD and interfaced for resiliency analysis.

42 ENGINEERING↗

Remote Off-grid Microgrid Design Support Tool (ROMDST) - An Optimal Design Support Tool for Remote, Resilient, and Reliable Microgrids Phase II - Final Report

The objective of the project is to develop an advanced optimization-based design support tool for AC or DC microgrids in remote locations, where utility grids may not be accessible. The mathematical model and the interface are being developed such that multiple design objectives and criteria/constraints can be easily enabled or disabled, to deliver a flexible tool relevant to a large, diverse user base, and to facilitate future feature developments. The new tool delivered by this project leverages the team’s extensive expertise in the development, testing, deployment, and commercialization of the state-of-the-art Distributed Energy Resources Customer Adoption Model (DER-CAM) – which is the foundation for the new tool. Phase I of the project leverages the microgrid design and decision support tool DER-CAM. Key Phase I developments include the following adaption to the DER-CAM model: a) AC or DC microgrid architectures, b) multiple economic objectives (e.g. single customer vs community vs utility perspective), c) constraints on fuel availability (e.g. total fuel available during outage periods), d) active and reactive power flow constraints for normal and N-1 contingency cases, e) component part load efficiencies (e.g. power electronic devices), and f) interactive data visualization capabilities (e.g. design topology elements). A component library including components’ default technical and economical characteristics was also developed. In Phase II, the project is focused on tool testing and validation, use for real-world microgrid designs, and outreach. Fully developing this tool will have the following impacts: 1) optimal off-grid microgrid designs that replace existing back of the envelope or non-optimal calculations, reducing capital costs and risk of microgrid deployment; 2) removing barriers to microgrid assessments by lowering microgrid soft costs, as the tool is freely usable; 3) reliable and resilient designs that reduce the cost of critical load shedding due to component outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Remote Off-grid Microgrid Design Support Tool (ROMDST) - An Optimal Design Support Tool for Remote, Resilient, and Reliable Microgrids (Phase II, Final Report)

The objective of the project is to develop an advanced optimization-based design support tool for AC or DC microgrids in remote locations, where utility grids may not be accessible. The mathematical model and the interface are being developed such that multiple design objectives and criteria/constraints can be easily enabled or disabled, to deliver a flexible tool relevant to a large, diverse user base, and to facilitate future feature developments. The new tool delivered by this project leverages the team’s extensive expertise in the development, testing, deployment, and commercialization of the state-of-the-art Distributed Energy Resources Customer Adoption Model (DER-CAM) – which is the foundation for the new tool. Phase I of the project leverages the microgrid design and decision support tool DER-CAM. Key Phase I developments include the following adaption to the DER-CAM model: a) AC or DC microgrid architectures, b) multiple economic objectives (e.g. single customer vs community vs utility perspective), c) constraints on fuel availability (e.g. total fuel available during outage periods), d) active and reactive power flow constraints for normal and N-1 contingency cases, e) component part load efficiencies (e.g. power electronic devices), and f) interactive data visualization capabilities (e.g. design topology elements). A component library including components’ default technical and economical characteristics was also developed. In Phase II, the project is focused on tool testing and validation, use for real-world microgrid designs, and outreach. Fully developing this tool will have the following impacts: 1) optimal off-grid microgrid designs that replace existing back of the envelope or non-optimal calculations, reducing capital costs and risk of microgrid deployment; 2) removing barriers to microgrid assessments by lowering microgrid soft costs, as the tool is freely usable; 3) reliable and resilient designs that reduce the cost of critical load shedding due to component outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Demonstration of Multi-Gamma Based Sensor Technology for As-Fired Coal Property Measurement

This project demonstrated the application of the use of an advanced multigamma attenuation (MGA) sensor to accurately and precisely measure coal properties at the point of injection into burners. Accurate and precise coal property information at the burner provides the opportunity to adjust burner parameters to better follow changing load condition, optimize flame stability, and decrease nitrogen oxide formation at each burner. In addition, coal property information at the burner will assist in managing slag flow behavior, fireside ash related deposition, corrosion, and erosion issues. The advantage of having multiple gamma emitters is that the atomic/elemental interaction with the gamma energy takes place at several energies and the resulting attenuation is dependent upon the atomic number of the atom/element encountered in the coal.

01 COAL, LIGNITE, AND PEAT↗

Solid Particle Number and Mass Emissions from Lean and Stoichiometric Gasoline Direct Injection Engine Operation

In this work, engine-out particle mass (PM) and particle number (PN) emissions were experimentally examined from a gasoline direct injection (GDI) engine operating in two lean combustion modes and one stoichiometric mode with a fuel of known properties. Ten steady state operating points, two constant speed load steps, and an engine cold start were examined. Results showed that solid particles emitted from the engine under steady state stoichiometric conditions had a uniquely broad size distribution that was relatively flat between the diameters of 10 and 100 nm. In most operating conditions, lean homogenous modes can achieve lower particle emissions than stoichiometric modes while improving engine thermal efficiency. Alternatively, lean stratified operating modes resulted in significantly higher PN and PM emissions than both lean homogeneous and stoichiometric modes with increased efficiency only at low engine load. Stoichiometric load steps showed minimal soot emissions while ash-mode emissions spike dramatically due to oil consumption caused by piston ring adjustment. Correlation of PN to PM for steady state stoichiometric cases was in good agreement with that reported from multiple prior studies for both diesel and stoichiometric GDI engines. However, the lean cases resulted in higher PN to PM ratios indicating more small particles per unit mass. High ash particle concentration, especially in lean operation illustrates that oil control is important for mitigating impacts on downstream gasoline particulate filters (GPF) from which ash particles are cannot be removed during filter regeneration. Further research is necessary to elucidate the origin and composition of sub-23 nm particles from GDI engines and their effect on aftertreatment technology if lean homogeneous modes are to be employed.

Bock, Noah↗

Transverse shear effects on the stress-intensity factor for a circumferentially cracked, specially orthotropic cylindrical shell

The problem of a cylindrical shell containing a circumferential through crack is considered by taking into account the effect of transverse shear deformations. The formulation is given for a specially orthotropic material within the confines of a linearized shallow shell theory. The particular theory used permits the consideration of all five boundary conditions regarding moment and stress resultants on the crack surface. Consequently, aside from multiplicative constants representing the stress intensity factors, the membrane and bending components of the asymptotic stress fields near the crack tip are found to be identical. The stress intensity factors are calculated separately for a cylinder under a uniform membrane load, and that under a uniform bending moment. Sample results showing the nature of the out-of-plane crack surface displacement and the effect of the Poisson's ratio are presented.

Delale, F.↗

High performance zinc anode for battery applications

An improved zinc anode for use in a high density rechargeable alkaline battery is disclosed. A process for making the zinc electrode comprises electrolytic loading of the zinc active material from a slightly acidic zinc nitrate solution into a substrate of nickel, copper or silver. The substrate comprises a sintered plaque having very fine pores, a high surface area, and 80-85 percent total initial porosity. The residual porosity after zinc loading is approximately 25-30%. The electrode of the present invention exhibits reduced zinc mobility, shape change and distortion, and demonstrates reduced dendrite buildup cycling of the battery. The disclosed battery is useful for applications requiring high energy density and multiple charge capability.

Casey, John E., Jr.↗

LH2 Tank Composite Coverplate Development and Flight Qualification for the X-33

In this paper, the development history for the first cryogenic pressurized fuel tank coverplates is presented along with a synopsis of the development strategy and technologies which led to success on this program. Coverplates are the large access panels used to access launch vehicle fuel tanks. These structures incorporate all of the requirements for a pressure vessel as well as the added requirement to mount all of the miscellaneous access points required for a fuel management system. The first composite coverplates to meet the requirements for flight qualification were developed on the X-33 program. The X-33 composite coverplates went from an open requirement to successful finished flight hardware with multiple unique configurations, complete with verification testing, in less than eighteen months. Besides the rapid development schedule, these components introduced several new technologies previously unseen in cryogenic composites including solutions to cryogenic shrinkage, self-supporting sealing surfaces, and highly loaded composite bosses with precision sealing interfaces. These components were proven to seal liquid hydrogen at cryogenic temperatures under maximum loading and pressure conditions.

Wright, Richard J.↗

Software for Allocating Resources in the Deep Space Network

TIGRAS 2.0 is a computer program designed to satisfy a need for improved means for analyzing the tracking demands of interplanetary space-flight missions upon the set of ground antenna resources of the Deep Space Network (DSN) and for allocating those resources. Written in Microsoft Visual C++, TIGRAS 2.0 provides a single rich graphical analysis environment for use by diverse DSN personnel, by connecting to various data sources (relational databases or files) based on the stages of the analyses being performed. Notable among the algorithms implemented by TIGRAS 2.0 are a DSN antenna-load-forecasting algorithm and a conflict-aware DSN schedule-generating algorithm. Computers running TIGRAS 2.0 can also be connected using SOAP/XML to a Web services server that provides analysis services via the World Wide Web. TIGRAS 2.0 supports multiple windows and multiple panes in each window for users to view and use information, all in the same environment, to eliminate repeated switching among various application programs and Web pages. TIGRAS 2.0 enables the use of multiple windows for various requirements, trajectory-based time intervals during which spacecraft are viewable, ground resources, forecasts, and schedules. Each window includes a time navigation pane, a selection pane, a graphical display pane, a list pane, and a statistics pane.

Wang, Yeou-Fang↗