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

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At least 253 records · Page 14

Grid Forming Inverter With Increased Short-Circuit Contribution to Address Inverter-Based Microgrid Protection Challenges

Substantial differences in fault levels between grid-tied and islanded modes is one of the primary challenges of microgrid protection. During grid-tied mode, the bulk grid provides significant short-circuit, while during islanded operation the short-circuit magnitude is small due to inverter-based resources limiting their current output close to nominal ratings. Consequently, conventional distribution protection strategies based on overcurrent cannot reliably protect microgrids when operating in islanded mode. Fuses and circuit breakers are particularly affected because of their inverse characteristics. Presently, the absence of affordable solutions for protecting microgrids in islanded mode leads to microgrids shutting down during electrical faults. The contribution of this article is two-fold. The first innovation proposes specific hardware modifications to grid-forming inverters to increase their short-circuit current during electrical faults. The second innovation introduces a novel control strategy designed to preserve control stability margins even when the grid-filter saturates, ensuring sinusoidal output currents under normal and fault conditions. Through experimental results, the inverter with the proposed modifications can provide more than three-times its nominal current during electrical faults. For the prototype testbed, this was sufficient to enable the use of traditional legacy overcurrent protection, achieving the fuse-to-relay and relay-to-relay minimum coordination time for the line-to-ground, line-to-line to ground, and three-phase electrical faults.

42 ENGINEERING↗

A Neural Network-Based Power Mismatch Elimination Strategy for Integrated Solar and ESS AC/DC Systems (MARS)

The multiport autonomous reconfigurable solar power plant (MARS) is a promising concept for the integration of photovoltaic (PV) and energy storage system (ESS) to the transmission ac grid and a high-voltage direct current (HVdc) link. The presence of PV and ESS in each arm of the MARS results in uneven distribution of active power among different submodules (SMs), thereby leading to unbalanced SM capacitor voltages and potentially compromising the system stability. Moreover, in the case of partial shadings, shaded PV SMs will suffer from decreased power injections causing power mismatch in the MARS system. To address this issue, a neural-network-based power mismatch elimination (NNPME) strategy is proposed in this article. The proposed NNPME strategy optimizes ESS usage and leverages both dc and ac circulating currents to facilitate power transfer among the SMs, arms, and phases of the MARS system. Simulation and control hardware-in-the-loop (cHIL) experiments demonstrate the effectiveness of the proposed NNPME strategy. Compared with the traditional approaches, the proposed NNPME strategy can significantly enhance system efficiency and ensure stable and continuous operation, even in the presence of uneven power distribution within the MARS system.

14 SOLAR ENERGY↗

Reaction Pathways over ZnZrO 2 -Based Catalysts and Catalytic Sorbents

Reactive capture and conversion (RCC) is a process intensification approach that integrates CO 2 capture and hydrogenation within a single unit, removing the CO 2 purification and storage steps of traditional process flow schemes. This alters the catalytic step from a traditional steady-state (SS) flow process to a transient capture and conversion cycle, which could lead to product distributions distinct from those observed in conventional SS experiments. Such differences are investigated in the combined capture and hydrogenation of carbon dioxide to methanol over a ZnZrO 2 catalyst and a ZnZrO 2 + NaNO 3 /Mg 3 AlO x catalytic sorbent (CS) using fixed-bed kinetic measurements, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and steady-state isotopic transient kinetic analysis-DRIFTS (SSITKA-DRIFTS). Under SS conditions, ZnZrO 2 produced methanol through sequential hydrogenation of HCOO* and CH 3 O* intermediates. On the contrary, CO was attributed primarily to CO 2 dissociation at oxygen vacancies, as supported by isotopic shifts and measured reaction orders. For the CS, isotopic switching experiments suggested that monodentate carbonate species (CO 3 2− , abbreviated as m-CO 3 2− ) act as active intermediates that can be hydrogenated to HCOO* and subsequently to CH 3 O. Under RCC conditions, in situ DRIFTS and isotopic experiments reveal that m-CO 3 2− species formed during the CO 2 capture step follow two competing routes upon H 2 exposure: (i) direct hydrogenation to methane on the sorbent domain or (ii) migration of m-CO 3 2− to the ZnZrO 2 domain, where they are hydrogenated to methanol through the HCOO pathway. Overall, RCC enables carbonate hydrogenation routes not observed under SS cofeed conditions. Thus, the reaction pathways and rates during RCC can be different from operation under conventional SS conditions, and the product distribution is determined here by competition between carbonate hydrogenation on sorbent sites and migration to ZnZrO 2 for methanol synthesis.

CCUS↗

Elastic dijet production in electron scattering on a longitudinally polarized proton at small x : A portal to orbital angular momentum distributions

We calculate the elastic production of dijets from electron collisions with a longitudinally polarized proton target at small values of the Bjorken x variable. Building on the pioneering proposals of Hatta [Gluon orbital angular momentum at small- x , .] and Bhattacharya [Signature of the gluon orbital angular momentum, ., Probing the quark orbital angular momentum at electron-ion colliders using exclusive π 0 production, ., and Exploring orbital angular momentum and spin-orbit correlation for gluons at the Electron-Ion Collider, .] for measuring the quark and gluon orbital angular momentum (OAM) distributions, our focus is on both the longitudinal double spin asymmetry (DSA) and longitudinal single spin asymmetry (SSA). We compute the numerators of these asymmetries in the small- x formalism of the light-cone operator treatment. Utilizing the small- x expressions for the OAM distributions derived earlier in Kovchegov and Manley [Orbital angular momentum at small x revisited, .], we demonstrate that the DSA provides a robust probe for both the quark and gluon OAM distributions within the proton. In contrast, we find that while the SSA is also sensitive to the OAM distributions, extraction of the latter from the SSA would require new developments in small- x theory and phenomenology, and is probably not feasible at this point in time. These findings highlight the potential of DSA measurements in elastic dijet production at the future Electron-Ion Collider to provide the first-ever direct access to the quark and gluon OAM distributions at small x , paving the way for new insights into the proton spin puzzle. Published by the American Physical Society 2025

Kovchegov, Yuri V. (ORCID:0000000169909173)↗

Modeling distributed energy resource aggregations in security constrained unit commitment and economic dispatch

The Federal Energy Regulatory Commission (FERC) recently issued Order 2222, which requires all wholesale electricity markets in the US to allow distributed energy resources (DERs) to participate in the market as aggregated resources. These DER aggregations may be composed of many individual resources that are offered and dispatched by the market as a single entity. We present here a model of a distributed energy resource aggregator (DERA) that is scheduled by a market operator’s security constrained unit commitment (SCUC) and security constrained economic dispatch (SCED). The DERA model includes constraints for battery energy storage systems (BESSs), demand response resources (DRRs), and a simple distributed energy resource (DER). This paper describes a model for each resource type and presents two methods for the DERA to generate market offer curves: a profit-maximizing optimization to compute cost curves and a direct cost algorithm to determine dispatch costs for each resource and combine into cost curves. Once all participating DERAs are scheduled in SCUC/SCED, the model is then modified to dispatch individual DERs to maximize profit or minimize schedule deviation of the DERAs. A simulation of a representative day illustrates the DERA offers, the scheduled generation, and the DERA dispatch. Findings show the potential for unavoidable schedule deviations due to internal DER constraints and due to economic incentives to deviate from the SCUC/SCED schedules. This highlights the importance of DERA offer construction on market efficiency and system reliability. Novel aspects of our approach include: (1) We consider the asymmetry of price incentives impacting DERAs from the wholesale market compared to those impacting consumers from the retail market, as imposed by current regulations and laws. (2) We model aggregate consumer response through statistically parameterizable utility functions rather than a potentially impractical approach of modeling each individual consumer. (3) We show how to use the DERA operational dispatch model to create offers into the wholesale electricity market. (4) We show how DERAs may fail to meet their scheduled dispatch because the market offer format may not permit them to fully express their operational features such as intertemporal costs and constraints to the market.

aggregations↗

Enabling DER visibility using a distributed dissemination network

The electrical grid is currently undergoing a series of rapid transformational changes that have resulted in the introduction of new actors and operational schemes that have fragmented the data and control planes. To help address the issue, this paper describes the implementation of a sensor-oriented, distributed data dissemination network that seeks to eliminate data silos. The implementation is based on the DGSS architecture previously described in [1]. The developed product seeks to facilitate the seamless integration of multi-operator, multi-origin, multi-domain sensor data by using a distributed systems approach. The proposed solution decouples the sensor’s data streams from the application-specific infrastructure and migrates them into a software-defined databus that can be configured to suit the end application’s demands. To further validate DGSS capabilities, a DER oriented use case has been developed.

Sensor Dissemination Networks, Enhanced DER visibi↗

Stability Analysis of Power Systems with High Penetration of State-of-the-Art Inverter Technologies

With the increasing level of inverter-based resources (IBRs) in modern power systems, this paper presents a small-signal stability analysis for power systems comprising synchronous generators (SGs) and IBRs. Four types of inverter controls are considered: two grid-following (GFL) controls, with or without grid support functions; droop-based grid-forming (GFM) controls; and virtual oscillator control-based GFM. We also analyze the impact of STATCOM and synchronous condensers on system stability to assess their role in the energy mix transition. With the small-signal dynamic behavior of the major technologies modeled, this paper provides stringent stability assessments using the IEEE 39-bus benchmark system modified to simulate future power systems. The exhaustive test cases allow for (a) assessing the impacts of different types and controls of generation and supplementary grid assets, as well as system inertia and line impedance on grid stability, and (b) elucidating pathways for the stabilization of IBR-dominated power systems. The analysis also indicates that future power systems can be stabilized with only a fraction of the total generation as voltage sources without SGs or significant system inertia if they are well distributed. This study provides insights into future power system operations with a high level of IBRs that can also be used for planning and operation studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Assessment of effective elastic constants of U-10Mo fuel: A multiscale modeling and homogenization study

The significant microstructural changes that U-Mo fuel undergoes during operation degrades its mechanical properties and structural integrity. Microstructural evolution entails the formation, evolution, and redistribution of porosity in conjunction with grain refinement. In the present paper, we employ numerical approaches to assess the impact of the various microstructural features—grains, nanoscale intragranular fission gas bubbles, and mesoscale intergranular voids—on the degradation of elastic constants. Phase-field microstructure models are combined with the asymptotic expansion homogenization technique in order to derive the effective elastic constants as a function of porosity and fission density. Here the results are verified and compared against theoretical bounds. Using this approach, elastic degradation in operating nuclear fuels can be quantified when the distributions of microstructural features are known.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Innovative laser-based methods for monitoring fuel retention in ITER

This paper addresses the challenge of tritium inventory management in ITER and future fusion reactors, highlighting the importance of accurate tritium measurement and its spatial distribution within the vacuum vessel. Given ITER’s operational constraints, especially the limit on tritium retention, precise measurement is essential for both safety and regulatory compliance. To tackle these questions, the paper presents the T-monitor diagnostic system developed by Forschungszentrum Jülich, which uses Laser-Induced Desorption (LID) in combination with Diagnostic Residual Gas Analysis (DRGA) to measure hydrogen isotope concentrations on the surface of divertor tiles. The system integrates a high-power laser, advanced optical components, and a Fast Scanning Mirror Unit (FSMU) for accurate laser spot positioning with rapid response. Designed to measure in situ tritium retention, the diagnostic provides high-resolution spatial mapping, vital for evaluating detritiation strategies. The laser heating process increases the divertor surface temperature to 1600 K within the laser spot, promoting hydrogen isotope desorption. Accurate measurements require the precise control of laser parameters, including pulse duration and spot size, with a target relative accuracy of 20%. The optical design includes both in-vessel and ex-vessel components, such as durable high-reflectivity mirrors made of gold and copper, selected not only for their infrared performance but also for their transmission of visible wavelengths for observation purposes. To protect optical components from contamination, a pneumatic shutter is used.

Hydrogen isotopes↗

Tailoring coherent beam combined laser pulse trains for high peak and average power applications

Laser systems based on coherent beam combination (CBC) that rely on tiled pupil architecture intrinsically carry digital capabilities independently applicable to all three essential characteristics of a laser pulse: amplitude, phase and polarization. Those capabilities allow the far-field energy distribution to be flexibly tailored in real time. Operation in the femtosecond regime at high repetition rates gives access to a wide range of applications requiring both high peak and average powers. We address the task of independent peak versus average power adjustment needed for applications seeking to decouple nonlinear phenomena associated with GW peak power from the thermal load inherent to kW average power operation. The technical solutions proposed are presented in the framework of the Ecole Polytechnique XCAN CBC laser platform (61 independent channels) with an emphasis on thermal management measures implemented to ensure its nominal operation.

47 OTHER INSTRUMENTATION↗

Visualizing degradation mechanisms in a gas-fed CO 2 reduction cell via operando X-ray tomography

We utilize operando X-ray computed tomography, coupled with real-time electrochemical analysis, to reveal the underlying failure mechanisms of membrane electrode assemblies (MEAs) for electrochemical CO 2 reduction (eCO 2 R). Through operando imaging, we can obtain unprecedented insights into the dynamic behavior of the MEA under different operating conditions, revealing critical changes in interface interactions, phase distribution, and structural integrity over time. Our findings identify phenomena giving rise to the transition from CO 2 R to the hydrogen evolution reaction (HER), as evidenced by shifts in cathode potential and CO 2 R selectivity. The formation of inhomogeneous precipitates at the gas diffusion electrode disrupts the CO 2 supply and reduces the active sites for eCO 2 R, resulting in a shift toward H2 production during low current density operation. Additionally, under high current density conditions, rapid water crossover up to the microporous layer/gas diffusion layer promotes the transition from CO 2 R to HER, further shifting cell potential toward anodic direction. Oscillating voltage conditions reveal the dissolution and regrowth of precipitates, providing direct visualization of the competing selectivity of CO 2 R and HER. This work offers new insight into the degradation mechanisms of MEAs, with implications for the design of more durable CO 2 R systems.

Lee, Sol A [California Institute of Technology (Ca↗

Polarized Photocathodes development for the EIC: Optimizing Spin and Quantum Efficiency

GaAs/GaAsP superlattice photocathodes play a critical role for producing highly polarized electron beams for the Electron-Ion Collider (EIC) at Brookhaven National Laboratory. The electron pre-injector for the EIC requires electron bunches with high bunch charge (1-2 nC) and high polarization, from GaAs-based superlattice photocathode. Herein, we have systematically investigated a range of GaAs/GaAsP superlattice photocathodes fabricated via molecular beam epitaxy (MBE) and metal-organic chemical vapor deposition (MOCVD). Through optimization of pre-cleaning procedures and surface doping conditions, we aim to identify the most promising photocathode configurations for future EIC operations. To enhance the quantum efficiency (QE), a Distributed Bragg Reflector structure is frequently incorporated beneath the superlattice. While this approach effectively increases QE, it also introduces additional complexities that can adversely influence spin polarization and the spectral response at specific laser wavelengths. This note provides an overview of superlattice GaAs development and outlines the EIC team’s ongoing efforts to address related challenges and advance high-performance photocathode development tailored for the EIC. Over five years of multi-institutional collaboration and measurements of about 50 SL-GaAs samples, our analysis presents statistics on samples exhibiting high ESP and high QE. It will help to set the initial ESP requirements for the EIC project.

43 PARTICLE ACCELERATORS↗

Equipment Self-Assessment Guide Checklist

This Equipment Self-Assessment Checklist is designed for asset owners and operators (AOOs) responsible for the deployment, operation, maintenance, or cybersecurity oversight of grid systems and digital energy technologies. It provides a structured inspection checklist for evaluating the security, integrity, and operational trustworthiness of equipment across substations, generation sites, distributed energy resources (DERs), and control environments.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

Uncertainty quantification and sensitivity analysis of a nuclear thermal propulsion reactor startup sequence

The research presented in this article describes progress in applying stochastic methods, uncertainty quantification, parametric studies, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated via the radiation transport code Griffin to simulate neutronics. Our goal is to develop a reduced-order (surrogate) model that can be rapidly sampled with perturbations to multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums (CDs), which is itself controlled by a hybrid proportional-integral-derivative (PID) controller actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time [Λ] and effective delayed neutron fraction [ β eff ] from a transient Griffin simulation executed via Griffin’s improved quasi-static solver to provide the kinetic parameters) as inputs to functions that control the CD rotation angle. By investigating numerous stochastic approaches, we developed a dual-purpose surrogate model of the NTP system, using polynomial regression in the Multiphysics Object-Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM). The trained model can be rapidly sampled while simultaneously perturbing various input parameters, such as coefficients on the PID control or temperature (directly affecting the neutron cross section). The surrogate model delivers accurate (within 5%) results at speeds orders of magnitude faster (minutes, not days of computational time) than the base model. Once the surrogate model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs as well as the effects of these inputs on the model output. For example, coefficients used in the PID control system may vary due to some type of physical interference, or uncertainty may exist in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters, and operational boundaries can be determined. The goal of this work is to support development of an advanced control system for operating CDs in a functioning NTP system. This work is a scoping study of the MOOSE STM.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Data collected using small uncrewed aircraft systems during the TRacking Aerosol Convection interactions ExpeRiment (TRACER)

Abstract. The main goal of the TRacking Aerosol Convection interactions ExpeRiment (TRACER) project was to further understand the role that regional circulations and aerosol loading play in the convective cloud life cycle across the greater Houston, Texas, area. To accomplish this goal, the United States Department of Energy and research partners collaborated to deploy atmospheric observing systems across the region. Cloud and precipitation radars, radiosondes, and air quality sensors captured atmospheric and cloud characteristics. A dense lower-atmospheric dataset was developed using ground-based remote sensors, a tethersonde, and uncrewed aerial systems (UASs). TRACER-UAS is a subproject that deployed two UAS platforms to gather high-resolution observations in the lower atmosphere between 1 June and 30 September 2022. The University of Oklahoma CopterSonde and the University of Colorado Boulder RAAVEN (Robust Autonomous Aerial Vehicle – Endurant Nimble) were flown at two coastal locations between the Gulf of Mexico and Houston. The University of Colorado Boulder RAAVEN gathered measurements of atmospheric thermodynamic state, winds and turbulence, and aerosol size distribution. Meanwhile, the University of Oklahoma CopterSonde system operated on a regular basis to resolve the vertical structure of the thermodynamic and kinematic state. Together, a complementary dataset of over 200 flight hours across 61 d was generated, and data from each platform proved to be in strong agreement. In this paper, the platforms and respective data collection and processing are described. The dataset described herein provides information on boundary layer evolution, the sea breeze circulation, conditions prior to and nearby deep convection, and the vertical structure and evolution of aerosols. The quality-controlled TRACER-UAS observations from the CopterSonde and RAAVEN can be found at https://doi.org/10.5439/1969004 (Lappin, 2023) and https://doi.org/10.5439/1985470 (de Boer, 2023), respectively.

54 ENVIRONMENTAL SCIENCES↗

Delivery-Risk-Aware Flexibility Scheduling and Dispatch for Aggregated Flexible Loads

Flexible loads like smart thermostats and water heaters can shift energy consumption and provide flexibility to the grid. However, this flexibility is dependent on occupant behavior and can lead to delivery risk, which causes utilities and grid operations to consider them as unreliable for purposes of grid operation. To date, they have not been well integrated into wholesale electricity markets or ancillary service offerings. With proper consideration of uncertainty and risk, these resources can be one of the most cost-effective sources of flexibility. This work uses stochastic optimization to quantify and bid flexibility from a fleet of flexible resources while considering their delivery risk.

DER↗

Uncertainty Quantification and Sensitivity Analysis of Non-Nuclear Advanced Controls Testbed Reactor Mockup

The research presented in this report describes our progress in applying stochastic methods and uncertainty quantification, parametric study, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated with Griffin, with the goal of developing a reduced order (surrogate) model which can be rapidly sampled while perturbing multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums, which are controlled by a hybrid proportional, integral and derivative (PID) controller, actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time and $\beta$ from a transient Griffin simulation executed with the improved quasi-static method to provide the kinetic parameters) as inputs to functions which control the CD rotation angle. Using a number of stochastic method approaches, we developed a dual purpose training-surrogate model of the NTP system using polynomial regression. The trained model can be rapidly sampled while simultaneously perturbing various input parameters of the model, such as coefficients on the PID control, or temperature (directly affect the neutron cross section). The surrogate model delivers accurate results orders-of-magnitude faster (minutes, not days) than the base model. Once the base model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs and their effect on the output. For example, coefficients used in the PID control system may vary due to some physical interference, or there may be uncertainty in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters and operational boundaries can be determined. The goal of this work is to support development of an advanced control system to operate CDs in a functioning NTP system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Electric Utility Distribution Costs: Scoping Study on Trends, Drivers, and Possible Response Strategies [Slides]

This scoping study synthesizes information that will help stakeholders understand the scope, scale, and drivers of recent increases in investor-owned utility (IOU) expenditures on local distribution power grids, while providing regulators and other decision-makers with potential strategies to keep electricity bills down. The study includes five distinct components. Drawing first on data from FERC Form 1, it summarizes key trends in past and recent IOU distribution costs. Next, through a review of a sample of distribution-system plans, it characterizes material drivers of planned distribution expenditures. Ultimately, regulators must approve cost recovery for IOU expenditures, including those for the distribution system. The study therefore also: examines trends in utility requests and regulatory approvals related to changes in retail rates and return on equity; identifies areas where utility shareholder and customer incentives may be misaligned; and develops a menu of options that state regulators might consider to optimize distribution system expenditures. Some of the key findings include: - IOU distribution spending at a national level has grown by 6%/yr since 2014 in real dollar terms, 4x faster than in the prior 20 years and consisting mostly of capital (not operating) expenditure. - On a per-kWh basis, increases in IOU distribution costs since 2014 represent over 30% of the overall national-average increase in retail electricity rates. - Regional spending growth has ranged from 2-8%/yr, with larger estimated rate impacts in CAISO, then NYISO & ISO-NE, and then the Southeast, MISO & PJM (see figure). - Some utilities are planning for significantly increased distribution system spending. Planned spending on managing the existing system (asset replacement, safety & reliability, and resilience are all important drivers) exceeds that for capacity expansion. - IOU rate increase requests ($18 billion in 2025) and public utility commission (PUC) approval levels (average of 64% of requested amounts from 2021-2025) have recently hit multi-decadal highs. - PUCs in New England and the Southeast have recently approved a greater fraction of rate requests (>75%, on average) than in ther regions, while PUCs in California and the Southeast have generally authorized higher equity returns than in other regions. - Regulators have many tools to tackle potential misalignments between utility and customer interests and, more specifically, to optimize and reduce distribution costs. Shorter-term options include those related to return on equity, capital structure, depreciation, trackers, construction work in progress, and securitization. Longer-term options include performance-based regulation and a wide variety of planning-related requirements. All options embed important tradeoffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗