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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 505 records · Page 28
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DOE OSTI2025

Enhanced Power Grid Maintenance Planning and Quantum-Inspired Combinatorial Prospects

Efficient and reliable scheduling of maintenance for power generation and transmission infrastructure is essential for minimizing operational costs and ensuring grid stability. This paper introduces an integrated optimization framework for coordinated maintenance scheduling of generators and transmission lines under resource and reliability constraints. The model minimizes a composite cost function including maintenance and generation costs, as well as penalties for delayed maintenance, while satisfying N−1 security constraints, operational limits, and crew availability. Case studies on the IEEE 300-bus test system demonstrate the effectiveness of the proposed approach in producing feasible and cost-effective maintenance schedules. To address scalability and combinatorial complexity, the model is mapped into a Quadratic Unconstrained Binary Optimization (QUBO) problem, enabling exploration of solution approaches based on Quantum Imaginary Time Evolution (QITE). While the QUBO reformulation provides a foundation for future quantum-inspired optimization, this study focuses primarily on the development and demonstration of the classical optimization framework and illustrates the potential applicability of QITE in large-scale maintenance scheduling.

Chen, Yang [ORNL] (ORCID:0000000271693874)↗
DOE OSTI2025

Data efficiency assessment of generative adversarial networks in energy applications

This study investigates the data requirements of generative artificial intelligence (AI), particularly generative adversarial networks (GANs), for reliable data augmentation in energy applications. Generative AI, though seen as a solution to data limitations, requires substantial data to learn meaningful distributions—a challenge often overlooked. This study addresses the challenge through synthetic data generation for critical heat flux (CHF) and power grid demand, focusing on renewable and nuclear energy. Two variants of GAN employed are conditional GAN (cGAN) and Wasserstein GAN (wGAN). Our findings include the strong dependency of GAN on data size, with performance declining on smaller datasets and varying performance when generalizing to unseen experiments. Mass flux and heated length significantly influence CHF predictions. wGAN is more robust to feature exclusion, making it suitable for constrained synthetic data generation. In energy demand forecasting, wGAN performed well for solar, wind, and load predictions. Longer lookback hours and larger datasets improved predictions, especially for load power. Seasonal variations posed challenges, with wGAN achieving a relatively high error of Root Mean Squared Error (RMSE) of 0.32 for load power prediction, compared to RMSE of 0.07 under same-season conditions. Feature exclusions impacted cGAN the most, while wGAN showed greater robustness. This study concludes that, while generative AI is effective for data augmentation, it requires substantial data and careful training to generate realistic synthetic data and generalize to new experiments in engineering applications.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A product data network to enable faster, easier, and better planning of building envelopes

The building envelopes contributes significantly to the energy-efficiency of the building. Building performance simulation has made it possible to compare façade technologies regarding energy demand, daylighting, thermal and visual comfort in detail. Planners, such as architects and engineers, need experience to find product data with the right quality and level of detail, and to process the data to fit the calculation and the application. In the available time, planners can compare only a limited number of products, which means that better solutions could go unnoticed. This paper presents a new concept for making product data easily accessible for building façade planning. The concept consists of a network of databases for the efficient exchange and use of optical and calorimetric data of glazing units, shading devices, and combinations of both. The paper presents the research questions, an analysis of the current challenges, six design goals for the product data network and its implementation together with a discussion. Many product data sources can be connected to many planning software applications via the specified application programming interface. When planning software connects to the product data network, the planning of building envelopes can be much faster because planners do not need to spend so much time to search and process product data manually. The planning of building envelopes can also become much easier, especially for planners with limited experience. They do not need to understand all the details about which data fits which calculation if the software company implements this. The planning of building envelopes can become much more reliable when software companies validate their use of the product data network, because the current manual process is prone to errors. The planning of building envelopes can also improve because more products can be compared in the available time, allowing better solutions to be found.

Maurer, Christoph↗
DOE OSTI2025

Durability Research Is Pivotal for Perovskite Photovoltaics

Metal halide perovskite solar cells have shown promising power conversion efficiencies, but commercialization requires that decent durability is also demonstrated. Under normal operation, solar cells are subject to a complex combination of stressors, such as visible light, ultraviolet light, heat, humidity, mechanical stress and electric potential, which complicates the understanding of failure mechanisms. Existing stress tests do not act as a time machine. In new materials systems such as perovskite photovoltaics, the tests have no known relationship to field service. In this Perspective we recommend following a durability learning cycle that interleaves photovoltaic module engineering with field testing; accelerated testing; and preconditioning and performance engineering. We advocate for field testing to demonstrate real-world performance and identify field-relevant failure modes, and urge the community to develop accelerated and qualification tests that account for device metastability, variations in material composition and different/various processing methods. In conclusion, these practices are more difficult, but more important, than the simple pursuit of higher initial efficiencies.

14 SOLAR ENERGY↗
DOE OSTI2025

Navigating the Noise: Bringing Clarity to ML Parameterization Design With O $\boldsymbol{\mathcal{O}}$(100) Ensembles

Abstract Machine‐learning (ML) parameterizations of subgrid processes (here of turbulence, convection, and radiation) may one day replace conventional parameterizations by emulating high‐resolution physics without the cost of explicit simulation. However, uncertainty about the relationship between offline and online performance (i.e., when integrated with a large‐scale general circulation model) hinders their development. Much of this uncertainty stems from limited sampling of the noisy, emergent effects of upstream ML design decisions on downstream online hybrid simulation. Our work rectifies the sampling issue via the construction of a semi‐automated, end‐to‐end pipeline for size ensembles of hybrid simulations, revealing important nuances in how systematic reductions in offline error manifest in changes to online error and online stability. For example, removing dropout and switching from a Mean Squared Error to a Mean Absolute Error loss both reduce offline error, but they have opposite effects on online error and online stability. Other design decisions, like incorporating memory, converting moisture input from specific humidity to relative humidity, using batch normalization, and training on multiple climates do not come with any such compromises. Finally, we show that ensemble sizes of may be necessary to reliably detect causally relevant differences online. By enabling rapid online experimentation at scale, we can empirically settle debates regarding subgrid ML parameterization design that would have otherwise remained unresolved in the noise.

Lin, Jerry [Department of Earth System Sciences Un↗
DOE OSTI2025

Facets of hydro power and future trends in a Nordic Context

Hydropower technologies bolster high penetration of variable renewable energies (VREs) in the net zero emissions scenarios. Nevertheless, there are various challenges to meeting the ambitious goal, such as stability, reliability, resiliency, security, lack of reactive power, voltage support and inertia, large-scale storage deployment and coordination, interconnectedness, demand-side response, higher thermal cycles with increased start/stops, and inadequate Levelized Cost of Energy (LCOE) for system-wise VRE integration and profitability. This survey conducts a bottom-up analysis to unveil the opportunities to utilize hydropower facilities and disentangle the nested problem for intertwining design features, control algorithms, operation, optimization approaches, incentives, services, and market mechanisms using a three-pillar framework perspective: grid owners, power producers, and machine designers. The survey identified emerging trends in real-time and capacity markets, flexible power systems, and enhanced grid capabilities, including advanced voltage support and updated grid codes. These developments present significant opportunities for hydropower, such as achieving super-flexibility through hybridization, expanded reactive power capabilities, and advanced operational modes like a synchronous condenser and power adequator functionalities. These opportunities require novel design philosophies — including new winding, stator, and rotor configurations, optimized ventilation, and active cooling systems — to enhance performance under stressed grid and climate conditions. Finally, integrating climate and energy models for multi-basin optimization with finer spatial and temporal granularity enhances the planning accuracy for water management of hydropower while addressing environmental challenges. The review delivers helpful prospective suggestions and tools that would serve researchers, power engineers, and stakeholders in making decisions about hydropower technologies and services in 2050 and beyond.

13 HYDRO ENERGY↗
DOE OSTI2026

Deriving reliable nucleation rates from metadynamics simulations: Application to Yukawa fluids

In order to solidify the usefulness of metadynamics in studying nucleation of crystals from supercooled liquids, this work provides a specific procedure to calculate nucleation free energy barriers. After a pedagogical review of the important elements of classical nucleation theory and how metadynamics is used to find nucleation free energy barriers, we explain the benefits of local collective variables over more common global collective variables. We show how a metadynamics free energy barrier must be carefully post-processed so that classical nucleation theory can be applied to calculate nucleation rates. We apply our procedure to a Yukawa plasma and show that a particular physically motivated fit to metadynamics data reproduces low-temperature reference data, justifying the usefulness of metadynamics to predict nucleation rates.

42 ENGINEERING↗
DOE OSTI2025

Encrypted Control Using Modified Learning With Errors-based Schemes

Cyber-physical systems (CPSs) require reliable, safe, and secure control of critical infrastructure, combining computational and networking capabilities, which heighten the risk of cyber attacks. These attacks can disrupt the physical process, causing unforeseen consequences. One solution is the use of fully homomorphic encryption (FHE) to protect the control loop, allowing for secure computations and communications without compromising signal and control system privacy. The challenge with FHE, however, is its requirement for inputs to be integers. This paper introduces a modified Learning With Errors (LWE) FHE approach that encodes control system dynamics and signals into integers. Our proposed scheme leverages a generalized LWE encoding function and modifies the Gentry-Sahai-Waters (GSW) gadget decomposition tool to encrypt the control system. Using the modified LWE scheme, we formalize a fully encrypted control system, supported by simulated results.

42 - ENGINEERING↗
DOE OSTI2025

EV Charging Infrastructure Energization: An Overview of Approaches for Simplifying Processes and Accelerating Timelines to Processing EV Charging Load Service Requests

The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure and electricity. Growth in electricity demand from EV charging, coupled with growth in other sectors like data centers and electrification of other sectors, is impacting electricity infrastructure and load service request processes after two decades of relatively flat electricity demand. While most electric vehicle charging occurs at home, enroute and depot charging for medium and heavy-duty vehicles, both using high-powered EV charging, are critical to meet electric vehicle operational needs. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have expressed distress that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

THERMAL STRUCTURAL AND SHOCK EVENT EVALUATIONS OF THE FUELING PELLET INJECTION SYSTEM FOR ITER

The US is among seven partner nations in a collaborative effort to design, build, and demonstrate fusion’s ability to be a large-scale carbon free energy source. Each country has its own Domestic Agencies (DA) that contribute directly to the ITER project. US ITER, which is a DOE Office of Science project managed by Oak Ridge National Laboratory, is developing world class engineering solutions to the design, construction, and assembly of the burning plasma experiment that can demonstrate the scientific and technological feasibility of fusion. US ITER’s scope includes completing the preliminary and final design, qualifying materials and processes for manufacture and testing, executing manufacturing, and delivering the Fueling Pellet Injection System (FPIS) to the ITER site for assembly. The US-ITER FPIS system is designed to inject cryogenically frozen pellets of deuterium-tritium (D-T) into the plasma. The FPIS has two main functions: 1. Provide a steady supply of deuterium and tritium fuel, 2. Mitigating the impact of edge localized modes on the plasma facing components. The FPIS will have the capability to reside in three port cells within a tritium second barrier containment cask. Each pellet cask contains three flight tubes linking with penetrations on the torus cryopump housing and vacuum vessel (VV): two for the magnetic high field side (HFS) pellet injection and one for the magnetic low field side (LFS) pellet injection. This paper presents results of the thermal-structural analyses of the FPIS flight tube structural components when subjected to various loads such as electromagnetic (EM) loads, nuclear heating, seismic, and operational, and dynamic shock events. The resulting temperatures and stresses under combined conditions have been found to satisfy the design criteria to ensure safe and reliable operation of the FPIS flight tubes within the vacuum vessel.

Martinez, Oscar↗
DOE OSTI2025

Oxygen stable isotopes in the nuclear fuel cycle: Assessment of the potential for determining the fabrication and provenance history of anhydrous and hydrous uranium oxides

Determining the origin and history of interdicted nuclear materials is a central challenge in nuclear forensics. The oxygen stable isotope composition of uranium oxide compounds has emerged as a promising forensic signature, attracting increasing attention since the early 2000s. This review examines analytical techniques for measuring oxygen isotope compositions in uranium oxides and evaluates how the nuclear fuel production cycle introduces or modifies these isotopic signatures. The potential for forensic geolocation is explored through workflows that calibrate the relationship between environmental water oxygen isotopes and those found in uranium oxides. Key strengths and limitations of this approach are assessed, including gaps in knowledge related to isotope fractionation during specific stages of the fuel cycle, and processing facility water inputs. The importance of proper sample handling and storage under inert atmospheres, as well as a deeper understanding of both intra-sample oxygen isotope heterogeneity, and hydrous uranium oxide phase formation, is highlighted for improving the reliability of forensic interpretations. In conclusion, the development of uranium oxide standards with well-characterized δ 18 O values and international collaboration toward consensus on their use are identified as essential steps for advancing the field.

Attribution↗
DOE OSTI2025

Nondestructive Evaluation of Concrete: Elastic Property Imaging Through Full Waveform Inversion

Concrete is a major construction material worldwide and plays a crucial role in the nuclear industry. The elastic properties of concrete are prone to change and degrade while in service, as it is often subjected to extreme operational and environmental conditions. An accurate evaluation of concrete's elastic properties is thus essential to ensure structural integrity and safety. This is especially true for concrete in nuclear power plants, where irradiation effects significantly impact concrete mechanical properties. There are various methods to assess these properties, with ultrasound-based techniques showing high potential due to their nondestructive nature, cost-effectiveness, and safety. While several nondestructive evaluation methods exist, most rely on idealizations such as assuming homogeneous material and plane wavefronts. In this work, we address these issues by introducing an ultrasound-based nondestructive method aimed at reconstructing spatially varying images of concrete mechanical properties. By accurately modeling wave physics, including scattering and reflection, we overcome several of the aforementioned idealizations and aim to utilize the full waveform for imaging material properties through depth, resulting in more reliable images. Full waveform inversion (FWI) was first introduced by geophysicists to reconstruct subsurface elastic property images. The goal is to minimize the difference between simulated and recorded wavefield signals, often through gradient-based optimization algorithms. While FWI is primarily conducted using the acoustic approximation of the wave equation, few works focus on elastic FWI, where the goal is to reconstruct images of not only the pressure wave speed but also the shear wave speed and density (or their equivalents). This work explores the potential of using elastic FWI to predict concrete mechanical properties as an initial effort for a more accurate monitoring of concrete conditions in service. Reconstructing images of different elastic parameters enables more specificity and accurate condition diagnosis. This paper will detail this approach and provide examples demonstrating the effectiveness of elastic FWI in reconstructing comprehensive maps of concrete mechanical properties.

42 - ENGINEERING↗
DOE OSTI2024

Spectral and Temperature-Dependent Optical Metrology: Towards More Robust, Effective and Durable Materials for Concentrated Solar Power

The primary objective of this project is to develop reliable and standardized spectroscopic measurement techniques to determine radiative properties, specifically the emittance and reflectance, of materials relevant for the next generation (Gen3) concentrated solar power (CSP) technologies. Experimental measurements will span near- and mid-infrared wavelengths (1–20 µm) with emphasis on quantifying the influences of: (1) operating temperatures of 25–1000 °C, (2) thermal cycling, and (3) environmental exposure of materials during operation (vacuum/air). A secondary goal is to develop open-access and digitized databases to host and share experimental data, together with standardized measurement protocols and operating procedures to determine optical properties of materials. This project will also include reasonable emphasis on developing predictive modeling tools to augment experimental data to extract more fundamental and material-specific radiative properties.

14 SOLAR ENERGY↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

An Overview of Manufacturing Controls for Production of High-Consequence, Single-Use Systems

Extended Testing (Crowder, et al. (2025) ) is a reliability demonstration technique that can be used to dramatically reduce sample size requirements. Manufacturing controls are needed to supplement extended testing by identifying production issues that a reduced sample sizes might overlook, especially built-in, or latent, manufacturing defects. This report focuses on some of the most commonly used, yet most impactful, manufacturing control tools that are used to limit production-related defects and efficiently screen any remaining defects at final inspection. These tools include statistical process control (SPC), acceptance sampling, environmental stress screening (HASS and ESS), and mistake proofing. The goal is to minimize the probability that built-in defects ever reach the customer. In terms of nuclear weapons (NW), the goal is to prevent defective units from ever entering the nation’s NW stockpile. Examples of each of the techniques are illustrated with case studies.

42 ENGINEERING↗
DOE OSTI2024

Theoretical studies of chemical reactions related to the formation and growth of polycyclic aromatic hydrocarbons (PAH) and molecular properties of their key intermediates (Final Progress Report)

The formation mechanisms of polycyclic aromatic hydrocarbons, (PAHs) – organic molecules carrying fused benzene rings – are of great interest to scientists and engineers due to their importance in combustion chemistry and astrochemistry. On Earth, PAHs are largely produced in incomplete combustion of fossil fuel and are considered as critical precursors to unwanted soot particles leading to combustion inefficiency and causing air pollution along with detrimental health effects. Simple PAH molecules initially formed in the gas phase, are further involved in a build-up process in combustion flames leading to larger PAH, bowl-shaped nanostructures, fullerenes, and solid-phase species including carbonaceous dust, graphene particles, and soot. In deep space, PAH and their derivatives are potential key intermediates and nucleation sites leading eventually to carbonaceous nanoparticles (“interstellar grains”). Therefore, the understanding of the key processes in the synthesis of PAHs along with their precursors and their degradation mechanisms in combustion systems and in interstellar, circumstellar, and planetary atmospheric environments will provide critical insights into how complex aromatic structures, carbonaceous nanoparticles, and fullerenes are formed and destroyed. Achieving this understanding is an important step in the development of the efficient combustion processes and of the ecofriendly devices with reduced environmental pollution as well as technological strategies for the production of hydrogen and solid carbon through thermal or plasma-assisted pyrolysis of natural gas and biomass. Also, the understanding of the key processes of PAH and soot growth will help in our comprehension of chemical evolution in the universe. Detailed information on the mechanisms and reliable rate constants of the key elementary chemical reactions involved in PAH formation and destruction processes and in inception of soot particles is often missing, with the main deficiencies being the absence of temperature- and pressure-dependent rate constants for the broad range of conditions occurring in various terrestrial and interstellar processes and the lack of data on the reaction products and their branching ratios. Complementary to experimental studies, these gaps in knowledge can be filled by using quantum chemical calculations of reaction potential energy surfaces providing us with accurate energies of reaction products, intermediates, and transition states, revealing the reaction mechanism, and giving the molecular properties required to compute rate constants for relevant reaction steps and product branching ratios using the RRKM-Master Equation (ME) method. Molecular dynamics (MD) simulations can be used in cases when a reaction rate cannot be properly described by statistical theories. During the terminal renewal project period we employed these ab initio/RRKM-ME and MD approaches to complete our studies on several key reactions relevant to the formation/growth of PAH and inception of soot particles including (1) the reaction mechanism and kinetics of the resonance stabilized fulvenallenyl radical with propargyl and C 3 H 4 isomers; (2) the reaction mechanism and kinetics for the C + indene and C 2 + styrene reactions producing naphthyl or azulenyl radicals in low-temperature environments; (3) the MD study of non-equilibrium dimerization of acepyrene and coronene and its radical. The information derived from our theoretical calculations contributed to a better fundamental understanding of the reaction mechanisms and provide missing critical kinetic data to improve combustion models of hydrocarbon fuels and astrochemical models of the growth of carbonaceous molecules and particles in cold molecular clouds, circumstellar envelopes, and planetary atmospheres.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

BIL GRID-READY WIND: Reliable and Economical Grid Services Design, Implementation, and Demonstration at the Great Pathfinder Wind Power Plant

The GRID-READY WIND project aimed to demonstrate the ability of utility-scale wind power plants (WPPs) to deliver traditional and emerging grid services (GSs) in both grid-following (GFL) and grid-forming (GFM) modes through a centralized control framework, supplemented by local control adjustments at the wind turbine generator as needed. Throughout the project, the team offered recommendations on how the grid services demonstrated with WPPs could be applied to other inverter-based resources (IBRs), such as photovoltaic (PV) systems and battery energy storage systems (BESS), while considering the unique dynamics of these resources arising from their energy generation characteristics. The project sought to enhance the confidence of system operators (SOs) and planners in utilizing WPPs, alongside other IBRs such as PV plants and BESS, to provide essential grid services over extended periods under diverse operating conditions, thereby supporting their integration into the bulk power system.

17 WIND ENERGY↗
DOE OSTI2026

MULTI-FIDELITY MODELING AND UNCERTAINTY QUANTIFICATION OF INVERTER BASED RESOURCES IN INTEGRATED T&D SYSTEMS

Uncertainty quantification plays a pivotal role in improving the accuracy and reliability of inverter operation within modern power systems that are increasingly dominated by inverter-based resources (IBRs). IBRs, especially those operating under grid forming (GFM) control, rely heavily on a complex set of control parameters and system measurements to maintain voltage, frequency, and power balance. Traditional deterministic modeling approaches often fail to capture these parameter deviations, potentially resulting in suboptimal control actions, reduced system stability, or even instability under high penetration of IBRs. In this paper, we demonstrate the application of model calibration and uncertainty quantification (UQ) principles to an integrated transmission and distribution (T&D) model involving a GFM converter and provide a framework for prioritizing control improvements, guiding robust design, and informing adaptive strategies that can accommodate real-time variability in system conditions. The proposed approach could be valuable in enhancing the robustness of current and future power systems under increased IBR penetrations.

24 POWER TRANSMISSION AND DISTRIBUTION↗