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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

V1G Frequency Regulation: Algorithm Development, Validation & Analysis at Scale

Researchers at Argonne National Laboratory developed and validated a high-fidelity digital twin of a smart charging (V1G) ecosystem to model the participation of up to 1,000 unique electric vehicles (EVs) in the PJM frequency regulation market. Utilizing a discrete-event framework, the simulation models complex interactions, from dynamic grid signals (updated every 2 seconds) to individual EV charging dynamics. The simulation incorporates multiple EV models created from real-world lab test data. Researchers tested multiple control algorithms to balance the dual objectives of maximizing aggregator’s revenue and driver charging needs. Results demonstrate that aggregated EVs function as a controllable, highly effective grid resource, achieving high PJM Performance Scores (80–90%). Additionally, an optimized, market-aware bidding strategy was identified as key to profitability. The platform was shown to provide drivers with an average charging discount of nearly 50%. The algorithm was further validated in the lab using production EVs and charging stations to compare simulation results with real-world performance.

Manne, Nithin↗
DOE OSTI2024

How Fisheries Biologists Can Facilitate the Clean Energy Transition

Abstract Fisheries and aquatic biologists play a critical role in creating environmentally protective hydropower flow requirements that govern flow timing, frequency, magnitude, and rate of change. Hydropower's role in the U.S. electrical grid is expected to evolve in response to increased wind and solar generation as hydropower will be called upon to quickly ramp up and down in response to changes in wind and solar generation. For this reason, hydropower is expected to have increased value as fossil generation is phased out, even as rapid flow fluctuations linked with hydropower flexibility may strand fish, alter habitat, and create unsafe recreational conditions. We face a new challenge in facilitating the renewable energy transition—designing environmental flow requirements that protect against the impacts of flow fluctuations while allowing adequate hydropower flexibility to support a stable grid. In this paper, we discuss hydropower environmental flow requirements, operational flexibility, and electrical grid stability, their potential interactions, and opportunities to align environmental and power system needs to support healthy ecosystems, multiple water uses, and decarbonization of the electric grid.

13 HYDRO ENERGY↗
DOE OSTI2025

Improved Understanding of Multicentury Greenland Ice Sheet Response to Strong Warming in the Coupled CESM2‐CISM2 With Regional Grid Refinement

The simulation of ice sheet‐climate interactions, such as surface mass balance fluxes, is sensitive to model grid resolution. Here we simulate the multi‐century evolution of the Greenland Ice Sheet (GrIS) and its interaction with the climate using the Community Earth System Model version 2.2 (CESM2.2) including an interactive GrIS component (the Community Ice Sheet Model v2.1 [CISM2.1]) under an idealized warming scenario (atmospheric CO 2 increases by 1% yr -1 until quadrupling the pre‐industrial level and then is held fixed). A variable‐resolution (VR) grid with 1/4° regional refinement over the broader Arctic and 1° resolution elsewhere is applied to the atmosphere and land components, and the results are compared with conventional 1° lat‐lon grid simulations to investigate the impact of grid refinement. Compared with the 1° runs, the VR run features a slower rate of surface melt, especially over the western and northern GrIS, where the ice surface slopes gently toward the periphery. This difference pattern originates primarily from higher snow albedo and, thus, weaker albedo feedback in the VR run. The VR grid better captures the CISM ice sheet topography by reducing elevation discrepancies between CAM and CISM and is, therefore, less reliant on the downscaling algorithm, which is known to underestimate albedo gradients. The sea level rise contribution from the GrIS in the VR run is 53 mm by year 150 and 831 mm by year 350, approximately 40% and 20% less than that of the 1° runs, respectively.

Earth System Model↗
DOE OSTI2024

An Integrated Assessment of a G3 GMD Event on Large-Scale Power Grids: From Magnetometer Data to Geomagnetically Induced Current Analysis

Solar activities can cause geomagnetic disturbances (GMDs) that give rise to geomagnetically induced currents (GICs) which may compromise the reliability of the power system. In order to build more reliable models representing GMD interactions with the power grid, the power system’s detailed electrical model must be considered along with fluctuations in the earth’s magnetic and induced surface electric fields. Here, this study investigates the impact of incorporating spatially varying magnetic fields into surface electric field models on GMD risk metrics. A spatially independent magnetic field model and a spatially varying model are compared through simulations. To perform this analysis, the earth’s magnetic field disturbances are transformed into surface electric fields using respective one-dimensional earth conductivity models. Then, the modeling impact of these electric fields is studied using a 2,000-bus grid for Texas and a 25,000-bus grid for the northeast and mid- Atlantic regions of the United States. Simulation results reveal that the inclusion of spatially varying magnetic fields results in considerable differences in GMD risk metrics, highlighting the importance of accounting for spatial variability when assessing GMD risks in the power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

A State-Space Model for Stability Boundary Analysis of Grid-Following Voltage Source Converters Considering Grid Conditions

With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification.

grid-connected inverters↗
DOE OSTI2025

Electrical and Thermal Load Impacts of Three District Heating and Cooling Designs for an Existing Community in Washington, DC

District energy systems that provide building heating and cooling are a promising option to provide low-cost, energy efficient heating and cooling solutions for communities. As some buildings move to electrified heating designs, there may be significant increases in electric grid demand, particularly in the winter. District energy systems may be able to help reduce these high electrical demands on the electric grid, while also providing decreased overall energy consumption with an increased flexibility in electrical energy usage. To evaluate and compare district options for district-based heating and cooling, an existing neighborhood of Washington, DC consisting of 35 existing buildings was selected as a case study. This study models and compares a fourth generation (4G) district heating and cooling systems that provide hot and chilled water from a central plant directly to each prosumer and a fifth generation (5G) district heating and cooling systems that provide near-ambient water via geothermal boreholes to interface with an energy transfer station with a heat pump at each prosumer. These district systems are compared against a baseline of the non-connected buildings with their self-contained and current HVAC systems. The neighborhood was selected as a good candidate for a district system for its diversity of loads (mix of different commercial and property types) and the availability of building characteristics. URBANopt District Energy Systems (DES) was used to model the buildings and create initial Modelica models for the district systems. Finally, the DES models were tuned and simulated in Dymola, and the outputs were post-processed for verification and to calculate the electrical and thermal grid impact metrics. This is the first documentation of this workflow and its complete analysis. The three designed systems are compared via their grid metrics including: total energy consumption, electrical demand peak loads, daily peak-to-valley ratios, and system ramping. A detailed discussion is provided about how each system impacts and interacts with the electric grid.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Identifying Potential Sub-Synchronous Oscillations Using Impedance Scan Approach: Preprint

This paper presents an impedance scan study on the real-world power system in Australia that has observed 17 to 20 Hz intermittent subsynchronous oscillations. Through the impedance scan of each of the IBRs, both individually and collectively, potential resonance modes are identified. The impedance scans were carried out using electromagnetic transient PSCAD models of the network. The network comprises of site-specific, black-boxed models of IBRs supplied by the generators. The impedance scan approach was divided in three major steps: (1) the first step is to identify IBRs where impedance analysis needs to be performed based on the magnitude of oscillations observed at their points of interconnection (POIs); (2) the second step focuses on performing impedance scans at selected IBRs in single-machine infinite-bus (SMIB) configuration to identify internal resonance modes of an IBR and to evaluate if any of these modes become unstable under certain grid conditions; (3) the third step performs impedance scans at a few selected IBRs while connected to the wider network model to obtain the impedance response of both the IBR and the grid - this step evaluates control interactions among IBRs. The impedance scan study found that a few IBRs have an underdamped resonance mode at around 17 Hz, which becomes unstable under a certain operating condition. Another interesting finding was that certain IBRs increase the effective grid impedance seen by another IBR in proximity for a particular operating condition. Under this operating condition, the resulting subsynchronous oscillation mode is more pronounced due to a combination of control interactions among IBRs through the transmission network under study and a resonance mode inside the IBRs.

control interactions↗
DOE OSTI2024

Understanding and Predicting the Spatially Resolved Adsorption Properties of Nanoporous Materials

Using knowledge from statistical thermodynamics and crystallography, we develop an image–image translation model, called SorbIIT, that uses three-dimensional grids of adsorbate–adsorbent interaction energies as input to predict the spatially resolved loading surface of nanoporous materials over a broad range of temperatures and pressures. SorbIIT consists of a closed-form differential model for loading-surface prediction and a U-Net to generate spatial differential distributions from the energy grids. SorbIIT is trained using the energy grids and adsorbate distributions (obtained from high-throughput simulations) of 50 synthesized and 70 hypothetical zeolites and applied for predicting the adsorption of carbon dioxide, hydrogen sulfide, n-butane, 2-methylpropane, krypton, and xenon in other zeolites from 256 to 400 K. In conclusion, employing a quadratic isotherm model for the local differentiation, SorbIIT yields mean R 2 values of 0.998 for total adsorption and 0.6904 for local adsorption with a resolution of 0.2 Å, and a value of 0.721 for the structural similarity of the local loading distribution.

Sun, Yangzesheng [Univ. of Minnesota, Minneapolis,↗
DOE OSTI2025

Accelerating magnonic simulations with the pseudospectral Landau-Lifshitz equation

The pseudospectral Landau-Lifshitz (PS-LL) model can describe atomic-scale magnetic exchange interactions within a continuum framework. This is achieved by employing a convolution kernel that models the nonlocal interaction in a grid-independent manner. Even though the PS-LL was originally introduced to address atomic exchange, any nonlocal kernel can be modeled. In the field of magnonics, the dipole field is fundamental to describe the dispersion relation of magnons, the quasiparticle representation of angular momentum. Because dipole-dipole interactions are long-range, numerical approaches typically rely on convolutions. Here, we demonstrate that the PS-LL model can be used to perform magnonic simulations with a single convolution kernel derived from analytical solutions. We demonstrate a twofold increase in computational speed compared with the full dipole calculation. This approach is valid insofar as the excitations are linear, which is typically the case for magnons. Our results have the potential to accelerate magnonic research, particularly for the inverse design method, where several simulations must be performed to achieve the desired outcome.

Mathematics and computing↗
DOE OSTI2025

Data-driven modeling of dynamic occupant thermostat override behavior for demand response applications

Buildings consume nearly 40% of global energy and produce similar emissions. Whiletechnological advances address efficiency, occupant behavior causes energy use variations up to 300% between identical buildings. This gap between predicted and actual building performance impacts building design, operations, and grid demand management programs. Through analyses of smart thermostat data from 1,400 single-occupant homes, the researchdemonstrates that occupants respond to 8°F thermostat setpoint changes within a median of 15 minutes, while 2°F changes trigger responses within a median of 30 minutes. This highlights an understudied temporal relationship between thermostat setbacks and response time of occupant behaviors. Models of such behavior dynamics are required to incorporate occupant impacts into building performance simulation. A key contribution of this dissertation is the Thermal Frustration Theory (TFT), which positsthat thermal discomfort driven behaviors are caused by the time-accumulation of discomfort, not simply a temperature deviation threshold or a delay from an initiating event. Using a dataset of 634 thermostats, each with 25+ manual setpoint changes, a comparative analysis of TFT and comfort zone and a delayed response theories demonstrated that personalized TFT models better predict when manual setpoint change occur. This was measured by the area under the curve statistical measure (AUC); all three models perform similarly by a Matthews Correlation Coefficient measure. Higher AUC performance is especially important for modeling occupant behavior in demand response programs where false negatives of rare occupant interactions could adversely affect grid stability. EnergyPlus based simulations were conducted with TFT-derived occupant models, demonstrating the ability to identify parameters of known TFT models from only data observable with smart thermostats, even under the presence of noise from routine overrides. Overall, the dissertation highlights that thermostat interactions are neither static,instantaneous, nor driven solely by the environment. Instead, temporal accumulation of discomfort and routine-based behavior play important roles. The methodology and results offer a pathway towards more accurate modeling of human-building interactions for policy assessment, building design, and demand response programs.

Sharma, Kunind [Northeastern University] (ORCID:00↗
DOE OSTI2025

Computational Analysis and Optimized Modeling of Geomagnetically Induced Currents in Power Transformers

In this project we aim to better understand the effect of geomagnetically induced currents (GIC) on power transformers. Expanding upon our previous work focused on producing a methodology for accuracy-enhanced computation of GIC signatures (i.e., time-domain current magnitude variation for the event duration) from a combination of physics-based and data-driven computational tools, we propose the use of these GIC signatures as inputs for a physically-detailed and optimized model of the power transformer to investigate how GIC determination and transformer modeling influence the evaluation of GIC effects on the transformer operation, as well as in its interaction with the power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Building Cybersecurity Educational Materials for Students: The Windfarm Capture-The-Flag Exercise

Securing and protecting critical infrastructure in an increasingly digital world is vital but it is all too often an afterthought. It is especially important that students become aware of internet safety and security at an early age. However, the availability of interactive and educational cybersecurity material targeted toward students is minimal in the United States. Here we show an example of interactive cyber security educational material that an educator can use in their classroom to encourage students to think about the interaction between real-world physical objects, cyber security, and information security. By putting together a “capture-the-flag” exercise, students can see in real time how hackers and cybercriminals exploit vulnerabilities and gain access information. The students try to “capture” the “flag” (i.e., information) in the wind farm by looking for oddities in the code or by taking advantage of weaknesses in everyday protocols. Students can also see how cybersecurity interacts with the power grid through the wind farm project scenario and how a hacker could cause serious problems to a critical infrastructure sector. Our goal for the project is getting students interested in cybersecurity and help them develop an awareness of how important having robust security systems is. We also hope that this project demonstrates the importance of introducing these concepts early and inspires others to create similar projects geared toward students.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Modeling Framework for Data Center

This chapter highlights the critical need for advanced modeling of data centers due to their rapidly increasing energy consumption and impact on grid reliability. Driven by the demand for AI applications, data centers are projected to consume a significant portion of US energy by 2028, putting stress on an already challenged power grid. The chapter emphasizes the importance of "fast" time-scale models to understand the dynamic interactions between data centers and the grid, especially given the rapid power fluctuations of AI workloads. It outlines a modeling framework that includes both offline and real-time EMT domain simulations, detailing the necessary representations for various components like utility interfaces, transformers, IT loads, UPS, cooling loads, Battery Energy Storage Systems (BESS), generators, protection systems, and higher-level control systems. While standard simulation tools like PSCAD offer basic models, custom development is often required to accurately capture the unique and fast-changing behaviors of modern data centers. The chapter also discusses key metrics and test cases for validating these models, focusing on transient load responses, protection relay coordination, and demand flexibility. Finally, it addresses the challenges of modeling large-scale data centers, such as computational complexity and the trade-off between model fidelity and practicality, suggesting hybrid modeling approaches as a solution. The overarching goal is to create a robust framework that helps assess data center impacts on grid stability, identify vulnerabilities, and inform the development of standards for reliable integration of these large loads into the bulk power system.

25 ENERGY STORAGE↗
DOE OSTI2026

MCP-eGridGPT (MCP-Enabled Chatbot with Electrical Power System Analysis and Interactive Visualization Tool) [SWR-25-126]

This software is an advanced chatbot system that integrates the Model Context Protocol (MCP) to provide intelligent electrical power system analysis and automated visualization generation. The system enables users to interact with complex electrical engineering tools through natural language, automatically analyzes power system data for voltage violations and grid health assessment, and generates professional interactive HTML dashboards and reports. Key features include dynamic tool discovery from MCP servers, multi-LLM provider support, intelligent data interpretation using large language models, automated chart generation, and a web-based interface for real-time analysis. The software bridges sophisticated electrical engineering analysis with user-friendly interfaces, making power system diagnostics accessible through conversational AI.

Choi, Seong [National Laboratory of the Rockies (N↗
DOE OSTI2024

R-SEEDS Final Report

DER aggregation and grid digitalization imply a future grid that would benefit from more fluid interaction between the bulk power system and the distribution system. This scenario presents a challenge for grid modeling, which treats the two systems separately. Grid modeling also focuses on the engineering aspects of grids without incorporating modeling of the human and social dimensions of the grid as a cyber-physical-social system. The R-SEEDS project examines the integration of human and social models into grid modeling and its implications on decarbonization, energy justice, and distributional impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Behavior of Multiple PV Plants in Future Power Grids During Events

As the integration of multiple photovoltaic (PV) plants into power grids grows, the dynamic response of each plant and their interactions during transient events demands a deeper understanding. In this paper, the dynamic behavior of multiple PV plants connected to future power grids is comprehensively explored using site-specific high-fidelity electromagnetic transient (EMT) PV plant models and generic high-fidelity EMT PV plant models. This research demonstrates the need to employ multiple high-fidelity EMT PV plant models to understand the intricate interactions between multiple PV plants during grid events. These models, developed in Fortran within the PSCAD environment, encompass a range of operational scenarios and plant configurations, offering invaluable insights crucial for future system planning with multiple PV plants to enhance grid stability.

Marthi, Phani Ratna Vanamali [ORNL] (ORCID:0000000↗
DOE OSTI2026

MFC 5.0: An exascale many-physics flow solver

Many problems of interest in engineering, medicine, and the fundamental sciences rely on high-fidelity flow simulation, making performant computational fluid dynamics solvers a mainstay of the open-source software community. Previous work MFC 3.0 was made a published, documented, and open-source solver via Bryngelson et al. Comp. Phys. Comm. (2021) with numerous physical features, numerical methods, and scalable infrastructure. MFC 5.0 is a significant update to MFC 3.0, featuring a broad set of well-established and novel physical models and numerical methods, as well as the introduction of GPU and APU (or superchip) acceleration. Here, we exhibit state-of-the-art performance and ideal scaling on the first two exascale supercomputers, OLCF Frontier and LLNL El Capitan. Combined with MFC’s single-accelerator performance, MFC achieves exascale computation in practice, and achieved the largest-to-date public CFD simulation at 200 trillion grid points as a 2025 ACM Gordon Bell Prize finalist. New physical features include the immersed boundary method, N-fluid phase change, Euler–Euler and Euler–Lagrange sub-grid bubble models, fluid-structure interaction, hypo- and hyper-elastic materials, chemically reacting flow, two-material surface tension, magnetohydrodynamics (MHD), and more. Numerical techniques now represent the current state-of-the-art, including general relaxation characteristic boundary conditions, WENO variants, Strang splitting for stiff sub-grid flow features, and low Mach number treatments. Weak scaling to tens of thousands of GPUs on OLCF Summit and Frontier and LLNL El Capitan achieves efficiencies within 5% of ideal to over 90% of their respective system sizes. Strong scaling results for a 16-times increase in device count show parallel efficiencies over 90% on OLCF Frontier. MFC’s software stack has undergone further improvements, including continuous integration, which ensures code resilience and correctness through over 300 regression tests; metaprogramming, which reduces code length while maintaining performance portability; and code generation for computing chemical reactions

Computational fluid dynamics↗
DOE OSTI2025

Digital Real-Time Simulation and Power Quality Analysis of a Hydrogen-Generating Nuclear-Renewable Integrated Energy System

This paper investigates the challenges and solutions associated with integrating a hydrogen-generating nuclear-renewable integrated energy system (NR-IES) under a transactive energy framework. The proposed system directs excess nuclear power to hydrogen production during periods of low grid demand while utilizing renewables to maintain grid stability. Using digital real-time simulation (DRTS) in the Typhoon HIL 404 model, the dynamic interactions between nuclear power plants, electrolyzers, and power grids are analyzed to mitigate issues such as harmonic distortion, power quality degradation, and low power factor caused by large non-linear loads. A three-phase power conversion system is modeled using the Typhoon HIL 404 model and includes a generator, a variable load, an electrolyzer, and power filters. Active harmonic filters (AHFs) and hybrid active power filters (HAPFs) are implemented to address harmonic mitigation and reactive power compensation. The results reveal that the HAPF topology effectively balances cost efficiency and performance and significantly reduces active filter current requirements compared to AHF-only systems. During maximum electrolyzer operation at 4 MW, the grid frequency dropped below 59.3 Hz without filtering; however, the implementation of power filters successfully restored the frequency to 59.9 Hz, demonstrating its effectiveness in maintaining grid stability. Future work will focus on integrating a deep reinforcement learning (DRL) framework with real-time simulation and optimizing real-time power dispatch, thus enabling a scalable, efficient NR-IES for sustainable energy markets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗