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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration

Increasing penetration of distributed energy resources and behind-the-meter renewables may soon disrupt the efficacy of critical protection schemes, such as under-frequency load shedding (UFLS). Improved data exchange and coordination across the transmission-distribution boundary will be required to maintain reliability of bulk electric system. Standards-based data integration platforms using agreed-upon semantic vocabularies, such as the Common Information Model, will be key to enabling adaptive protection schemes requiring synthesized data from both the bulk power system and behind-the-meter resources. This paper introduces a cloud-based open-source data integration environment and UFLS clustering algorithm being developed to enable adaptive relay coordination between transmission and distribution utilities in the state of Vermont.

Anderson, Alexander A.↗
DOE OSTI2025

Kolmogorov-Arnold wavefunctions

Here, this work investigates Kolmogorov-Arnold network-based (KAN) wave-function Ansätz as viable representations for quantum Monte Carlo simulations. Through systematic analysis of one-dimensional model systems, we evaluate their computational efficiency and representational power against established methods. Our numerical experiments suggest some efficient training methods and we explore how the computational cost scales with desired precision, particle number, and system parameters. Roughly speaking, KANs seem to be 10 times cheaper computationally than other neural-network-based Ansätz . We also introduce a novel approach for handling strong short-range potentials—a persistent challenge for many numerical techniques—which generalizes efficiently to higher-dimensional, physically relevant systems with short-ranged strong potentials common in atomic and nuclear physics.

1-dimensional systems↗
DOE OSTI2024

On the Use of Tidal Power for Enhancing Power System Resilience with Networked Microgrids

The resilience of a power system to withstand a high-impact low-frequency event is a growing concern, especially in coastal communities that tend to be densely populated and very prone to extreme events such as storms and flooding. In such areas, marine renewable energy can be integrated with the existing renewable energy sources to improve generation diversity and power system resiliency. Using networked microgrids as an example, this paper proposes an empirical study to investigate the impact of marine resources, in particular, tidal energy on the power system resiliency. A set of quantitative metrics with intuitive physical interpretations is used to evaluate the resiliency of a power system that is enhanced with distributed generation in the form of rooftop photovoltaic systems and tidal generators. The effectiveness of resource diversification on the power system resiliency is demonstrated through simulations on a model of a real-world coastal distribution feeder located in Sequim, Washington.

Peerzada, Aaqib A.↗
DOE OSTI2024

Distribution Transformer Demand: Understanding Demand Segmentation, Drivers, and Management Through 2050

The National Renewable Energy Laboratory (NREL) has been working closely with the U.S. Department of Energy's Office of Electricity (OE) to understand the critical drivers and potential means of managing distribution transformer demand through 2050. This effort has consulted with utility representative organizations and transformer manufacturers to understand the problem, characterized the in-service assets, and modeled future demand. Distribution transformers, or service transformers, range from 10 to 5,000 kilovolt-amperes (kVA), have a high-side voltage of less than 34.5 kilovolts, and have step-down power delivery for customer end use. This research will help the manufacturing sector understand production requirements and better inform utility strategies for managing their demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Digital Safety Analysis for Small Modular Nuclear Reactors (SMRs)

A Documented Safety Analysis (DSA) is a Department of Energy (DOE) construct that defines the extent to which a nuclear facility can be operated safely. It includes a description of hazards, safe boundaries, and hazard controls. The authors assert that a Digital Safety Analysis (DgSA) is far superior to a legacy DSA for several reasons: • The underling database is structured such that it is possible to perform a comprehensive design review and safety analysis by iterating systematically across a hierarchy of linked objects versus a redundant and spotty review by entities of various abilities under unknown resource and schedule constraints. • The analysis of a new design can discover elements that are similar to elements in previous designs. The discovery of similarities is made possible by using the same structure for the underlying database for each new DgSA. The “prior learning” from previous designs is then applied automatically to new designs. • Outputs from the DgSA are from a single source to ensure consistency among various views of the same information. After the DgSA is released, the continued use of a single source implements a configuration management program to ensure consistency between the design basis, the design, the built system, and system procedures. • The development of the DgSA is agile in that any change in a linked object triggers an analysis of impacts on other linked objects and updates of linked objects are made accordingly. After the DgSA is released, the continued maintenance of these links and objects automates the “unreviewed safety question” process.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Digital Safety Analysis for Small Modular Nuclear Reactors (SMRs)

The licensing process for any nuclear installation generally requires the review and approval of numerous documents by a regulatory body. Alternate approaches are needed where similar nuclear installations are planned to be built and operated at multiple sites around the world. Such is the case for the deployment of small modular nuclear reactors (SMRs) under development by multiple enterprises in multiple countries. As a use case for this paper, the authors propose an alternative to the Documented Safety Analysis (DSA) required by the United States Department of Energy (DOE) for the licensing of its nuclear installations. The DSA is a DOE construct that requires the review and approval of numerous documents. It includes an in-depth description of hazards, safe boundaries, and hazard controls.

Microreactors↗
DOE OSTI2024

Powered By ReEDS™ [Slides]

The National Renewable Energy Laboratory's flagship Regional Energy Deployment System (ReEDS) electric grid planning model is informing the answers to some of the biggest questions surrounding electricity sector research. Powered By ReEDS is the third webinar in the Powered By series. Each webinar highlights an innovative NREL grid planning and analysis tool and its real-world applications. The series is an exciting opportunity to learn directly from NREL's grid experts, so make sure to bring your questions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. Here, this paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

25 ENERGY STORAGE↗
DOE OSTI2026

Summary of GFL Inverter Capability and Performance: Malawi [Slides]

This presentation provides a comprehensive comparison of inverter-based resource (IBR) technical requirements across multiple international grid codes - including IEEE 2800, ESO, EirGrid, and Malawi's evolving regulatory framework - to support capacity building for electricity-sector institutions in Malawi. It highlights key performance expectations for grid-following (GFL) inverters across critical domains such as primary and fast frequency response, ramping behavior, frequency and voltage ride-through capabilities, reactive power and voltage control, ROCOF withstand, phase jump tolerance, system strength considerations, protection schemes, and dynamic modeling requirements. Emphasizing a "Do no harm, do something, do more" philosophy, the document synthesizes best practices and operational benchmarks to guide the integration and stability of inverter-based resources within Malawi's power system. The presentation forms part of the SABESS Center of Excellence initiative supported by the Global Energy Alliance for People and the Planet.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Implementation of a turbine farm model into the Energy Exascale Earth System Model for investigation and quantification of global climate impacts

Although there has been widespread deployment of wind farms in the United States, and plans to continue deployment into the future, the complete effects of wind farms on Earth systems are not well understood. The work performed here has incorporated wind farm models into the Energy Exascale Earth System Model (E3SM) capable of simulating the effects of extracting momentum from the atmospheric flow field using power generating wind farms. This new capability will allow scientists to quantify the impacts of wind farm induced changes on Earth systems by exploiting E3SM’s ability to couple atmospheric, oceanic, and biogeochemical (BGC) models on a global scale and monitor precipitation levels, extreme weather events, soil moisture content and jet stream location over decades-long time periods. This tool will be used to inform decision making on wind farm citing and will contribute to the Lab’s ability to assess energy technology impacts on the environment and evaluate the trade-offs between energy infrastructure investments and their impacts on natural systems.

17 WIND ENERGY↗
DOE OSTI2025

A DATA EFFICIENT SPARSE MODELING FRAMEWORK FOR POWER ESTIMATION IN WATER TREATMENT SENSING OPERATIONS

With increasing freshwater scarcity, advanced process design mechanisms such as Closed-Circuit Reverse Osmosis (CCRO) and Digital/Physical Twin systems are gaining traction in water treatment and reuse operations. While digital and physical twin models enable improved system insight and control, their development is often expensive and computationally intensive, requiring large volumes of synthetic or experimental data to characterize underlying process dynamics. This work introduces a sparse surrogate modeling framework to estimate power consumption from measured flow and pressure variables, along with their nonlinear polynomial and interaction expansions. To ensure model reliability and reduce overfitting, a two-stage pipeline is proposed. First, a dynamic data filtering algorithm is employed to remove uninformative observations and transient operational states. Second, a sparse penalized regression technique is applied to select a minimal set of parsimonious features. The proposed model achieves high sparsity, retaining only 7 out of 34 candidate features (≈79.41% sparsity) while delivering a root mean square error (RMSE) of 0.072 on the test dataset.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2025

CERF: IM3 Projected Western US Power Plant Locations

Overview The Capacity Expansion Regional Feasibility (CERF) model is an open-source geospatial python package that provides new power plant locations at a 1km resolution. The model ingests U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. This dataset provides CERF power plant siting results for IM3 Phase 2 simulations across eight different scenarios for the Western US through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 CERF siting results in this dataset correspond to capacity expansion plans in the GCAM-USA IM3 Phase 2 simulation data and are available for each of the above scenarios. Data Details Temporal Range: 2015-2055 in 5-year timesteps. Note that 2015 is the experiment base year and 2020 and beyond represent model simulation years. Spatial Range: Plant locations are provided for the eleven states in the Western US including Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. Spatial Resolution: 1 km-squared, provided in x and y coordinates Geospatial Projection: Albers Equal Area Conic (ESRI:102003) File Type: csv The dataset contains subdirectories for each of the eight scenarios described in the overview. Each scenario folder contains two subfolders with the following information: 1. Power Plant Data This directory contains a single .csv file of power plant locations for both pre-existing (non-CERF sited plants in operation in 2015) and new (CERF-sited) power plants across the temporal range along with additional CERF model output parameters for CERF-sited plants. Plant with a siting year earlier than 2020 correspond to facilities that are operational leading into the first timestep CERF simulation. For a more detailed description of CERF model output parameters, see the CERF model documentation. Note that the cerf_plant_id parameter is unique within each scenario file but not across scenario files. Parameter Descriptions scenario - Name of scenario cerf_plant_id - Unique siting identifier cerf_sited - If True, indicates that plant was sited by CERF model. If False, indicates pre-existing facility region_name - Name of region (state) tech_id - Technology ID tech_name - Full generation technology name inclusive of cooling type (if applicable) and additional characteristics tech_simple - Simplified generation technology type unit_size_mw - Power plant unit size (MW) xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) index - Index position in the flattend 2D array buffer_in_km - Exclusion buffer around site (km) sited_year - Year of siting retirement_year - Year of retirement lmp_zone - Locational marginal price (LMP) zone ID locational_marginal_price_usd_per_mwh - Locational marginal price ($/MWh) generation_mwh_per_year - Generation output (MWh/yr) operating_cost_usd_per_year - Cost of plant operations ($/yr) net_operational_value - Net operational value based on LMP and and operating costs ($/yr) interconnection_cost - Cost of interconnection for transmission & gas pipeline (if applicable) net_locational_cost -- Difference of interconnection cost and operating value ($/yr) capacity_factor_fraction - Capacity factor (fraction) carbon_capture_rate_fraction - Carbon capture rate (fraction) fuel_co2_content_tons_per_btu - Fuel CO2 content (tons/Btu) fuel_price_usd_per_mmbtu - Fuel price ($/MMBtu) fuel_price_esc_rate_fraction - Fuel price escalation rate (fraction) heat_rate_btu_per_kWh - Heat rate (Btu/kWh) lifetime_yrs - Technology lifetime for annuity (years) operational_life_yrs - Operational lifetime for retirement (years) variable_om_usd_per_mwh - Variable operation and maintenance costs of yearly capacity use ($/MWh) variable_om_esc_rate_fraction - Variable operation and maintenance costs escalation rate (fraction) carbon_tax_usd_per_ton - Carbon tax ($/ton) carbon_tax_esc_rate_fraction - Carbon tax escalation rate (fraction) 2. Storage Data This directory contains information on new and pre-existing energy storage facilities operational in each timestep along with various storage operational parameters. The 2015 timestep provides pre-existing energy storage data and corresponds with facilities that are operational leading into the first model simulation timestep. Note that coordinates in the storage files correspond to the interconnection point on the grid (substation location), not individual energy storage locations. Energy storage is added in a cumulative process at each given interconnection point. That is, each individual file provides the total operational storage capacity interconnected to the specified substation for the given timestep, inclusive of previously installed storage at that location and new storage installed in that timestep at that location. Parameters scenario - Name of scenario timestep - Simulation timestep name - Unique storage identifier s_typ - Type of energy storage technology (battery or pumped storage hydro) s_node - Node ID of interconnecting substation xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) charge_rate - Maximum charge rate (power capacity) of storage system (MW) discharge_rate - Maximum discharge rate (power capacity) of storage system (MW) duration - Duration of storage system (hours) max_SoC - Allowed maximum state of charge (energy capacity) of storage system (MWh) min_SoC -Allowed minimum state of charge (energy capacity) of storage system (MWh) charge_eff - Efficiency of charge (fraction between 0 and 1) discharge_eff - Efficiency of discharge (fraction between 0 and 1) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

CERF↗
DOE OSTI2026

Time-Domain Vortex Induced Vibration Modeling of Reference Dynamic Power Cable for the Gulf of Maine

Vortex-induced vibration (VIV) is a phenomenon known to decrease the fatigue life of dynamic power cables used in floating offshore wind systems through increased bending loading cycles. A variety of modeling solutions have been proposed to study this, but none enable fully-coupled simulations leveraging open-source tools. To address this, a time-domain VIV model has been successfully implemented into the open-source mooring dynamics model MoorDyn. The semi-empirical VIV model describes a lift force acting on segments of a flexible cylinder, making it well suited for implementation into MoorDyn. The new capability successfully predicted the frequencies and magnitudes of strain in both steady and oscillating flows when compared to the original validation results and matched peak spectral response when compared to experimental results, verifying successful implementation. MoorDyn with VIV was then leveraged to simulate a 15 MW floating turbine with a dynamic power cable in the Gulf of Maine using OpenFAST for six return periods of combined wind, wave, and current conditions. Increased curvature and tension fluctuations in higher flow speeds were observed when simulating VIV. Maximum tensions and curvatures also increased, with the 500 year conditions violating the curvature factor of safety of 2.0. These results highlight the importance of considering VIV when designing dynamic power cables for the Gulf of Maine, and indicate that cost effective mitigation strategies should be explored for the area. They also demonstrate the utility of this new modeling capability, which provides the first open-source tool for fully coupled time-domain floating offshore wind simulations with dynamic power cable VIV.

17 WIND ENERGY↗
DOE OSTI2025

Modeling and Power-Hardware-in-the-Loop Validation of Synchronous Wind: An Inverterless Grid-Forming Wind Power Plant

Grid-forming (GFM) control of Type-3 and Type-4 wind turbine generators (WTGs) has attracted substantial attention in power systems research; however, the limited overcurrent capability of power electronics converters continues to deteriorate the grid strength of the evolving power systems. Synchronous wind, also known as a Type-5 WTG, offers a unique GFM solution to address grid integration and grid strength issues by keeping the grid largely synchronous at very high integration levels of renewable generation. A Type-5 WTG interfaces with the electric grid via a synchronous generator driven by a variable-speed hydraulic torque converter; hence, the wind rotor operates in variable-speed mode for maximum power generation, and the generator shaft remains synchronous to the grid. This paper develops and tests a high-fidelity model of a Type-5 WTG in a power-hardware-in-the-loop (PHIL) testing environment. The PHIL demonstration shows that a Type-5 WTG inherently behaves as a GFM unit and can obtain similar performance in terms of power responses, wind rotor dynamics, and efficiency compared to a Type-3 WTG in high-wind conditions. The developed model provides further insight into how Type-5 WTGs can benefit the smooth transition to power systems with high integration levels of inverter-based resources.

grid strength↗
DOE OSTI2025

Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi‐Member and Stochastic Parameterizations

Abstract Deep learning is a powerful tool to represent subgrid processes in climate models, but many application cases have so far used idealized settings and deterministic approaches. Here, we develop stochastic parameterizations with calibrated uncertainty quantification to learn subgrid convective and turbulent processes and surface radiative fluxes of a superparameterization embedded in an Earth System Model (ESM). We explore three methods to construct stochastic parameterizations: (a) a single Deep Neural Network (DNN) with Monte Carlo Dropout; (b) a multi‐member parameterization; and (c) a Variational Encoder Decoder with latent space perturbation. We show that the multi‐member parameterization improves the representation of convective processes, especially in the planetary boundary layer, compared to individual DNNs. The respective uncertainty quantification illustrates that methods (b) and (c) are advantageous compared to a dropout‐based DNN parameterization regarding the spread of convective processes. Hybrid simulations with our best‐performing multi‐member parameterizations remained challenging and crash within the first days. Therefore, we develop a pragmatic partial coupling strategy relying on the superparameterization for condensate emulation. Partial coupling reduces the computational efficiency of hybrid Earth‐like simulations but enables model stability over 5 months with our multi‐member parameterizations. However, our hybrid simulations exhibit biases in thermodynamic fields and differences in precipitation patterns. Despite this, the multi‐member parameterizations enable improvements in reproducing tropical extreme precipitation compared to a traditional convection parameterization. Despite these challenges, our results indicate the potential of a new generation of multi‐member machine learning parameterizations leveraging uncertainty quantification to improve the representation of stochasticity of subgrid effects.

Behrens, Gunnar [Deutsches Zentrum für Luft‐ und R↗
DOE OSTI2024

NMPC for Mode-Switching Operation of Reversible Solid Oxide Cell Systems

Solid oxide cells (SOCs) are a promising dual-mode technology that generates hydrogen through high-temperature water electrolysis and generates power through a fuel cell reaction that consumes hydrogen. Reversible operation of SOCs requires a transition between these two modes for hydrogen production setpoints as the demand and price of electricity fluctuate. Moreover, a well-functioning control system is important to avoid cell degradation during mode-switching operation. In this work, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional integral (PI) control strategies, while ramping between the modes of hydrogen and power production. While both control methods provide similar performance in many metrics, NMPC significantly reduces cell thermal gradients and curvatures (mixed spatial-temporal partial derivatives) during mode switching. A dynamic process flowsheet of the reversible SOC system was developed in the open-source, equation-based IDAES modeling framework. Our IDAES dynamic simulation results show that NMPC can ramp the SOC system between hydrogen and power production targets within short mode-switching times. Moreover, NMPC can comply with operating limits in the SOC system more effectively than PI, and only NMPC can directly enforce user-specified limits for mixed spatial-temporal partial derivatives of temperature. This allows for management of the trade-off be-tween operating efficiency and cell degradation, which is dependent on these temperature curvatures.

Li, Mingrui↗
DOE OSTI2024

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↗
DOE OSTI2024

Droughts in Wind and Solar Power: Assessing Climate Model Simulations for a Net‐Zero Energy Future

Abstract Understanding and predicting “droughts” in wind and solar power availability can help the electric grid operator planning and operation toward deep renewable penetration. We assess climate models' ability to simulate these droughts at different horizontal resolutions, ∼100 and ∼25 km, over Western North America and Texas. We find that these power droughts are associated with the high/low pressure systems. The simulated wind and solar power variabilities and their corresponding droughts during historical periods are more sensitive to the model bias than to the model resolution. Future climate simulations reveal varied future change of these droughts across different regions. Although model resolution does not affect the simulation of historical droughts, it does impact the simulated future changes. This suggests that regional response to future warming can vary considerably in high‐ and low‐resolution models. These insights have important implications for adapting power system planning and operations to the changing climate.

Liu, Xue [Department of Oceanography Texas A&amp,M↗