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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 1,603 records · Page 89

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NASA NTRS2013

Sensitivity of warm-frontal processes to cloud-nucleating aerosol concentrations

An extratropical cyclone that crossed the United States on 9-11 April 2009 was successfully simulated at high resolution (3-km horizontal grid spacing) using the Colorado State University Regional Atmospheric Modeling System. The sensitivity of the associated warm front to increasing pollution levels was then explored by conducting the same experiment with three different background profiles of cloud-nucleating aerosol concentration. To the authors' knowledge, no study has examined the indirect effects of aerosols on warm fronts. The budgets of ice, cloud water, and rain in the simulation with the lowest aerosol concentrations were examined. The ice mass was found to be produced in equal amounts through vapor deposition and riming, and the melting of ice produced approximately 75% of the total rain. Conversion of cloud water to rain accounted for the other 25%. When cloud-nucleating aerosol concentrations were increased, significant changes were seen in the budget terms, but total precipitation remained relatively constant. Vapor deposition onto ice increased, but riming of cloud water decreased such that there was only a small change in the total ice production and hence there was no significant change in melting. These responses can be understood in terms of a buffering effect in which smaller cloud droplets in the mixed-phase region lead to both an enhanced vapor deposition and decreased riming efficiency with increasing aerosol concentrations. Overall, while large changes were seen in the microphysical structure of the frontal cloud, cloud-nucleating aerosols had little impact on the precipitation production of the warm front.

ice↗

DOE OSTI2025

Interleaved Cuk Converter Wave Energy System With Advanced Control and Grid Support Functions for Seamless Integration

This paper presents an innovative wave energy conversion system that integrates an interleaved Cuk converter with advanced nonlinear control for seamless grid integration. The system efficiently extracts power on the DC side using the interleaved Cuk converter, while an inverter manages power transfer to the grid or load on the AC side. A nonlinear control architecture, based on the Lyapunov energy function, ensures stable and optimal operation under varying wave conditions, effectively addressing the challenges of variability and unpredictability inherent in wave energy. The proposed system also incorporates features to enhance power quality and minimize losses, making it a robust solution for renewable energy integration. The system's effectiveness in harnessing wave energy and achieving smooth grid integration is validated through comprehensive computer simulations in MATLAB/Simulink, with case study results demonstrating its capabilities.

HYDRO ENERGY,TIDAL AND WAVE POWER↗

DOE OSTI2026

A comprehensive framework for validating simulation models of power system equipment using terminal measurements

Accurate simulation of power-plants is essential to the planning and operation of modern power grids. The current methods used to periodically check power-plant simulation models have many open questions about their limitations and accuracy. The research in this project explored using Monte-Carlo Experimentation (MCE) as a means for answering these important questions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1985

Development and testing of a simple assimilation technique to derive average wind fields from simulated scatterometer data

A simple algorithm is developed and tested to derive a regularly spaced wind field in a limited area from simulated multiorbit scatterometer data. The data are generated by sampling a time-varying known wind field, the 1000-mb FGGE data, from a simulated scatterometer. A simple assimilation technique is used to derive a regularly spaced (100-km grid) wind field representation of two-day averages from the simulated data. Several test cases are considered, and it is noted that the assimilation technique might be applicable to large-scale ocean or atmospheric models.

Legler, D. M.↗

DOE OSTI2026

High-Resolution Large-Eddy Simulations of Historical U.S. Gulf Coast Hurricanes

This dataset provides coupled mesoscale and microscale (large-eddy simulation; LES) atmospheric simulations of five historical U.S. Gulf Coast hurricanes. Meso-microscale coupled simulations of Hurricanes Harvey (2017), Nate (2017), Michael (2018), Laura (2020), and Delta (2020) were performed with the Weather Research and Forecasting (WRF) model v4.1.5. The mesoscale component captures the multi-day evolution of each storm's track, intensity, and large-scale structure across the Gulf of Mexico, while the LES component explicitly resolves the dominant turbulent eddies in the hurricane boundary layer at a horizontal grid spacing of 33.33 m. Together, these simulations characterize tropical cyclone wind fields across atmospheric scales ranging from ~100 km down to ~100 m, spanning storm intensities from Category 2 through Category 4 on the Saffir–Simpson scale. This dataset contains the Large-Eddy simulations. The data will be divided according to the storm intensity level at the simulation time. Category 2: Harvey, Nate Category 3: Michael, Delta Category 4: Michael, Laura

17 WIND ENERGY↗

DOE OSTI2026

High-Resolution Mesoscale Simulations of Historical U.S. Gulf Coast Hurricanes

17 WIND ENERGY↗

DOE OSTI2020

Toward particle-resolved accuracy in Euler–Lagrange simulations of multiphase flow using machine learning and pairwise interaction extended point-particle (PIEP) approximation

This study presents two different machine learning approaches for the modeling of hydrodynamic force on particles in a particle-laden multiphase flow. Results from particle-resolved direct numerical simulations (PR-DNS) of flow over a random array of stationary particles for eight combinations of particle Reynolds number (Re) and volume fraction (φ) are used in the development of the models. The first approach follows a two-step process. In the first flow prediction step, the perturbation flow due to a particle is obtained as an axisymmetric superposable wake using linear regression. In the second force prediction step, the force on a particle is evaluated in terms of the perturbation flow induced by all its neighbors using the generalized Faxén form of the force expression. In the second approach, the force data on all the particles from the PR-DNS simulations are used to develop an artificial neural network (ANN) model for direct prediction of force on a particle. Due to the unavoidable limitation on the number of fully resolved particles in the PR-DNS simulations, direct force prediction with the ANN model tends to over-fit the data and performs poorly in the prediction of test data. In contrast, due to the millions of grid points used in the PR-DNS simulations, accurate flow prediction is possible, which then allows accurate prediction of particle force. This hybridization of multiphase physics and machine learning is particularly important, since it blends the strength of each, and the resulting pairwise interaction extended point-particle model cannot be developed by either physics or machine learning alone.

42 ENGINEERING↗

DOE OSTI2023

Hardware-based Advanced Electromagnetic Transient Simulation for A Large-Scale PV Plant in Real Time Digital Simulator

Power electronics-based resources, such as high-voltage direct current (HVdc) substations, photovoltaic (PV) plants, wind plants, electric vehicle charging stations, and energy storage systems, are increasingly being integrated within the power grid. Recently, multiple reports have emphasized the necessity for high-fidelity electromagnetic transient (EMT) simulations of these large-scale power electronics-based resources to accurately understand their behavior in power grids. However, performing hardware-based EMT simulations with high-fidelity models for such large power electronics systems is challenging due to the small time-step requirements and the involvement of a large number of states. This paper presents the implementation of hardware-based high-fidelity EMT dynamic model of a large-scale PV plant, accomplished through custom model development using the specific-C language in real-time digital simulator hardware (RTDS) and software (RSCAD).

Choi, Jongchan↗

DOE OSTI2022

Power HIL Validation of a MW-Scale Grid-Forming Inverter's Stabilization of Otherwise Unstable Cases of the Maui Transmission System

This presentation summarizes MW-scale power hardware-in-the-loop experiments using a 2.2 MW grid-forming inverter connected to a real-time electromagnetic transient simulation of the Maui transmission system. The hardware inverter used is a commercially available "off-the-shelf" inverter from a major manufacturer that is capable of operating in grid-forming mode or grid-following mode. The hardware inverter was connected via power hardware-in-the-loop to a real-time model of the year-2023 Maui power system, which consists of a networked transmission system with diverse generation sources. The results of the simulations indicate that with sufficient synchronous machines online, the system is stable without grid-forming inverters, but that as the amount of synchronous machines is reduced, the system becomes unstable. Changing the hardware inverter (scaled up to represent a 30 MW plant) into grid-forming mode mitigates the instability in various low-inertia cases, including a zero-inertia scenario with 100% of generation from PV and wind. This result broadly agrees with pure simulation results.

battery energy storage system↗

DOE OSTI2021

Multi-species collisions for delta-f gyrokinetic simulations: Implementation and verification with GENE

A multi-species linearized collision operator based on the model developed by Sugama et al. has been implemented in the nonlinear gyrokinetic code, GENE. Such a model conserves particles, momentum, and energy to machine precision, and is shown to have negative definite free energy dissipation characteristics, satisfying Boltzmann’s H-theorem, including for realistic mass ratio. Finite Larmor Radius (FLR) effects have also been implemented into the local version of the code. For the global version of the code, the collision operator has been developed to allow for block-structured velocity space grids, allowing for computationally tractable collisional global simulations. The validity of the collision operator has been demonstrated by relaxation and conservation tests, as well as appropriate benchmarks. The newly implemented operator shall be used in future simulations to study magnetically confined fusion plasma turbulence and transport in more extreme regions with higher collisionality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

A method for assessing economic, environmental, and reliability tradeoffs of interregional transmission connecting ERCOT (the Texas grid) to the eastern and western grids

Reliable development of the power grid is an evolving concern for humanity due to extreme weather that frequently threatens power sector infrastructure. The state of Texas is a uniquely structured testbed for grid planners to study when looking for solutions to development, innovation, and overcoming such challenges. Because of its size and islanded structure, Texas is small enough to model, but big enough to matter. Texas is a global leader in energy production, energy consumption, and maintains an unusually diverse fuel mix. In addition, the state has experienced winter freezes, heat waves, wind storms, droughts and floods that have threatened power sector infrastructure or caused recent blackouts and calls for demand side conservation. One of the most devastating of these events was the North American winter storm, dubbed “Winter Storm Uri” by the Weather Channel, that froze the region in February 2021 and led to an extended power outage event that put the majority of Texan residents in darkness for days. While preparing to avoid such outage events in the future, various tools have been proposed to improve grid reliability, including energy efficiency, demand response, and distributed energy resources. An additional option would be to develop interregional transmission that connects the Texas grid to other national grids. To assess the merits of this idea, we developed a novel, universally-applicable and internationally-relevant framework to study how the Texas grid would evolve alongside access to various interregional ties. This method allows us to stress the synthetic grid structure and analyze how it would respond to the shock of a simulated winter storm event. Our method leverages open-source modeling tools, such as PowerGenome, pyGRETA, and GenX to synthesize unique zonal grid data, construct a consolidated network of model regions, and simulate different developmental pathways of capacity expansion and operational dispatch. We demonstrate our method with an analysis connecting the Electric Reliability Council of Texas (ERCOT), the grid that serves most of Texas, the Western Electricity Coordinating Council (WECC), the grid that serves the western half of the contiguous U.S., and the Eastern Interconnect, the grid that serves the eastern half of the contiguous U.S. Our results indicate that the cost-optimal capacity of interregional transmission connecting the ERCOT grid to other grids lies between 9–13 GW assuming baseline conditions. Building this amount of connecting capacity in one or multiple directions lowers the costs and emissions of development and operation by up to $16 billion and 257 million metric tonnes (MMT) respectively. Additionally, our results show that the interregional connections between ERCOT and other national grids reduce the amount of total load shed required through mild winter storm events. However, our results also show that there is a threshold of very extreme winter storm conditions, spanning multiple service areas, above which the connections exacerbate resource adequacy problems. Therefore, the results indicate that the connections need to be carefully planned alongside the rest of the grid infrastructure to avoid over-reliance on specific resources or technology options.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1981

A mesoscale sixth-order numerical modelling system

A numerical simulation system is currently under development for NASA which is intended to improve the modeling of subsynoptic and mesoscale adjustments associated with cyclogenesis, severe storm development and atmospheric transport processes. The model utilizes a standard hydrostatic sigma-p coordinate primitive equation set, with x,y-space differencing accurate to eighth order. A three-step dynamic initialization procedure is employed between the analysis of real-time data and grid interpolation. Results of an 18-hour simulation during which synoptic scale cyclogenesis, subsynoptic scale jet streak adjustments, mesoscale convergence zones and tornadic storms were observed have shown the present model to have the potential for simulating the fine-scale structure of features associated with cyclogenesis and intense squall-line development. The mesoscale model was also found to produce less truncation than the NWS LFM model, although a frictionless version of the mesoscale model somewhat overdeepens and overaccelerates features.

Kaplan, M. L.↗

DOE OSTI2020

Multi-species collisions for delta-f gyrokinetic simulations: Implementation and verification with GENE

we report a multi-species linearized collision operator based on the model developed by Sugama et al. has been implemented in the nonlinear gyrokinetic code, GENE. Such a model conserves particles, momentum, and energy to machine precision, and is shown to have negative definite free energy dissipation characteristics, satisfying Boltzmann’s H-theorem, including for realistic mass ratio. Finite Larmor Radius (FLR) effects have also been implemented into the local version of the code. For the global version of the code, the collision operator has been developed to allow for block-structured velocity space grids, allowing for computationally tractable collisional global simulations. The validity of the collision operator has been demonstrated by relaxation and conservation tests, as well as appropriate benchmarks. The newly implemented operator shall be used in future simulations to study magnetically confined fusion plasma turbulence and transport in more extreme regions with higher collisionality.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Integrating NDVI-Based Within-Wetland Vegetation Classification in a Land Surface Model Improves Methane Emission Estimations

Earth system models (ESMs) are a common tool for estimating local and global greenhouse gas emissions under current and projected future conditions. Efforts are underway to expand the representation of wetlands in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) by resolving the simultaneous contributions to greenhouse gas fluxes from multiple, different, sub-grid-scale patch-types, representing different eco-hydrological patches within a wetland. However, for this effort to be effective, it should be coupled with the detection and mapping of within-wetland eco-hydrological patches in real-world wetlands, providing models with corresponding information about vegetation cover. In this short communication, we describe the application of a recently developed NDVI-based method for within-wetland vegetation classification on a coastal wetland in Louisiana and the use of the resulting yearly vegetation cover as input for ELM simulations. Processed Harmonized Landsat and Sentinel-2 (HLS) datasets were used to drive the sub-grid composition of simulated wetland vegetation each year, thus tracking the spatial heterogeneity of wetlands at sufficient spatial and temporal resolutions and providing necessary input for improving the estimation of methane emissions from wetlands. Our results show that including NDVI-based classification in an ELM reduced the uncertainty in predicted methane flux by decreasing the model’s RMSE when compared to Eddy Covariance measurements, while a minimal bias was introduced due to the resampling technique involved in processing HLS data. Our study shows promising results in integrating the remote sensing-based classification of within-wetland vegetation cover into earth system models, while improving their performances toward more accurate predictions of important greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Co-Simulation of Electric Power Distribution Systems and Buildings including Ultra-Fast HVAC Models and Optimal DER Control

Smart homes and virtual power plant (VPP) controls are growing fields of research with potential for improved electric power grid operation. A novel testbed for the co-simulation of electric power distribution systems and distributed energy resources (DERs) is employed to evaluate VPP scenarios and propose an optimization procedure. DERs of specific interest include behind-the-meter (BTM) solar photovoltaic (PV) systems as well as heating, ventilation, and air-conditioning (HVAC) systems. The simulation of HVAC systems is enabled by a machine learning procedure that produces ultra-fast models for electric power and indoor temperature of associated buildings that are up to 133 times faster than typical white-box implementations. Hundreds of these models, each with different properties, are randomly populated into a modified IEEE 123-bus test system to represent a typical U.S. community. Advanced VPP controls are developed based on the Consumer Technology Association (CTA) 2045 standard to leverage HVAC systems as generalized energy storage (GES) such that BTM solar PV is better utilized locally and occurrences of distribution system power peaks are reduced, while also maintaining occupant thermal comfort. An optimization is performed to determine the best control settings for targeted peak power and total daily energy increase minimization with example peak load reductions of 25+%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1992

Flowfield predictions for multiple body launch vehicles

A method is developed for simulating inviscid and viscous flow around multicomponent launch vehicles. Grids are generated by the GENIE general-purpose grid-generation code, and the flow solver is a finite-volume Runge-Kutta time-stepping method. Turbulence effects are simulated using Baldwin and Lomax (1978) turbulence model. Calculations are presented for three multibody launch vehicle configurations: one with two small-diameter solid motors, one with nine small-diameter solid motors, and one with three large-diameter solid motors.

Deese, Jerry E.↗

NASA NTRS1995

The importance of mesoscale circulations generated by subgrid-scale landscape heterogeneities in general circulation models

A mesoscale atmospheric model was used to evaluate the impact of subgrid-scale landscape discontinuities on the vertical profiles of resolved temperature, moisture, and moist static energy in the planetary boundary layer (PBL) of general circulation models (GCMs). These profiles were produced with a 3D version of the model (using a horizontal grid resolution of 7.5 km and 13 vertical layers in the PBL) by averaging horizontally the various atmospheric variables over a 180 x 180 sq km domain-about the size of the horizontal domain represented by a single grid element in a GCM. They were compared to corresponding vertical profiles produced with a 1D version of the model, which simulates the PBL, as in a GCM, over a single horizontal grid element. Differences obtained between the horizontally averaged atmospheric variables produced with the 3D simulations and the 1D simulations emphasize the impact of subgrid-scale landscape discontinuities on GCM-resolved variables. Various types of landscape discontinuities, characterized by horizontal contrasts of surface wetness and size of land patches, were simulated under various background-wind conditions. Differences of temperature, specific humidity, and moist static energy as large as 4 K, 6 g/kg, and 10 kJ/kg were obtained in some cases. These differences were not affected significantly by moderate winds but were sensitive to the spatial distribution of surface wetness. These results emphasize the need to parameterize mesoscale processes induced by landscape discontinuities in GCMss.

Lynn, Barry H.↗

DOE OSTI2024

Data-Driven Unit Commitment Refinement - a Scalable Approach for Complex Modern Power Grids

Integration of renewable generation, which is often intermittent and decentralized, substantially increases the stochasticity and complexity of power grid operations. Future power systems planning will require significant computational capability to evaluate balance between demand and supply under varying conditions, both temporally and spatially. The standard approach for generation unit commitment is to use mixed-integer linear programming to find the optimal generation schedule considering ramping and generator constraints. In the future grid this poses computational scalability challenges because generation and demand are not known with certainty due to stochasticity in weather and complexity of the grid. To address this challenge, we present a data-driven unit commitment approach that can efficiently include stochastic weather impacts and contingency considerations to improve unit commitment. Our approach uses graph-based data analytics techniques on solutions to the security constrained (and possibly stochastic) economic dispatch problem to identify potential improvements to a given unit commitment. Recent breakthroughs in fully-parallel stochastic economic dispatch software allow this approach to be scalably deployed. Simulations on synthetic South Carolina and Texas grids show this method can improve grid reliability with security constraints over a set of contingencies, while also meaningfully lowering total generation cost.

Holt, Timothy↗