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DOE OSTI2015

Grid Integration Studies: Data Requirements, Greening the Grid

A grid integration study is an analytical framework used to evaluate a power system with high penetration levels of variable renewable energy (VRE). A grid integration study simulates the operation of the power system under different VRE scenarios, identifying reliability constraints and evaluating the cost of actions to alleviate those constraints. These VRE scenarios establish where, how much, and over what timeframe to build generation and transmission capacity, ideally capturing the spatial diversity benefits of wind and solar resources. The results help build confidence among policymakers, system operators, and investors to move forward with plans to increase the amount of VRE on the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2010

A NEW MULTI-DIMENSIONAL GENERAL RELATIVISTIC NEUTRINO HYDRODYNAMIC CODE FOR CORE-COLLAPSE SUPERNOVAE. I. METHOD AND CODE TESTS IN SPHERICAL SYMMETRY

We present a new general relativistic code for hydrodynamical supernova simulations with neutrino transport in spherical and azimuthal symmetry (one dimension and two dimensions, respectively). The code is a combination of the COCONUT hydro module, which is a Riemann-solver-based, high-resolution shock-capturing method, and the three-flavor, fully energy-dependent VERTEX scheme for the transport of massless neutrinos. VERTEX integrates the coupled neutrino energy and momentum equations with a variable Eddington factor closure computed from a model Boltzmann equation and uses the 'ray-by-ray plus' approximation in two dimensions, assuming the neutrino distribution to be axially symmetric around the radial direction at every point in space, and thus the neutrino flux to be radial. Our spacetime treatment employs the Arnowitt-Deser-Misner 3+1 formalism with the conformal flatness condition for the spatial three metric. This approach is exact for the one-dimensional case and has previously been shown to yield very accurate results for spherical and rotational stellar core collapse. We introduce new formulations of the energy equation to improve total energy conservation in relativistic and Newtonian hydro simulations with grid-based Eulerian finite-volume codes. Moreover, a modified version of the VERTEX scheme is developed that simultaneously conserves energy and lepton number in the neutrino transport with better accuracy and higher numerical stability in the high-energy tail of the spectrum. To verify our code, we conduct a series of tests in spherical symmetry, including a detailed comparison with published results of the collapse, shock formation, shock breakout, and accretion phases. Long-time simulations of proto-neutron star cooling until several seconds after core bounce both demonstrate the robustness of the new COCONUT-VERTEX code and show the approximate treatment of relativistic effects by means of an effective relativistic gravitational potential as in PROMETHEUS-VERTEX to be remarkably accurate in spherical symmetry.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Large Eddy Simulation of turbulent flow in rod bundle with spacer grids

Pressurized water nuclear reactor fuel assemblies are made of fuel rods held by spacer grids, which are the core components of the nuclear power plants. Hot fuel rods are cooled by the coolant water flow, and the spacer grids with mixing vanes distort the mainstream, producing the swirling flow which can enhance the heat transfer to improve CHF (Critical Heat Flux). Heat transfer between fuel rods and coolant is a crucial part of thermal-hydraulic analysis. For the purpose to improve the thermal hydraulic performance of the fuel assemblies, many experiments have been conducted to understand the flow structures and three-dimensional behaviors of the turbulence in the rod bundle sub-channels and then to optimize the design of the spacer grid. In the experimental work, which requires lots of efforts to get reliable data, LDA (Laser Doppler Anemometry) and PIV (Particle Image Velocimetry) are generally used to measure the velocity profile and turbulent intensity in the sub-channels. Computational Fluid Dynamics (CFD) is another useful way to study the characteristics of the detailed flow condition and heat transfer phenomena in the subchannels. The main issue of the single-phase CFD is to accurately predict the flow and turbulence characteristics. RANS method is generally used to simulate the induced lateral velocity and the heat transfer process. With the development of computer technology, some more precise but previously time-consuming turbulent models, such as LES (Large Eddy Simulation), are gradually used for the simulation of rod bundle flow with current advanced CPU resources. Ikeno and Kajishima explained the decay of swirling turbulent flow in the rod bundle using LES method. Benhamadouche acquired the turbulence induced forces on the central rod of the rod bundle through performing the LES of the flow downstream the spacer grid. Chang and Tavoularis conducted hybrid simulations with SAS SST and LES of a 5 x 5 rod bundle, and several vortices were identified in the vicinity of the vanes and the generation mechanisms, evolution progress and influence on the velocities of these vortices were clarified. In the paper we present CFD simulations of turbulent flow in rod bundle sub-channels with spacer grids of two different experiments. One is MATiS-H benchmark experiment with scaled spacer grids, which is conducted by KAERI, and is used as a CFD benchmark test, and the other is a 5 x 5 rod bundle with typical spacer grids using PIV technology, with the cooperation of Harbin Engineering University. The main objectives of the calculations are to validate LES methodology by the benchmark experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

Doppler shift measurement of Balmer-alpha line spectrum emission from a plasma in a negative hydrogen ion source

Balmer-α light emission from the extraction region of the LHD one-third ion source has shown a characteristic Doppler broadening in the wavelength spectrum detected by a high resolution spectrometer. The spectrum resembles Gaussian distribution near the wavelength of the intensity peak, while it has an additional component of a broader foot. The measured broadening near the wavelength of the intensity peak corresponds to 0.6 eV hydrogen atom temperature. The spectrum exhibits a larger expansion in the blue wing which becomes smaller when the line of sight is tilted toward the driver region from the original observation axis parallel to the plasma grid. A surface collision simulation model predicts the possibility of hydrogen reflection at the plasma grid surface to form a broad Balmer-α light emission spectrum.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

Development and validation of an enhanced filtered drag model for simulating gas-solid fluidization of Geldart A particles in all flow regimes

Coarse-grid two-fluid simulation of gas-solid fluidized bed reactors based on the kinetic theory of granular flow exhibits a significant dependence on drag models, especially for Geldart A particles. Many drag models are available in the literature, which have been reported to work for different systems. This work focused on the evaluation of an enhanced filtered drag model along with other different drag models derived from different methods for three-dimensional two-fluid model simulations of gas-solid fluidized beds of Geldart A particles covering a broad range of fluidization regimes, including bubbling fluidization, turbulent fluidization, fast fluidization, and dilute phase transport regimes. Eight drag models were selected, which included five heterogeneous drag models and three homogeneous drag models. Comparison with the available experimental data demonstrates the need for modification of homogeneous drag models to account for the effect of mesoscale structures (i.e., bubbles and clusters). The enhanced filtered drag model and energy-minimization multi-scale (EMMS) drag models were found to achieve superior predictions in all fluidization regimes, while the other drag models were only capable of predicting certain fluidization regimes. Finally, the results of this work provide a guideline for choosing appropriate drag models for simulating Geldart A particles and suggestions on developing more reliable and general drag models applicable in all flow regimes.

42 ENGINEERING↗

NASA NTRSDate not supplied

Computational Assessment of the Impact of Wave Count on Rotating Detonation Engine Performance

The impact of the number of azimuthally propagating waves on the performance of a Rotating Detonation Engine (RDE) is investigated using a simplified two-dimensional computational fluid dynamic simulation. The basic RDE configuration examined has no exit throat. The inlet is assumed lossless and does not allow backflow. The adiabatic, inviscid, and premixed simulation utilizes a particularly simple finite rate reaction mechanism that allows user control over the relative amounts of deflagration and detonation that occur, the presence and extent of a reaction delay associated with fuel and oxidizer mixing, and the number of waves present in the domain. The simplifications and idealizations decouple the effect of wave count from other potential loss mechanisms. Performance is measured using exhaust flow total pressure gain relative to the inlet total pressure. One, two, and three wave solutions are computed under identical boundary conditions and grid resolution. For simulations with no mixing delay and minimal deflagration, the number of waves present has negligible impact on performance. With a mixing delay, performance decreases with increasing wave number. With increased deflagration, performance increases with increasing wave number. With both effects simulated it is found that the two wave solution performs better than either the one or three wave solutions. The causes of these trends are explored. They imply that for practical, RDE’s, the number of waves that are present can impact performance.

Detonation↗

NASA NTRSDate not supplied

Computational Assessment of the Impact of Wave Count on Rotating Detonation Engine Performance

Detonation↗

DOE OSTI2021

A Network-Aware Distributed Energy Resource Aggregation Framework for Flexible, Cost-Optimal, and Resilient Operation

To efficiently use the ubiquitous behind-the-meter distributed energy resources (DERs) in distribution systems for providing grid services, this paper presents a hierarchical control framework for DER optimal aggregation and control. We first develop a convex optimization model to evaluate the DER flexibility, and then use a convex model-predictive-control based approach to dispatch those DERs. The hierarchical control framework consists of a utility controller, community aggregators and multiple home energy management systems. The flexibility of the DERs is evaluated by each controller in the hierarchy such that the resultant flexibility is feasible given its operational domain. Based on the determined flexibility, the hierarchical controllers then compute optimal setpoints for the DERs to help the distribution system regulate node voltages and provide other distribution grid services. Numerical simulations performed on a model of a real distribution feeder in Colorado, using actual DER data in a residential community demonstrate that the proposed approach can effectively alleviate voltage issues and support resilient operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Anatomy of a Summertime Convective Event over the Arabian Region

This study investigates the structure and evolution of a summertime convective event that occurred on 14 July 2015 over the Arabian region. We use the WRF Model with 1-km horizontal grid spacing and test three PBL parameterizations: the Mellor–Yamada–Nakanishi–Niino (MYNN) scheme; the Asymmetrical Convective Model, version 2, (ACM2) scheme; and the quasi-normal scale-elimination (QNSE) scheme. Convection initiates near the Al Hajar Mountains of northern Oman at around 1100 local time (LT; 0700 UTC) and propagates northwestward. A nonorographic convective band along the west coast of the United Arab Emirates (UAE) develops after 1500 LT as a result of the convergence of cold pools with the sea breeze from the Arabian Gulf. The model simulation employing the QNSE scheme simulates the convection initiation and propagation well. Although the MYNN and ACM2 simulations show convective initiation near the Al Hajar Mountains, they fail to simulate the development of the convective band along the UAE west coast. The MYNN run simulates colder near-surface temperatures and a weaker sea breeze, whereas the ACM2 run simulates a stronger sea breeze but a drier lower troposphere. Sensitivity simulations using horizontal grid spacings of 9 and 3 km show that lower-resolution runs develop broader convective structures and weaker cold pools and horizontal wind divergence, affecting the development of convection along the west coast of the UAE. The 1-km run using the QNSE PBL scheme realistically captures the sequence of events that leads to the moist convection over the UAE and adjacent mountains.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Co-simulation Framework for Community-scale Building-grid Integration [SWR-21-75]

Distributed energy resources (DERs), including rooftop solar, energy storage, and flexible loads, are gaining popularity as costs decline and as building owners and utilities realize their benefits. DERs can improve distribution system efficiency, help prevent the need for expensive grid upgrades, and increase the resilience of local communities. However, they can also cause difficulties in grid operations and can require controls to achieve their benefits. To address this challenge, NREL researchers have developed a community-scale solution that assesses the impacts of DERs and their control strategies on a distribution system. The framework has been shown to reduce solar photovoltaic (PV) curtailment to 0%, mitigate the adverse impact of solar variability on the distribution voltage, and provide up to 5-day critical load support during emergency events. Utilizing 5 different modules representing the feeder, buildings, home energy management systems, an aggregator, and a utility controller, NREL expects this simulation technology to play a critical role in the continued integration of DERs. According to the Energy Information Administration (EIA), solar curtailments accounted for 94% of the total energy curtailed in the California Independent System Operator (CAISO) in 2020. By enabling Independent System Operators (ISOs) and utility operators to bring solar curtailments to 0%, the electrical grid can become less dependent on fossil-fueled power generation sources. NREL's co-simulation framework contains five major components: Distribution Feeder Model: describes the distribution feeder topology using OpenDSS, including the locations of all DERs. Residential Building Model: simulates a large number of buildings at a high resolution using OCHRETM. The model is equipped to control equipment based on signals from an external module. The model includes major household appliances such as HVAC and a water heater, non-dispatchable load models, a distributed PV system, and a home battery system. Home Energy Management System: optimizes the controls for the devices in a home using foreseeTM. The control can adjust based on the user preferences including cost, comfort, and convenience. In hierarchical control scenarios, where the houses follow signals from an aggregator, the home energy management system provides a flexibility band with a range of power and follows the dispatch signals received from aggregator. Community-Level Aggregator: solves for optimal energy dispatch based on the flexibility bands received from each home and the grid service signal received from the utility controller. Utility-Level Controller: provides grid signals for voltage control using Distributed Energy Resources (DERs), such as solar systems, in the community.

Balamurugan, Sivasathya Pradha↗

NASA NTRS2002

Opportunities for Breakthroughs in Large-Scale Computational Simulation and Design

Opportunities for breakthroughs in the large-scale computational simulation and design of aerospace vehicles are presented. Computational fluid dynamics tools to be used within multidisciplinary analysis and design methods are emphasized. The opportunities stem from speedups and robustness improvements in the underlying unit operations associated with simulation (geometry modeling, grid generation, physical modeling, analysis, etc.). Further, an improved programming environment can synergistically integrate these unit operations to leverage the gains. The speedups result from reducing the problem setup time through geometry modeling and grid generation operations, and reducing the solution time through the operation counts associated with solving the discretized equations to a sufficient accuracy. The opportunities are addressed only at a general level here, but an extensive list of references containing further details is included. The opportunities discussed are being addressed through the Fast Adaptive Aerospace Tools (FAAST) element of the Advanced Systems Concept to Test (ASCoT) and the third Generation Reusable Launch Vehicles (RLV) projects at NASA Langley Research Center. The overall goal is to enable greater inroads into the design process with large-scale simulations.

Alexandrov, Natalia↗

DOE OSTI2023

A new coupling of a GPU-resident large-eddy simulation code with a multiphysics wind turbine simulation tool

The development of new wind farm control strategies can benefit from combined analysis of flow dynamics in the farm and the behavior of individual turbines within one simulation environment. In this work, we present such an environment by developing a new coupling between the large-eddy simulation (LES) code GRASP and the multiphysics wind turbine simulation tool OpenFAST via an actuator line model (ALM). In addition, the implementation of the recently proposed filtered actuator line model (FALM) within the coupling is described. The new ALM implementation is cross-verified with results from four other commonly used research LES codes. The results for the blade loads and the near wake obtained with the new coupling are consistent with the other codes. Deviations are observed in the far wake. The results further indicate that the FALM is able to reduce the lift and power overprediction from which the traditional ALM suffers on coarse LES grids. This new simulation environment paves the way for future wind farm simulations under realistic weather conditions by leveraging GRASP's ability to impose data from large-scale meteorological models as boundary conditions.

17 WIND ENERGY↗

DOE OSTI2023

A Transductive Graph Neural Network learning for Grid Resilience Analysis

Power grids are critical infrastructures that require robust resilience analysis to ensure reliable and uninterrupted electricity supply. Traditional simulation-based methods for grid resilience analysis suffer from computational complexity and limited ability to capture the full spectrum of potential disruptions. This paper presents a novel approach to enhance grid resilience by leveraging transductive graph neural network (GNN) learning to identify critical nodes and links. By leveraging the graph structure and system features, GNNs effectively learn resilience metrics and accurately identify critical nodes based on actual grid operational behavior. The efficacy of the proposed approach is demonstrated through case studies on node criticality scoring and critical node/line identification in cascading outage scenarios. The results highlight the advantages of learning-based methods over traditional simulation-based approaches and their potential to revolutionize grid resilience analysis. The contributions of this paper include a graph-based scalable approach for fast cascading analysis, an inductive formulation for training GNN models, and a transfer learning-based approach to scale the model to largescale power systems.

grid resilience, graph neural networks, transducti↗

DOE OSTI2017

Novel Control Strategy for Multiple Run-of-the-River Hydro Power Plants to Provide Grid Ancillary Services

Electricity generated by Hydropower Plants (HPPs) contributes a considerable portion of bulk electricity generation and delivers it with a low carbon footprint. In fact, HPP electricity generation provides the largest share from renewable energy resources, which includes solar and wind energy. The increasing penetration of wind and solar penetration leads to a lowered inertia in the grid and hence poses stability challenges. In recent years, breakthrough in energy storage technologies have demonstrated the economic and technical feasibility of extensive deployments in power grids. Multiple ROR HPPs if integrated with scalable, multi time-step energy storage so that the total output can be controlled. Although, the size of a single energy storage is far smaller than that of a typical reservoir, cohesively managing multiple sets of energy storage distributed in different locations is proposed. The ratings of storages and multiple ROR HPPs approximately equals the rating of a large, conventional HPP. The challenges associated with the system architecture and operation are described. Energy storage technologies such as supercapacitors, flywheels, batteries etc. can function as a dispatchable synthetic reservoir with a scalable size of energy storage will be integrated. Supercapacitors, flywheels, and battery are chosen to provide fast, medium, and slow responses to support grid requirements. Various dynamic and transient power grid conditions are simulated and performances of integrated ROR HPPs with energy storage is provided. The end goal of this research is to investigate the inertial equivalence of a large, conventional HPP with a unique set of multiple ROR HPPs and optimally rated energy storage systems.

13 HYDRO ENERGY↗

DOE OSTI2024

Enhancing Extreme Precipitation Predictions With Dynamical Downscaling: A Convection‐Permitting Modeling Study in Texas and Oklahoma

Precipitation in the Southern Plains of the United States is relatively well depicted by the Community Earth System Model (CESM). However, despite its ability to capture seasonal mean precipitation anomalies, CESM consistently underestimates extreme pluvial and drought events, rendering it an insufficient tool for extending simulation lead times for exceptional events, such as the abnormally dry May 2011, which helped drive Texas into its worst period of drought in more than a century, and the abnormally wet May 2015, which led to widespread flooding in that state. Ensemble‐based regional climate experiments are completed for the two extreme years using Weather Research and Forecasting model (WRF) and downscaled from CESM. WRF simulations are at convection‐permitting grid resolution for improved physical representation of simulated precipitation over the Southern Great Plains. By integrating convection‐permitting models (CPMs) into each individual member of a CESM ocean data assimilation ensemble, this study demonstrates that high‐resolution dynamical downscaling can improve model skillfulness at capturing these two events and is thus a potentially useful tool for forecasting extremely high and extremely low precipitation events at subseasonal or even seasonal lead times.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) was successful at producing a baseline multi-model assessment of global simulations with model grid spacings of 25–50 km in the atmosphere and 10–25 km in the ocean, a significant increase when compared to models with standard resolutions on the order of 1° that are typically used as part of the Coupled Model Intercomparison Project (CMIP) experiments. In addition to over 250 peer-reviewed manuscripts using the published HighResMIP1 datasets, the results were widely cited in the Intergovernmental Panel on Climate Change report and were the basis of a variety of derived datasets, including tracked cyclones (both tropical and extratropical), river discharge, storm surge, and impact studies. There were also suggestions from the few ocean eddy-rich coupled simulations that aspects of climate variability and change might be significantly influenced by improved process representation in such models. The compromises that HighResMIP1 made should now be revisited, given the recent major advances in modelling and computing resources. Aspects that will be reconsidered include experimental design and simulation length, complexity, and resolution. In addition, larger ensemble sizes and a wider range of future scenarios would enhance the applicability of HighResMIP. Therefore, we propose the High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) to improve and extend the previous work, to address new science questions, and to further advance our understanding of the role of horizontal resolution (and hence process representation) in state-of-the-art climate simulations. With further increases in high-performance computing resources and modelling advances, along with the ability to take full advantage of these computational resources, an enhanced investigation of the drivers and consequences of variability and change in both large- and synoptic-scale weather and climate is now possible. With the arrival of global cloud-resolving models (currently run for relatively short timescales), there is also an opportunity to improve links between such models and more traditional CMIP models, with HighResMIP providing a bridge to link understanding between these domains. HighResMIP also aims to link to other CMIP projects and international efforts such as the World Climate Research Program lighthouse activities and various digital twin initiatives. It also has the potential to be used as training and validation data for the fast-evolving machine learning climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Including Dust Coagulation in Hydrodynamic Models of Protoplanetary Disks: Dust Evolution in the Vicinity of a Jupiter-mass Planet

Dust growth is often neglected when building models of protoplanetary disks due to its complexity and computational expense. However, it does play a major role in shaping the evolution of protoplanetary dust and planet formation. In this paper, we present a numerical model coupling 2D hydrodynamic evolution of a protoplanetary disk, including a Jupiter-mass planet, and dust coagulation. This is obtained by including multiple dust fluids in a single grid-based hydrodynamic simulation and solving the Smoluchowski equation for dust coagulation on top of solving for the hydrodynamic evolution. We find that fragmentation of dust aggregates trapped in a pressure bump outside of the planetary gap leads to an enhancement in the density of small grains. Additionally, we compare the results obtained from the full-coagulation treatment to the commonly used, fixed-dust-size approach and to previously applied, less computationally intensive methods for including dust coagulation. We find that the full-coagulation results cannot be reproduced using the fixed-size treatment, but some can be mimicked using a relatively simple method for estimating the characteristic dust size in every grid cell.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Uncertainty quantification in LES of channel flow

Here, in this paper, we present a Bayesian framework for estimating joint densities for large eddy simulation (LES) sub-grid scale model parameters based on canonical forced isotropic turbulence direct numerical simulation (DNS) data. The framework accounts for noise in the independent variables, and we present alternative formulations for accounting for discrepancies between model and data. To generate probability densities for flow characteristics, posterior densities for sub-grid scale model parameters are propagated forward through LES of channel flow and compared with DNS data. Synthesis of the calibration and prediction results demonstrates that model parameters have an explicit filter width dependence and are highly correlated. Discrepancies between DNS and calibrated LES results point to additional model form inadequacies that need to be accounted for.

97 MATHEMATICS AND COMPUTING↗