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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↗

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↗

DOE OSTI2019

A multi-scale experimental investigation of flow properties in coarse-grained hydrate reservoirs during production (Final Scientific/Technical Report)

In this project, “A multi-scale experimental investigation of flow properties in coarse-grained hydrate reservoirs during production” we explored the relative permeability and dissipation behavior of hydrate-bearing coarse-grained sediment at the core scale and we observed the formation and dissociation of these materials at the pore scale with micro-CT and Raman experiments. The 3-year project results inform reservoir simulation efforts, critical to determining the viability of the coarse-grained hydrate reservoir as an energy resource. We performed the first 3 phase relative permeability experiments in a hydrate-bearing medium using the steady state method (gas and water flow in the presence of hydrate). Results support a model where water is the most wetting phase, hydrate is the intermediate wetting phase, and gas is the least wetting phase. This model can be used to predict relative permeability of gas and water in the presence of hydrate. We showed that when hydrate dissociates, it does so at a pressure and temperature predicted for fresh water (no salinity) conditions. At the scale of a grid block, reservoir simulation models should assume that hydrate dissociates at the freshwater phase boundary. We observed that the chemistry and the pore habit of methane hydrates change dramatically over the timescales of experiments (hours to weeks). It takes weeks to months for hydrates to evolve from a non-stoichiometric to stoichiometric compound with 3:1 large cage vs small cage occupancy. We documented hydrates forming initially in small clayey silt surfaces but gradually concentrated in large pores in sand-sized sediment.

03 NATURAL GAS↗

DOE OSTI2018

Simulation-Based Parameter Optimization Framework for Large-Scale Hybrid Smart Grid Communications Systems Design

The design of reliable, dynamic, fault-tolerant hybrid smart grid communication networks is a challenge to achieve for autonomous power grids. Hybrid networks use different communications technologies for different area networks. A simulation-based parameter optimization framework is proposed to tune parameters of hybrid communication technologies to achieve the optimal network performance. It consists of three main components: a parallel executor used to speedup a list of simulations; a sampler running simulations using the parallel executor at each generation; and a hybrid stochastic optimization algorithm for tuning configurable parameters of hybrid designs and applications. The proposed hybrid metaheuristic optimization algorithm combines an evolutionary algorithm with a gradient method to quickly achieve an approximately global optimum solution. Three optimization test functions are employed to train the adjustable parameters of the hybrid algorithm. Results show the proposed parameter optimization framework can help the designer choose the right hybrid architecture with an optimal parameter set for a large-scale broadband PLC-WiMAX hybrid smart grid communication network.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

CFD simulations of circulating fluidized bed risers, part I: Grid study(Reprinted from Powder Technology, vol 254, pg 170-180, 2014)

Explore the source record for details and available documents.

Circulating fluidized bed↗

DOE OSTI2016

Characterization of the High-Speed-Stage Bearing Skidding of Wind Turbine Gearboxes Induced by Dynamic Electricity Grid Events: Preprint

Bearing behavior is an important factor for wind turbine drivetrain reliability. Extreme loads and dynamic excitations pose challenges to the bearing design and therefore its performance. Excessive skidding of the bearing rollers should be avoided because it can cause scuffing failures. Excitations coming from wind and the electricity grid can subject the drivetrain to fluctuating torque and nontorque loads. Wind-induced excitations have been investigated predominantly in literature. However, modern wind turbines are subjected more and more to grid-induced loads because of stricter electricity grid regulations. For example, during fault-ride-through events, turbines are required to stay connected for a longer period of time during the grid failure. This work investigates the influence of electrically induced excitations on the skidding behaviour of the tapered roller bearings on the high-speed stage of a wind turbine gearbox. This skidding behaviour during dynamic events is described as a potential bearing failure initiator by many researchers; however, only limited full-scale dynamic testing is documented. Therefore, a dedicated gridloss-type event is defined in the paper and conducted in a dynamometer test on a full-scale wind turbine nacelle. During the event, a complete electricity grid failure is simulated while the turbine is at rated speed and predefined torque levels. Particular focus is on the characterization of the high-speed shaft tapered roller bearing slip behavior. Strain-gauge bridges in grooves along the circumference of the outer ring are used to characterize the bearing load zone in detail. It is shown that during the torque reversals of the transient event, roller slip can be induced. This indicates the potential of the applied load case to go beyond the preload of the tapered roller bearing. Furthermore, the relation between the applied torque and skidding level is studied.

17 WIND ENERGY↗

DOE OSTI2016

Characterization of the High-Speed-Stage Bearing Skidding of Wind Turbine Gearboxes Induced by Dynamic Electricity Grid Events

17 WIND ENERGY↗

DOE OSTI2015

Atomic chemistry in turbulent astrophysical media. I. EFFECT OF Atomic cooling

We carry out direct numerical simulations of turbulent astrophysical media that explicitly track ionizations, recombinations, and species-by-species radiative cooling. The simulations assume solar composition and follows the evolution of hydrogen, helium, carbon, oxygen, sodium, and magnesium, but they do not include the presence of an ionizing background. In this case, the medium reaches a global steady state that is purely a function of the one-dimensional turbulent velocity dispersion, σ{sub 1D}, and the product of the mean density and the driving scale of turbulence, nL. Our simulations span a grid of models with σ{sub 1D} ranging from 6 to 58 km s{sup −1} and nL ranging from 10{sup 16} to 10{sup 20} cm{sup −2}, which correspond to turbulent Mach numbers from M = 0.2 to 10.6. The species abundances are well described by single-temperature estimates whenever M is small, but local equilibrium models can not accurately predict the global equilibrium abundances when M≳1. To allow future studies to account for nonequilibrium effects in turbulent media, we gather our results into a series of tables, which we will extend in the future to encompass a wider range of elements, compositions, and ionizing processes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Foresee: A user-centric home energy management system for energy efficiency and demand response

This paper presents foresee, a user-centric home energy management system that can help optimize how a home operates to concurrently meet users' needs, achieve energy efficiency and commensurate utility cost savings, and reliably deliver grid services based on utility signals. Foresee is built on a multiobjective model predictive control framework, wherein the objectives consist of energy cost, thermal comfort, user convenience, and carbon emission. Foresee learns user preferences on different objectives and acts on their behalf to operate building equipment, such as home appliances, photovoltaic systems, and battery storage. In this work, machine-learning algorithms were used to derive data-driven appliance models and usage patterns to predict the home's future energy consumption. This approach enables highly accurate predictions of comfort needs, energy costs, environmental impacts, and grid service availability. Simulation studies were performed on field data from a residential building stock data set collected in the Pacific Northwest. Results indicated that foresee generated up to 7.6% whole-home energy savings without requiring substantial behavioral changes. When responding to demand response events, foresee was able to provide load forecasts upon receipt of event notifications and delivered the committed demand response services with 10% or fewer errors. Foresee fully utilized the potential of the battery storage and controllable building loads and delivered up to 7.0-kW load reduction and 13.5-kW load increase. As a result, these benefits are provided while maintaining the occupants' thermal comfort or convenience in using their appliances.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Density effects on post-shock turbulence structure and dynamics

Turbulence structure resulting from multi-fluid or multi-species, variable-density isotropic turbulence interaction with a Mach 2 shock is studied using turbulence-resolving shock-capturing simulations and Eulerian (grid) and Lagrangian (particle) methods. The complex roles that density plays in the modification of turbulence by the shock wave are identified. Statistical analyses of the velocity gradient tensor (VGT) show that density variations significantly change the turbulence structure and flow topology. Specifically, a stronger symmetrization of the joint probability density function (PDF) of second and third invariants of the anisotropic VGT, PDF $(Q^{\ast },R^{\ast })$ , as well as the PDF of the vortex stretching contribution to the enstrophy equation, are observed in the multi-species case. Furthermore, subsequent to the interaction with the shock, turbulent statistics also acquire a differential distribution in regions having different densities. This results in a nearly symmetric PDF $(Q^{\ast },R^{\ast })$ in heavy-fluid regions, while the light-fluid regions retain the characteristic tear-drop shape. To understand this behaviour and the return to ‘standard’ turbulence structure as the flow evolves away from the shock, Lagrangian dynamics of the VGT and its invariants is studied by considering particle residence times and conditional particle variables in different flow regions. The pressure Hessian contributions to the VGT invariants transport equations are shown to be not only affected by the shock wave, but also by the density in the multi-fluid case, making them critically important to the flow dynamics and turbulence structure.

42 ENGINEERING↗

DOE OSTI2015

Evidence for Bolgiano-Obukhov scaling in rotating stratified turbulence using high-resolution direct numerical simulations

We report results on rotating stratified turbulence in the absence of forcing, with large-scale isotropic initial conditions, using direct numerical simulations computed on grids of up to $4096^3$ points. The Reynolds and Froude numbers are respectively equal to $Re=5.4\times 10^4$ and $Fr=0.0242$. The ratio of the Brunt-V\"ais\"al\"a to the inertial wave frequency, $N/f$, is taken to be equal to 5, a choice appropriate to model the dynamics of the southern abyssal ocean at mid latitudes. This gives a global buoyancy Reynolds number $R_B=ReFr^2=32$, a value sufficient for some isotropy to be recovered in the small scales beyond the Ozmidov scale, but still moderate enough that the intermediate scales where waves are prevalent are well resolved. We concentrate on the large-scale dynamics and confirm that the Froude number based on a typical vertical length scale is of order unity, with strong gradients in the vertical. Two characteristic scales emerge from this computation, and are identified from sharp variations in the spectral distribution of either total energy or helicity. A spectral break is also observed at a scale at which the partition of energy between the kinetic and potential modes changes abruptly, and beyond which a Kolmogorov-like spectrum recovers. Large slanted layers are ubiquitous in the flow in the velocity and temperature fields, and a large-scale enhancement of energy is also observed, directly attributable to the effect of rotation.

Bolgiano-Obukhov↗