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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 55 records · Page 3

Architecture for Quantum-in-the Loop Real-Time Simulations for Designing Resilient Smart Grids

With the power grid growing more complex every day with the inclusion of new sensors and regulatory approvals that enable end-users and small local developers to participate in the grid, it is becoming challenging for conventional smart grid simulation, emulation, and testing technologies to keep up. In this work, we propose that quantum-encoded real-time simulations can be helpful under the new paradigm and operational circumstances to solve optimization problems for power grids. By leveraging the principles of quantum mechanics, the proposed quantum-in-loop (QIL) framework will enable better and faster optimization solutions based on real-world, real-time data streams, facilitating the real-time planning and operations of electrical grids that rely on millions of distributed sensors and controllers. Furthermore, QIL will allow researchers and engineers to assist utilities in designing, developing, and de-risking algorithms to optimize power grid operation and resilience by considering inputs from millions of grid-connected devices. QIL framework is being developed to have a self-limiting triage mechanism, which will help engineers and practitioners identify fundamental physical limits on quantum processors, revealing what quantum algorithms can and cannot do in utility-specific use cases and must continue to count on classical high-performance computing infrastructure.

digital real-time simulation↗

Revised Kimberlina Groundwater Simulations

Kimberlina Groundwater Qaulity Simulations (Version 3: 2015 October) by Lawrence Livermore National Labratory. Submitted to the EDX team at the National Energy Technology Laboratory for research use. This dataset contains 562 updated groundwater quality simulations based on the Kimberlina site. It is a six-layer model including the aquifers and aquitards inbetween the ground surface and the reservoir. The input files and associated leakage information for these simulations are included in the zip file "nrap_kim_well31_fluxes and inputs.tar.gz". These 562 simulations are the successful results out of 1000 monte carlo simulations, with time length greater than 5 years. Each simulation consists 6 output files, therefore, there are 3372 files (6*562) in total. One single example simulation of full time length (200 year) is also provided in the zip file "single_simulation_200yr_sim0012.tar.gz". These 6 groundwater quality parameters are: - pH (use absolute value) - TDS (mg/kg) - Pressure (Pa) - CO2 Liquid Saturation (fraction range 0.0-1.0) - CO2 Gas Concentration (mol/L) - CO2 Liquid Concentration (mol/kg) Their correponding file names, take the first simulation for example, are: ph0001.ntab (for pH) , tds0001.ntab (for TDS), usnt0001.p.ntab (for pressure), usnt0001.s_liquid.ntab (for liquid saturation), usnt0001.c_co2_gas.ntab (for CO2 gas concentration) and usnt0001.c_co2_liquid.ntab (for CO2 liquid concentration). Each output file contains at least 19 columns (variables). The total number of columns depends on the simulation time length. The column data include the information of numerical records, geologic location and sizes and the simulated parameter values over time. The first 13 variables are about numerical records and relative geologic information for a simulation grid: 1. index: simulation index 2. i: the ith grid of x-axis 3. j: the jth grid of y-axis 4. k: the kth grid of z-axis 5. element_ref: element type reference 6. nuft_ind: nuft index 7. x: grid location in the x axis direction 8. y: grid location in the y axis direction 9. z: grid location in the z axis direction 10. dx: grid length in the x axis direction 11. dy: grid length in the y axis direction 12. dz: grid length in the z axis direction 13. volume: volume of the simulation grid The rest (14, 15, 16...) variables are the simulated parameter values over time, take pH as an example, are: 14. ph000y: initial pH value. 15. ph001y: simulated pH value at the end of the 1st year. 16. ph002y: simulated pH value at the end of the 2nd year. ... (and so on)... The zip input files have the input fluxes of brine and CO2 (in kg/s) allocated to model layers 1,2,3 and 5 (layers 4 and 6 are assumed to be no-flow aquitards) through the following nodes: (src1 WELL 7 7 25 25 10 32) #Etchegoin (src2 WELL 7 7 25 25 33 72) #Macoma Chanac (src3 WELL 7 7 25 25 73 83) #Santa Margarita Mclure (src4 WELL 7 7 25 25 84 89) #Fruitvale Round Mountain (aquitard) (src5 WELL 7 7 25 25 90 96) #Olcese Sand (thief zone) (src6 WELL 7 7 25 25 97 99) #tremblor Freeman (aquitard) ex: brn1 is assigned to src 1 from i=(7,7), j=(25,25), k=(10,32) Edited by Ya-Mei Yang at National Energy Technology Laboratory

brine leakage↗

Thread Group Multithreading: Accelerating the Computation of an Agent-Based Power System Modeling and Simulation Tool -- C GridLAB-D

GridLAB-DTM is an open source next generation agent-based smart-grid simulator that provides unprecedented capability to model the performance of smart grid technologies. Over the past few years, GridLAB-D has been used to conduct important analyses of smart grid concepts, but it is still quite limited by its computational performance. In order to break through the performance bottleneck to meet the need for large scale power grid simulations, we develop a thread group mechanism to implement highly granular multithreaded computation in GridLAB-D. We achieve close to linear speedups on multithreading version compared against the single-thread version of the same code running on general purpose multi-core commodity for a benchmark simple house model. The performance of the multithreading code shows favorable scalability properties and resource utilization, and much shorter execution time for large-scale power grid simulations.

Jin, Shuangshuang↗

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. However, cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree. In this paper, we present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a large parallel system without full physical duplication of computation and memory. The performance of a prototype implementation executed on up to 1,024 graphical processing units of a supercomputing system has been evaluated with three benchmarks—heat diffusion, forest fire, and disease propagation models—delivering a speed up of over two orders of magnitude compared to replicated runs. Finally, the results demonstrate a significantly faster and scalable way to execute many what-if scenario ensembles of large simulations via cloning using the CloneX interface.

97 MATHEMATICS AND COMPUTING↗

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

Grid operators are now considering using distributed energy resources (DERs) to provide distribution voltage regulation rather than installing costly voltage regulation hardware. DER devices include multiple adjustable reactive power control functions, so grid operators have the difficult decision of selecting the best operating mode and settings for the DER. In this work, we develop a novel state estimation-based particle swarm optimization (PSO) for distribution voltage regulation using DER-reactive power setpoints and establish a methodology to validate and compare it against alternative DER control technologies (volt–VAR (VV), extremum seeking control (ESC)) in increasingly higher fidelity environments. Distribution system real-time simulations with virtualized and power hardware-in-the-loop (PHIL)-interfaced DER equipment were run to evaluate the implementations and select the best voltage regulation technique. Each method improved the distribution system voltage profile; VV did not reach the global optimum but the PSO and ESC methods optimized the reactive power contributions of multiple DER devices to approach the optimal solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Stability and Fidelity of Power-Hardware-in-the-Loop Using NREL's CGI

The presentation focuses on dynamic analysis of power hardware-in-the-loop (PHIL) experiments using National Renewable Energy Laboratory Flatirons Campus' grid simulator - 7MVA Controllable Grid Interface (CGI). A control diagram of typical PHIL experiment is described, and transfer functions of critical components are explained. An impedance-based definition of PHIL experiment bandwidth is defined using open loop transfer functions of the system. Further an example resistive divider circuit is introduced that is used to explain implication of PHIL on accuracy of simulation by comparing measured results against ideal expected signals. At the end the real-life PHIL simulation using Maui power system model is described showing various oscillation modes observed and discussing the meaning of these in context of dynamic bandwidth of simulation.

grid simulator↗

Assessment of mesoscale solid stress in coarse‐grid TFM simulation of Geldart A particles in all fluidization regimes

This study focused on assessing the effect of mesoscale solid stress in the coarse grid two‐fluid model (TFM) simulation of gas–solid fluidized beds of Geldart Group A particles over a broad range of flow regimes, including bubbling, turbulent, fast, and pneumatic transport fluidization regimes. Particularly, the impact of mesoscale solid pressure, mesoscale solid viscosity, and mesoscale solid stress anisotropy were investigated by comparing six different coarse‐grid TFM settings. Compared with the available experimental data, it is found that both the kinetic theory‐based TFM with only drag correction and the filtered TFM can predict the flow behavior in all fluidization regimes. Mesoscale solid pressure and viscosity have the opposite impact on flow hydrodynamics; they compete and offset each other, which confirms the assumption employed in many previous studies that the mesoscale solid stress could be neglected in coarse‐grid TFM simulation. Published 2018. This article is a U.S. Government work and is in the public domain in the USA. AIChE J , 64: 3565–3581, 2018

Gao, Xi↗

NREL and Clemson University Drivetrain Test Facility Collaboration: Cooperative Research and Development Final Report, CRADA Number CRD-13-509

The National Renewable Energy Laboratory (NREL) and Clemson University have a mutual interest in collaborating in the development of wind turbine drivetrain testing facilities and grid simulators. NREL and Clemson University will work together to share resources and experiences in the development of future wind energy test facilities and capabilities. The CRADA includes sharing of facility topologies and capabilities, modeling efforts, commissioning plans, test protocols, infrastructure cost data, test plans, pro forma contracting instruments, and safe operating strategies. Further, NREL and Clemson University will exchange staff for training and development purposes, including collaborative participation in commissioning and customer testing. DOE has provided NREL with over 10 years of support in developing custom facilities and capabilities to enable testing of full-scale integrated wind turbine drivetrain systems in accordance with the needs of the US wind industry. NREL currently operates a 2.5MW dynamometer and is in the processes of building a 5MW dynamometer and a grid simulator (referred to as a 'Controllable Grid Interface' or CGI). Clemson University is currently building a drivetrain testing facility with two dynamometers, 7.5 MW and 15 MW, and 15 MW Hardware in the loop grid simulator.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Dynamic Temporal Graph Sequence Data for Resilience-Oriented Distribution Network Reconfiguration

This dataset comprises temporal dynamic graph sequences generated from power grid simulations focused on grid reconfiguration to enhance resilience. The simulations model failure propagation under varying conditions, with nodes assigned distinct failure probabilities. For each time step, the dataset captures the evolution of node states (functional or failed) and features critical to grid operations, such as pv_output, load_profile, load_dispatch, dg_output, loss, and voltage. Node types include sources, normal loads, and nodes with specific equipment like PVs, micro turbines, or shunt capacitors. The dataset is structured to support the training of dynamic graph neural networks, facilitating research on node feature prediction and edge dynamics under failure scenarios. Three distinct configurations are included, providing a robust foundation for modeling power grid resilience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Synchronization Algorithms for Co-Simulation of Power Grid and Communication Networks

The ongoing modernization of power grids consists of integrating them with communication networks in order to achieve robust and resilient control of grid operations. To understand the operation of the new smart grid, one approach is to use simulation software. Unfortunately, current power grid simulators at best utilize inadequate approximations to simulate communication networks, if at all. Cooperative simulation of specialized power grid and communication network simulators promises to more accurately reproduce the interactions of real smart grid deployments. However, co-simulation is a challenging problem. A co-simulation must manage the exchange of informa- tion, including the synchronization of simulator clocks, between all simulators while maintaining adequate computational perfor- mance. This paper describes two new conservative algorithms for reducing the overhead of time synchronization, namely Active Set Conservative and Reactive Conservative. We provide a detailed analysis of their performance characteristics with respect to the current state of the art including both conservative and optimistic synchronization algorithms. In addition, we provide guidelines for selecting the appropriate synchronization algorithm based on the requirements of the co-simulation. The newly proposed algorithms are shown to achieve as much as 14% and 63% im- provement, respectively, over the existing conservative algorithm.

co-simulation↗

Simulating dispatchable grid services provided by flexible building loads: State of the art and needed building energy modeling improvements

End-use electrical loads in residential and commercial buildings are evolving into flexible and cost-effective resources to improve electric grid reliability, reduce costs, and support increased hosting of distributed renewable generation. This article reviews the simulation of utility services delivered by buildings for the purpose of electric grid operational modeling. We consider services delivered to (1) the high-voltage bulk power system through the coordinated action of many, distributed building loads working together, and (2) targeted support provided to the operation of low-voltage electric distribution grids. Although an exhaustive exploration is not possible, we emphasize the ancillary services and voltage management buildings can provide and summarize the gaps in our ability to simulate them with traditional building energy modeling (BEM) tools, suggesting pathways for future research and development.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Inferring Neutron Star Merger Ejecta Morphology with Kilonovae

In this study we incorporate a new grid of kilonova simulations produced by the Monte Carlo radiative transfer code SuperNu in an inference pipeline for astrophysical transients and evaluate their performance. These simulations contain four different two-component ejecta morphology classes. We analyze follow-up observational strategies by Vera Rubin Observatory in optical and James Webb Space Telescope (JWST) in mid-infrared (MIR). Our analysis suggests that, within these strategies, it is possible to discriminate between the four different morphologies only when late-time JWST observations in MIR are available. We conclude that follow-ups by the new Vera Rubin Observatory alone are not sufficient to determine ejecta morphology. Additionally, we make comparisons between surrogate models based on radiative transfer simulation grids by SuperNu and POSSIS, by analyzing the historic kilonova AT2017gfo that accompanied the gravitational wave event GW170817. We show that both SuperNu and POSSIS models provide similar fits to photometric observations but their qualitative interpretations differ.

79 ASTRONOMY AND ASTROPHYSICS↗

2024.03.13 Bushing Subcommittee presentation on Transformer Bushing Seismic Resilience: Design, Hazard, & Prevention Analysis [Slides]

Presents results from power grid simulations on synthetic grids that estimate the impact from power transformer failures due to earthquakes. In the best-case scenario, there is an 82.9% likelihood of load loss greater or equal to 51 MW. Methodologies are described as well as path forward to improving transformer resilience and, consequently, the resilience of the bulk power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗

City-Wide Distributed Roof-Top Photovoltaic System Adoption Forecast, Grid Impact Simulation, & Neighborhood Microgrid Contribution Assessment

The adoption of distributed photovoltaic (PV) systems grew significantly in recent years. Market projections anticipate future growth for both residential and commercial installations. To understand grid impacts associated with distributed PV, useful hosting capacity studies require accurate representations of the spatial distribution of PV adoptions. Prediction of PV locations and numbers depends on median income data, building use zoning maps, and permit records to understand existing trends and predict future adoption rates and locations throughout an entire city. Using the PV adoption data, advanced and realistic simulations were performed to capture the distributed PV impacts on the grid. Also, using graph theory community detection hundreds of neighborhood microgrids can be discovered for the entire city by identifying densely connected loads that are sparsely connected to other communities. Then, based on the PV adoption predictions, this work identified the contribution of PV within each of the newly discovered graph theory defined microgrid communities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Clemson University Wind Turbine Drivetrain Test Facility

In November of 2009, Clemson University was awarded a competitive grant from the U.S. Department of Energy to design, build and operate a facility for full-scale, highly accelerated mechanical testing of next-generation wind turbine drivetrain technologies. The primary goal of the project was to design, construct, commission, and operate a state-of-the-art sustainable facility that permits full-scale highly accelerated testing of advanced drivetrain systems for large wind turbines. The secondary goal was to meet the objectives of the American Recovery and Reinvestment Act of 2009, especially in job creation, and provide a positive impact on economically distressed areas in the United States, and preservation and economic recovery in an expeditious manner. The project was executed according to a managed cooperative agreement with the Department of Energy and was an extraordinary success. The resultant new facility is located in North Charleston, SC, providing easy transportation access by rail, road or ship and operates on an open access model such that it is available to the U.S. Wind Industry for research, analysis, and evaluation activities. The 72 m by 97 m facility features two mechanical dynamometer test bays for evaluating the torque and blade dynamic forces experienced by the rotors of wind turbine drivetrains. The dynamometers are rated at 7.5 MW and 15 MW of low speed shaft power and are configured as independent test areas capable of simultaneous operation. All six degrees of freedom, three linear and three rotational, for blade and rotor dynamics are replicated through the combination of a drive motor, speed reduction gearbox and a controllable hydraulic load application unit (LAU). This new LAU setup readily supports accelerated lifetime mechanical testing and load analysis for the entire drivetrain system of the nacelle and easily simulates a wide variety of realistic operating scenarios in a controlled laboratory environment. The development of these two dynamometer test rigs is the first significant achievement for the project. These test rigs embody a new manner of test due to the system configuration and completely new design with a free floating loading hub in the LAU. This project provided the catalyst for the advancement to this new test rig configuration that has been adopted by every significant wind turbine test rig constructed since the inception of this project. There are currently two different vendors supplying these new systems. Catalyzing this new design is the second major success of the project. With the increased market penetration of wind energy over the past decade, many regions and countries have developed specific electrical grid specifications and performance codes for large wind farms to ensure operational reliability and stability. These grid codes provide requirements for interconnection with the grid during low or high voltage phenomena, typically encountered during and after system fault events. Given the installed infrastructure of the Wind Turbine Drivetrain Testing Facility (WTDTF), a natural expansion of facility capability was to include the necessary equipment for performing fault ride-through evaluations of wind turbines to the Low Voltage Ride Through (LVRT) codes. Once the decision was made to expand the scope of the original grant into fault ride-through testing, it was clear that there are several markets, not just wind, which could benefit from this type of test and that simple fault ride-through testing could be extended into a broader scope of electrical testing capabilities. It was at this point that Clemson University was awarded a second grant to build a 15 MW Hardware-In-the-Loop (HIL) Grid Simulator in order to establish world class electrical testing capabilities to compliment the mechanical testing at the WTDTF. This third significant achievement resulted in the 15 MW HIL Grid Simulator as the corner stone of the Duke Energy eGRID Center and is collocated with the WTDTF in the SCE&G Energy Innovation Center at the new Facility in North Charleston, SC, USA. Before the eGRID was completed, it was recognized that the ability to test solar farm equipment was but a small step away thru the addition of enhanced equipment to provide for DC testing. In yet another expansion/success, a 2.5 MW rectifier system was designed and implemented by Clemson staff to enhance the Center’s capabilities. The program required over 250,000 man-hours of on-site construction labor reworking the brownfield facility on the former Navy Base, clearly satisfying one of the major goals of the Reinvestment Act. This was done while winning numerous awards for design and construction of the facility, including the Top US Project for 2014 from the Trade Journal Engineering News Record. The project was a major collaborative developmental activity managed by Clemson University staff that involved the DOE and many partners and organizations.

17 WIND ENERGY↗

A Nonlinear Algebraic Multigrid Framework for the Power Flow Equations

Multigrid is a highly scalable class of methods most often used for solving large linear systems. In this paper we develop a nonlinear algebraic multigrid framework for the power flow equations, a complex quadratic system of the form ${diag}({v})\overline{Y{v}}={s}$, where $Y$ is approximately a complex scalar rotation of a real graph Laplacian. This is a standard problem that needs to be solved repeatedly during power grid simulations. A key difference between our multigrid framework and typical multigrid approaches is the use of a novel multiplicative coarse-grid correction to enable a dynamic multigrid hierarchy. We also develop a new type of smoother that allows one to coarsen together the different types of nodes that appear in power grid simulations. In developing a specific multigrid method, one must make a number of choices that can significantly affect the method's performance, such as how to construct the restriction and interpolation operators, what smoother to use, and how aggressively to coarsen. In this paper, we make simple but reasonable choices that result in a scalable and robust power flow solver. Experiments demonstrate this scalability and show that it is significantly more robust to poor initial guesses than current state-of-the-art solvers.

97 MATHEMATICS AND COMPUTING↗

Short-term wind forecasting using statistical models with a fully observable wind flow

The utility of model output data from the Weather Research and Forecasting mesoscale model is explored for very short-term forecasting (5-30 minutes horizon) of wind speed to be used in large scale simulations of an autonomous electric power grid. Using this synthetic data for the development and evaluation of short-term forecasting algorithms offer many unique advantages over observational data, such as the ability to observe the full wind flow field in the surrounding region. Several short-term forecasting algorithms are implemented and evaluated using the synthetic data at several different time horizons and for three different geographic locations. Comparison is made with observational data from one location. We find that short-term forecasts of the synthetic data considering wind flow from the surrounding region perform 26% better than persistence in terms of root mean square error at the 5-minute time horizon. This improvement is comparable to studies of observational data in the literature. These results provide motivation to use synthetic data for short term forecasting in grid simulations, and open the door to future algorithmic improvements.

17 WIND ENERGY↗