Resilient Adaptive Parallel sImulator for griD (RAPID): An Open Source Power System Simulation Toolbox
Not Available
42 ENGINEERING↗
SEARCH · Search NASA
Results for “grid simulation”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
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↗
Numerical simulation of a powered-lift landing, tracking flow features using overset grids, and simulation of high lift devices on a fighter-lift-and-control wing
Attached as appendices to this report are documents describing work performed on the simulation of a landing powered-lift delta wing, the tracking of flow features using overset grids, and the simulation of flaps on the Wright Patterson Lab's fighter-lift-and-control (FLAC) wing. Numerical simulation of a powered-lift landing includes the computation of flow about a delta wing at four fixed heights as well as a simulated landing, in which the delta wing descends toward the ground. Comparison of computed and experimental lift coefficients indicates that the simulations capture the qualitative trends in lift-loss encountered by thrust-vectoring aircraft operating in ground effect. Power spectra of temporal variations of pressure indicate computed vortex shedding frequencies close to the jet exit are in the experimentally observed frequency range; the power spectra of pressure also provide insights into the mechanisms of lift oscillations. Also, a method for using overset grids to track dynamic flow features is described and the method is validated by tracking a moving shock and vortices shed behind a circular cylinder. Finally, Chimera gridding strategies were used to develop pressure coefficient contours for the FLAC wing for a Mach no. of 0.18 and Reynolds no. of 2.5 million.
Chawla, Kalpana↗
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↗
Grid-Stretching Capability for the GEOS-Chem 13.0.0 Atmospheric Chemistry Model
Modeling atmospheric chemistry at fine resolution globally is computationally expensive; the capability to focus on specific geographic regions using a multi scale grid is desirable. Here, we develop, validate, and demonstrate stretched grids in the GEOS-Chem atmospheric chemistry model in its high-performance implementation (GCHP). These multiscale grids are specified at runtime by four parameters that offer users nimble control of the region that is refined and the resolution of the refinement. We validate the stretched-grid simulation versus global cubed-sphere simulations. We demonstrate the operation and flexibility of stretched-grid simulations with two case studies that compare simulated tropospheric NO2column densities from stretched-grid and cubed-sphere simulations to retrieved column densities from the TROPOspheric Monitoring Instrument (TROPOMI). The first case study uses a stretched grid with a broad refinement covering the contiguous US to produces imulated columns that perform similarly to a C180 (∼50 km) cubed-sphere simulation at less than one-ninth the computational expense. The second case study experiments with a large stretch-factor for a global stretched-grid simulation with a highly localized refinement with∼10 km resolution for California. We find that the refinement improves spatial agreement with TROPOMI columns compared to a C90 cubed-sphere simulation of comparable computational demands. Overall we find that stretched grids in GEOS-Chem are a practical tool for fine resolution regional- or continental-scale simulations of atmospheric chemistry. Stretched grids are available in GEOS-Chem version 13.0.0
GEOS-Chem↗
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↗
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↗
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↗
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↗
Spatial and Temporal Uncertainty of Crop Yield Aggregations
The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.
Aggregation uncertainty↗
Novel Data Driven Noise Emulation Framework using Deep Neural Network for Generating Synthetic PMU Measurements
Sensors play a critical role in supporting day-to-day grid operations and they are essential to operator’s decision-making process. Furthermore, sensors and sensor behaviors need to be emulated with grid simulations to perform modeling studies and to design cutting edge power systems applications. Ensuring the accurate behavior of these applications requires accurate emulation of sensors and pertinent signals. However, most grid simulators and modeling tools assume either zero error scenarios or simplistic noise models that may not always correlate to real-world sensors. To address the above issue, this work presents an initial study on the noise characteristics of phasor measurement units (PMUs), along with models for recreating their unique noise signatures. The proposed methods (both analytical and machine-learning-based) provide a substantial increase in a sensor’s model fidelity, a feature that can be leveraged by an end-user application to yield more accurate system representations. The proposed methods were then applied to micro PMU data from the EPFL microgrid campus to extract sensor noise profiles. This data was used to train a deep learning model, which was tested to emulate the noise characteristics present in actual signals. Based on the observed results and the employed data-driven methodology, the proposed methods may be adapted to replicate the behavior of other grid sensors and power new applications capable of detecting sensor degradation and eventual device failures in near real-time.
PMU, noise emulation, synthetic measurements, deep↗
Toward Adaptive Mixed-Element Unstructured Grids for Simulations of Viscous Flows
Accurate prediction of surface skin friction and heat transfer for viscous flow applications using computational fluid dynamics tools necessitates thin wall-normal elements in the boundary layer. A tetrahedral adaptation process is extended to incorporate the advancing front local reconnection procedure. Thin boundary-layer grids are adapted from the solution, which governs the boundary-layer grid parameters such as first cell height off the wall. The process enables grid-converged steady-state results from a CAD file. Results are presented across the speed range from low subsonic flow over an airfoil to high-speed flows over blunt bodies and a rocket.
CFD↗
Toward Adaptive Mixed-Element Unstructured Grids for Simulations of Viscous Flows
Accurate prediction of surface skin friction and heat transfer for viscous flow applications using computational fluid dynamics tools necessitates thin wall-normal elements in the boundary layer. A tetrahedral adaptation process is extended to incorporate the advancing front local reconnection procedure. Thin boundary-layer grids are adapted from the solution, which governs the boundary-layer grid parameters such as first cell height off the wall. The process enables grid-converged steady-state results from a CAD file. Results are presented across the speed range from low subsonic flow over an airfoil to high-speed flows over blunt bodies and a rocket.
chemically reacting flow↗