Search NASA⌕ Search

SEARCH · Search NASA

Results for “grid analysis”

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.

At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Frequency Stability Enhancement in a Fully Solar Power Grid: A Case Study on the Saudi Model

Recently, renewable energy sources (RES) such as solar photovoltaic (PV) have been recognized for their significant potential. Several studies have explored the issue of frequency stability with high RES penetration. A significant observation related to this issue is the decline in the weighted short circuit ratio (WSCR), which has the potential to adversely affect system stability. This research uniquely focuses on the gradual transition of the Saudi Electricity Company (SEC) system to a fully integrated solar PV grid, offering insight and methodology that can be adapted for other power systems. While a variety of mitigation methods are available, synchronous condensers (SC) were used in this study to stabilize grid frequency, and their implementation has been shown to improve the overall performance of the system. In response to the observed decline in WSCR, a comprehensive short circuit analysis was applied across all regions in the Saudi power grid model to evaluate the reduction in short circuit power and highlight areas requiring enhancement. Finally, scenarios illustrating frequency response with a gradual increase in SCR were analyzed, with the objective of establishing a stable, fully solar PV power system that is resilient to sudden power grid disturbances.

14 SOLAR ENERGY↗
NASA NTRS1997

Gradient-Based Aerodynamic Shape Optimization Using ADI Method for Large-Scale Problems

A gradient-based shape optimization methodology, that is intended for practical three-dimensional aerodynamic applications, has been developed. It is based on the quasi-analytical sensitivities. The flow analysis is rendered by a fully implicit, finite volume formulation of the Euler equations.The aerodynamic sensitivity equation is solved using the alternating-direction-implicit (ADI) algorithm for memory efficiency. A flexible wing geometry model, that is based on surface parameterization and platform schedules, is utilized. The present methodology and its components have been tested via several comparisons. Initially, the flow analysis for for a wing is compared with those obtained using an unfactored, preconditioned conjugate gradient approach (PCG), and an extensively validated CFD code. Then, the sensitivities computed with the present method have been compared with those obtained using the finite-difference and the PCG approaches. Effects of grid refinement and convergence tolerance on the analysis and shape optimization have been explored. Finally the new procedure has been demonstrated in the design of a cranked arrow wing at Mach 2.4. Despite the expected increase in the computational time, the results indicate that shape optimization, which require large numbers of grid points can be resolved with a gradient-based approach.

Pandya, Mohagna J.↗
DOE OSTI2018

Tomographic analysis of tangential viewing cameras (invited)

Many tokamaks now use visible light cameras to observe plasma-wall interactions and integrated line emission. The DIII-D coherence imaging spectroscopy diagnostic cameras image interferograms that encode line integrated velocity. By modeling the 2D camera image pixels as line of sight integrals through an axisymmetric discrete grid, it is possible to do tomographic analysis to determine the local plasma line emissivity and parallel velocity. Approaches to solve the inverse problem posed by these tangential viewing cameras are presented. The inversion begins with calculation of the sparse response matrix that encompasses all the geometry and diagnostic information and reduces the process of image formation to a sparse matrix-vector multiply. Our report includes techniques for determining the detailed geometry of the camera views and methods for handling physical quantities that vary spatially. Additionally, the size of the response matrix has driven the development of capability to distribute the coarse parallel calculation across a heterogeneous cluster of computers on the Energy Sciences Network. Iterative techniques are then used to solve the sparse matrix-vector linear system

47 OTHER INSTRUMENTATION↗
NASA NTRS1980

Grid generation using differential systems techniques

The errors in approximating the derivatives of a function by traditional central differences at grid points of a curvilinear coordinate system were examined. The implications concerning the accuracy of the numerical solution of a partial differential equation are explained by considering several numerical examples. Although this study only considers the two dimensional case, the techniques and implications are equally valid for three dimensional grids. An interesting feature of the error analysis is its simplicity. Most of the results follow by merely working with the truncation terms of some power series expansion. These series expansions also give rise to higher order difference approximations which can significantly reduce error when the grid spacing changes rapidly, as might be the case in problems with shock waves or thin boundary layers.

Thompson, J. F.↗
NASA NTRS1995

Computational System For Rapid CFD Analysis In Engineering

Computational system comprising modular hardware and software sub-systems developed to accelerate and facilitate use of techniques of computational fluid dynamics (CFD) in engineering environment. Addresses integration of all aspects of CFD analysis process, including definition of hardware surfaces, generation of computational grids, CFD flow solution, and postprocessing. Incorporates interfaces for integration of all hardware and software tools needed to perform complete CFD analysis. Includes tools for efficient definition of flow geometry, generation of computational grids, computation of flows on grids, and postprocessing of flow data. System accepts geometric input from any of three basic sources: computer-aided design (CAD), computer-aided engineering (CAE), or definition by user.

Barson, Steven L.↗
NASA NTRS2013

The Impact of Back-Sputtered Carbon on the Accelerator Grid Wear Rates of the NEXT and NSTAR Ion Thrusters

A study was conducted to quantify the impact of back-sputtered carbon on the downstream accelerator grid erosion rates of the NEXT (NASA's Evolutionary Xenon Thruster) Long Duration Test (LDT1). A similar analysis that was conducted for the NSTAR (NASA's Solar Electric Propulsion Technology Applications Readiness Program) Life Demonstration Test (LDT2) was used as a foundation for the analysis developed herein. A new carbon surface coverage model was developed that accounted for multiple carbon adlayers before complete surface coverage is achieved. The resulting model requires knowledge of more model inputs, so they were conservatively estimated using the results of past thin film sputtering studies and particle reflection predictions. In addition, accelerator current densities across the grid were rigorously determined using an ion optics code to determine accelerator current distributions and an algorithm to determine beam current densities along a grid using downstream measurements. The improved analysis was applied to the NSTAR test results for evaluation. The improved analysis demonstrated that the impact of back-sputtered carbon on pit and groove wear rate for the NSTAR LDT2 was negligible throughout most of eroded grid radius. The improved analysis also predicted the accelerator current density for transition from net erosion to net deposition considerably more accurately than the original analysis. The improved analysis was used to estimate the impact of back-sputtered carbon on the accelerator grid pit and groove wear rate of the NEXT Long Duration Test (LDT1). Unlike the NSTAR analysis, the NEXT analysis was more challenging because the thruster was operated for extended durations at various operating conditions and was unavailable for measurements because the test is ongoing. As a result, the NEXT LDT1 estimates presented herein are considered preliminary until the results of future posttest analyses are incorporated. The worst-case impact of carbon back-sputtering was determined to be the full power operating condition, but the maximum impact of back-sputtered carbon was only a four percent reduction in wear rate. As a result, back-sputtered carbon is estimated to have an insignificant impact on the first failure mode of the NEXT LDT at all operating conditions.

Soulas, George C.↗
NASA NTRS2013

The Impact of Back-Sputtered Carbon on the Accelerator Grid Wear Rates of the NEXT and NSTAR Ion Thrusters

A study was conducted to quantify the impact of back-sputtered carbon on the downstream accelerator grid erosion rates of the NASA's Evolutionary Xenon Thruster (NEXT) Long Duration Test (LDT1). A similar analysis that was conducted for the NASA's Solar Electric Propulsion Technology Applications Readiness Program (NSTAR) Life Demonstration Test (LDT2) was used as a foundation for the analysis developed herein. A new carbon surface coverage model was developed that accounted for multiple carbon adlayers before complete surface coverage is achieved. The resulting model requires knowledge of more model inputs, so they were conservatively estimated using the results of past thin film sputtering studies and particle reflection predictions. In addition, accelerator current densities across the grid were rigorously determined using an ion optics code to determine accelerator current distributions and an algorithm to determine beam current densities along a grid using downstream measurements. The improved analysis was applied to the NSTAR test results for evaluation. The improved analysis demonstrated that the impact of back-sputtered carbon on pit and groove wear rate for the NSTAR LDT2 was negligible throughout most of eroded grid radius. The improved analysis also predicted the accelerator current density for transition from net erosion to net deposition considerably more accurately than the original analysis. The improved analysis was used to estimate the impact of back-sputtered carbon on the accelerator grid pit and groove wear rate of the NEXT Long Duration Test (LDT1). Unlike the NSTAR analysis, the NEXT analysis was more challenging because the thruster was operated for extended durations at various operating conditions and was unavailable for measurements because the test is ongoing. As a result, the NEXT LDT1 estimates presented herein are considered preliminary until the results of future post-test analyses are incorporated. The worst-case impact of carbon back-sputtering was determined to be the full power operating condition, but the maximum impact of back-sputtered carbon was only a 4 percent reduction in wear rate. As a result, back-sputtered carbon is estimated to have an insignificant impact on the first failure mode of the NEXT LDT1 at all operating conditions.

Soulas, George C.↗
DOE OSTI2016

Experimental Investigation of Bearing Slip in a Wind Turbine Gearbox During a Transient Grid Loss Event

This work investigates the behaviour of the high speed stage of a wind turbine gearbox during a transient grid loss event. Dynamometer testing on a full scale wind turbine nacelle is used. A combination of external and internal gearbox measurements is analysed. Particular focus is on the characterization of the high speed shaft tapered roller bearing slip behaviour. This slipping behaviour is linked to dynamic events by many researchers and described as potential bearing failure initiator. However only limited full scale dynamic testing is documented. Strain gauge bridges in grooves along the circumference of the outer ring are used to characterize the bearing behaviour in detail. It is shown that during the transient event the high speed shaft experiences a combined torsional and bending deformation. These unfavourable loading conditions induce roller slip in the bearings during the torque reversals indicating the potential of the applied load case to go beyond the preload of the tapered roller bearing.

17 WIND ENERGY↗
DOE OSTI2026

Sub-melt nanosecond pulsed-laser induced densification and strain-field relaxation in single-crystal diamond

Dislocations and polishing-induced defect networks in synthetic diamond introduce local strain fields and broaden Raman features, limiting performance in optical, thermal, and electronic applications. Laser annealing is emerging as a promising approach to repair surface and near-surface defects in diamond without entering the melt regime, yet surface densification, defect-state modification, and associated structural changes have not been well quantified. In this work, we show that sub-melt nanosecond pulsed-laser annealing (PLA) induces near-surface densification and defect-mediated strain relaxation in single-crystal Chemical Vapor Deposition (CVD) diamond. Single- and two-pulse PLA were applied, and structural evolution was quantified using co-registered ISO 25,178 white-light interferometry, depth-resolved Raman spectroscopy, and cross-sectional STEM with geometric phase analysis (GPA). Across a 5 × 6 grid (n = 30), responsive regions exhibit large reductions in local slope (Sdq 45–65%), developed area (Sdr 60–90%), height spread (Sp, Sz 30–65%), void volume (Vv 57–60%), and roughness amplitude (Sa, Sq 48–57%), consistent with densification of ∼4–6.5 nm. Raman profiling shows narrowing of the diamond line and improved spectral uniformity to depths of ∼2–3 μm. Given that the Raman probing depth significantly exceeds the densified layer thickness, this response is interpreted as consistent with long-range strain-field redistribution originating from the near-surface region. STEM-GPA strain maps further support this interpretation, showing smoother strain fields, suppressed hotspots, and redistribution of localized strain concentrations following PLA. These results are consistent with defect-mediated strain relaxation and densification-driven modification of the near-surface energy state. The approach provides a scalable pathway for improving near-surface structural quality in diamond relevant to electronic, photonic, and quantum applications.

Areal surface metrology (ISO 25,178)↗
DOE OSTI2017

Estimating the price (in)elasticity of off-grid electricity demand

Community-scale power infrastructure may be the only electrification option for tens of millions households that remain out of reach from centralized power grids. The responsiveness of household electricity demand to price is a crucial design input for off-grid systems. While the price elasticity of electricity demand of grid-connected consumers has been abundantly studied, few studies focus on off-grid communities where substantial econometric challenges arise, including the absence of metered consumption data and electricity prices that are simultaneously determined by cost and demand considerations. This study attempts to address these challenges for the case of off-grid micro hydropower consumers. It makes two core contributions: First, we propose the surface area of the contributing hydrologic catchment as a new instrumental variable to estimate elasticity using a cross sectional dataset of existing micro hydropower infrastructure. Second, we provide a first price-elasticity estimate (-0.15) for off-grid electricity demand in Nepal. We surmise that the small (in absolute value) elasticity value found in this study arises from the low levels of consumption observed off-the-grid. We use a Monte Carlo analysis to show that failing to account for this disparity can lead to substantial financial losses caused by suboptimal power infrastructure design.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Understanding Precipitation Bias Sensitivities in E3SM-Multi-Scale Modeling Framework From a Dilution Framework

We investigate a set of Energy Exascale Earth System Model Multi-scale modeling framework (MMF) (E3SM-MMF) simulations that vary the dimensionality and momentum transport configurations of the embedded cloud-resolving models (CRMs), including unusually ambitious 3D configurations. Issues endemic to all MMF simulations include too much Intertropical Convergence Zone rainfall and too little over the Amazon. Systematic MMF improvements include more on-equatorial rainfall across the Warm Pool. Interesting sensitivities to the CRM domain are found in the regional time-mean precipitation pattern over the tropics. The 2D E3SM-MMF produces an unrealistically rainy region over the northwestern tropical Pacific; this is reduced in computationally ambitious 3D configurations that use 1,024 embedded CRM grid columns per host cell. Trajectory analysis indicates that these regional improvements are associated with desirably fewer tropical cyclones and less extreme precipitation rates. To understand why and how the representation of precipitation improved in 3D, we propose a framework that dilution is stronger in 3D. This viewpoint is supported by multiple indirect lines of evidence, including a delayed moisture-precipitation pickup, smaller precipitation efficiency, and amplified convective mass flux profiles and more high clouds. We also demonstrate that the effects of varying embedded CRM dimensionality and momentum transport on precipitation can be identified during the first few simulated days, providing an opportunity for rapid model tuning without high computational cost. Meanwhile the results imply that other less computationally intensive ways to enhance dilution within MMF CRMs may also be strategic tuning targets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach

Thermostatically controlled loads, e.g., air conditioners and heaters, are by far the most widespread consumers of electricity. Normally the devices are calibrated to provide the so-called bang-bang control – changing from on to off, and vice versa, depending on temperature. We considered aggregation of a large group of similar devices into a statistical ensemble, where the devices operate following the same dynamics, subject to stochastic perturbations and randomized, Poisson on/off switching policy. Using theoretical and computational tools of statistical physics, we analyzed how the ensemble relaxes to a stationary distribution and established a relationship between the relaxation and the statistics of the probability flux associated with devices’ cycling in the mixed (discrete, switch on/off, and continuous temperature) phase space. This allowed us to derive the spectrum of the non-equilibrium (detailed balance broken) statistical system and uncover how switching policy affects oscillatory trends and the speed of the relaxation. Relaxation of the ensemble is of practical interest because it describes how the ensemble recovers from significant perturbations, e.g., forced temporary switching off aimed at utilizing the flexibility of the ensemble to provide “demand response” services to change consumption temporarily to balance a larger power grid. We discuss how the statistical analysis can guide further development of the emerging demand response technology.

Science & Technology - Other Topics↗
DOE OSTI2013

Periodic boundary conditions for QM/MM calculations: Ewald summation for extended Gaussian basis sets

An implementation of Ewald summation for use in mixed quantum mechanics/molecular mechanics (QM/MM) calculations is presented, which builds upon previous work by others that was limited to semi-empirical electronic structure for the QM region. Unlike previous work, our implementation describes the wave function's periodic images using “ChElPG” atomic charges, which are determined by fitting to the QM electrostatic potential evaluated on a real-space grid. This implementation is stable even for large Gaussian basis sets with diffuse exponents, and is thus appropriate when the QM region is described by a correlated wave function. Derivatives of the ChElPG charges with respect to the QM density matrix are a potentially serious bottleneck in this approach, so we introduce a ChElPG algorithm based on atom-centered Lebedev grids. The ChElPG charges thus obtained exhibit good rotational invariance even for sparse grids, enabling significant cost savings. Detailed analysis of the optimal choice of user-selected Ewald parameters, as well as timing breakdowns, is presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

An Analysis of Post Attack Impacts and Effects of Learning Parameters on Vulnerability Assessment of Power Grid

Due to the increasing number of heterogeneous devices connected to electric power grid, the attack surface increases the threat actors. Game theory and machine learning are being used to study the power system failures caused by external manipulation. Most of existing works in the literature focus on one-shot process of attacks and fail to show the dynamic evolution of the defense strategy. In this paper, we focus on an adversarial multistage sequential game between the adversaries of the smart electric power transmission and distribution system. We study the impact of exploration rate and convergence of the attack strategies (sequences of action that creates large scale blackout based on the system capacity) based on the reinforcement learning approach. We also illustrate how the learned attack actions disrupt the normal operation of the grid by creating transmission line outages, bus voltage violations, and generation loss. This simulation studies are conducted on IEEE 9 and 39 bus systems. The results show the improvement of the defense strategy through the learning process. The results also prove the feasibility of the learned attack actions by replicating the disturbances created in simulated power system.

attack impacts↗
DOE OSTI2020

Q-Learning-Based Impact Assessment of Propagating Extreme Weather on Distribution Grids

The increasing number of power outage events due to extreme weather conditions is hampering us socioeconomically. Preparing in advance for the extreme weather event is critical. It can help utility operators to reduce grid damages, restore grid service quickly, allocate energy resources and repair crews strategically, and hence dramatically increase grid resilience. In this paper, we propose a method to identify the sequence of worst impact zones in the power grid caused by extreme weather events based on Q-learning (a reinforcement learning algorithm). To quantity the weather severity and its effect on the grid, we model the impact of extreme weather on the grid as a function of intensity, vulnerability, and exposure. A modified IEEE 123-node distribution feeder is presented in a mesh grid and experimented for sequences of zones identification. Finally, simulation results present the identified sequences and their associated impacts on the grid caused by extreme weather events.

distribution system↗
DOE OSTI2021

Fault Detection Utilizing Convolution Neural Network on Timeseries Synchrophasor Data From Phasor Measurement Units

An end-to-end supervised learning method is proposed for fault detection in the electric grid using Big Data from multiple Phasor Measurement Units (PMUs). The approach consists of preprocessing steps aimed at reducing data noise and dimensionality, followed by utilization of six classification models considered for detecting faults. Three of the models were variants of Convolutional Neural Network (CNN) architectures that consider a single type of measurement (voltage, current or frequency) at all PMUs or all types together also at all PMUs. CNN based models were compared to traditional methods of Logistic Regression (LR), Multi-layer Perceptron (MLP) and Support Vector Machine (SVM). Evaluation was conducted on two-year data measured by PMUs at 37 locations in a large electric grid. Here, the response variable for classification were extracted from the grid-wide outage event log. Experiments show that CNN-based models outperformed traditional methods on one year out-of-sample outage detection over the entire grid.

42 ENGINEERING↗
DOE OSTI2016

Quantifying the impact of microgrid location and behavior on transmission network congestion

This work presents a preliminary analysis considering impact of a grid-connected microgrid on network transmission of the power system. The locational marginal prices of the power system are used to strategically place the microgrid to avoid congestion problems. In addition, a Monte Carlo simulation approach is implemented to confirm that network congestion can be attenuated if appropriate price-based signals are set to define the import and export dynamic between the two systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗