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DOE OSTI2013

Automating Natural Disaster Impact Analysis: An Open Resource to Visually Estimate a Hurricane s Impact on the Electric Grid

An ORNL team working on the Energy Awareness and Resiliency Standardized Services (EARSS) project developed a fully automated procedure to take wind speed and location estimates provided by hurricane forecasters and provide a geospatial estimate on the impact to the electric grid in terms of outage areas and projected duration of outages. Hurricane Sandy was one of the worst US storms ever, with reported injuries and deaths, millions of people without power for several days, and billions of dollars in economic impact. Hurricane advisories were released for Sandy from October 22 through 31, 2012. The fact that the geoprocessing was automated was significant there were 64 advisories for Sandy. Manual analysis typically takes about one hour for each advisory. During a storm event, advisories are released every two to three hours around the clock, and an analyst capable of performing the manual analysis has other tasks they would like to focus on. Initial predictions of a big impact and landfall usually occur three days in advance, so time is of the essence to prepare for utility repair. Automated processing developed at ORNL allowed this analysis to be completed and made publicly available within minutes of each new advisory being released.

EARSS↗

NASA NTRS2024

SUPIN: A Tool for the Aerodynamic Design and Analysis of Supersonic Inlets

The Supersonic Inlet Design and Analysis Tool (SUPIN) is a computational program that performs geometric modeling and aerodynamic design and analysis of a set of supersonic inlets whose types include the axisymmetric pitot, three-dimensional pitot, axisymmetric, two-dimensional, two-dimensional bifurcated-duct, and streamline-traced inlets. The inlets are modeled by dividing the inlet flowpath into components that start at the freestream and ends at the engine face. The primary components of the inlet include the external supersonic diffuser, throat section, and subsonic diffuser. Each component is characterized by a set of inputs that include geometric and aerodynamic factors. Examples of the geometric factors are angles, lengths, area ratios, and coordinates that describe the geometry of the components. Examples of the aerodynamic factors are Mach numbers, flow ratios, and pressure ratios that set constraints or desired aerodynamic properties of the component. These input factors are specified within a text-based input data file that is read into SUPIN. SUPIN is a Fortran 95 program that performs the inlet design and analysis as a batch or non-interactive process. SUPIN writes output data files describing the inlet geometry and aerodynamic performance. SUPIN uses analytic, empirical, and numerical methods to perform the inlet design and analysis. The inlet geometry is constructed using planar and three-dimensional geometry constructs and is represented by coordinates, angles, areas, profiles, and surfaces. Surfaces are output in the form of a Plot3D surface grid file. SUPIN does have some capability to automatically generate planar and three-dimensional, multi-block, structured grids for computational fluid dynamics (CFD) analysis. The aerodynamic analysis performed by SUPIN computes quasi-one-dimensional properties, such as Mach numbers, pressures, and temperatures, through the inlet flowpath. Planar aerodynamic properties, such as those for shock and Mach waves, are computed for the supersonic compression of the external supersonic diffuser and throat section. The inlet performance is characterized by the inlet flow rates, total pressure recovery, and inlet drag. The primary intent of this document is to describe the usage of SUPIN. The methods used within SUPIN are documented and may serve as a useful reference for understanding the aerodynamic design and analysis of supersonic inlets.

supersonic inlets↗

DOE OSTI2019

Impedance-Based Prediction of Distortions Generated by Resonance in Grid-Connected Converters

Small-signal impedance-based analysis can effectively predict the frequency and damping of resonance modes in power electronic systems. However, it cannot predict the magnitude of resonance or explain resonance-generated distortions in the absence of an external disturbance at the resonance frequency. This paper presents an impedance-based theory for the prediction of the magnitude of resonance or resonance-generated distortions in grid-connected converters. It is discovered that the impedance response of a converter starts changing with the magnitude of resonance at its terminals. The changing converter impedance response may stabilize an unstable growing resonance mode beyond a certain magnitude, at which point the converter enters a limit cycle mode of sustained oscillations. The proposed theory uses large-signal impedance for the prediction of resonance-generated distortions; the large-signal impedance of an electrical equipment represents its impedance response for different magnitudes of perturbation injected at its terminals. Large-signal impedance-based prediction of resonance-generated distortions is demonstrated for a three-phase grid-connected voltage-source converter.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids: Preprint

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. Different types of DERs such as Photovoltaics (PV), energy storage, electric vehicles (EVs), etc. have varying effects on the grid based on how and where they are deployed. Again, the DER deployment and its impact are network-dependent, while the traditional electric grids were not designed to host DERs. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper investigates the impacts of integrating a mix of DERs in the utility distribution network in Colorado, U.S. Firstly, BTM DERs at the residential scale including distributed PV; battery energy storage systems (BESS); heating, ventilation, and air-conditioning (HVAC) load; electric water heater (EWH) load; and EVs are modeled. The impacts of integrating these resources on the distribution network are evaluated by conducting time-series simulations for different scenarios considering different days to capture the worst-case conditions. Monte Carlo simulations are conducted to generate the realistic EV charging profile. The voltage issues, substation transformer loadings, and critical nodes in the network are identified with the incorporation of uncoordinated EV charging loads and other DER in the network. This analysis helps visualize the DER impact on the grid, identify the challenges, and provides an insight into the new distribution management and control needs to enable reliable and resilient distribution grid operations. Additionally, further analysis is performed to estimate the daily residential electricity cost with the inclusion of DERs under time-of-use tariffs. The result shows the daily residential electricity cost reduced by 20:7% on average with DERs compared to the case without DERs.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2021

Techno-economic analysis of long-duration energy storage and flexible power generation technologies to support high-variable renewable energy grids

As variable renewable energy penetration increases beyond 80%, clean power systems will require long-duration energy storage or flexible, low-carbon generation. Here, we provide a detailed techno-economic evaluation and uncertainty analysis of applicable technologies and identify challenges and opportunities to support electric grid planning. We show that for a 120-h storage duration rating, hydrogen systems with geologic storage and natural gas with carbon capture are the least-cost low-carbon technologies for both current and future capital costs. These results are robust to uncertainty for the future capital cost scenario, but adiabatic compressed air and pumped thermal storage could be the least-cost technologies in the current capital cost scenario under uncertainty. Finally, we present a new storage system using heavy-duty vehicle fuel cells that could reduce the levelized cost of energy by 13%–20% compared with the best previously considered storage technology and, thus, could help enable very high (>80%) renewable energy grids.

25 ENERGY STORAGE↗

DOE OSTI2022

Structure-Informed Graph Learning of Networked Dependencies for Online Prediction of Power System Transient Dynamics

Online transient analysis plays an increasingly important role in dynamic power grids as the renewable generation continues growing. Traditional numerical methods for transient analysis not only are computationally intensive but also require precise contingency information as input, and therefore, are not suitable for online applications. Existing online transient assessment studies focus on the determination of post-contingency system stability or stability margin. Here, this paper develops a novel graph-learning framework, Deep-learning Neural Representation or DNR, for online prediction, of the time-series trajectories of the system states using initial system responses that can be measured by phasor measurement units (PMUs). The proposed DNR framework consists of two sequential modules: a Network Constructor that captures network dependencies among generators, and a Dynamics Predictor that predicts the system trajectories. The key to improved prediction performance is the introduction of the spatio-temporal message-passing operations into graph neural networks with structural knowledge. Its effectiveness and scalability are validated through comparative studies, demonstrating the prediction performance under different contingency scenarios for systems of different sizes. This framework provides a solution to online predicting post-fault system dynamics based on real-time PMU measurements. Additionally, it can also be applied to facilitate the offline transient simulation without simulating the entire trajectories.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Impact analysis of personalized thermostat demand response

Demand response (DR) aims to curtail peak electric load to avoid running inefficient power plants, reduce costly transmission capacity increases, and improve grid reliability. One method of DR for residential settings involves the utility or third part remotely adjusting thermostat temperatures. Cooling setpoints may be increased 2°F – 6°F for hours, irrespective of occupant comfort. To maintain their comfort, occupants override these setpoint changes impacting the reliability of DR services provided to the grid. This paper presents a preliminary impact analysis of replacing the current DR approach of uniform thermostat setbacks for an entire population with personalized and context aware DR based on a dynamic model of occupant thermal comfort behavior. Over 151k interactions with ecobee thermostats are analyzed to predict the impact of such personalized DR on overrides, energy curtailment magnitude, and reliability.

Kane, Michael↗

DOE OSTI2014

On the Numerical Dispersion of Electromagnetic Particle-In-Cell Code : Finite Grid Instability

The Particle-In-Cell (PIC) method is widely used in relativistic particle beam and laser plasma modeling. However, the PIC method exhibits numerical instabilities that can render unphysical simulation results or even destroy the simulation. For electromagnetic relativistic beam and plasma modeling, the most relevant numerical instabilities are the finite grid instability and the numerical Cherenkov instability. We review the numerical dispersion relation of the electromagnetic PIC algorithm to analyze the origin of these instabilities. We rigorously derive the faithful 3D numerical dispersion of the PIC algorithm, and then specialize to the Yee FDTD scheme. In particular, we account for the manner in which the PIC algorithm updates and samples the fields and distribution function. Temporal and spatial phase factors from solving Maxwell's equations on the Yee grid with the leapfrog scheme are also explicitly accounted for. Numerical solutions to the electrostatic-like modes in the 1D dispersion relation for a cold drifting plasma are obtained for parameters of interest. In the succeeding analysis, we investigate how the finite grid instability arises from the interaction of the numerical 1D modes admitted in the system and their aliases. The most significant interaction is due critically to the correct representation of the operators in the dispersion relation. We obtain a simple analytic expression for the peak growth rate due to this interaction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1997

Application of Chimera Grid Scheme to Combustor Flowfields at all Speeds

A CFD method for solving combustor flowfields at all speeds on complex configurations is presented. The approach is based on the ALLSPD-3D code which uses the compressible formulation of the flow equations including real gas effects, nonequilibrium chemistry and spray combustion. To facilitate the analysis of complex geometries, the chimera grid method is utilized. To the best of our knowledge, this is the first application of the chimera scheme to reacting flows. In order to evaluate the effectiveness of this numerical approach, several benchmark calculations of subsonic flows are presented. These include steady and unsteady flows, and bluff-body stabilized spray and premixed combustion flames.

Yungster, Shaye↗

DOE OSTI2023

Field Measurement and Analysis of Frequency and RoCoF for Low-Inertia Power Systems

The frequency measurement and rate of change of frequency (RoCoF) calculations are important for active power, frequency control, and frequency-related protection in power system operations. With the rapid decrease in inertia under modern power systems, however, multiple power variations introduced by variable renewable energy bring large RoCoF and introduce oscillations in frequency measurements. To shed light on this issue, this article proposes a frequency measurement and RoCoF analysis technology, as well as the sensitivity analysis for the real low-inertia power grid. First, a real-world event in an island power grid is analyzed as an example, and an event numerical model is estimated considering four uncertainties, including event RoCoF, oscillation magnitude, oscillation frequency, and underfrequency load-shedding threshold. Then, a sensitivity analysis is performed using the Sobol indices method and quasi-Monte Carlo simulations to identify the dominant uncertainties based on the event model. Here, the dominant uncertainties are compared to provide a guideline for the frequency estimation algorithm selection under different event cases. This algorithm is compared with an enhanced zero-crossing algorithm and gives a 3.41% better RoCoF error rate. Finally, an experiment is conducted using universal grid analyzers to validate the simulation results and the theoretical analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

A Multiyear Gridded Data Ensemble of Surface Biogenic Carbon Fluxes for North America: Evaluation and Analysis of Results

Accurate and fine-scale estimates of biogenic carbon fluxes are critical for measuring and monitoring the biosphere's responses and feedback to the climate system. Currently available data products from flux towers and model-intercomparison projects struggle to adequately represent spatiotemporal dynamics of surface biogenic carbon fluxes, and to quantify their uncertainties, which also are crucial to atmospheric inversion systems. To address these gaps, we introduce a new perturbed-parameter model ensemble with the CASA model to estimate surface biogenic carbon fluxes at monthly and 3-hourly scales for North America at ~500-m and 5-km resolutions. We first use the Extended Fourier Amplitude Sensitivity Testing to choose the three most sensitive parameters to be perturbed, maximum light use efficiency (E max ), optimal temperature of photosynthesis (T opt ), and temperature response of respiration (Q 10 ). The initial range for each parameter is broadly sampled for the L1 ensemble, but then we pruned E max with site-level primary productivity to derive an L2 ensemble with narrower uncertainty ranges. Ensembles are strongly correlated with site-level results at both monthly and 3-hourly scales, and the spread across L1/L2 ensemble members encompasses the range of AmeriFlux observations. Monthly variability in the L2 ensemble mean is 85% of the observed variability. The L2 ensemble outperforms diverse data products with the highest Taylor skill scores at diurnal to annual scales. Finally, the ensemble's seasonality agrees well with other models for most biome types and in high and middle latitudes, but inconsistencies are found in subtropical and tropical ecoregions and for annual totals over North America.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Backup Power Performance of Solar-plus-Storage Systems during Routine Power Interruptions: A Case Study Application of Berkeley Lab’s PRESTO Model

This technical brief estimates the expected performance of a solar photovoltaic and energy storage system (PVESS) for providing backup power during short-duration power interruption events, accounting for the unpredictable nature of those events. The analysis relies on the Power Reliability Event Simulation TOol (PRESTO), a publicly available model developed by Berkeley Lab to simulate the occurrence of short-duration power interruption events at the county-level. A separate storage dispatch model is then used to simulate PVESS operation and backup performance for each of the large number of interruption events produced by PRESTO. In performing this simulation, the analysis accounts for how the customer operates its battery on a day-to-day basis—in this case, we assume the battery is cycled each day in response to time-of-use rates—and how that, in turn, impacts the battery’s state of charge at the beginning of each interruption event. The analysis presented here is intended to demonstrate an application of the PRESTO model as well as to illustrate some of the key determinants of PVESS backup power performance during short-duration power interruption events. The analysis focuses initially on a typical single-family home in Maricopa County, Arizona, and includes a limited set of scenarios related to system sizing, backup power configuration, and whether the customer charges its battery storage system from the grid during normal operating conditions. The analysis also presents comparative results for two other counties, in Massachusetts (Middlesex) and California (Los Angeles), illustrating how regional differences in climate, interruption patterns, and retail rate structures can affect PVESS performance as a backup power source. In the conclusions, we highlight a number of other important considerations for evaluating PVESS backup power capabilities.

14 SOLAR ENERGY↗

NASA NTRS1984

Analysis of inviscid and viscous flows in cascades with an explicit multiple-grid algorithm

A rapid technique is used for calculating inviscid and viscous flows in turbomachinery cascades. The Euler and thin-layer Navier-Stokes equations are solved using the original explicit MacCormack algorithm. The Baldwin-Lomax eddy viscosity model is used for turbulent flows. Convergence to a steady state is accelerated by use of a variable time-step and a multiple-grid scheme. Computer time is reduced through vectorization. Details of the numerical method are presented along with computed results for two low-speed wind tunnel turning vanes, a space shuttle fuel pump turbine rotor, and a supersonic inflow compressor rotor. The method can predict subtle viscous flow phenomena in cascades and is fast enough to be used as a design tool.

Chima, R. V.↗

NASA NTRS1984

Analysis of inviscid and viscous flows in cascades with an explicit multiple-grid algorithm

Chima, R. V.↗

NASA NTRS1985

The error associated with use of various forms of the divergence equation to diagnose geopotential and temperature

An experimental study was made of errors arising from diagnosing the geopotential and temperature for numerical weather prediction models by means of an inviscid divergence equation (DE). The experiment consisted of a simulation of a snow storm which occurred in 1979, with observational data being input for every point of the model grid and for the geopotential boundary condition, thereby eliminating errors in the horizontal and vertical analysis. The DE terms were recorded at each grid point, and were found to include synoptic-scale geopotential height errors up to 23 m and rms temperature errors exceeding 26 C in the PBL. The errors were minimal above 800 mb. The various unsuccessful attempts to reduce or eliminate the errors are described.

Modica, G. M.↗

NASA NTRS2002

National Combustion Code Parallel Performance Enhancements

The National Combustion Code (NCC) is being developed by an industry-government team for the design and analysis of combustion systems. The unstructured grid, reacting flow code uses a distributed memory, message passing model for its parallel implementation. The focus of the present effort has been to improve the performance of the NCC code to meet combustor designer requirements for model accuracy and analysis turnaround time. Improving the performance of this code contributes significantly to the overall reduction in time and cost of the combustor design cycle. This report describes recent parallel processing modifications to NCC that have improved the parallel scalability of the code, enabling a two hour turnaround for a 1.3 million element fully reacting combustion simulation on an SGI Origin 2000.

Quealy, Angela↗

DOE OSTI2014

Distinguishing magnetic particle size of iron oxide nanoparticles with first-order reversal curves

Magnetic nanoparticles encompass a wide range of scientific study and technological applications. The success of using the nanoparticles in various applications demands control over size, dispersibility, and magnetics. Hence, the nanoparticles are often characterized by transmission electron microscopy (TEM), X-ray diffraction, and magnetic hysteresis loops. TEM analysis requires a thin layer of dispersed particles on the grid, which may often lead to particle aggregation thus making size analysis difficult. Magnetic hysteresis loops on the other hand provide information on the bulk property of the material without discriminating size, composition, and interaction effects. First order reversal curves (FORCs), described as an assembly of partial hysteresis loops originating from the major loop are efficient in identifying the domain size, composition, and interaction in a magnetic system. This study presents FORC diagrams on a variety of well-characterized biogenic and synthetic magnetite nanoparticles. It also introduces deconvoluted reversible and irreversible components from FORC as an important method for obtaining a semi-quantitative measure of the effective magnetic particle size. This is particularly important in a system with aggregation and interaction among the particles that often leads to either the differences between physical size and effective magnetic size. We also emphasize the extraction of secondary components by masking dominant coercivity fraction on FORC diagram to explore more detailed characterization of nanoparticle systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2026

Techno-Economic Evaluation of a 600MW Pumped Storage Hydropower Plant using the Pumped Storage Hydropower Valuation Tool

This paper presents a techno-economic evaluation of the proposed 600 MW, 8-hour Craig – Hayden pumped storage hydropower project using the U.S. Department of Energy’s Pumped Storage Hydropower Valuation Tool. The analysis integrates plant technical characteristics, regional grid conditions, and market-based operating assumptions to quantify stacked value streams from energy arbitrage, capacity, ancillary services, transmission congestion relief, and reliability. Both price taker and price influencer frameworks are applied to examine the impact of market participation and system interactions on lifecycle economic performance using Benefit - Cost Analysis and Multi - Criteria Decision Analysis. The results show that the price taker approach provides higher revenue estimates based on exogenous price signals, while the price influencer approach captures production cost savings, renewable curtailment reduction, and market price formation, yielding more conservative but system-representative outcomes. The study demonstrates the strategic value of long-duration PSH for enhancing operational flexibility, resource adequacy, and grid reliability in a high-renewable Western Interconnection.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046↗