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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A Guide for Public Utility Commissions: Building Internal Technical Capacity and Recruiting Talent for Grid Resilience

This guide offers insight into how PUCs can strategically expand their technical workforce to meet evolving gird resilience demands. It outlines critical skill sets needed to support informed regulatory decision-making around resilience, such as modeling and weather forecasting, electric power systems analysis, and advanced data interpretation. In addition, it provides strategies for developing technical talent both internally and through additional recruitment efforts. Two appendices provide a list of grid resilience training resources and a compendium of sample job descriptions that reflect grid resilience technical expertise for PUC consideration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Parameter Reduction of Composite Load Model Using Active Subspace Method

Over the past decades, the increasing penetration of distributed energy resources (DERs) has dramatically changed the power load composition in the distribution networks. The traditional static and dynamic load models can hardly capture the dynamic behavior of modern loads especially for fault-induced delayed voltage recovery (FIDVR) events. Thus, a more comprehensive composite load model with combination of static load, different types of induction motors, single-phase A/C motor, electronic load and DERs has been proposed by Western Electricity Coordinating Council (WECC). However, due to the large number of parameters and model complexity, the WECC composite load model (WECC CMLD) raises new challenges to power system studies. To overcome these challenges, in this paper, a cutting-edge parameter reduction (PR) approach for WECC CMLD based on active subspace method (ASM) is proposed. Firstly, the WECC CMLD is parameterized in a discrete-time manner for the application of the proposed method. Then, parameter sensitivities are calculated by discovering the active subspace, which is a lower-dimensional linear subspace of the parameter space of WECC CMLD in which the dynamic response is most sensitive. The interdependency among parameters can be taken into consideration by our approach. Finally, the numerical experiments validate the effectiveness and advantages of the proposed approach for WECC CMLD model.

active subspace↗
DOE OSTI2024

Managing Increased Electric Vehicle Shares on Decarbonized Bulk Power Systems

Transportation electrification and power sector decarbonization - the convergence of these two trends present a complex planning problem requiring realistic, region-specific modeling and analysis to ensure that both can happen rapidly and cost effectively. This project, funded through the U.S. Department of Energy's Vehicle Technologies Office, models the evolution of the U.S. bulk power system (through 2050) in response to large-scale EV charging across all on-road vehicle segments. We will assess the opportunity and value of demand-side flexibility (i.e., "smart" charging) for reducing energy costs, increasing renewable generation shares, and managing future EV loads on the bulk power system. Overall, this study aims to provide an improved understanding of least-cost solutions for managing EV load growth on the grid and will make high-resolution EV load data sets publicly available for further analysis.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2025

Reliability Analysis of Power Grids Considering Component Failures of Variable Energy Resources

This paper proposes an improved model for the reliability assessment of power systems considering component failures of variable energy resources (VER). The inherent intermittency of VER such as solar photovoltaic (PV) and wind farms, along with their susceptibility to component failures, present significant challenges to reliable system operation. These issues, combined with power grid operation and network constraints, complicate the reliable operation of VER-integrated power systems. Here, to address these concerns, this paper introduces a reliability assessment framework that considers VER input variability, its impact on component availability, and their resulting impact on overall system reliability. Stochastic models based on discrete Markov processes are developed to incorporate variable irradiance, wind speeds, and their effects on PV and wind component failure rates. A next-event and state transition-based approach is then developed to integrate the stochastic models into a mixed-timing sequential Monte Carlo simulation framework for composite reliability assessment. Case studies on the RTS-GMLC system demonstrate the effectiveness of the proposed model in evaluating the reliability of VER-integrated systems.

Pandit, Dilip [Sandia National Laboratories (SNL-N↗
DOE OSTI2023

Aggregation of Inverter-Based Resources for Modeling and Simulation

In order to conduct system dynamic studies, it is necessary to have dynamic models of both inverter and plant levels. Detailed and aggregated modeling approaches are two essential options. The detailed modeling method involves capturing the dynamic characteristics of each individual device (e.g., wind turbine or PV array), as well as their interconnections. However, as the scale of the IBR plant increases, the complexity and computation time required for detailed modeling also increase. On the other hand, aggregated modeling offers a more efficient way of representing large-scale IBRs in power system dynamic studies. This approach involves aggregating a large number of wind turbines, PV arrays, inverters, and/or plant controllers into one or a smaller number of equivalent models. In order to analyze the impact of a high-level IBR penetration in power systems, it is important to develop accurate and computationally efficient models for both the detailed and aggregated methods.

14 SOLAR ENERGY↗
DOE OSTI2024

Advancing our understanding of instabilities in high-energy-density systems through the study of benchmark datasets with advanced modeling tools

Numerous types of pulsed power driven inertial confinement fusion (ICF) and high energy density (HED) systems rely on implosion stability to achieve desired temperatures, pressures, and densities. Sandia National Laboratories Pulsed Power Sciences Center’s main ICF platform, Magnetized Liner Inertial Fusion (MagLIF), suffers from implosion instabilities which limit attainable fuel conditions and can compromise fuel confinement. This Truman Fellowship research primarily focused on computationally exploring (a) methods for improving our understanding of hydrodynamic and magnetohydrodynamic instabilities that form during cylindrical liner implosions, (b) methods for mitigating implosion instabilities, particularly those that degrade performance of MagLIF targets, and (c) novel MagLIF target designs intended to improve target performance primarily via enhanced implosion stability. Several multi-dimensional computational tools were used, including the magnetohydrodynamics code ALEGRA, the radiation-magnetohydrodynamics code HYDRA, and the magnetohydrodynamics code KRAKEN. This research succeeded in executing and analyzing simulations of automagnetizing liner implosions, shockless MagLIF implosions, dynamic screw pinch driven cylindrical liner implosions, and cylindrically convergent HED instability studies. The methods and tools explored and developed in this Truman Fellowship research have been published in several peer-reviewed journal articles and will serve as useful contributions to the fields of pulsed power science and engineering, particularly pertaining to pulsed power ICF and HED science.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Validation of Subhourly Clipping Loss Error Corrections

Under-performance of solar PV systems is an important issue that increases risks for stakeholders, including developers, investors and operators. Recently some attention has focused on underestimation of inverter clipping losses as a possible source of over-prediction where sub-hourly solar variability is high. Several models and data sets have been analyzed over the past few years, with the aim of quantifying, predicting, and correcting underestimated clipping loss errors for systems with high DC/AC ratio and solar variability. In this research, we apply a machine learning model developed at NREL to two physical PV systems, to correct for subhourly clipping losses. For each system, we compare overall AC power output for the model taken at 1-minute intervals to AC power output taken at 1-hour intervals with the addition of the subhourly clipping correction. Our findings consistently show that the addition of the clipping loss correction lead to a reduction in mean bias error of 0.8% and 1.2% for systems A and B, respectively, with no additional filtering applied. When examining high solar variability periods where clipping is more pronounced, system A and B experienced a 1.8% and 2.7% reduction in mean bias error, respectively, when the clipping correction was applied.

machine learning↗
DOE OSTI2021

Validation of Subhourly Clipping Loss Error Corrections: Preprint

Under-performance of solar PV systems is an important issue that increases risks for stakeholders, including developers, investors and operators. Recently some attention has focused on underestimation of inverter clipping losses as a possible source of over-prediction where sub-hourly solar variability is high. Several models and data sets have been analyzed over the past few years, with the aim of quantifying, predicting, and correcting underestimated clipping loss errors for systems with high DC/AC ratio and solar variability. In this research, we apply a machine learning model developed at NREL to two physical PV systems, to correct for subhourly clipping losses. For each system, we compare overall AC power output for the model taken at 1-minute intervals to AC power output taken at 1-hour intervals with the addition of the subhourly clipping correction. Our findings consistently show that the addition of the clipping loss correction lead to a reduction in mean bias error of 0.6\% and 1.1\% for systems A and B, respectively, with no additional filtering applied. When examining high solar variability periods where clipping is more pronounced, system A and B experienced a 1.4\% and 2.5\% reduction in mean bias error, respectively, when the clipping correction was applied.

machine learning↗
DOE OSTI2021

Substation-Level Grid Topology Optimization Using Bus Splitting: Preprint

Operations of substation circuit breakers are of high significance for performing system maintenance and topology optimization. Bus splitting is one type of topology changes where the two bus-bars at a substation become electrically disconnected after certain actions of circuit breakers. As these events involve detailed substation modeling, they are not typically considered in power system routine operation and control. In this paper, an improved substation-level topology optimization is developed by expanding traditional line switching with breaker-level bus splitting, which can further reduce grid congestion and generation costs. A tight McCormick relaxation is proposed to reformulate the bi-linear terms in the resultant topology optimization model. Thus, a tractable mixed-integer linear program formulation is presented which can be efficiently solved for real-time control. Numerical studies on the IEEE 14-bus and 118-bus systems demonstrate the performance and economic benefits of the proposed topology optimization approach.

bus split↗
DOE OSTI2020

Induced Markov chain for wind farm generation forecasting

Systems and methods for forecasting power generation in a wind farm are disclosed. The systems and methods utilize an induced Markov chain model to generate a forecast of power generation of the wind farm. The forecast is at least one of a point forecast or a distributional forecast. Additionally, the systems and methods modify at least one of: (i) a generation of electricity at a power plant coupled to a common power grid as the wind farm; or (ii) a distribution of electricity in the common power grid based on the forecast of power generation of the wind farm. In an exemplary approach, utilizing the induced Markov chain model to generate the forecast may include determining a series of time adjacent power output measurements based on historical wind power measurements and calculating a time series of difference values based on the series of time adjacent power output measurements.

17 WIND ENERGY↗
DOE OSTI2023

Frequency Recovery in Power Grids Using High-Performance Computing

Maintaining electric power system stability is paramount, especially in extreme contingencies involving unexpected outages of multiple generators or transmission lines that are typical during severe weather events. Such outages often lead to large supply-demand mismatches followed by subsequent system frequency deviations from their nominal value. The extent of frequency deviations is an important metric of system resilience, and its timely mitigation is a central goal of power system operation and control. This paper develops a novel nonlinear model predictive control (NMPC) method to minimize frequency deviations when the grid is affected by an unforeseen loss of multiple components. Our method is based on a novel multi-period alternating current optimal power flow (ACOPF) formulation that accurately models both nonlinear electric power flow physics and the primary and secondary frequency response of generator control mechanisms. We develop a distributed parallel Julia package for solving the large-scale nonlinear optimization problems that result from our NMPC method and thereby address realistic test instances on existing high-performance computing architectures. Our method demonstrates superior performance in terms of frequency recovery over existing industry practices, where generator levels are set based on the solution of single-period classical ACOPF models.

nonlinear model predictive control↗
DOE OSTI2023

Analyzing at-scale distribution grid response to extreme temperatures

Threats against power grids continue to increase, as extreme weather conditions and natural disasters (extreme events) become more frequent. Hence, there is a need for the simulation and modeling of power grids to reflect realistic conditions during extreme events conditions, especially distribution systems. Herein, this paper presents a modeling and simulation platform for electric distribution grids which can estimate overall power demand during extreme weather conditions. The presented platform's efficacy is shown by demonstrating estimation of electrical demand for 1) Electricity Reliability Council of Texas (ERCOT) during winter storm Uri in 2021, and 2) alternative hypothetical scenarios of integrating Distributed Energy Resources (DERs), weatherization, and load electrification. In comparing to the actual demand served by ERCOT during the winter storm Uri of 2021, the proposed platform estimates approximately 34 GW of peak capacity deficit. These numbers are consistent with state-of-the-art prediction results published in the literature. For the case of the future electrification of heating loads, peak capacity of 78 GW (124% increase) is estimated, which would be reduced to 47 GW (38% increase) with the adoption of efficient heating appliances and improved thermal insulation. Integrating distributed solar PV and storage into the grid causes improvement in the local energy utilization and hence reduces the potential unmet energy by 31% and 40%, respectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Impact of climate change on water availability and its propagation through the Western U.S. power grid

Climate impact assessment for power systems has tended to focus on the effects of water availability on generation without explicitly considering how these impacts propagate through the interconnected grid to affect generation in other locations. We investigate the impact of projected water availability on the operations of the contemporary Western U.S. power grid, focusing specifically on regional interdependencies. Hydrologic simulations derived from three GCMs (CCSM4, INMCM4 and GFDL-CM3) and two radiative scenarios (RCP4.5 and RCP8.5) are used to force a large-scale, distributed water management model (MOSART-WM), which translates water availability into power generation constraints at hydropower plants and water-dependent thermo-electric plants. Power system dynamics are evaluated using the production cost model PLEXOS. We find that the inter-regional connections across the Western U.S. electricity infrastructure are key in managing drastic variations in regional water availability. Net generation in the Northwest and Northern California is substantially sensitive to local water availability. Generation from the Desert Southwest emerges as a critical resource to compensate for variations in water availability in those regions. Climate change impacts on Northwestern water availability therefore drive future changes in other regions’ generation and regional power flows. The large inter-annual hydrological variability of Northern California exacerbates grid stress arising from long-term changes in water availability in the Northwest. While the regional power flow directions seem insensitive to long-term variations in water availability, the analysis highlights the need to consider other compounding regional factors such as changes in Southern California net load or changes in regional fuel prices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Real-Time Simulation of Solid Oxide Electrolyzers (SOEC) for Dynamic Operability Improvement and Cyber-Physical System Development

As more intermittent-renewable generations are being added to the power grid, solid oxide electrolysis cells (SOEC) must enhance their rapid load transition capabilities to load follow and support grid resilience. At NETL, we developed real-time SOEC models to research SOEC transients during load step changes. The gained insights can be useful for dynamic operability improvement. These real-time SOEC models also established the basis for cyber-physical SOEC hybrid energy systems. (Virtual presentation to the 2025 MILLENNIUM CLEAN and SUSTAINABLE POWER workshop, University of Genoa, Italy)

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Developing a PSCAD Model of the Reduced 240-Bus WECC Test System: Preprint

Fast-acting controls of inverter-based resources (IBR) introduce unprecedented dynamics to bulk power systems and island power grids, especially the high-frequency dynamics ranging from $>5$ Hz to hundreds of Hz. These oscillatory stability problems cannot be captured by the phasor domain simulations, e.g., in PSS/E, Powerworld and TSAT, due to insufficient modeling. Instead, they should be studied by electromagnetic transient (EMT) simulations by using proper EMT dynamic models. This paper develops and validates the PSCAD model of the reduced 240-bus Western Electricity Coordinating Council (WECC) test system. The PSCAD model will be released to the public, which can be used by both academia and power industry practitioners for studying the fast dynamic problems without any Critical Energy/Electric Infrastructure Information (CEII).

240-bus WECC test system↗
DOE OSTI2024

Hydrogen Storage for Load-Following and Clean Power: Duct-firing of Hydrogen to Improve the Capacity Factor of NGCC Plants (Final Report, Phase II Pre-Front End Engineering Design Study)

GTI Energy (GTI) and team members Southern Company Services (SCS), Pacific Gas & Electric (PG&E) and the Electric Power Research Institute (EPRI) performed a Phase II Pre-Feed Study under contract DE-FE0032008 for Hydrogen Storage for Load-Following and Clean Power. The configuration of the proposed system consists of subsystems for on-site H 2 production, on-site H 2 storage (up to 54 MWth in commercial vessels) and H 2 combustion in a duct burner in a Heat Recovery Steam Generator (HRSG) integrated with an existing fossil asset. Here, the firing rate of the duct burner is varied to let the plant respond to fluctuations of electrical load and H 2 production is relatively constant by storing H 2 . The proposed system is an improvement over alternate low carbon dispatchable power options. Technoeconomic analyses show H 2 produced with GTI’s patented Compact Hydrogen Generator (CHG) with inherent carbon capture will be lower cost (Levelized Cost of Hydrogen, LCOH) relative to hydrogen produced with a Steam Methane Reformer (SMR) with an amine system for carbon capture. This lower cost hydrogen enables our integrated system to deliver electricity (Levelized Cost of Electricity, LCOE) at 17.4% lower cost relative to a SMR sourced H 2 -fired HRSG (with an amine system for carbon capture) – Steam Turbine Generator (STG). Our analysis using EPRI’s US REGEN macroeconomic model shows our system will have significant demand in the power market and therefore require significant capacity expansion (CHG plants built to deliver hydrogen) to deliver low cost, low carbon power. In Phase II, our Team has completed a detailed system definition including the development of process models, definition of battery limits, Process Flow Diagrams (PFDs), Piping and Instrumentation Drawings (P&IDs), and a plant layout. A preliminary design for the key components of the CHG was developed including component lists & specifications. An evaluation of environmental and permitting considerations was completed and included the development of an Environmental Information Volume (EIV). The duct burners, which are flexible and can burn hydrogen and/or natural gas, were defined and initial CFD analyses were completed.

03 NATURAL GAS↗
DOE OSTI2023

Reproducible benchmark for the SNAP 8 experimental reactor at dry conditions

Here, this work provides fully reproducible benchmark models of the Systems for Nuclear Auxiliary Power (SNAP) 8 Experimental Reactor. Validation benchmarks of the criticality configuration experiments under dry conditions with no coolant are presented. In addition, relevant reactivity worth experiments, and measurement of power distributions are validated and presented here. Discrepancies between modeled and experimental results are at most 110 pcm for fuel and poison worths, and critical configurations that do not manipulate control elements are within 50 pcm. Larger discrepancies found in reflector element worth experiments are due to experimental methodology which was noted as being simplified due to limited calculational capabilities at the time, while discrepancy in the control element manipulated critical configuration is due the absence of structural components for modeling simplification. Power distributions closely follow what was observed in experiment with expected peaking in reflecting elements. All models are well documented with cited references describing and justifying assumptions, simplifications, and adjustments to reproduce the models with any nuclear safety codes; model inputs and outputs are stored in the snapReactors GitHub repository.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗