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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Energetic Stability of Freestanding and Metal-Supported Borophenes: Quantum Monte Carlo and Density-Functional Theory Calculations

Quantum Monte Carlo (QMC) and density-functional theory (DFT) calculations were carried out to study cohesion energetics of two-dimensional (2D) sheets of boron atoms called borophenes. Our QMC calculations confirmed the polymorphism among free-standing borophenes that was reported in previous DFT studies. Although Perdew-Burke-Ernzerhof (PBE) calculations significantly overestimate the cohesive energies of 2D boron sheets, DFT-PBE relative energetics with respect to each other among various free-standing borophenes are found to be in quantitative agreement with the corresponding QMC results. This suggests that one can make reliable predictions for relative stability of different boron sheets through DFT-PBE calculations. Our analysis of PBE formation energies of borophenes on metal surfaces shows that the polymorphic range is extended for borophenes on the Ag(111) and the Au(111) surfaces beyond that of free-standing borophenes, reflecting recent experimental synthesis of beta(12) and chi(3) boron sheets on the Ag(111) surface. We have also found that a hexagonal borophene can be stabilized through charge transfer from a metal surface and is energetically favored on the AI(111) surface over other borophene structures. Finally, it is found that the bilayer formation could be energetically favored over its monolayer form for the borophene-Au system, especially for borophenes with hexagonal hole densities eta lower than 1/9. This leads to our prediction that in addition to its monolayer form, a bilayer eta = 1/12 borophene can be synthesized on the Au(111) surface, opening a new possibility for borophene-based electronic devices.

ab initio↗
DOE OSTI2014

QM/MM Simulation (B3LYP) of the RNase A Cleavage-Transesterification Reaction Supports a Triester AN+DN Associative Mechanism with an O2´ H Internal Proton Transfer

The mechanism of the backbone cleavage transesterification step of the RNase A enzyme remains controversial even after 60 years of study. We report QM/MM free energy calculations for two optimized reaction paths based on an analysis of all structural data and identified by a search for reaction coordinates using a reliable quantum chemistry method (B3LYP), equilibrated structural optimizations, and free energy estimations. Both paths are initiated by nucleophilic attack of the ribose O2? oxygen on the neighboring diester phosphate bond and both reach the same product state (PS) (a O3??O2? cyclic phosphate and a O5? hydroxyl terminated fragment). Path 1, resembles the widely accepted dianionic transition state (TS) general acid (His 119)/base (His 12) classical mechanism. However, this path has a barrier (25 kcal/mol) higher than that of the rate limiting hydrolysis step and a very loose TS. In Path 2, the proton initially coordinating the O2? migrates to the non-bridging O1P in the initial reaction path rather than directly to the general base resulting in a triester (substrate as base) AN+DN mechanism with a monoanionic weakly stable intermediate. The structures in the transition region are associative with low barriers (TS1 10, TS2 7.5 kcal/mol). The Path 2 mechanism is consistent with the many results from enzyme and buffer catalyzed and uncatalyzed analog reactions and leads to a PS consistent with the reactive state for the following hydrolysis step. The differences between the consistently estimated barriers in Path 1 and 2 lead to a 1011 difference in rate strongly supporting the less accepted triester mechanism.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2022

A Bayesian Deep Learning Approach to Near-Term Climate Prediction

Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a complementary machine-learning-based approach to climate prediction. The example problem setting we consider consists of predicting natural variability of the North Atlantic sea surface temperature on the interannual timescale in the pre-industrial control simulation of the Community Earth System Model. While previous works have considered the use of recurrent networks such as convolutional LSTMs and reservoir computing networks in this and other similar problem settings, we currently focus on the use of feedforward convolutional networks. In particular, we find that a feedforward convolutional network with a Densenet architecture is able to outperform a convolutional LSTM in terms of predictive skill. Next, we go on to consider a probabilistic formulation of the same network based on Stein variational gradient descent and find that in addition to providing useful measures of predictive uncertainty, the probabilistic (Bayesian) version improves on its deterministic counterpart in terms of predictive skill. Finally, we characterize the reliability of the ensemble of machine learning models obtained in the probabilistic setting by using analysis tools developed in the context of ensemble numerical weather prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Stress-induced Effects Caused by 3D IC TSV Packaging in Advanced Semiconductor Device Performance

Potential challenges with managing mechanical stress and the consequent effects on device performance for advanced 3D through-silicon-via (TSV) based technologies are outlined. The paper addresses the growing need in a simulation-based design verification flow capable to analyze a design of 3D IC stacks and to determine across-die out-of-spec variations in device electrical characteristics caused by the layout and through-silicon-via (TSV)/package-induced mechanical stress. The limited characterization/measurement capabilities for 3D IC stacks and a strict ''good die'' requirement make this type of analysis critical for the achievement of an acceptable level of functional and parametric yield and reliability. The paper focuses on the development of a design-for-manufacturability (DFM) type of methodology for managing mechanical stresses during a sequence of designs of 3D TSV-based dies, stacks and packages. A set of physics-based compact models for a multi-scale simulation to assess the mechanical stress across the device layers in silicon chips stacked and packaged with the 3D TSV technology is proposed. A calibration technique based on fitting to measured stress components and electrical characteristics of the test-chip devices is presented. A strategy for generation of a simulation feeding data and respective materials characterization approach are proposed, with the goal to generate a database for multi-scale material parameters of wafer-level and package-level structures. For model validation, high-resolution strain measurements in Si channels of the test-chip devices are needed. At the nanoscale, the transmission electron microscopy (TEM) is the only technique available for sub-10 nm strain measurements so far.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Rotational stabilization of the resistive wall modes in tokamaks with a ferritic wall

The dynamics of the rotating resistive wall modes (RWMs) is analyzed in the presence of a uniform ferromagnetic resistive wall with μ{sup ^}≡μ/μ{sub 0}≤4 (μ is the wall magnetic permeability, and μ{sub 0} is the vacuum one). This mimics a possible arrangement in ITER with ferromagnetic steel in test blanket modules or in future experiments in JT-60SA tokamak [Y. Kamada, P. Barabaschi, S. Ishida, the JT-60SA Team, and JT-60SA Research Plan Contributors, Nucl. Fusion 53, 104010 (2013)]. The earlier studies predict that such a wall must provide a destabilizing influence on the plasma by reducing the beta limit and increasing the growth rates, compared to the reference case with μ{sup ^}=1. This is true for the locked modes, but the presented results show that the mode rotation changes the tendency to the opposite. At μ{sup ^}>1, the rotational stabilization related to the energy sink in the wall becomes even stronger than at μ{sup ^}=1, and this “external” effect develops at lower rotation frequency, estimated as several kHz at realistic conditions. The study is based on the cylindrical dispersion relation valid for arbitrary growth rates and frequencies. This relation is solved numerically, and the solutions are compared with analytical dependences obtained for slow (s/d{sub w}≫1) and fast (s/d{sub w}≪1) “ferromagnetic” rotating RWMs, where s is the skin depth and d{sub w} is the wall thickness. It is found that the standard thin-wall modeling becomes progressively less reliable at larger μ{sup ^}, and the wall should be treated as magnetically thick. The analysis is performed assuming only a linear plasma response to external perturbations without constraints on the plasma current and pressure profiles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2012

AGE AND STRUCTURE PARAMETERS OF THE REMOTE M31 GLOBULAR CLUSTER B514 BASED ON HST, 2MASS, GALEX, AND BATC OBSERVATIONS

B514 is a remote M31 globular cluster (GC) which is located at a projected distance of R{sub p} {approx_equal} 55 kpc. Deep observations with the Advanced Camera for Surveys on the Hubble Space Telescope are used to provide accurate integrated light and star counts of B514. By coupling the analysis of the distribution of the integrated light with star counts, we are able to reliably follow the profile of the cluster out to {approx}40''. Based on the combined profile, we study in detail its surface brightness distribution in the F606W and F814W filters and determine its structural parameters by fitting a single-mass isotropic King model. The results showed that the surface brightness distribution departs from the best-fit King model for r > 10''. B514 is quite flat in the inner region and has a larger half-light radius than the majority of normal GCs of the same luminosity. It is interesting that, in the M{sub V} versus log R{sub h} plane, B514 lies nearly on the threshold for ordinary GCs as defined by Mackey and van den Bergh. In addition, B514 was observed as part of the Beijing-Arizona-Taiwan-Connecticut (BATC) Multicolor Sky Survey, using 13 intermediate-band filters covering a wavelength range of 3000-8500 A. Based on aperture photometry, we obtain its spectral energy distributions (SEDs) as defined by the 13 BATC filters. We determine the cluster's age and mass by comparing its SEDs (from 2267 to 20000 Angstrom-Sign , comprised of photometric data from the near-ultraviolet band of the Galaxy Evolution Explorer, 5 Sloan Digital Sky Survey bands, 13 BATC intermediate-band filters, and Two Micron All Sky Survey near-infrared JHK{sub s} filters) with theoretical stellar population synthesis models, resulting in an age of 11.5 {+-} 3.5 Gyr. This age confirms the previous suggestion that B514 is an old GC in M31. B514 has a mass of 0.96-1.08 Multiplication-Sign 10{sup 6} M{sub Sun} and is a medium-mass GC in M31.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Local position-space two-nucleon potentials from leading to fourth order of chiral effective field theory

We present local, position-space chiral NN potentials through four orders of chiral effective field theory ranging from leading order (LO) to next-to-next-to-next-to-leading order (N 3 LO, fourth order) of the Δ-less version of the theory. The long-range parts of these potentials are fixed by the very accurate πN LECs as determined in the Roy-Steiner equations analysis. At the highest order (N 3 LO), the NN data below 190 MeV laboratory energy are reproduced with the respectable χ 2 /datum of 1.45. A comparison of the N 3 LO potential with the phenomenological Argonne v 18 (AV18) potential reveals substantial agreement between the two potentials in the intermediate range ruled by chiral symmetry, thus, providing a chiral underpinning for the phenomenological AV18 potential. Our chiral NN potentials may serve as a solid basis for systematic ab initio calculations of nuclear structure and reactions that allow for a comprehensive error analysis. In particular, the order by order development of the potentials will make possible a reliable determination of the truncation error at each order. Our new family of local position-space potentials differs from existing potentials of this kind by a weaker tensor force as reflected in relatively low D-state probabilities of the deuteron (P D ≲ 4.0 % for our N 3 LO potentials) and predictions for the triton binding energy above 8.00 MeV (from two-body forces alone). As a consequence, our potentials may lead to different predictions when applied to light and intermediate-mass nuclei in ab initio calculations and, potentially, help solve some of the outstanding problems in microscopic nuclear structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Appending High-Resolution Elevation Data to GPS Speed Traces for Vehicle Energy Modeling and Simulation

Accurate and reliable global positioning system (GPS)-based vehicle use data are highly valuable for many transportation, analysis, and automotive considerations. Model-based design, real-world fuel economy analysis, and the growing field of autonomous and connected technologies (including predictive powertrain control and self-driving cars) all have a vested interest in high-fidelity estimation of powertrain loads and vehicle usage profiles. Unfortunately, road grade can be a difficult property to extract from GPS data with consistency. In this report, we present a methodology for appending high-resolution elevation data to GPS speed traces via a static digital elevation model. Anomalous data points in the digital elevation model are addressed during a filtration/smoothing routine, resulting in an elevation profile that can be used to calculate road grade. This process is evaluated against a large, commercially available height/slope dataset from the Navteq/Nokia/HERE Advanced Driver Assistance Systems product. Results will show good agreement with the Advanced Driver Assistance Systems data in the ability to estimate road grade between any two consecutive points in the contiguous United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Solar Technology Test, Evaluation, and Data Collection: Cooperative Research and Development Final Report, CRADA Number CRD-08-279

Under this Agreement, NREL will work with Abengoa Solar Inc. on the testing, evaluation, and collection of data related to Abengoa Solar Inc. solar technologies and systems. This work includes, but is not limited to, testing and evaluation of solar component and system technologies, data collection and monitoring, performance evaluation, reliability testing, thermal energy storage integration, solar resource measurement and forecasting, grid impact testing, and analysis. This work will be conducted at NREL, SolarTAC (Aurora), and other field test locations.

14 SOLAR ENERGY↗
DOE OSTI2023

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring

The monitoring of plant equipment for failure prediction is one of the key contributors to operation and maintenance (O&M) costs for a nuclear power plant (NPP) because O&M monitoring depends on labor-intensive activities that are required to meet high equipment reliability standards. These activities rely primarily on humans for information gathering, condition diagnosis, and predictive analysis. Online monitoring aims to automate these activities by relying on sensors to replace human information gathering and machine learning to replace human analysis and decision making. To facilitate automated monitoring, a systematic strategy for anomaly detection is needed to optimally use the available sensor data, empirical models, and physics-supported models. This strategy is essential to provide credible reasoning on why and when an empirical (i.e., purely data-driven) versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. The extant methods usually adopt an ad hoc trial-and-error approach that, in addition to being time-consuming and costly, is also highly subjective; it is impacted by the background and the skill set of the personnel making the decisions. Thus, such an approach cannot guarantee an optimum outcome. This represents the motivation of the current research effort, which is focused on devising a scientifically supported strategy for the optimum selection of anomaly detection methods. This report presents a detailed assessment of the main anomaly detection techniques within the empirical or hybrid method streams. Empirical methods include pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The listed techniques within these two streams represent the vast majority of techniques performed for anomaly detection. Using the techniques as outcomes, a strategy was developed to enable a systematic decision-making process to lead to one of these techniques. The strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability and suitability for training and testing, cause-effect, entropy inference, and model fitting. Each of these decision points in the strategy is explained in detail in this report with examples, along with the scientific basis behind the decisions and outcomes in common and simplified terminology. The strategy is developed for use by any NPP staff with basic engineering or science knowledge. A user-friendly graphical state flow diagram was also developed as a visual presentation of the strategy. The strategy was tested and demonstrated through two pilot projects for the application of anomaly detection at an NPP. Each pilot had two use cases: an initial case in which certain decisions were made that resulted in one or more empirical techniques and a revised use case where one or more key decisions were modified resulting in using a set of hybrid methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Assessing the Thermal Rigidity of a Metal-Cutting Machine

In assessing the quality of metal-cutting machines, quantitative estimates of its various properties are required: the quality assessment is a kind of aggregate. A shortcoming of such assessment is the lack of a measure of thermal stability. Determining the thermal stability of the machine tool from the thermal properties of a sample of the material employed does not provide reliable information. Therefore, in the present work, an appropriate unit of measurement is developed by analysis of the machine tool’s motion under thermal forces. On that basis, the thermal rigidity of the structure may be determined.

42 ENGINEERING↗
DOE OSTI2023

Round-Robin Interlaboratory Study on Rare-Earth Elements in U.S.-Based Geologic Materials

In a study funded by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), the University of North Dakota (UND) Energy and Environmental Research Center (EERC) performed a first-of-its-kind round-robin interlaboratory study (RRIS) to determine lab-to-lab and method-to-method variability in analyzing the rare earth element (REE) content of domestic resources. Analyses of REEs on eleven different materials were accomplished by the laboratories using four different procedures: ASTM D6357 (Procedure A), ASTM D4503 (Procedure B), an alternate in-house procedure for digestion and REE analysis (Procedure C), and neutron activation analysis (NAA). The results of the RRIS suggest that NAA is the most accurate and reliable method for many of the REEs in these types of materials; however, the method is limited in that it is able to determining only ten of the sixteen REEs. Five of the seven labs reporting data for Procedure A and three of the five labs reporting for Procedure B showed excellent performance in terms of repeatability, reproducibility, agreement with NAA, and SRM recoveries based on AOAC International guidelines on method performance. This indicates that when strictly followed these methods are suitable for REE determination in most materials, although are subject to the overall capabilities and experience of individual laboratories.

58 GEOSCIENCES↗
DOE OSTI2015

Statistical model selection for better prediction and discovering science mechanisms that affect reliability

Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidate inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. As a result, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Secure control systems with application to cyber-physical systems

Control systems are computer-based systems with networked units consisting of sensors, actuators, control processing units, and communication devices. The role of control system is to interact, monitor, and control physical processes. Reactive power control is a fundamental issue in ensuring the security of the power network. It is claimed that Synchronous Condensers (SC) have been used at both distribution and transmission voltage levels to improve stability and to maintain voltages within desired limits under changing load conditions and contingency situations. Performance of PI controller corresponding to various tripping faults are analyzed for SC systems. Most of the eort in protecting these systems has been in protection against random failures or reliability. However, besides failures these systems are subject to various signal attacks for which new analysis are discussed here. When a breach does occur, it is necessary to react in a time commensurate with the physical dynamics of the system as it responds to the attack. Failure to act swiftly enough may result in undesirable, and possibly irreversible, physical eects. Therefore, it is meaningful to evaluate the security of a cyber-physical system, especially to protect it from cyber-attack. Illustrative numerical examples are provided together with an application to the SC systems.

Dong, Jin↗
DOE OSTI2024

South Asia Group for Energy-India

The South Asia Group for Energy (SAGE) is working with Grid India and the Central Electricity Authority (CEA) to determine the best methods to deploy more inverter-based resources (IBR) such as solar photovoltaic generators and utility-scale battery. To address grid strength and stability concerns, planners and operators are working with the National Renewable Energy Laboratory's (NREL) team, through SAGE, to identify potential solutions for strengthening the grid and fostering grid reliability.

ENERGY PLANNING, POLICY, AND ECONOMY↗