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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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DOE OSTI2025

Nuclear Materials Packaging, Transportation, and Systems Analysis Group Software Quality Assurance Plan: ANSYS Mechanical Finite Element Analysis Software Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic, and electromagnetic simulation capabilities. ANSYS has two main programs, which use the same solvers: (1) Mechanical APDL (ANSYS Design Parametric Language), a Fortran-based coding platform, and (2) ANSYS Workbench, which uses a graphical user interface to aid in finite element analysis implementation. This plan covers both APDL and Workbench. The ANSYS computer program is a large-scale, multipurpose finite element program that can be used to solve several classes of engineering analyses. The analysis capabilities of ANSYS include the ability to solve static and dynamic structural analyses, steady-state and transient heat transfer problems, mode-frequency and buckling eigenvalue problems, static or time-varying magnetic analyses, and various types of field and coupled-field applications. The program contains many special features that allow nonlinearities or secondary effects such as plasticity, large strain, hyperelasticity, creep, swelling, large deflections, contact, stress stiffening, temperature dependency, material anisotropy, and radiation to be included in the solution. As ANSYS has been developed, other special capabilities such as substructuring, submodeling, random vibration, kinetostatics, kinetodynamics, free convection fluid analysis, acoustics, magnetics, piezoelectrics, coupled-field analysis, and design optimization have been added to the program. These capabilities contribute further to making ANSYS a multipurpose analysis tool for varied engineering disciplines. The ANSYS program has been in commercial use for over 50 years and has been used extensively in the aerospace, automotive, construction, electronic, energy services, manufacturing, nuclear, plastics, oil, and steel industries. Additionally, many consulting firms and hundreds of universities have used ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. Ansys design analysis software is the first created within a quality system with ISO 9001 certification, the internationally accepted quality standard. Product development, testing, maintenance and support processes also meet the United States Nuclear Regulatory Commission's quality requirements, as they have for nearly four decades. The Quality Assurance Service Agreement is suitable for the customers working in the nuclear industry who need to meet specific federal regulations including 10CRF50 Appendix B and provisions of 10CFR21. ANSYS has retained its original International Organization for Standardization (ISO) 9001 accreditation certificate since1995-05-04, It’s current certificate is valid until 2027-05-29.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

ORNL Input to GDSA Repository Systems Analysis FY21

This document satisfies the M3 milestone M3SF-21OR010304082 titled “ORNL Input to GDSA Repository Systems.” This document describes the current status of Oak Ridge National Laboratory’s (ORNL’s) efforts related to analyses of dual-purpose canister (DPC) disposal in unsaturated alluvium with a focus on thermal hydrological constraints on criticality timing and power output. This analysis updates previous analyses of thermal hydrological constraints on timing and power output of a potential criticality event in Dual-Purpose Canisters (DPCs) in a hypothetical repository in unsaturated alluvium using a more realistic representation of heat transport inside dry DPCs. PFLOTRAN was used for the simulations of multiphase thermal hydrology near a single DPC. The scenario considers a DPC failure at 9000 years, allowing water to enter and eventually fill the DPC. Once the DPC is filled to a level that could support a criticality event, different values for criticality power output were added to the decay heat. The main objective is to bound the power output that could be produced by a criticality event without driving water out of the package. For the conditions analyzed here, following a package breach, the alluvial formation could supply enough water to allow enough accumulation in the DPC to support a criticality event. However, the power output that would be generated is limited to modest values by loss of water moderator due to evaporation and vapor diffusion. In the reference case scenario, the DPC would not start to fill with water until about 16,000 years post closure and would not fill to a level that allows a criticality event until approximately 25,000 years post closure. The long-term average power output that could be sustained without driving off the water and terminating the criticality event is limited to approximately 100 W. Sensitivity to assumed conditions and parameters in the reference case, especially the deep percolation rate, need to be addressed but could not be undertaken because of numerical failures of the PFLOTRAN code running in general mode in the dry conditions of an unsaturated alluvium repository

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

A Resilient Integrated Resource Planning Framework for Transmission Systems: Analysis and Optimization

This article presents a resilient Integrated Resource Planning (IRP) framework designed for transmission systems, with a specific focus on analyzing and optimizing responses to High-Impact Low-Probability (HILP) events. The framework aims to improve the resilience of transmission networks in the face of extreme events by prioritizing the assessment of events with significant consequences. Unlike traditional reliability-based planning methods that average the impact of various outage durations, this work adopts a metric based on the proximity of outage lines to generators to select HILP events. The system’s baseline resilience is evaluated by calculating load curtailment in different parts of the network resulting from HILP outage events. The transmission network is represented as an undirected graph. Graph-theoretic techniques are used to identify islands with or without generators, potentially forming segmented grids or microgrids. This article introduces Expected Load Curtailment (ELC) as a metric to quantify the system’s resilience. The framework allows for the re-evaluation of system resilience by integrating additional generating resources to achieve desired resilience levels. Optimization is performed in the re-evaluation stage to determine the optimal placement of distributed energy resources (DERs) for enhancing resilience, i.e., minimizing ELC. Case studies on the IEEE 24-bus system illustrate the effectiveness of the proposed framework. In the broader context, this resilient IRP framework aligns with energy sustainability goals by promoting robust and resilient transmission networks, as the optimal placement of DERs for resilience enhancement not only strengthens the system’s ability to withstand and recover from disruptions but also contributes to efficient resource utilization, advancing the overarching goal of energy sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

SEIN: Breaking Barriers Resilient Energy System Analysis [Slides]

The Solar Energy Innovation Network (SEIN) is a collaborative research program that supports multi-stakeholder teams in researching and sharing solutions to real-world challenges associated with solar energy adoption. The Breaking Barriers project was selected to participate in the Solar Energy Innovation Network, Round 2, and was led by Groundswell, a D.C.-based clean energy project developer. The Breaking Barriers team included Partnership for Southern Equity, Atlanta University Center campus facility managers and professors, the City of Atlanta's Neighborhood Planning Unit T, and Georgia Power Company. The project aimed to design and construct innovative urban energy resiliency hubs integrating microgrid technology, solar generation, and energy storage in Atlanta colleges and communities. The hubs will help these historically Black colleges and universities (HBCUs) and the energy-burdened broader community in West Atlanta be more resilient, in addition to informing new course curricula at Atlanta University Center campuses. With many possible options for the system's battery size, the Breaking Barriers team needed insight into the relationships between BESS size, economic performance, and resilience at Spelman College's Manley Center. These insights are crucial for entering procurement negotiations with project developers, establishing resilience capabilities that the HBCU campuses can plan around, and guiding the team's fundraising targets. This analysis includes estimates of PV and battery performance, costs, savings, and resilience for multiple battery sizes. In order to provide power during a grid outage, the resilient energy system also needs to be connected to the Manley Center in a safe and island-able manner (electrically isolated from the grid). Analysis of potential electrical configurations and estimated setup costs is key to successfully entering a required interconnection agreement with Georgia Power, as well as informing requests for engineering firms to construct the system. This analysis includes conceptual options and rough order of magnitude cost estimates for electrically interconnecting the resilient energy system to the Manley Center and the grid. The Breaking Barriers team used this analysis to select preferred system characteristics and design for the resilient energy system.

14 SOLAR ENERGY↗
DOE OSTI2026

PowerAnalytics.jl: User-Centric Power Systems Analysis in Julia

The National Laboratory of the Rockies recently released version 1 of PowerAnalytics.jl, an analysis module for the outputs of its popular open-source electrical power systems modeling platform Sienna. It features an extensible framework - based on the flexible selecting of components, the execution of arbitrary metrics on them, and a familiar DataFrames-based output interface with embedded metadata - to process results in the Sienna style while keeping the interface as simple as possible for non-Julia experts. Here, I describe the package and where it fits into the Sienna ecosystem, how I harnessed user-centered design and Julia features to achieve beginner friendliness without sacrificing performance and expressibility, and what lessons might be drawn from the package's design and implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Multi-system analysis of offshore geologic carbon storage: a review of open-source data science solutions

Geologic carbon storage projects are maturing worldwide and the footprint of deployment in the offshore is expanding. At present, there are ten projects in operation or that have been completed, more than 50 in construction and development, and dozens of characterization studies completed or underway. Offshore geologic carbon storage offers potential benefits over onshore geologic carbon storage. These offshore projects are generally remote in location, distant from population centers, and avoid complicated pore space rights while having abundant prospective storage potential. Some offshore fields targeted for carbon storage have comparatively fewer prior borehole penetrations except for areas that have been explored for petroleum production, minimizing potential issues such as pressure interference and infrastructure impacts. Yet offshore geologic carbon storage projects face distinctive technical and economic challenges, such as seafloor geohazards (e.g., seabed instability), expensive maritime transport, and meteorological-oceanographic conditions that can damage infrastructure and impact operations. Analytical capabilities and improved computational speeds have advanced engineering, earth and energy sciences in the wake of the arrival of modern data science over the last decade. These advancements have created an opportunity for integrated, multi-systems modeling approaches utilizing artificial intelligence and machine learning that are no longer limited by computational issues. Analytical tools developed alongside this advancement in data science can be leveraged to calibrate the potential advantages and challenges of carbon storage operations in the offshore. New methods and approaches that incorporate data science to analyze multiple aspects of engineered and natural systems can provide insights that complement the characterization and onsite engineering that traditional commercial and operational software addresses. These new methods and approaches can potentially improve the outcome of energy operations and carbon storage. Providing multi-system, science-driven data analytics enhances the knowledge base that offshore developers, operators, and regulatory bodies may draw from to improve offshore site selection and operational efficiency. Here, we provide a brief synopsis of geologic carbon storage efforts to date, an overview of the engineered and natural systems involved in offshore geologic carbon storage, and a review of publicly available, open-source, offshore and/or carbon storage related data- and science-driven tools developed by 2010 or later that are suitable for screening and assessing regions for offshore geologic carbon storage.

artificial intelligence↗
DOE OSTI2026

Dynamical Downscaling of Earth System Model Data for Energy System Analysis

Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

The IMG/M data management and analysis system v.7: content updates and new features

The Integrated Microbial Genomes & Microbiomes system at the Department of Energy (DOE) Joint Genome Institute (JGI) continues to provide support for users to perform comparative analysis of isolate and single cell genomes, metagenomes, and metatranscriptomes. In addition to datasets produced by the JGI, IMG v.7 also includes datasets imported from public sources such as NCBI Genbank, SRA, and the DOE National Microbiome Data Collaborative (NMDC), or submitted by external users. In the past couple years, we have continued our effort to help the user community by improving the annotation pipeline, upgrading the contents with new reference database versions, and adding new analysis functionalities such as advanced scaffold search, Average Nucleotide Identity (ANI) for high-quality metagenome bins, new cassette search, improved gene neighborhood display, and improvements to metatranscriptome data display and analysis. Here, we also extended the collaboration and integration efforts with other DOE-funded projects such as NMDC and DOE Biology Knowledgebase (KBase).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

LLRF System Analysis for the Fermilab PIP-II Superconducting LINAC

PIP-II is a superconducting linac that is in the initial acceleration chain for the Fermilab accelerator complex. The RF system consists of a warm front-end with an RFQ and buncher cavities along with 25 superconducting cryo-modules comprised of cavities with five different acceleration \(β\). The LLRF system for the linac has to provide field and resonance control for a total of 125 RF cavities. Various components of the LLRF system have been tested with and without beam at the PIP-II test stands. The LLRF system design is derived from the LCLS-II project with its self-excited loop architecture used in the majority of the cryo-modules. The PIP-II beam loading at 2 mA is much higher than the LCLS-II linac. The control system architecture is analyzed and evaluated for the operational limits of feedback gains and their ability to meet the project regulation requirements for cavity field amplitude and phase regulation.

Varghese, P. [Fermilab] (ORCID:0009000925131983)↗
DOE OSTI2021

Radioactive nuclei in the early Solar system: analysis of the 15 isotopes produced by core-collapse supernovae

Short-lived radioactive isotopes (SLRs) with half-lives between 0.1 and 100 Myr can be used to probe the origin of the Solar system. In this work, we examine the core-collapse supernovae production of the 15 SLRs produced: 26 Al, 36 Cl, 41 Ca, 53 Mn, 60 Fe, 92 Nb, 97 Tc, 98 Tc, 107 Pd, 126 Sn, 129 I, 135 Cs, 146 Sm, 182 Hf, and 205 Pb. Here, we probe the impact of the uncertainties of the core-collapse explosion mechanism by examining a collection of 62 core-collapse models with initial masses of 15, 20, and 25 M ⊙ , explosion energies between 3.4 × 10 50 and 1.8 × 10 52 erg and compact remnant masses between 1.5 and 4.89 M ⊙ . We identify the impact of both explosion energy and remnant mass on the final yields of the SLRs. Isotopes produced within the innermost regions of the star, such as 92 Nb and 97 Tc, are the most affected by the remnant mass, 92 Nb varying by five orders of magnitude. Isotopes synthesized primarily in explosive C-burning and explosive He-burning, such as 60 Fe, are most affected by explosion energies. 60 Fe increases by two orders of magnitude from the lowest to the highest explosion energy in the 15 M ⊙ model. The final yield of each examined SLR is used to compare to literature models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Particle Receiver Models for Systems Analysis

Particle receivers are gaining importance in the field of Concentrating Solar Power (CSP) due to the high temperature that particles can achieve without degradation. Several researchers are studying the potential of this technology by means of system analyses, which need simple and light models of the system. This study presents two simple models for the particle receiver. The simplest model is a correlation obtained by fitting the results calculated with a more complex receiver model simulated in CFD. The other model is a 1D model, which is benchmarked against the same CFD results. Although both models achieve high coefficient of determination, R2, when compared to CFD results, the 1D model seems to provide more accurate results (especially during sunsets and sunrises). Both models are integrated into a tecno-economic model developed in previous work. The LCOE obtained with the 1D model is between 7% and 10% greater than the one obtained with the correlation.

González-Portillo, Luis F. (ORCID:0000000348643825↗
DOE OSTI2025

System Analysis of an Internal Combustion Engine (ICE) - Solid Oxide Fuel Cell (SOFC) Hybrid Cycle

The variability of renewable energy sources poses challenges for reliable grid operation. Conventional thermal power sources, though reliable, often lack operational flexibility. Hybrid energy systems that integrate Solid Oxide Fuel cells (SOFC) with Internal Combustion Engines (ICE) offer a promising solution by achieving relatively higher efficiency and grid-following capability. This study investigates performance of a 100-kW pressurized SOFC-ICE hybrid cycle. In this configuration, unutilized SOFC fuel is used to drive the engine, with a turbocharger providing air supply and an external reformer generating syngas. System components were numerically modeled using MATLAB/SIMULINK for the SOFC and reformer, and EBSILON® for the ICE and balance of plant. Parametric studies varied fuel utilization (70-90%), reformer temperature (600 – 1000K), anode off-gas recirculation (0 – 70%), and current density (0.2 – 0.55 A/cm2). Results show that the SOFC and ICE operate as thermally independent topping and bottoming cycles, achieving peak efficiency of 62% under optimized conditions.

hybrid↗
DOE OSTI2021

A coupled human–natural system analysis of freshwater security under climate and population change

Limited water availability, population growth, and climate change have resulted in freshwater crises in many countries. Jordan’s situation is emblematic, compounded by conflict-induced population shocks. Integrating knowledge across hydrology, climatology, agriculture, political science, geography, and economics, we present the Jordan Water Model, a nationwide coupled human–natural-engineered systems model that is used to evaluate Jordan’s freshwater security under climate and socioeconomic changes. The complex systems model simulates the trajectory of Jordan’s water system, representing dynamic interactions between a hierarchy of actors and the natural and engineered water environment. A multiagent modeling approach enables the quantification of impacts at the level of thousands of representative agents across sectors, allowing for the evaluation of both systemwide and distributional outcomes translated into a suite of water-security metrics (vulnerability, equity, shortage duration, and economic well-being). Model results indicate severe, potentially destabilizing, declines in freshwater security. Per capita water availability decreases by approximately 50% by the end of the century. Without intervening measures, >90% of the low-income household population experiences critical insecurity by the end of the century, receiving <40 L per capita per day. Widening disparity in freshwater use, lengthening shortage durations, and declining economic welfare are prevalent across narratives. To gain a foothold on its freshwater future, Jordan must enact a sweeping portfolio of ambitious interventions that include large-scale desalinization and comprehensive water sector reform, with model results revealing exponential improvements in water security through the coordination of supply- and demand-side measures.

42 ENGINEERING↗
DOE OSTI2024

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop: Preprint

Geothermal cost and performance evaluation implemented via technoeconomic assessment (TEA) modeling is critical for the Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for the Annual Technology Baseline (ATB). The ATB data are inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL’s reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the US generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on technoeconomic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next generation technologies such as closed loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

Annual Technology Baseline↗
DOE OSTI2025

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop

Geothermal cost and performance evaluation implemented via techno-economic assessment (TEA) modeling is critical for the U.S. Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for NREL's Annual Technology Baseline (ATB), which provides inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL's reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the U.S. generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on techno-economic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next-generation technologies such as closed-loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

annual technology baseline↗
DOE OSTI2022

Systems Analysis of the Physiological and Molecular Mechanisms of Sorghum Nitrogen Use Efficiency, Water Use Efficiency and Interactions with the Soil Microbiome (Final Report for DE-SC0014395)

The specific project objectives were to: 1) Conduct deep census surveys of root microbiomes concurrent with phenotypic characterizations of a diverse panel of sorghum genotypes across multiple years to define the microbes associated with the most productive lines under drought and low nitrogen conditions. 2) Associate systems-level genotypic, microbial, and environmental factors with improved sorghum performance using robust statistical approaches. 3) Develop culture collections of sorghum root/leaf associated microbes that recapitulate root-enriched sequences defined in the census. 4) Perform controlled environment experiments for in-depth characterization and hypothesis testing of G sorghum x G microbe x E interactions . Validate physiological mechanisms, map genetic loci for stress tolerance, and determine the persistence of optimal microbial strains under greenhouse and field conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Co-Simulation Meets AI: MCP-Driven Power System Analysis

GridGPT, a fine-tuned Generative AI model is designed for on-premise use in grid control rooms. This presentation will demonstrate how eGridGPT can seamlessly integrate with control room solutions to offer operators, engineers, and corporate users enhanced guidance and decision support. It is to show how this innovative AI solution can improve state estimation, boost variable energy forecasting, and optimize grid operations. By leveraging eGridGPT's unique features, audience will learn to unlock new levels of automation, predictive analytics, and reliability within their power systems, ultimately leading to reduced downtime and improved operational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗