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DOE OSTI2026

Current Best Practices on Wildfire Risk Reduction for Electric Transmission and Distribution Systems

This report provides a set of best practices in response to Section 4(d) of Executive Order 14308, Empowering Commonsense Wildfire Prevention and Response. The information contained herein is expected to be used in conjunction with other materials at the Federal Energy Regulatory Commission Wildfire Risk Mitigation Technical Conference (Docket No. AD25-16-000), with possible direction to the North American Electric Reliability Corporation to take action. The objective of this report is to provide an overview of existing and emerging best practices currently employed or planned by utilities for wildfire mitigation, demonstrating how these efforts align with the executive order’s emphasis on reducing electric utility–caused wildfires while also balancing cost-effectiveness. Additionally, while most practices in utility-developed wildfire mitigation plans focus on risk reduction through robustness and operational reliability, this report also discusses best practices for resilience. The best practices are adopted from publicly available utility wildfire mitigation plans from the United States and Canada, recent findings from wildfire risk reduction research, and industry engagement.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Advancing Understanding of Geothermal Representation in the Power Sector to Accelerate Deployment

Driven mostly by decarbonization goals, geothermal interest in the US power sector has grown considerably, gradually evolving from being considered a niche technology, to being recognized as a viable source of clean, baseload, grid-balancing power, and renewable electric power generation. Furthermore, recent technical advances that could greatly accelerate deployment in the near future, and US federal incentives for low-carbon generation technologies, including geothermal, can enable opportunities for integrating geothermal into utilities resource planning portfolios. However, in general, utilities do not have in-house expertise to evaluate geothermal technologies and its potential role in helping decarbonize the grid as well as help them achieve their individual decarbonization goals. To date, geothermal is rarely included in Capacity Expansion Models (CEM) which utilities use in their planning activities and resource/technologies prioritization. To this end, EPRI and NREL are working together in a DOE-GTO funded research project to improve geothermal understanding (opportunities, value, risks) among the power industry to help accelerate geothermal deployment. In the present paper we describe the approach and preliminary findings of this work, focused on two topics: 1) Expand the degree of understanding on the value, opportunity, and risk of geothermal technologies among utilities and related companies/groups, specifically around geothermal for power generation. 2) Improve representation of geothermal power technologies in capacity expansion models (CEM).

capacity expansion models↗

DOE OSTI2026

Distribution System Plan Template and Guide for Electric Utilities for Adaptation by States and Utilities [Slides]

LBNL researchers developed a template and companion guide for structuring distribution system plans. The template covers 10 key sections in utility distribution system plans and underlying topics: -Executive Summary -Planning Objectives -Current Distribution System -Planning Approach -Asst Management, Reliability and Resilience -O&M Expenses -Capacity Expansion Planning -Solution Identification -Cost-effectiveness -Implementation For each section in the template, the companion guide provides: a description of the topics covered and their importance; the type of content to include in the plan; an example utility approach; and references to other utility plans that serve as models for the topic.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Examples of State and Utility Actions on Proactive Planning and Investments

As states across the U.S. confront rising electricity demand, clean energy deployment, grid modernization imperatives, and the integration of large new loads, some regulators and utilities are shifting away from reactive, “just-in-time” investment approaches toward more proactive planning and investment frameworks. This report compiles examples of jurisdictional and utility actions that reshape planning processes, cost recovery mechanisms, and performance oversight to anticipate—rather than simply respond to—future grid needs. Several themes emerge from state actions examined in this report. First, legislatures and commissions are increasingly directing utilities to proactively upgrade their distribution and transmission systems, reflecting a shift toward a forward-looking system that aligns planning with state policy goals. Second, states are establishing long-term, iterative planning frameworks that often feature multi-year horizons, biannual or annual compliance reporting, structured opportunities for stakeholder engagement, and emphasis on collaboration among utilities, regulators, and stakeholders. Third, states are actively investigating innovative cost recovery mechanisms designed to support accelerated electrification and grid modernization, while balancing consumer advocates’ concerns regarding the ratepayer financial risks of premature investments. Fourth, performance metrics and reporting requirements are being developed to ensure transparency and accountability for proactive investments. Fifth, methodological improvements in planning—such as aligning load forecasting assumptions, incorporating sensitivities, and considering load management potential across building, vehicles, storage, and demand response—are recurring areas of stakeholder focus across jurisdictions. Overall, these developments signify a growing recognition among state regulators, utilities, and stakeholders that proactive planning—supported by clear definitions, consistent and transparent methodologies, robust performance metrics, and innovative cost recovery mechanisms—is a tool that can be used to address the scale and urgency of contemporary grid needs.

electricity market↗

DOE OSTI2024

Review of Literature and Utility Commission Proceedings Relevant to Integrated System Planning: Annotated Bibliography Prepared to Support the Washington Utilities and Transportation Commission

In 2024 the Washington State Legislature passed the Decarbonization Act for Large Combination Utilities (Engrossed Substitute House Bill 1589 – the Act). The Act requires a large combination electric and gas utility to conduct integrated system planning supporting electrification and gas system decarbonization, including a reduction in the gas rate base. The utility is required to submit the first integrated system plan (ISP) by January 1, 2027. The requirements are to be developed and adopted by the Washington Utilities and Transportation Commission (UTC) by July 1, 2025. In October 2024 Pacific Northwest National Laboratory (PNNL) and Lawrence Berkeley National Laboratory (LBNL) began providing technical assistance to the UTC to support the ISP rulemaking. PNNL and LBNL have prepared this annotated bibliography of research and reports, and state examples of coordinated gas and electric planning, future of gas, and future of heat proceedings in other U.S. States and one Canadian Province. The items described here have been selected by the authors for their potential relevance to the UTC’s integrated system planning rule discussions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Risk-controlled Expansion Planning with Distributed Resources (REPAIR) v1.0

The Risk-controlled Expansion Planning with Distributed Resources (REPAIR) is an innovative tool to support decisions around utility grid planning to prevent and mitigate the impact of outages caused by routine equipment failures (reliability) or by extreme events (resilience), such as storms, earthquakes or wildfires that long term interruption of service. REPAIR is a risk-based optimization and decision-making model allowing informed and transparent "cost vs risk" decisions regarding infrastructural planning of electric utilities. The model considers long-term resilience and reliability planning strategies that rely on traditional infrastructure upgrade (e.g. circuit hardening, reinforcement, new substations, etc.) or new investment alternatives, such as DERs.

Heleno, Miguel [Lawrence Berkeley National Laborat↗

DOE OSTI2026

Generative large language models for predictive maintenance planning

Maintenance planning and the generation of necessary components for tasks can prove time-consuming and complex. Automating the creation of recurring or similar tasks by leveraging previous planning packages and data, while uncovering insights to automate planning package generation, presents an opportunity to conserve valuable time and resources. This work aims to harness the textual and probabilistic capabilities of large language models (LLMs) to automate the generation of planning packages. Utilizing diverse data sources ranging from raw data to handwritten text, both singular and collaborative LLMs are trained and tested. Results demonstrate their capability to generate essential planning package components, effectively replicating the statistical patterns in the data. This demonstrates the use of these tools inside a digital asset for automated planning. This work outlines a methodology for constructing datasets, a training suite, and evaluation methods for LLM-based textual and conversational planning tools utilized in an asset digital twin. Results indicate that the fine-tuned models generate estimated planning information within the statistical ranges observed in real maintenance data. The models achieve high accuracy (>90%) in document question-answering and instruction generation tasks. Furthermore, the conversational retrieval-augmented generation (RAG) assistant system achieves 100% document retrieval accuracy, while conversational information capture exceeds 98% across the majority of work-package assistant modules.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Bridging the Gap on Data, Metrics, and Analyses for Grid Resilience to Weather Events: Information that utilities can provide regulators, state energy offices, and other stakeholders

A growing number of states require regulated utilities to file resilience plans to improve the electric grid’s ability to anticipate, withstand, adapt to and recover from increasingly severe weather events. This report aims to help state regulators identify and request data, metrics, and analyses from utilities and use it in decisions on utility resilience plans and investments. The report reviews state requirements and utility plans focused on overall grid resilience, climate change resilience and vulnerabilities, infrastructure modernization, storm protection, and wildfire mitigation. It details types of data, metrics, and analyses across five categories--and provides examples of each from the utility plans. The first category is vulnerability assessments, or evaluations of the susceptibility of systems, communities, or assets to potential harm from identified hazards. The second is data on hazards and the exposure of utility assets and customers to these hazards. The third is attribute metrics, or system characteristics that contribute to or describe the resilience of a system. The fourth is performance metrics, which are impacts of resilience investments on system performance--typically a reduction of negative impacts from hazard events. Finally, evaluation and prioritization are analyses that utilities conduct to estimate impacts from resilience measures (evaluation) and prioritize measures based on costs and estimated impacts (prioritization). The report concludes with examples of key trends and emerging best practices for states and utilities, and identifies areas for further research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Moving from Information Assurance to Functional Assurance with Engineered Controls

Cyber threats to operational technology demand more than traditional IT defenses—they require full-spectrum mission assurance. Cyber-Informed Engineering (CIE) is an approach that embeds engineered controls into system design to ensure critical functions remain safe and reliable, even under attack. Unlike conventional cybersecurity tools, engineered controls act directly on physical processes to prevent unacceptable outcomes such as equipment damage or mission failure. This session will outline the CIE framework and share examples of consequence-based design that deliver true resilience, not just fail-safe behaviors. Attendees will learn how to integrate these principles into the engineering lifecycle to support resilient-by-design architectures and inform emerging standards. This talk sets the stage for the panel discussion on advancing CIE across sectors as digital and physical systems converge.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

FY25 Ion Exchange Processing for the West Area Risk Management (WARM) Project

The West Area Risk Management (WARM) Project was established to enable near-term retrieval and pretreatment of tank waste from Hanford’s 200 West Area and to support deployment of an ion exchange (IX) system capable of producing cesium-depleted supernate suitable for offsite treatment and disposal. The WARM experimental campaign was designed to provide key data for design and operational planning of the 200 W IX system, which plans to utilize crystalline silicotitanate (CST) as the active media for cesium removal. This report documents a comprehensive FY25 experimental campaign designed to produce key technical data required for design and operational planning of the WARM IX system. Testing includes assessing Cs and Sr breakthrough performance in a 4-column system, Cs capacity batch contact testing, phosphate precipitation assessments, reduced-hydroxide feed displacement evaluation, and Sr speciation impacts on Sr removal. The experimental results provide detailed trends in Cs and Sr loading behavior, breakthrough performance across a 4-column staged IX system, distribution profiles within CST beds, and projections of operational flowrates relative to Waste Acceptance Criteria (WAC) limits. Batch contact testing established equilibrium partitioning behavior for the S1–S5 simulants and characterized how matrix chemistry influenced Cs sorption onto CST. Additionally, further evaluations on waste matrix as it pertains to precipitation potential were also determined. Collectively, these datasets support engineering design choices for WARM system throughput and pretreatment planning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Exploring Wildfire & Energy data toward State Prioritization Index (WESPI)

Energy infrastructure can both induce and suffer risks from wildfires ranging from direct damage to energy assets such as substations and power lines to Public Safety Power Shutoffs. Recent wildfire events underscore the need for data-driven approaches that help states and utilities proactively plan for wildfire risk. Existing national tools such as Federal Emergency Management Agency (FEMA)’s National Risk Index (NRI) are valuable for community hazard planning. However, they are less suited for energy infrastructure, as they emphasize population and building exposure rather than system vulnerabilities. In this paper, we explore relationships between energy and wildfire data and present a Wildfire-Energy State Prioritization Index (WESPI). Our methodology combines data from the US Forest Service’s Fire Simulation (FSIM) dataset with energy resilience metrics, historical fire incidents, and geospatial data on transmission lines and fire stations. Correlation analyses suggest that FSIM burn probability is more strongly associated with power outage metrics (ρ = 0.32) than NRI wildfire frequency, and counties with a greater density of fire stations experience more frequent, but less intense wildfires. We further leverage data for burn probability, transmission line density, and fire station density to develop a Wildfire-Energy State Prioritization Index (WESPI) to highlight counties where wildfire hazard, infrastructure exposure, and limited suppression capacity converge. The index provides a consistent, scalable framework for state energy offices and utilities to screen counties for vegetation management, optimization of outage management system deployment, and to inform wildfire mitigation plans.

Critical infrastructure↗

DOE OSTI2024

Enhancing Cloud Cybersecurity: Prescriptive Controls for Operational Technology

This whitepaper provides strategic insights and recommendations into security cloud-based solutions for electric utilities, encompassing operational technology (OT), virtual power plants (VPP), distributed energy resources (DERs), applications, networks, and data storage as they transition to and leverage cloud infrastructure through managed service providers (MSPs) and cloud service providers (CSPs). Principles derived from established frameworks serve as a foundation for best practices across cybersecurity projects and remove the constraints of settling on a single framework. For organizations that prefer not to integrate a specific framework altogether, elements of the proposed approach could be adopted or tailored to best fit defined requirements and expected functionalities. The Cirrus assessment, a utility cloud feasibility tool, and the roadmap it provides serve as a precursor to this paper, which seeks to be a valuable resource for defining next steps following cloud technology integration feasibility appraisal. With its comprehensive approach to adoption, the Cirrus framework offers strategic guidance on responsibly preparing for or deploying a utility cloud solution. The previously published whitepaper, “Use Case-Informed Framework for Utility Cloud Migration,” details the guiding strategy, research, and deployment of cloud solutions within electric and interconnected grid systems. Before implementing the controls suggested in this document, it is recommended that stakeholders complete Cirrus's cloud integration assessment and pair the results with their unique cybersecurity controls to form a comprehensive cloud-based utility cybersecurity plan. The Cirrus outcome will consider a series of future architectures for the grid before and after the energy transition and evaluate the arguments for and against cloud applications for each electric and interconnected grid layer. This document is a companion to the original whitepaper, "Use Case-Informed Framework for Utility Cloud Migration" to further identify and recommend security controls based on Cirrus’s cloud integration assessment output. The following whitepaper outlines the cybersecurity controls that secure cloud-service models pertinent to the electric sector using the predefined categories identify, protect, detect, and respond and recover. The objective is to outline prescriptive security controls based on the type of architecture and data stored in the cloud. The focus includes dissecting the shared responsibility model and elucidating what on-premises Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) entail. A pivotal consideration in this context is allocating responsibility for foundational cybersecurity aspects—having used Cirrus for the cloud integration assessment. The ensuing controls detailed herein also represent a checklist of controls necessary for a secure cloud transition, equipping utilities with the knowledge to navigate this digital transformation with confidence and strategic foresight in a safe and responsible manner.

42 ENGINEERING↗

DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗

DOE OSTI2024

Battery State of Health Estimator: Cooperative Research and Development Final Report

NREL has developed a software tool to enable Renewance to estimate the degradation of batteries from basic information such as the type of battery and the application of that battery during its first life, so that used batteries may be evaluated for potential repurposing at low cost. This software tool utilizes NREL's BLAST-Lite battery degradation modeling code, which was updated with additional models for commercially produced lithium-ion batteries as a part of this CRADA. The software tool enables users to input details such as battery type and application so that lifetime estimates can be made without any programming or expert battery knowledge. The application input loads in saved values for parameters such as cycles per year, depth-of-discharge, and other battery operating parameters from a file defined by Renewance. These parameters may be modified to refine simulations for specific batteries. The software tool also incorporates a degradation model optimization tool, whereby existing battery degradation models may be tuned according to measured battery health. This ensures that new models still predict degradation behaviors expected from a certain battery chemistry, but with the overall degradation rate tuned to a specific battery make and model. The new model can then be saved for estimating the degradation of other similar batteries. An additional task was planned to utilize machine-learning to enable battery health diagnosis from rapid EIS measurements to accelerate the screening of used batteries. This task was not completed due to lack of available data for training a machine-learning model. CRADA benefit to DOE, Participant, and US Taxpayer: Further development of open-source software tool BLAST-Lite for predicting the lifetime of commercially produced Lithium-ion batteries (NREL SWR-22-69).

25 ENERGY STORAGE↗

DOE OSTI2024

Best Practices in Integrated Resource Planning: A guide for planners developing the electricity resource mix of the future

Most states today require regulated electric utilities to file an IRP every 1 to 5 years, and some utilities voluntarily prepare these plans. Planning needs have changed in recent years due to emerging load growth, plant retirements, rising costs, and more extreme weather events – among other factors. In response, Synapse Energy Economics and Lawrence Berkeley National Laboratory produced a joint report, Best Practices in Integrated Resource Planning: A guide for planners developing the electricity resource mix of the future. The guide offers best planning practices for electricity systems undergoing a major transition, but also contains a wealth of practical guidance to develop technically sophisticated, clearer, more effective, and state-of-the-art electric utility resource plans. The guide is for resource planning professionals and stakeholders involved in resource planning processes. This diverse group includes utility personnel tasked with conducting resource planning and making investment decisions, state regulatory commissions that develop planning guidance and oversee the resource planning process, and stakeholders that represent a wide range of interests—utility consumer advocates, environmental groups, industrial customers, local governments, independent power producers, and many other

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

The molten salt tritium transport experiment: A pumped fluoride salt loop for hydrogen isotope experimentation

Molten salt reactors (MSRs) and fusion reactors propose to use molten salts as coolants and breeder blanket materials, respectively. Tritium, however, poses safety concerns in both reactor types due to its ability to permeate through reactor materials and potential for environmental release. This manuscript addresses the tritium transport phenomena in molten salts and presents the design and analysis of the Molten Salt Tritium Transport Experiment (MSTTE). MSTTE is a forced-convection fluoride salt loop intended to measure hydrogen isotope permeation through structural materials in a flowing salt system. In the first phase, MSTTE will use FLiNaK salt and deuterium as surrogates for FLiBe and tritium, with future plans to utilize tritium and FLiBe. MSTTE couples a Copenhagen Atomics pumped salt loop with an external test section that introduces hydrogen isotopes into the loop and measures transport phenomena. The Hydrogen Injection System (HIS) controls hydrogen isotope introduction into the molten salt loop. Here, the permeation test section measures the permeation rate through stainless steel tubing in contact with flowing salt. Computational fluid dynamics (CFD) analysis ensures fully developed salt flow in the permeation test section. MSTTE is modeled with MELCOR-TMAP to predict the permeation rate as a function of experimental variables such as source term, salt flow rate, and salt temperature. Results indicate that the source term is the only parameter with a significant effect on the permeation rate. Pressure drop analysis suggests that the loop should operate below 200 LPM to maintain a pressure drop below 200 kPa. Additionally, finite-element analysis assesses thermal stress during loop operation to ensure the experiment's safe design. MSTTE will provide semi-integral data on tritium transport phenomena in molten salts and serve as a testbed for advancing molten salt technology.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Extending the operational boundaries of RMP-ELM suppression with optimized 3D field control

The use of 3D magnetic fields is one of the promising approaches to control edge localized modes (ELMs), and ITER has plans to utilize a flexible 3D coil set for ELM suppression using 3D fields. This study focuses on optimizing the 3D field spectrum to expand the operational window for n = 1 resonant magnetic perturbation (RMP) ELM suppression in KSTAR. The optimized n = 1 RMP effectively suppresses ELMs throughout the entire H-mode discharge, including the first ELM crash, while avoiding the onset of disruptive locked modes in low-density L-mode plasmas. The predicted suppression window aligns well with experimental data, highlighting the challenges and solutions of using n = 1 RMP at low densities. Moreover, the optimization successfully achieved n = 1 RMP ELM suppression for the first time in ITER-relevant q 95 and shaping conditions, including cases with q95 as low as 3.6, as well as other q 95 and shape configurations. This highlights the importance and utility of 3D coil optimization while emphasizing the potential of long-wavelength low-n RMP, which will be valuable for ex-vessel coils designed to avoid complications of nuclear degradation.

3D magnetic field control↗

DOE OSTI2026

Selecting Critical Scenarios of DER Adoption in Distribution Grids Using Bayesian Optimization

We develop a new methodology to select scenarios of DER adoption most critical for distribution grids. Anticipating risks of future voltage and line flow violations due to additional PV adopters is central for utility investment planning but continues to rely on deterministic or ad hoc scenario selection. We propose a highly efficient search framework based on multi-objective Bayesian Optimization. We treat underlying grid stress metrics as computationally expensive black-box functions, approximated via Gaussian Process surrogates and design an acquisition function based on probability of scenarios being Pareto-critical across a collection of line- and bus-based violation objectives. Our approach provides a statistical guarantee and offers an order of magnitude speed-up relative to a conservative exhaustive search. Case studies on realistic feeders with 200-400 buses demonstrate the effectiveness and accuracy of our approach.

Mulkin, Olivier↗