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At least 991 records · Page 55

Flexible AI Models for Grid Resilience

The rapid growth in size and complexity of artificial intelligence (AI) and machine learning (ML) models has led to increased energy demands, posing a threat to the reliability of the existing power grid. This project addresses the challenge of highly intermittent and energy-intensive inference workloads by (1) developing fidelity-adaptive neural networks capable of dynamic response to grid conditions and (2) integrating these networks with power flow simulations to assess their impact on power grid reliability. We will explore both top-down and bottom-up approaches to create hierarchies of submodels that provide a controlled trade-off between power draw and prediction accuracy. The top-down method utilizes NN pruning to reduce a flagship model into progressively smaller, energy-efficient variants. The bottom-up approach employs geometrically principled weight setting strategies to construct depth-efficient models from the ground up. A real-time hardware-in-the-loop (HIL) platform will be developed to simulate a scaled AC power grid, integrating live AI workload power draw and enabling dynamic model switching in response to grid feedback. This work will provide a novel framework for evaluating the impact of flexible AI/ML workloads on grid performance and establish new methodologies for energy-aware computing in data centers. The outcomes will demonstrate that adaptive AI/ML can play a critical role in improving grid stability while advancing NREL's leadership in energy-efficient computing research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Fuels Campaign Time-at-Temperature Irradiation Campaign and Post-Irradiation Examination Plan

With increasing per capita energy consumption and rapidly growing energy consumption predicted for data centers, the US faces challenges in meeting projected energy demands. The current administration is attempting to accelerate the deployment of new nuclear construction by providing significant investments in advanced nuclear and by modernizing regulatory approaches for the licensing new reactors. However, enabling extended power uprates (EPUs) for the current nuclear reactor fleet would provide a shorter-term solution to better calibrate near-term energy generation capacity to the ever-growing energy demands of the modern era. One pathway to achieve power uprates is to increase the operational window by reassessing fuel safety limits around anticipated transients. Existing light-water reactors (LWRs) utilize a targeted operational window with well-defined operational efficiencies, yet this window is also often bound by conservative safety limits that result in suboptimal operational performance. For example, the operation of the existing fleet is highly constrained by safeguards to operation related to anticipated operational occurrences (AOOs), which are moderate-frequency transients expected with a frequency greater than 0.01 per reactor-year. These AOOs include temperature excursions where the critical heat flux for the system is exceeded, resulting in a departure from nucleate boiling (DNB) at the cladding surface. This DNB event is a thermohydraulic condition that, with current conservative fuel safety limits, results in the fuel rods being classified as “failed,” meaning that the cladding may not be returned to service.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

FervoFlex: Long duration in-reservoir energy storage and load-following, dispatchable geothermal generation

Fervo recently achieved a groundbreaking milestone with the successful completion of its pioneering commercial geothermal project in Northern Nevada. This project is partially supported by the ARPA-E OPEN grant, FervoFlex™ technology—a long-duration in-reservoir energy storage and load-following, dispatchable geothermal generation system. Notably, this project marks a significant stride in commercial viability, delivering uninterrupted, 24/7 clean energy to Google data centers in Nevada (Terrell, Michael 2023)

15 GEOTHERMAL ENERGY↗

Northern Region Coal Prospects

This presentation was delivered to the audience attending the U.S. DOE/USEA Northern Regional Coal Workshop in Bismarck, ND on March 11, 2026. The presentation highlights the opportunity for coal plants in the region to provide power to military installations and data centers. There is also an analysis on how coal-fired power stations maintain regional supply during extreme cold weather events. Finally, a summary slide is presented that highlights a recent business case analysis on diverting captured carbon dioxide for use in enhanced oil recovery in the Bakken.

Bakken↗

Final Prototype Microreactor Transportation Safety Program

This report fulfills the fiscal year 2025 M2 Milestone M2AT-25PN0802042, Final Microreactor Transportation Safety Program Planning Framework. Microreactors are compact reactors capable of producing less than 50 megawatts of electrical energy. Typically, these reactors are factory-fabricated and designed to be easily transportable by truck, rail, vessel, or air. Microreactor designs often assume that the unit can be transported containing either unirradiated or irradiated fuel. Interest in microreactors is driven by several factors, including the need to generate power at remote locations, military installations, and facilities such as data centers, and in areas recovering from natural disasters.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Speed to Power: Solutions for Accelerating Large Load Connections

Rapid growth in demand from data centers and other large loads is creating a range of new challenges for electricity planners, investors, system operators, and regulators, leading to bottlenecks that have slowed connection of large loads to the electric grid. In response, innovative solutions for accelerating large load connections are beginning to emerge across the U.S. Drawing on an extensive document and literature review, this report identifies more than 40 potential solutions for accelerating large load connections, organized into five functional areas: load forecasting, interconnection, resource planning and procurement, markets and operations, and cost allocation and ratemaking. The five functional areas provide a framework for organizing challenges and solutions to large load connection bottlenecks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electricity Rate Designs for Large Loads: Evolving Practices and Opportunities 2026 Update

Electricity demand from large-load customers such as data centers is projected to grow significantly in the near term. While these large loads play an important role in advancing technology innovation and economic growth in the United States, meeting their energy needs requires utilities and regulators to consider important operational and financial risks, such as insufficient energy supply or underutilized investments, that can impact all customers. This paper builds on similar research published in January 2025, providing an overview of how utilities and regulators are managing these risks through different tariffs, including rate structures and electric service agreements. Regulators, utilities, customers, and other stakeholders can use this paper as a foundation when discussing issues and sharing perspectives on developing or reviewing large-load tariffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Alternative Fueling Station Locations

Alternative fueling stations are located throughout the United States and Canada, and their availability continues to grow. The Alternative Fuels Data Center (AFDC) maintains a website where you can find alternative fueling stations near you or on a route, obtain counts of alternative fueling stations by state, view maps, and more. The most recent dataset available for download here provides a "snapshot" of the alternative fueling station information for compressed natural gas (CNG), ethanol (E85), propane/liquefied petroleum gas (LPG), biodiesel (B20 and above), electric vehicle charging, hydrogen, and liquefied natural gas (LNG), as of July 29, 2021.

alt fuel↗

Cardinality-Regularized Hawkes-Granger Model

We propose a new sparse Granger-causal learning framework for temporal event data. We focus on a specific class of point processes called the Hawkes process. We begin by pointing out that most of the existing sparse causal learning algorithms for the Hawkes process suffer from a singularity in maximum likelihood estimation. As a result, their sparse solutions can appear only as numerical artifacts. In this paper, we propose a mathematically well-defined sparse causal learning framework based on a cardinality-regularized Hawkes process, which remedies the pathological issues of existing approaches. We leverage the proposed algorithm for the task of instance-wise causal event analysis, where sparsity plays a critical role. We validate the proposed framework with two real use-cases, one from the power grid and the other from the cloud data center management domain.

Ide, Tsuyoshi↗

Energy efficient integrated photonic systems based on inverse design

The energy footprint of modern information processing and communications systems is immense and utilizes a significant fraction of total global energy usage. Data centers alone consume over 70 billion kilowatt-hours per year. Much of this energy usage is intrinsic to the use of electronic wiring, making optical-based technologies a necessary and promising route to mitigating energy consumption in short- to medium-distance communication links. In this project, we developed and implemented a framework for the design of optical components, based on machine learning, which enables optical components relevant to optical information processing to be realized at their physical performance limits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ARM TBS and TigerShark deployment data in 2021

In 2021, observational data collected using ARM platforms, including seven TigerShark UAS flights and 133 tethered balloon system (TBS) flights, were archived by the ARM Data Center and made publicly available to the user community.

54 ENVIRONMENTAL SCIENCES↗

MSD CoP Webinar: Quantum Computing Futures through a Multisector Lens

Context: This webinar featured two presentations examining quantum computing and its complex implications across the energy, water, and materials sectors. Olivier Ezratty introduced quantum computing, its anticipated applications and added value, and the hardware required to support these systems. He also discussed their energy demands and the role of the Quantum Energy Initiative in developing an interdisciplinary research field focused on these challenges. David McCollum then explored the opportunities and multisectoral challenges associated with next-generation, quantum-accelerated data centers, including their potential energy and resource impacts and the infrastructure chokepoints that could emerge. Together, the presentations emphasized the need for long-term planning and cross-cutting research collaboration as quantum computing technologies continue to develop. Presenters: Olivier Ezratty (Quantum Energy Initiative); David McCollum (Oak Ridge National Laboratory) Moderator: Patrick M. Reed (MSD CoP Facilitation Team); Gokul Iyer (Pacific Northwest National Laboratory) This webinar was held on: July 9th, 2026 from 1:00–2:30 PM EDT.

Quantum Computing↗

Supply Chain for Photovoltaics in the United States: 2024 in Review

Solar photovoltaic (PV) and battery energy storage system (BESS) technologies are two immediately available options for meeting U.S. electricity demands, which are increasing due to expansion of loads from end uses including data centers, buildings, vehicles, and factories. Globally, PV and BESS supply chains are dominated by products manufactured in China and elsewhere by Chinese companies. However, U.S. PV and BESS manufacturing have recently grown, with some capacity in each step of the PV supply chain, albeit not enough to currently meet demand with domestic manufacturing alone. This study analyzes U.S. PV supply chains and costs in 2024, for the crystalline silicon and cadmium telluride module supply chains. The full report additionally addresses the PV balance of system, inverter and BESS supply chains. The study concludes with an analysis of technology installation trends, government support for domestic manufacturing, manufacturing jobs, and the domestic content of PV systems installed in the United States in 2024.

14 SOLAR ENERGY↗

Generic and ML Workloads in an HPC Datacenter: Node Energy, Job Failures, and Node-Job Analysis

HPC datacenters offer a backbone to the modern digital society. Increasingly, they run Machine Learning (ML) jobs next to generic, compute-intensive workloads, supporting science, business, and other decision-making processes. However, understanding how ML jobs impact the operation of HPC datacenters, relative to generic jobs, remains desirable but understudied. In this work, we leverage long-term operational data, collected from a national-scale production HPC datacenter, and statistically compare how ML and generic jobs can impact the performance, failures, resource utilization, and energy consumption of HPC datacenters. Our study provides key insights, e.g., ML-related power usage causes GPU nodes to run into temperature limitations, median/mean runtime and failure rates are higher for ML jobs than for generic jobs, both ML and generic jobs exhibit highly variable arrival processes and resource demands, significant amounts of energy are spent on unsuccessfully terminating jobs, and concurrent jobs tend to terminate in the same state. We open-source our cleaned-up data traces on Zenodo (https://doi. org/10.5281/zenodo.13685426), and provide our analysis toolkit as software hosted on GitHub (https://github.com/atlarge-research/2024-icpads-hpc-workload-characterization). This study offers multiple benefits for data center administrators, who can improve operational efficiency, and for researchers, who can further improve system designs, scheduling techniques, etc.

crossanalysis↗

Apollo 13 lunar photography

A data users' note announces the availability of Apollo 13 pictorial data and aids the investigator in the selection of Apollo 13 photographs for study. This note provides guidance in the interpretation of the photographs. The note includes brief descriptions of the Apollo 13 mission objectives, photographic equipment, and photographic coverage and quality. The National Space Science Data Center (NSSDC) can provide all forms of the photographs described.

Anderson, A. T.↗

Apollo 14 lunar photography. Part 1: Data user's note

The availability of Apollo 14 pictorial data is announced to aid investigators in the selection of Apollo 14 photographs for study. Guidance in the interpretation of the photographs is provided. As background information, the note includes brief descriptions of the Apollo 14 mission objectives, photographic equipment, and photographic coverage and quality. The National Space Science Data Center (NSSDC) can provide the photographs described.

Anderson, A. T.↗