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At least 253 records · Page 14

Integrating AI Data Centers with the Power Grid

The rapid expansion of artificial intelligence (AI) has triggered an unprecedented surge in electricity demand, with US data center energy use projected to double or triple 2023 levels by 2028. This exponential growth places strain on grid infrastructure, which can hinder timely construction of desired computing capacity. To bridge this supply-demand gap, utilities and AI developers are increasingly turning to demand flexibility, a strategy that incentivizes shifting or reducing power use during peak periods of grid stress. Data centers are uniquely equipped for flexible operations due to their digital workloads, built-in redundancy, and onsite energy assets. This article outlines four primary mechanisms to enable data center flexibility: computational load flexibility (shifting tasks temporally or geographically), flexible use of core facility infrastructure adjustments, energy storage utilization, and onsite electricity generation. To encourage adoption, utilities are deploying new tariff designs, including voluntary interruptible service riders, mandated flexibility requirements, and streamlined interconnection processes for flexible loads. For the highly capitalized and rapidly growing AI industry, the primary motivators for embracing these strategies are expediting facility interconnection, satisfying emerging regulatory mandates, and mitigating community resistance. While demand flexibility cannot substitute the long-term need for new bulk power generation, it serves as an essential, immediate solution for enabling near-term deployment. By transforming data centers from grid stressors into stabilizing assets, flexible operations can ensure reliable grid integration, ease market pressures, and support a resilient power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

LAF-Net: A Deep Residual and Cross-Attention Framework for Day-Ahead Load Forecasting: Preprint

Accurate day-ahead load forecasting is essential for reliable power system operations and market efficiency. System operators such as the Midcontinent Independent System Operator (MISO) rely on forecasts from multiple vendors, yet combining them effectively remains a persistent challenge due to vendor-specific biases. This paper presents a novel LSTM-Attention Fusion Network with Error Representation (LAF-Net) that enhances day-ahead hourly load forecasting through deep residual learning and multi-modal cross-attention. The proposed model builds a historical error memory from past vendor performance and dynamically queries it with future hour context to generate adaptive, hour-specific trust weights for each vendor. A bounded residual correction further refines forecasts by mitigating systematic and temporally localized errors. Tested on real MISO LBA data with multi-vendor forecasts, LAF-Net consistently outperforms the best vendor baseline across all 38 LBAs, achieving more than a 40% reduction in system-level mean absolute error (MAE) during peak load hours relative to the best vendor baseline.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SMART SiC Power ICs: Scalable, Manufacturable, and Robust Technology for SiC Power Integrated Circuits (Final Technical Report)

This collaborative project was initiated with the goal of developing Scalable, Manufacturable, and Robust Technology for SiC Power Integrated Circuits (SMART SiC Power ICs). In pursuit of this objective, innovative designs and fabrication processes were implemented, enabling the development of large-scale (>1 cm²) SiC Complementary Metal-Oxide-Semiconductor (CMOS) integrated circuits and high-voltage (400–600 V) lateral power MOSFETs (HV-LDMOS) on 150 mm 4H-SiC substrates. The resulting SMART SiC Power ICs are tailored to support a wide range of applications requiring diverse voltage and power levels, including automotive systems, industrial equipment, electronic data processing, energy harvesting, and power conditioning. To achieve the proposed ‘SMART’ technology for SiC ICs, the team focused on 1) the Development of highly scalable CMOS (with high channel mobilities for n-type and p-type MOSFETs), LDMOS (~600V, 10A rated), and IC technologies, 2) Establishment of a manufacturable process baseline in a production-grade-, 150mm, SiC fabrication facility, and 3) Demonstration of SMART SiC ICs. The project initially comprised of fabricating 5 lots. In lot 1 monolithic integration using a single process was achieved. Here, we were able to successfully accomplish Integrated HV NMOSFET with LV CMOS on N-epi/N+ Substrate. The HV NMOS demonstrated a Breakdown Voltage (BV) more than 600V. Circuit demonstration of CMOS was also another achievement from this lot. In lot 2, priority was in place for isolation and integration. Here we addressed the isolation concerns and integrated the HV NMOS and LV CMOS using the N-epi/P-epi/N+ substrate. Similar to the lot 1, we were able to achieve a BV of 600 V for HV NMOS. Optimized gate oxide process with high channel mobilities, better gate oxide reliability, development of SPICE models, successful ohmic process development, novel wafer area saving design layouts, P+ isolation schemes with channeling implantations and high temperature operational circuits demonstrations are some of the key highlights from lot 1 and lot2. In lot 3, discrete device performances of HV NMOS with a BV ~700V and reliable LV CMOS performances were achieved. Also, novel architectural solutions were successfully implemented to suppress the electric field crowding at the gate oxide for reliable operations. In lot 4, half bridge power driver ICs with a conversion efficiency of (target 90% to 95%) in the 1-5MHz switching frequency range for output power between 25 W to 3 kW have been included in. However, due to the unfortunate events of sudden foundry shutdown (SiCamore Semi) the processing of lot 4 wafers came to a complete stop (January 2024). Arrangements have recently been made to shift the fabrication to another foundry, General Electric Aerospace. The fabrication process now on course (as of December 2024). Characterizations are delayed due to this unfortunate circumstance. The proposed trench architectural-based devices and ICs (lot 5) underwent modifications from the original project proposal. This change was necessitated by limitations in the availability of trench-based processes at commercial production-grade fabrication facilities in the US. Apart from above achievements, a Process Development Kit (PDK) was successfully developed for planar type SiC CMOS/LDMOS.

42 ENGINEERING↗

Solar and Storage Integration in the U.S. Southeast: Implications for Resource Adequacy

Resource adequacy concerns may be very different in electricity systems that have higher levels of solar and storage, requiring changes to existing planning models. This study explores a novel approach to evaluating resource adequacy under future scenarios with higher solar and storage in the Southeast U.S. It uses NREL’s Probabilistic Resource Adequacy Suite (PRAS), a collection of probabilistic resource adequacy modeling tools, and compares results when interacting PRAS and a portfolio planning tool with a more traditional modeling approach. The results suggest that traditional models perform reasonably well with lower levels of solar PV, but at higher levels of solar probabilistic tools better capture the changes in resource adequacy concerns—such as winter energy availability—associated with higher solar systems. This is the final study in the Preparing Southeast Markets for Reliable and Affordable Integration of Solar into Operations and Planning project. Two prior reports can be found at: Solar and Storage Integration in the Southeastern United States: Economics, Reliability, and Operations. https://emp.lbl.gov/publications/solar-and-storage-integration Solar and Wind Forecast Error Reserve Sharing in a Multi-Utility Region. https://eta-publications.lbl.gov/sites/default/files/2024-11/multiutility_fe_reserve_sharing_final.pdf

14 SOLAR ENERGY↗

Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities

Improvements in process monitoring and control at water resource recovery facilities (WRRFs) could result in reductions in electricity consumption, chemical inputs, and greenhouse gas emissions, as well as improved energy recovery. Many current WRRF data collection, monitoring, and control approaches use 20th century process monitoring and control systems, which require large design safety factors to ensure reliability in the absence of more advanced, precise controls. Implementation of more modern data-driven control tools could lead to more efficient operations that provide intrinsic reliability with better overall process performance at full-scale. This project (1) developed and demonstrated data-driven process controls at full-scale facilities for five promising WRRF process technologies that provide whole-plant approaches and offer substantial energy and resource recovery benefits, and (2) created a Machine Learning (ML) Toolkit and an implementation guide of new process control approaches that walks users through each step of the ML workflow and illustrates the steps through case study examples.

54 ENVIRONMENTAL SCIENCES↗

A hybrid surrogate modeling framework for the Digital Twin of a Fluoride-salt-cooled High-temperature Reactor (FHR)

While nuclear energy is a non-greenhouse-gas emitting energy source, expensive operational costs due to the high-level of safety requirements decreases their competitiveness in the sustainable energy market. Advanced reactor concepts paired with Digital Twins aim to increase the commercialization gains of nuclear energy by reducing operational costs, increasing reactor reliability and enhancing power generation. To support Digital Twin tasks such as real-time autonomous control, proactive maintenance monitoring or optimizing power demand operations, a fast and accurate virtual representation of the Nuclear Power Plant (NPP) is required. The computational cost of high-fidelity, physics-based models are unsuitable for real-time analysis or scalability. Here, in this work, a hybrid surrogate modeling framework is developed fora Fluoride-salt-cooled High-temperature Reactor (FHR) that leverages physics-inspired models for key reactor components and uses data-driven methods for rapid system state space prediction. The Xenon reactivity feedback model is integrated to inform the surrogate model about the reactor core and the homologous pump theory model is the basis for representing pump degradation. Using a detailed, two dimensional thermal hydraulics model to generate data on the FHR, we train a network of Vectorized Autoregressive Moving-Average with eXogenous input (VARMAX) models to predict the remaining state values. The result is a surrogate model that provides a detailed reactor state representation of 41 system states and a pump degradation analysis. The framework is applied to Load Follows profiles, yielding high accuracy and a speedup that is more than 4000x faster compared to the higher- fidelity thermal hydraulics model, enabling real-time operational intelligence and applications in long horizon predictions. While the surrogate model framework is demonstrated for the particular case of FHR, the hybrid physical/data-driven modeling approach including the network of surrogates and the underlying modularity has the potential to be applied to other physical asset systems.

Digital Twins↗

Tangible Solutions for Grid Operation Upgrade

Many countries worldwide are setting clean energy targets to decarbonize the energy sector and add higher wind and solar capacities. Given their distributed nature, variable renewable energy (VRE) assets can have unique grid integration considerations, and require grid operation practices to be modernized. When transitioning to higher renewable energy levels, many system operators configure a dedicated renewable energy desk to manage renewable energy resource operation in the system control center. Further, system operation planning is conducted with VRE and load forecasting to enable reliable real-time system operation. NREL has partnered with many system operators in the region to identify appropriate technology and grid modernization solutions. NREL and partners from system operators in the region will present on the challenges and some solutions that have been applied and share best practices such as energy management system upgrades, VRE forecasting framework, grid flexibility improvements, and staff training.

emerging economies↗

LAROMance Grade 91 Model Integration in NEML2

New reactor designs are targeting higher operating temperatures for increased thermal efficiency when compared to the current fleet of light water reactors. Designing structural components for these high temperature environments with reliable long-term operations requires material models that can accurately capture the deformation mechanisms active in these environments. The LAROMance surrogate material models are based on a database of mechanistic crystal plasticity simulations for high-temperature conditions. Inputs to the LAROMance models reflect the microstructural pedigree of the material, like dislocation densities and precipitate contents. Based on the evolution of these microstructural features, the LAROMance model provides the engineering scale constitutive model response. The LAROMance model was recently parameterized for Grade 91, a high temperature alloy. In the present work, the Grade 91 LAROMance model is implemented in the New Material Model Library, version 2 (NEML2). NEML2 provides a modular way to build material models from smaller blocks and was developed to vectorize the material update to efficiently run on modern computational architectures with graphics processing unit accelerators. NEML2 constitutive models can be used in simulations based on the multiphysics object-oriented simulation environment (MOOSE). This report provides details on the implementation of the Grade 91 LAROMance model in NEML2 and its verification of engineering scale finite element simulations in MOOSE.

42 - ENGINEERING↗

Recent developments and operation of polarized photocathodes at Jefferson Lab

Spin-polarized electron sources are critical to a wide range of accelerator-based applications for nuclear and particle physics. At Thomas Jefferson National Accelerator Facility, they play a central role in delivering high-quality polarized beams for precision nuclear physics experiments and next-generation parity-violation measurements, where stringent control of systematic uncertainties is essential. These sources are also expected to be key components of other initiatives, including the Electron-Ion Collider and the potential future positron capabilities at Jefferson Lab. In this talk, I will present ongoing research and development efforts at Jefferson Lab focused on the design, fabrication and optimization of spin-polarized photocathodes. This includes growth using molecular beam epitaxy (MBE) or metal-organic chemical vapor deposition (MOCVD), along with detailed characterization of their performance metrics, such as quantum efficiency (QE), electron spin polarization and QE anisotropy, all of which are increasingly important metrics for polarized electron sources at Jefferson Lab and the Electron-Ion Collider. Strategies to mitigate QE anisotropy, which is critical for reducing helicity-correlated beam asymmetries in precision experiments such as MOLLER will be highlighted. Finally, I will present recent efforts aimed at improving the operational lifetime of spin-polarized photocathodes in injector environments, particularly under high-voltage conditions in DC electron guns. These developments are essential for enabling reliable, high-performance operation of polarized sources for current and future accelerator programs.

Kachwala, Alimohammed [Thomas Jefferson National A↗

Techno-Economic Assessment of Data Center Load Demand Powered by Small Modular Reactors and Distributed Energy Resources

The rapid increase in data center energy demand, driven by AI and large-scale data processing, poses significant challenges to global energy infrastructure. Data centers require substantial and reliable energy for continuous operations and high-performance computing. Current electrical grids face issues such as transmission bottlenecks and aging infrastructure, making it difficult to meet these demands. Integrating inverter-based-resources (IBRs) like solar and wind presents both opportunities and challenges due to their intermittent nature. Small Modular Reactors (SMRs) offer a promising solution with their enhanced safety, modularity, reliability, and scalability, providing consistent base load power ideal for data center operations. This study presents a comprehensive techno-economic assessment of powering data center load demand using a combination of SMRs and IBRs with grid-connected and islanded mode. This study utilized Idaho National Laboratory’s (INL) HPC data center hourly load profiles and Xendee microgrid optimization platform to conduct the analysis. In this configuration, SMRs serves as the primary base load power source, consistently providing a steady supply of electricity necessary to meet the minimum load demand of the data center with support from the IBRs. Key performance indicators such as Levelized Cost of Electricity (LCOE), Net Present Value (NPV) has been calculated to assess the economic feasibility. The findings from this research will underscore the strategic benefits of integrating SMR plant with DERs – particularly for critical infrastructure load such as data centers.

14 - SOLAR ENERGY↗

Over 8 hours of continuous operation of a free-electron laser driven by a laser-plasma accelerator

Since the emergence of laser-plasma accelerators (LPAs), substantial work has been dedicated to using LPAs to drive free-electron lasers (FELs) for a broad range of applications. Despite recent breakthroughs, which have proven the fundamental feasibility of operating FELs with an LPA source, stable FEL operation over multiple hours without operator input had yet to be achieved. In this work, we report significant improvements to the stability of a hundred terawatt laser system, resulting in successful demonstration of reliable, long-term operation of an LPA-driven FEL in the self-amplified spontaneous emission (SASE) regime at 420 nm. The LPA source delivered 100 MeV electron beams at 1 Hz with high stability over more than 10 h, enabling over 8 h of continuous FEL operation without operator input. The acquired data were subsequently used to investigate correlations between the measured undulator radiation and parameters of the drive laser, plasma source, and electron beam. The revealed connections between LPA and FEL performance gave important additional insights into ways to further improve and stabilize the system, thus demonstrating the capability of our setup to serve as a powerful platform for future studies of LPA-driven FEL operation. The one-of-a-kind integration of multiple stabilization concepts onto the LPA facility discussed in this manuscript yielded significant accelerator and light source improvements (with residual correlations suggesting even more is possible), which will positively impact LPA applications at large.

Kohrell, Finn [Lawrence Berkeley National Laborato↗

Energy Storage Improves Power Plant Flexibility and Economic Performance

Most existing coal-fired power plants were designed for sustained operation at full load to maximize efficiency, reliability, and revenue, as well as to operate air pollution control devices at design conditions. Depending on plant type and design, these plants can adjust output within a fixed range in response to plant operating or market conditions. The need for flexibility driven by increased penetration of variable and non-dispatchable power generation, such as wind and solar, is shifting the traditional mission profile of thermoelectric power plants in three ways: more frequent shutdowns when market or grid conditions warrant, more aggressive load ramp rates (rate of output change), and a lower minimum sustainable load, which provides a wider operating range and helps avoid costly plant shutdowns. Recent studies have shown that the flexibility of a coal-fired power plant can be improved by energy storage. The objective of this work was to analyze a set of energy storage options and determine their impact on the flexibility and economics of a representative coal-fired power plant. The effect of three energy storage systems integrated with a coal power plant on plant flexibility and economics was investigated. The results obtained in this project show that energy storage systems integrated with a thermal power plant improve plant flexibility and participation in the energy and ancillary services markets, which improves plant financial performance.

20 FOSSIL-FUELED POWER PLANTS↗

Grid Forming Inverter With Increased Short-Circuit Contribution to Address Inverter-Based Microgrid Protection Challenges

Substantial differences in fault levels between grid-tied and islanded modes is one of the primary challenges of microgrid protection. During grid-tied mode, the bulk grid provides significant short-circuit, while during islanded operation the short-circuit magnitude is small due to inverter-based resources limiting their current output close to nominal ratings. Consequently, conventional distribution protection strategies based on overcurrent cannot reliably protect microgrids when operating in islanded mode. Fuses and circuit breakers are particularly affected because of their inverse characteristics. Presently, the absence of affordable solutions for protecting microgrids in islanded mode leads to microgrids shutting down during electrical faults. The contribution of this article is two-fold. The first innovation proposes specific hardware modifications to grid-forming inverters to increase their short-circuit current during electrical faults. The second innovation introduces a novel control strategy designed to preserve control stability margins even when the grid-filter saturates, ensuring sinusoidal output currents under normal and fault conditions. Through experimental results, the inverter with the proposed modifications can provide more than three-times its nominal current during electrical faults. For the prototype testbed, this was sufficient to enable the use of traditional legacy overcurrent protection, achieving the fuse-to-relay and relay-to-relay minimum coordination time for the line-to-ground, line-to-line to ground, and three-phase electrical faults.

42 ENGINEERING↗

Predictive Modeling and Uncertainty Quantification in Condition Monitoring of Active Components: A Reactor Coolant Pump Use Case

This work develops data-driven models for onset of thermal barrier leakage in reactor coolant pumps. It incorporates uncertainty quantification to enhance the reliability and robustness of pre- dictions. Using synthetic data generated by the Generic Pressurized Water Reactor simulator, realistic degradation scenarios were simulated across lifecycle stages—beginning, middle, and end of life. Key variables, including differential pressure, flow rate, vibration, and temperatures, were analyzed using machine learning framework. The fully connected neural network models demonstrated exceptional performance, achieving R2 scores exceeding 0.99 and root mean square errors as low as around 8.23 × 10-2 gallon per minute (gpm) for the three stages of the lifecy- cle. UQ analysis further validated the model’s robustness, with narrow uncertainty bounds during steady-state operations and appropriately wider bounds during transitional phases, reflecting the physical behavior of the system. This work addresses important gaps in real-time condition moni- toring and regulatory compliance by integrating advanced condition monitoring technologies with UQ into IST programs. The ability to detect thermal barrier leakage early and quantify prediction reliability supports optimizing maintenance strategies while ensuring nuclear power plants’ safe and reliable operation.

99 - GENERAL AND MISCELLANEOUS↗

Microgrid Black Start Challenges: The Role of Grid-Forming Inverters

Grid-forming (GFM) inverters are becoming increasingly important for future power systems, particularly in establishing and restarting microgrids after blackouts. The use of GFM inverters enables microgrids to operate independently of utility power and provide key advantages over synchronous generators in black start scenarios, including rapid startup and stable voltage and frequency support for critical loads. However, inverter-driven black start introduces unique challenges and operational considerations. This article examines key challenges and solutions, emphasizing inverter design, control strategies, and microgrid system requirements. Drawing on analysis, simulation, and experimental results, this article highlights the central role of GFM inverters in ensuring reliable and resilient microgrid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reliable Protection for an Inverter-Based Resources Dominant Grid: Technology Development and Field Demonstration

The project aimed to address the challenges posed by the rapid growth of inverter-based resources (IBR) such as solar, wind, and battery storage, which have fundamentally changed fault behavior, system strength, and protection performance in bulk power systems. Traditional protection schemes, designed for synchronous generator-dominated grids, are inadequate under high IBR penetration. Overall, the project materially advances protection modeling and simulation capabilities needed to maintain reliable grid protection under high IBR penetration. The results build utility confidence in operating power systems safely and reliably across a wide range of generation mixes, supporting grid modernization goals.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Lower Snake River Dams Contribution to Grid Services

Hydroelectric generation and water storage have long been components of the clean energy mix, providing both reliable steady output and operational flexibility. As variable renewable energy sources such as wind and solar increasingly replace traditional generation, the role of all flexible resources—including hydropower—in balancing supply and demand continues to evolve. This study examined the contribution of the Lower Snake River (LSR) Dam plants to Bonneville Power Administration grid services in maintaining power system reliability within the Western Interconnection. By analyzing publicly available data, the study evaluated various reliability services through performance metrics including energy capacity, balancing and ramping, voltage and reactive power support, frequency response, and transmission impact. Results indicated that the LSR plants deliver services as expected based on their size, contributing to the balancing process, ramping capabilities, and operational reserves, particularly during peak load conditions and weather events, while also providing measurable frequency and voltage support to the grid.

13 HYDRO ENERGY↗