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DOE OSTI2013

Green Power Initiative

National energy policy supports the gathering of more detailed and authoritative data on the introduction of renewable bio-based fuels into new and existing district energy systems via the application of biomass gasification. The University of Iowa developed a biomass-fueled, university-scale steam generation system based on biomass gasification technologies. The system serves as a state-of-the-art research and educational facility in the emerging application of gasification in steam generation. The facility, which includes a smaller down-draft gasifier and a larger multi-stage biomass boiler, was designed to operate primarily on wood-based fuels, but has provisions for testing other biomass fuel sources produced within a 100-mile radius, providing enough flexibility to meet the fluctuating local supply of biomass from industry and Midwest agriculture. The equipment was installed in an existing, staffed facility. The down-draft gasifier unit is operated by College of Engineering staff and students, under the direct technical supervision of qualified Utilities plant staff. The Green Power Initiative also includes a substantial, innovative educational component. In addition to an onsite, graduate-level research program in biomass fuels, the investigators have integrated undergraduate and graduate level teaching – through classroom studies and experiential learning – and applied research into a biomass-based, university-scale, functioning power plant. University of Iowa is unique in that it currently has multiple renewable energy technologies deployed, including significant biomass combustion (oat hulls) at its Main Power Plant and a new reciprocating engine based renewable district energy system. This project complements and supports the national energy policy and State of Iowa initiatives in ethanol and biodiesel. Byproducts of ethanol and biodiesel processes (distiller grains) as well as industry residues (oat hulls, wood chips, construction and demolition waste), farm related material (seed corn and soybean seed), and poplar trees for cleaning up ground water are logical feed stocks for gasification.

09 BIOMASS FUELS↗

DOE OSTI2017

Optical Mode Converters Final Report CRADA No. TC-0838-94

The information age was maturing, and photonics was emerging as a significant technology with important'national security and commercial implications at the time of the CRADA. This was largely due to the vast information carrying capacity of optical beams and the availability of cheap.and effective optical fiber waveguides to guide the light. However, a major limitation to the widespread deployment of photonic systems was the high-cost (in an economic and performance sense) associated with coupling optical power between optoelectronic waveguide devices or between a device and an optical fiber. The problem was critical in the case of single-mode waveguide devices. Mitigating these costs would be a significant and pervasive enabler of the technology for a wide variety of applications that would have crucial defense and economic impact. The partners worked together to develop optical mode size converters on silicon substrates. Silicon was chosen because of its compatibility with the required photolithographic and micromachining techniques. By choosing silicon, these techniques could enable the close coupling of high-speed, high density silicon electronic circuitry to efficient low-cost photonics. The efficient coupling of electronics and photonics technologies would be important for many information age technologies. The joint nature of this project was intended to allow HP to benefit from some unique LLNL capabilities, and LLNL would be in a position to learn from HP and enhance its value to fundamental DP missions. Although the CRADA began as a hardware development project to develop the mode converter, it evolved into a software development venture. LLNL and HP researchers examined literature, performed some preliminary calculations, and evaluated production trade-offs of several known techniques to determine the best candidates for an integrated system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗

DOE OSTI2025

Graph Neural Networks for Surrogate Modeling of Offshore Floating Platforms

Floating offshore wind turbines (FOWTs) present an significant opportunity to increase renewable energy generation. However, significant challenges remain before FOWTs can be widely commercialized and deployed. In particular, hydrodynamic loading on the platforms can stress the overall structure, damage the mooring systems, and impact power generation. Studying these loads is difficult and often relies on computationally expensive models or experiments. In this work, we explore the use of graph neural networks (GNNs) to construct flexible, data-driven surrogates for hydrodynamic loads on platforms. We leverage the natural graph-like structure of offshore wind platform designs to enable the GNN model to learn to approximate the loads for different wave conditions and structural designs. We demonstrate potential uses for the surrogate by performing parameter sweeps and ridge analysis on the trained model to identify the impacts of different wave and structural features on the loads.

floating offshore wind turbines↗

DOE OSTI2024

Power Generation Enhancement through Latching Control for a Sliding Magnet-Based Wave Energy Converter

A Surface-Riding Wave Energy Converter (SR-WEC) featuring a sliding magnet inside a pitching cylindrical hull is investigated as an easily deployable small power device to support small-scale marine operations. This study extends the earlier development of the system by authors to enhance power performance through the application of end spring and latching control. The inclusion of springs at the tube’s end enhances the magnet release and travel speeds as well as the average power output compared to systems without them. Further improvement of power output can also be achieved by employing optimal latching control. We introduced constant-angle and variable-angle unlatching strategies to determine optimal parameters in combination with passive and reactive power take-off (PTO) controls to assess their effectiveness. The optimized latching control and end spring can increase 60–80% more power output compared with the case without them under certain PTO damping. Additionally, we discussed the effects of limiting peak powers and associated energy leaks with latching.

Lee, Yongseok↗

DOE OSTI2016

Energy Storage Requirements for Achieving 50% Penetration of Solar Photovoltaic Energy in California

We estimate the storage required to enable PV penetration up to 50% in California (with renewable penetration over 66%), and we quantify the complex relationships among storage, PV penetration, grid flexibility, and PV costs due to increased curtailment. We find that the storage needed depends strongly on the amount of other flexibility resources deployed. With very low-cost PV (three cents per kilowatt-hour) and a highly flexible electric power system, about 19 gigawatts of energy storage could enable 50% PV penetration with a marginal net PV levelized cost of energy (LCOE) comparable to the variable costs of future combined-cycle gas generators under carbon constraints. This system requires extensive use of flexible generation, transmission, demand response, and electrifying one quarter of the vehicle fleet in California with largely optimized charging. A less flexible system, or more expensive PV would require significantly greater amounts of storage. The amount of storage needed to support very large amounts of PV might fit within a least-cost framework driven by declining storage costs and reduced storage-duration needs due to high PV penetration.

14 SOLAR ENERGY↗

DOE OSTI2016

Sellafield FGMSP Additional Sludge Retrievals A Significant Step in Decommissioning Part of the U.K.'s Nuclear Legacy - 16180

The First Generation Magnox Storage Pond (FGMSP) is an open-air pond on the Sellafield site (U.K.) constructed to receive and store spent nuclear fuel from the UK's fleet of Magnox reactors. Operations ceased in 1986, leaving a significant mobile (sludge from the corrosion of fuel cladding) and solids (fuel, fuel fragments and other debris) inventory. In December 2013, Westinghouse Electric Company and EnergySolutions proposed to create an Additional Sludge Retrieval (ASR) capability, with the aim of starting sustainable sludge transfer and hazard reduction as soon as possible. The ASR project team proposed a sludge retrievals concept based on the use of a self-propelled, remote controlled Floating Platform. The deployment system was derived from a Floating Platform concept developed by Westinghouse to support field operations in European nuclear power plants. The system was designed, manufactured and successfully tested in real scale conditions, and was installed and fully commissioned in March 2015. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Artificial Intelligence and Digital Engineering as Enablers for System Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world’s energy demands and build energy security.

42 - ENGINEERING↗

DOE OSTI2025

Artificial Intelligence and Digital Engineering as Enablers for Systems Engineering in the Energy Sector

42 - ENGINEERING↗

DOE OSTI2018

Heat Storage Options for Sodium, Salt and Helium Cooled Reactors to Enable Variable Electricity to the Grid and Heat to Industry with Base-Load Reactor Operations

Electricity markets are changing rapidly because of (1) the addition of wind and solar and (2) the goal of a low-carbon electricity grid. These changes result in times of high electricity prices and very low or negative electricity prices. California has seen its first month where more than 20% of the time (mid-day) the wholesale price of electricity was zero or negative. This creates large incentives for coupling heat storage to advanced reactors to enable variable electricity and industrial-heat output (to maximize revenue) while the reactor operates at base load (minimize cost). Recent studies have examined coupling various types of heat storage to Rankine and Brayton power cycles. However, there has been little examination of heat-storage options between (1) the reactor and (2) the power-conversion system or industrial customer. Heat-storage systems can be incorporated into sodium , helium-, and salt-cooled reactors. Salt-cooled reactors include the fluoride-salt-cooled high-temperature reactor (FHR) with its solid fuel and clean coolant and the molten salt reactor (MSR) with its fuel dissolved in the salt. For sodium and salt reactors, it is assumed that a heat-storage system would be in the secondary loop between the reactor and power cycle. For helium-cooled reactors, heat storage can be in the primary or secondary loop. This report is a first look at the rational and the heat storage options for deploying gigawatt-watt hour heat-storage systems with GenIV reactors. Economics and safety are the primary selection criteria. The leading heat-storage candidate for sodium-cooled systems (a low-pressure secondary system with small temperature drop across the reactor core) is sodium coolant stored in large steel tanks, with the coolant transferring heat in channels. The design minimizes sodium volume in the storage and, thus, the risks and costs associated with sodium. For helium systems (high-pressure with large temperature drop across the core), the leading heat storage options are (1) varying the temperature of the reactor core, (2) steel or alumina firebrick in a secondary pressure vessel and (3) nitrate or hot-rock/firebrick at atmospheric pressure. For salt systems (low pressure, high temperatures, and small temperature drop across the reactor core) the leading heat-storage systems are secondary salts. In each case, options are identified and questions to be addressed are identified. In some cases there is a strong coupling between the heat-storage technology and the power cycle. The leading sodium heat-storage technology may imply changes in the power cycle. High-temperature salt systems couple efficiency to Brayton power cycles that may create large incentives for the heat storage to remain within the power cycle rather than in any intermediate heat transfer loop.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Design, Development and Testing Plan for Energy Efficiency Algorithms Related to Building-Integrated Cooling, Heating, and Power Systems

Building-integrated cooling, heating and power (CHP) systems are more efficient than conventional systems at providing local power and thermal energy, and favorable fuel prices are bound to spur their increased adoption. It is estimated that the total CHP technical potential in the commercial building sector is approximately 76 GW, but only a small fraction of it is actually deployed. Advanced control and monitoring systems that realize the full potential of these CHP systems can transform this capacity into an asset for both the owner and the grid and also accelerate the adoption of these systems in the building sector. However, to realize the full benefit of the CHP systems, we must ensure persistence of energy efficient operations. It has been demonstrated by several studies that as much as 30% of building energy use is wasted. Much of the waste results from the inability to anticipate load variations (design day vs. non-design day operations; diurnal variation of loads), identify improper operation, and efficiently operate, control and maintain building systems. Moreover, many buildings, even those with adequate control infrastructure, lack knowledgeable staff to operate and maintain energy systems. Operators of buildings with CHP systems will constantly need to make tradeoffs (economic dispatch) between onsite power generation and purchasing power, between onsite heat production from distributed generation versus heating/cooling from conventional systems, and different passive and active load management measures. Much of the inefficiency in the current building operations can be eliminated by use of automated performance monitoring (PM), real-time commissioning verification (CxV) and automated fault detection and diagnostic (AFDD) tools. Automation can help system operators make intelligent decisions. Remote and continuous monitoring of system conditions and performance will enable better management and integration of CHP with existing building systems. Continuous PM, real-time CxV and AFDD could alleviate burdens for operations staff, enhance operations and maintenance (O&M), and improve reliability of building and CHP systems. To address the O&M challenges and to provide a means to maximize the rate-of-return of building-integrated CHP systems, the Building Technologies Office (BTO) within the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) initiated a project to design, develop, and field test a VOLTTRON™-based supervisory controller and associated open-source algorithms. These algorithms will ensure real-time optimal operation of a building-integrated CHP system, support electric grid reliability, and lead to achieving the goal of a clean, efficient, reliable and affordable next-generation integrated energy systems. This report lists the components for which PM, real-time CxV and AFDD algorithms will be developed, how the algorithms will be tested, and metrics that will be used to validate the algorithms and easy of deployment. Deployment of these algorithms in the field will result in savings reduction in energy consumption of between 10% and 20%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Industry Perspectives on Advanced Inverters for U.S. Solar Photovoltaic Systems. Grid Benefits, Deployment Challenges, and Emerging Solutions

To clarify current utility strategies and other considerations related to advanced inverter deployment, we interviewed 20 representatives from 11 leading organizations closely involved with advanced inverter pilot testing, protocols, and implementation. Included were representatives from seven utilities, a regional transmission operator, an inverter manufacturer, a leading solar developer, and a consortium for grid codes and standards. Interview data represent geographically the advanced inverter activities identified in SEPA's prior survey results--most interviewed utilities serve California, Arizona, and Hawaii, though we also interviewed others from the Northeast, Mid-Atlantic, and Southeast.

14 SOLAR ENERGY↗

DOE OSTI2026

Dataset of Generative AI Workload Power Profiles

This dataset provides a collection of high-resolution (5/10 Hz or every 0.2/0.1 seconds) power consumption profiles for generative artificial intelligence (GenAI) workloads executed on NLR's High Performance Computing (HPC) platform Kestrel. The dataset also includes examples of representative whole-facility power profiles generated using a bottom-up, event-driven, data center energy model . This dataset is designed to support research in energy modeling, infrastructure planning, energy system integration, and sustainability analysis for AI-driven computing systems. The dataset captures time-resolved electrical power measurements across a diverse set of configurations, including variations in job type (inference vs. training), workload (LLM vs. image generation), datasets, and number of compute nodes. Power traces are provided in a standardized format and include both raw/instantaneous and aggregated files. Each profile is accompanied by metadata describing workload parameters, enabling reproducibility and cross-study comparison. The dataset is intended for use in applications such as data center infrastructure planning, energy modeling, demand response and grid impact studies, and development and validation of system-level simulation tools. By making these workload-specific power profiles publicly available, this dataset aims to address the current lack of open, empirical energy data for generative AI systems and to facilitate transparent, reproducible research on the energy and environmental impacts of large-scale AI deployment. If you use this dataset, please cite the associated publication: Vercellino et al., “Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning,” arXiv:2604.07345 (2026).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

EVI-Pro for Bogota Columbia [Slides]

The transportation sector is one of the largest producers of greenhouse gas emissions globally, with 37% of global CO 2 emissions in 2021 according to the International Energy Agency. Transitioning from internal combustion engine vehicles powered by fossil fuels to electrified transportation is a critical component in reducing those emissions significantly over the coming decades and avoiding the worst consequences of climate change. With governments and automakers increasingly announcing electrification targets and a progression away from the production and sale of internal combustion engine vehicles, a robust network of charging infrastructure must be built to enable the widespread use of electric vehicles (EVs). Some of the greatest hurdles to EV deployment are linked to the buildout of the required charging infrastructure including where it should be built, what types and how much charging would be optimal given high costs of installation, and the impact on the electrical grid. To this end, the National Renewable Energy Laboratory (NREL) conducts extensive research on EV deployment, including the development of the EVI-Pro model used to plan the future buildout of charging infrastructure given the travel patterns in a region. This document summarizes work done by NREL in the Bogotá, Colombia region to help Colombia plan for its EV deployment goals.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Simulation Methods for Transactive Energy

Transactive energy is a new approach for managing the electric power distribution system based on principles of economic value, with engineering constraints. This combined approach is well established in the bulk power system, but transactive energy incorporates many more participants and new types of participant, including end-use loads and distributed energy resources. The market mechanisms are new and largely untested, which calls for careful design to avoid unwanted results and behaviors. The supporting simulation platforms must be flexible and multi-disciplinary (market, distribution grid, bulk grid, buildings, appliances, distributed energy resources, communication systems). These platforms make it possible for products to be developed and tested on large realistic models, before deployment into the real world.

load modeling↗

DOE OSTI2017

Software Comparison for Renewable Energy Deployment in a Distribution Network

The main objective of this report is to evaluate different software options for performing robust distributed generation (DG) power system modeling. The features and capabilities of four simulation tools, OpenDSS, GridLAB-D, CYMDIST, and PowerWorld Simulator, are compared to analyze their effectiveness in analyzing distribution networks with DG. OpenDSS and GridLAB-D, two open source software, have the capability to simulate networks with fluctuating data values. These packages allow the running of a simulation each time instant by iterating only the main script file. CYMDIST, a commercial software, allows for time-series simulation to study variations on network controls. PowerWorld Simulator, another commercial tool, has a batch mode simulation function through the 'Time Step Simulation' tool, which obtains solutions for a list of specified time points. PowerWorld Simulator is intended for analysis of transmission-level systems, while the other three are designed for distribution systems. CYMDIST and PowerWorld Simulator feature easy-to-use graphical user interfaces (GUIs). OpenDSS and GridLAB-D, on the other hand, are based on command-line programs, which increase the time necessary to become familiar with the software packages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Transient Simulations with a Large Penetration of Converter-Interfaced Generation: Scientific Computing Challenges and Opportunities

Current trends in energy systems point to renewable energy sources (RESs) and battery energy storage systems (BESSs) becoming prevalent in power system operations. As of writing this article, the United States has more than 37 GW of utility-scale solar capacity and an additional 112 GW under development. With the rapidly declining capital costs of many of these technologies, we can expect significant deployments in the coming years.

analytical models↗

DOE OSTI2025

Assessing the Economic Value of Underground Thermal Storage for Hybrid Geothermal Power

Solutions are needed to address resource adequacy in the electric power system for highly decarbonized systems. The storage duration, the length of time a storage device can provide continuous output at its rated capacity, must be sufficient to receive full credit toward resource adequacy. Longer peaks and high fractions of variable renewable generation have increased the required duration to potentially seasonal durations. Underground Thermal Energy Storage (UTES) can be adapted to a hybrid storage power plant or heating and cooling applications to satisfy the need for long-duration storage. In this study, we use the Renewable Energy Deployment System (ReEDS) capacity expansion model to evaluate the increase in value for an enhanced geothermal system (EGS) resources by adding UTES. In modeled scenarios, using geothermal without storage as a baseline we compare the increase in economic value for plants with a range of storage characteristics. The added value of a hybrid storage plant changes depending on assumptions including the length of storage duration, efficiency, and ability to charge storage from the grid during periods of low energy prices. Relating proposed characteristics for geothermal UTES hybrids to the modeled economic value provides insight into economically viable costs for developing UTES as well as what combination of technology characteristics and future energy and policy assumptions drive significant value increases.

capacity expansion model↗