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DOE OSTI2026

Reese Housing Power Project (Final Technical Report)

The Reese Housing Power Project is located on Tribal trust land in Colusa, CA and expands existing medium-voltage distribution to seven new households with the addition of medium-voltage cabling, step down transformers, smart meters, and street lighting for the new development. The Tribe utilized their existing Co-Generation power plant and micro grid to supply the new homes with highly reliable power with fewer interruptions and at a reduced rate compared with the local utility. The project gives the Tribe greater independence from traditional power sources and provides jobs for the community. The project reduces electric energy costs, increases Tribe self-reliance, and provides highly reliable electric power to seven tribal members’ homes. Construction of the project also provided jobs for the community.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

5-minute Wind Power Data based on WFIP2 WRF Simulation

The second Wind Forecast Improvement Project (WFIP2) was a public-private partnership funded by the U.S. Department of Energy and NOAA, aimed at enhancing the forecast skill of numerical weather prediction models for turbine-height winds in regions with complex terrain. An 18-month Weather Research and Forecasting (WRF) model simulation was conducted over the Pacific Northwest, with model outputs validated against observational data collected during WFIP2. Simulated wind speeds were used to estimate wind power generation using reV (the Renewable Energy Potential Model developed by NREL) at ten wind project sites. Two sets of results were produced: one using wind speeds extracted from the model grid cell at the project centroid, and another using wind speeds from the actual turbine locations. For each dataset, power output was calculated using both actual turbine-specific power curves and nine generic power curves to convert wind speed into power.

17 WIND ENERGY↗

DOE OSTI2022

Small Hydropower Interconnections: Best Practices

Small hydropower projects have been the predominant source of capacity growth of U.S. hydropower for more than a decade, and they present the most cost-effective and environmentally permissible avenues for hydropower growth (DOE 2016; Johnson et al. 2018). However, interconnection to electricity distribution and transmission grids is a persistent barrier due to cost surprises and schedule overruns. As a culmination to research into the status and requirements of small hydropower interconnection across the United States, this paper presents the best practices for setting interconnection standards that can improve the process for small hydropower developers. As part of the analysis, the interconnection costs are compared between small hydropower, solar, and wind. The analysis of the small hydropower interconnection landscape across the United States was carried out by Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) with support from the U.S. Department of Energy Water Power Technologies Office. The research team was guided by a Technical Advisory Group (TAG) and gleaned data from publicly available sources, such as the HydroSource database (ORNL 2020) and interconnection queues hosted by utilities, balancing authorities, independent system operators (ISOs), and regional transmission organizations (RTOs). The results of this work are shared in a series of papers detailing the state of small hydropower in the United States (“Small Hydropower Interconnections: Small Hydropower in the United States”), the variety of state interconnection processes to connect power generators with the grid (“Small Hydropower Interconnections: State Interconnection Processes”), and an analysis of the interconnection processes (“Small Hydropower Interconnections: Analysis of Interconnection Processes”). In this, the final paper in the series, best practices for interconnection processes (“Small Hydropower Interconnections: Best Practices”) are identified from the solar energy and distributed wind energy industries that are transferrable to small hydropower development. This information will help overcome barriers to future small hydropower development.

13 HYDRO ENERGY↗

DOE OSTI2023

Carbon Capture Design and Costing: Phase 2 (C3DC2) (Final Project Report)

ION Clean Energy’s (ION) advanced solvent is one of the leading solvent systems currently under development for post-combustion carbon dioxide (CO 2 ) capture. ION has partnered with Nebraska Power Public District (NPPD), Sargent & Lundy, Koch Modular Process Systems, and Siemens to design a commercial-scale (700 MW) capture system utilizing ION’s advanced solvent, ICE-21, retrofitted onto NPPD’s Gerald Gentleman Station in Sutherland, Nebraska, USA. The capture system was designed to take full advantage of the solvent benefits including an efficient physical plant layout, reduced energy requirements, less solvent degradation, lower emissions, and lower capital costs relative to systems built with DOE BBS case benchmark solvents. This Front-End Engineering Design (FEED) study also included an investigation of utilizing biomass co-combustion with the aim of reaching near-zero emissions for this coal-fired power generating unit. The targeted biomass was from local resources in Nebraska tied to the production of ethanol.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

A model to assess Zircaloy’s mechanical property changes following a transient beyond critical heat flux

Maintaining the integrity of nuclear fuel rods is essential for ensuring public health and safety in nuclear power generation. During reactor operation, this integrity is confirmed by demonstrating compliance with established regulatory acceptance criteria. For moderate-frequency events, such as limiting transients and anticipated operational occurrences (AOOs), the current fuel integrity criterion is based on preventing boiling transition. This criterion assumes that prevention of boiling transition will prevent excessive cladding heating and, thus, fuel failure during normal operations. While conservative, this approach places significant constraints on core design, fuel cycle economics, and a plant’s ability to perform major power uprates, leading to suboptimal fuel utilization and inefficient carbon-free energy production. A more efficient approach could be achieved by revising the failure criterion to a material-specific limit rather than strictly preventing the boiling transition, since boiling transition per se is not a cause of fuel cladding failure. Here, as a result, a new licensing framework based on material properties, termed time-at-temperature (t@T), is needed. This approach would allow for brief periods of post–critical heat flux operation during an AOO without compromising safety. Implementing the t@T licensing strategy requires a robust technical foundation in material properties, which must be established through comprehensive data collection on both unirradiated and irradiated fuel and cladding materials. This foundation would enable the development of a safety basis that ensures safe operation while providing greater flexibility and efficiency for reactor operation. This paper documents a thorough review of the available data to establish a baseline knowledge that can inform the development of cladding mechanical models, as well as identify experimental data gaps that need to be addressed in future research. Machine learning and data informatics were utilized to extract the importance of parameters on the t@T parameter. Industry tools were used to perform baseline analyses to define the relevant transient conditions for data analysis. The subsequent review successfully identified applicable experimental data, as well as sufficient data to evaluate changes in cladding mechanical properties following an AOO transient. Rather than developing new models, this work coupled existing irradiation annealing and recrystallization models to calculate changes in hardness, yield stress, and ultimate tensile stress following an AOO event. The findings from this review were summarized to highlight the experimental data needs required to fill remaining gaps and support the development of future t@T licensing methodologies.

Cladding performance↗

DOE OSTI2023

SDOM (Storage Deployment Optimization Model) [SWR-21-73]

SDOM is designed to accurately represent the operation of energy storage across different timescales, including long-duration and seasonal applications, and the spatiotemporal diversity and complementarity among VRE sources. SDOM uses an hourly temporal resolution, a fine spatial resolution for VRE sources, and a 1-year optimization window. SDOM assumes that all builds of VRE are accompanied by sufficient additional transmission capacity to allow full utilization of these additional resources. Nuclear, hydropower, and other renewable generation (e.g., biomass and geothermal energy sources) are fixed based on operational data (time series) for a given year; thus, SDOM minimizes total system cost using conventional generators as balancing units and using VRE and storage technologies to achieve a user-defined carbon-free or renewable energy target. The total system cost includes capital costs, fixed operation-and-maintenance (FO&M) costs, variable operation-and-maintenance (VO&M) costs, and fuel cost for power generation and storage technologies.

Guerra Fernandez, Omar Jose↗

DOE OSTI2020

High Temperature Gas Sensor for Coal Combustion System

Robust gas sensors that offer real-time feedback about combustion in coal-fired power plants promise greater energy efficiency with fewer harmful emissions while also improving the bottom line for power generators. Currently, no technology meets this objective. Therefore, the objectives of this project are to develop an accurate, robust, reliable, high temperature sensor offering near real-time feedback to plant operators using a novel catalytic/non-catalytic sensor design to detect target gases available for oxidization. Such a sensor would inform power plant operators how to adjust the amount of fuel and air for an optimal performance.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Stochastic Model Predictive Control With Gaussian Wind Direction Preview for Wake Steering

This article addresses the problem of wake steering control for wind farms that explicitly consider the tradeoff between farm-level power generation and yaw duty cycle under variable and uncertain wind conditions. A novel stochastic model predictive control (MPC) algorithm is presented, which utilizes a stochastic model of the freestream wind field components in a receding horizon framework to compute optimal yaw set points that maximize the expected value of the farm power while constraining the yaw actuation. Different configurations of the algorithm are evaluated using a steady-state wind farm simulator. The proposed stochastic MPC algorithm can plan control actions over a future prediction horizon based on probabilistic estimates of the incoming wind magnitude and direction.

17 WIND ENERGY↗

DOE OSTI2023

Synergistic Heat Pumped Thermal Storage and Flexibly Carbon Capture System

As the U.S. grid evolves toward a lower-carbon system, fossil generation assets need to operate in energy markets with high variable renewable energy (VRE) penetration while also decreasing carbon emissions. Current carbon capture and storage (CCS) technologies suffer from high capital cost and an inability to operate flexibly during periods of oscillating demand. The ARPA-E FLECCS Program Phase 1 was created to fund designing and optimizing innovative CCS processes that enable flexibility on a high-VRE grid. To address this need, the Colorado State University (CSU) Team won funding to design a synergized system of thermal energy storage, power generation, and flexible carbon capture to enable breakthrough system performance that achieves an LCOE <$75/MWh with >99% capture rate. This approach will target new or existing natural gas combined cycle power plants. The proposed design utilizes novel hot and cold thermal energy storage (TES) technologies that store low-cost, off-peak electricity as thermal energy to power CCS solvent regeneration and boost plant output during periods of peak demand. The design provides an overall optimized net present value (NPV) by maximizing low carbon power to grid while prices are highest using Storworks Power’s concrete TES technology. The team also capitalizes on decades of ION Clean Energy’s (ION) development in low cost and flexible pioneering solvent technology, which has proven reductions in energy consumption and overall cost of 28% and 38%, respectively, compared with state-of-the-art CCS.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

Barriers to adopting artificial intelligence and machine learning technologies in nuclear power

Artificial intelligence and machine learning (AI/ML) technologies offer unique opportunities to transform nuclear plant operations and power generation. Benefits will be felt not only within existing analog and digital instrumentation and control, but also within work processes, the integration of people with technology and most importantly, the business case. The application of this new technology can help simplify complex problems and produce more effective decision-making, making nuclear power safer, more efficient, and more economically viable in the current energy market. Nonetheless, there are potential barriers to its adoption that must be overcome. The purpose of this paper is to categorize, review, and discuss barriers to AI/ML adoption within the nuclear power industry, with a focus on existing commercial reactors. Unique considerations for advanced reactors are also offered. Here we provide a comprehensive overview of the historical, technical, and business barriers that the industry faces, as well as stakeholder readiness, and end-user acceptance. We underscore the importance of user experience and offer potential solutions in overcoming each barrier. These include provisions for easier plant data access, a friendly regulatory environment, and investment in user trust and explainable AI.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Mixed stochastic-deterministic time-dependent density functional theory: application to stopping power of warm dense carbon

Warm dense matter (WDM) describes an intermediate phase, between condensed matter and classical plasmas, found in natural and man-made systems. In a laboratory setting, WDM is often created dynamically. It is typically laser or pulse-power generated and can be difficult to characterize experimentally. Measuring the energy loss of high energy ions, caused by a WDM target, is both a promising diagnostic and of fundamental importance to inertial confinement fusion research. However, electron coupling, degeneracy, and quantum effects limit the accuracy of easily calculable kinetic models for stopping power, while high temperatures make the traditional tools of condensed matter, e.g. time-dependent density functional theory (TD-DFT), often intractable. In this study, we have developed a mixed stochastic-deterministic approach to TD-DFT which provides more efficient computation while maintaining the required precision for model discrimination. Recently, this approach showed significant improvement compared to models when compared to experimental energy loss measurements in WDM carbon. Here, we describe this approach and demonstrate its application to warm dense carbon stopping across a range of projectile velocities. We compare direct stopping-power calculation to approaches based on combining homogeneous electron gas response with bound electrons, with parameters extracted from our TD-DFT calculations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Machine Learning–Adjusted WRF Forecasts to Support Wind Energy Needs in Black Start Operations

Abstract The push for increased capacity of renewable sources of electricity has led to the growth of wind-power generation, with a need for accurate forecasts of winds at hub height. Forecasts for these levels were uncommon until recently, and that, combined with the nocturnal collapse of the well-mixed boundary layer and daytime growth of the boundary layer through the levels important for energy generation, has contributed to errors in numerical modeling of wind generation resources. The present study explores several machine learning algorithms to both forecast and correct standard WRF Model forecasts of winds and temperature at hub height within wind turbine plants over several different time periods that are critical for the anticipation of potential blackouts and aiding in black start operations on the power grid. It was found that mean square error for day-2 wind forecasts from the WRF Model can be improved by over 90% with the use of a multioutput neural network, and that 60-min forecasts of WRF error, which can then be used to adjust forecasts, can be made with an LSTM with great accuracy. Nowcasting of temperature and wind speed over a 10-min period using an LSTM produced very low error and especially skillful forecasts of maximum and minimum values over the turbine plant area.

17 WIND ENERGY↗

DOE OSTI2024

U.S. Virgin Islands: 2023 Energy Baseline Report

This report summarizes the currently available data on U.S. Virgin Islands' energy sector as of December, 2023. It describes primary energy consumption, end uses, energy production, relevant policies, and key challenges, including details on the power generation and transportation sectors. The report serves as a baseline of understanding to assess energy needs and priorities on the island.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Comparative Analysis of Natural Gas Cogeneration Incentives on Electricity Production in Latin America

An analysis to assess the influence of country-dependent variables and incentives on the feasibility of natural gas cogeneration projects in Latin America is presented in this work. The analysis is performed using a hypothetical industrial plant, where the cogeneration solution consists in the recovery of waste heat from the power generation for steam production. The feasibility is evaluated by calculating the Return of Investment (ROI) and the Internal Rate of Return (IRR) of the project. Eight Latin American countries are studied considering their specific natural gas markets, regulation, and macroeconomic variables. Two scenarios, electricity production for self-consumption and electricity production with power surplus sale, are independently analyzed considering the effects of available incentives. In the countries where the project is feasible, the application of incentives leads to a significant reduction in the ROI and, consequently, to an increment in the IRR. The effect of the interest rate and environmental impact were also analyzed. In general terms, along the region, the regulation for cogeneration is incipient while incentives are very standard and similar respect to lowering of import, Value-Added Tax (VAT), and income taxes, which seems to be designed purely to promote capital investment. Following the results from this study, it is of paramount importance to create new policy instruments in the future to advance the regulatory framework for cogeneration in Latin America.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Estimation Methodology to Evaluate Hypothetical Downwind Impacts from Fusion Plants

The continuing move toward establishing fusion systems for power generation and the associated research to that end is prompting examination of the potential health and safety impacts of such plants to the environment and human health. As many fusion facilities will have tritium inventories on site as part of the fusion fuel, evaluating the potential for downwind impacts from fusion facilities or power plants resulting from accident or routine emissions is a general requirement for assessing location and impacts to workers and the public. As part of siting considerations and permitting, the fusion facilities would be evaluated for potential for downwind concentration and dose impacts. For accident assessment scenarios, the downwind impacts are usually modeled as an instantaneous (or near-instantaneous) release of material transported following the wind. A range of meteorological conditions are usually assessed to determine a bounding case which results in a dose exceeding a specified threshold (e.g., 95 th or 99 th percentile; DOE 2015). This report provides initial estimates of the downwind dose impacts from a potential tritium release at a fusion power plant-relevant facility and identifies potential distances required to limit impacts to nearby population. This effort is meant to provide a bounding analysis and theoretical understanding of impacts of tritium releases for facilities subject to various environmental and atmospheric conditions. Using a Gaussian dispersion model to simulate a brief plume, downwind concentration and dose is projected for tritium oxide. Releases are assumed to consist entirely of tritium oxide due to the increased dose impacts from the oxide form relative to the elemental form of tritium. We also briefly identify how climatological conditions could potentially be used to support risk profile determination.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The Role of Interface Band Alignment in Epitaxial SrTiO 3 /GaAs Heterojunctions

Recent concerns surrounding climate change and the contribution of fossil fuels to greenhouse gas (GHG) emissions have sparked interest and advancements in renewable energy sources including wind, solar, and hydroelectricity. These energy sources, often referred to as “clean energy”, generate no operational onsite GHG emissions. They also offer the potential for clean hydrogen production through water electrolysis, presenting a viable solution to create an environmentally friendly alternative energy carrier with the potential to decarbonize industrial processes reliant on hydrogen. To conduct a full life cycle analysis, it is crucial to account for the embodied emissions associated with renewable and nuclear power generation plants as they can significantly impact the GHG emissions linked to hydrogen production and its derived products. In this work, we conducted a comprehensive analysis of the embodied emissions associated with solar photovoltaic (PV), wind, hydro, and nuclear electricity. We investigated the implications of including plant-embodied emissions in the overall emission estimates of electrolysis hydrogen production and subsequently on the production of synthetic ammonia, methanol, and Fischer– Tropsch (FT) fuels. Results show that average embodied GHG emissions of solar PV, wind, hydro, and nuclear electricity generation in the United States (U.S.) were estimated to be 37, 9.8, 7.2, and 0.3 g CO 2 e/kWh, respectively. Life cycle GHG emissions of electrolytic hydrogen produced from solar PV, wind, and hydroelectricity were estimated as 2.1, 0.6, and 0.4 kg of CO 2 e/kg of H 2 , respectively, in contrast to the zero-emissions often used when the embodied emissions in their construction were excluded. Average life cycle emission estimates (CO 2 e/kg) of synthetic ammonia, methanol, and FT-fuel from solar PV electricity are increased by 5.5, 16, and 49 times, respectively, compared to the case when embodied emissions are excluded. This change also depends on the local irradiance for solar power, which can result in a further increase of GHG emissions by 35–41% in areas of low irradiance or reduce GHG emissions by 21–25% in areas with higher irradiance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Region-Specific Merchant Hydrogen Market Assessment and Techno-Economic Assessment of Electrolytic Hydrogen Generation: Cooperative Research and Development Final Report, CRADA Number CRD-18-00751

Utilities need to recover value from baseload and some renewable assets even when the electricity is curtailed. The declining cost of renewables (particularly solar), the persistently low-cost of natural gas, and the declining electricity demand, have all worked to lower the price of electricity. Furthermore, the baseload assets have a high turndown cost, which is not reflected in the low market electricity prices. One option for utilizing the curtailed electricity is hydrogen generation. One important aspect of this project will be to provide a “go/no-go” recommendation on the economic feasibility of pursuing hydrogen generation vs. other markets that could offtake curtailed electricity or nuclear steam. This project will specifically assess the opportunities for hydrogen production and use in the service territories of Southern Company Services (SCS), Exelon SBC, and Xcel Energy. Each utility partner represents a different mix of generation fleets: Exelon has significant nuclear assets, Xcel is primarily renewables (wind) with some nuclear, and SCS represents both a renewables fleet and a heavily baseload fleet, which includes significant nuclear. The Contractors will conduct the study of hydrogen market opportunities by first considering the approximate electricity demand and price profiles for the year, and power generation capacity that can be used to produce hydrogen. Therefore, a profile for hydrogen generation will also be developed to better understand the quantity and timing of hydrogen production. Once the hydrogen production schedule is estimated, hydrogen storage requirements can be determined. This effort will provide sufficient information to make a go/no-go decision on moving ahead with a detailed regional case study for hydrogen production in any of the three utility areas.

08 HYDROGEN↗

DOE OSTI2025

Fabrication and Testing of Solid-Solution Strengthened Corrosion Resistant Alloys For Service in Molten Fluoride Environments

The demand for higher system thermal efficiencies requires the operation of power generation cycles and heat conversion systems at progressively higher temperatures. As the system operating temperature increases, existing materials may not provide adequate mechanical properties or environmental compatibility or both. There is an increasing commercial interest in the development and deployment of liquid-fueled Molten Salt Reactors (MSRs). Hastelloy®N, the highest performing candidate MSR structural alloy, is not capable of operations at temperatures above 700°C, thus limiting the performance of these systems. Using an Integrated Computational Materials Engineering (ICME)-approach and small laboratory scale heats, ORNL developed a class of patented alloys covered by U.S. Patent 9, 435, 011 B2, “Creep-resistant, Cobalt-free alloys for high temperature, liquid-salt heat exchanger systems,” similar to Hastelloy®N in that they are primarily solid solution strengthened. In contrast to precipitation strengthened alloys, the microstructure of solid solution alloys and hence the high temperature mechanical properties are stable for extended periods of time allowing long reactor operating life. The new alloys have shown to possess good resistance to liquid fluorides at temperatures up to 850°C and have significantly improved creep properties when compared to Hastelloy®N. The purpose of the CRADA project was for ORNL to collaborate with Haynes International- a materials producer, MetalTek International- a foundry, and Kairos Power – an advanced reactor developer – to scale-up selected alloys, evaluate their properties, and identify one solid solution strengthened alloy that can meet the property requirements for the reactor being developed by Kairos Power and other similar liquid fluoride-salt cooled reactors. As part of the project, eight alloys were down-selected and fabricated in larger industrial scale heats by Haynes International. Resistance to molten salt was evaluated in flowing FLiNaK and FLiBe by Kairos Power using their Rotating Cage Loop (RCL) system. Accounting for iron deposition during these tests, the new alloys displayed very low net mass change showing excellent corrosion performance in molten salt. Creep properties evaluated at ORNL were found to be better than that of Hastelloy®N and 316 stainless steel. Long-term stabilities of the alloys evaluated by Haynes International showed that these alloys have excellent thermal stability in the temperature range 704.4-815.6°C, with the change in strength and ductility being less than 10-15% after a 4000-hour exposure at 815.6°C. Autogenously Gas Tungsten Arc Welding (GTAW) welded samples showed less than 10% change in yield strength / ultimate tensile strength / total elongation compared to the basemetal, indicating that the alloys have excellent weldability. Three parts were successfully investment-cast using one alloy with very little voiding showing feasibility of fabricating parts using the casting process. This project enabled extensive interaction between the material producer Haynes International, casting supplier MetalTek, and reactor developer Kairos Power. This facilitated testing of materials and components produced using the newly developed alloys by the end-user. This allowed the generation of critical dataset required for down-selection of a few promising alloys for further development. This data is also currently being shared with other reactor designers for them to evaluate the suitability of this alloy for their reactor design. The availability of this alloy will ultimately enable the design and development and deployment of MSRs with increased temperature of operation and thus, improved efficiencies.

99 GENERAL AND MISCELLANEOUS↗