Engineering topics
Publications and source records attributed to Guaita, Nahuel.
This report provides recommended parameters for incorporating nuclear energy systems into decarbonization modeling scenarios. The values are primarily intended for the Net Zero World (NZW) Initiative but are expected to prove useful to other related efforts. Both costs and operational metrics are provided in the study for large reactors and small modular reactors (SMR).
Nuclear energy is increasingly being considered for such targeted energy applications as data centers in light of their high capacity factors and low carbon emissions. This paper focuses on assessing the tradeoffs between economies of scale versus mass production to identify promising reactor sizes to meet data center demands. A framework is then built using the best cost estimates from the literature to identify ideal reactor power sizes for the needs of the given data center. Results should not be taken to be deterministic but highlight the variability of ideal reactor power output against the required demand. While certain advocates claim that with the gigawatts of clean, firm energy needed, large plants are ideal, others advocate for SMRs that can be deployed in large quantities and reap the benefits from learning effects. The findings of this study showcase that identifying the optimal size for a reactor is likely more nuanced and dependent on the application and its requirements. Overall, the study does show potential economic promise for coupling nuclear reactors to data centers and industrial heat applications under certain key conditions and assumptions.
This study focuses on post-combustion capture and oxy-fuel combustion for the boilers at the mill, as well as steam integration with the nuclear power plant. The primary goal of the research outlined in this report is to design, analyze, and document the integration of industrial-scale HTGR with a reference Kraft Pulp Mill. The purpose is to deliver reliable, cost-effective, and sustainable clean energy alternatives while reducing CO2 emissions. Specifically, this study focuses on 6 different scenarios that include carbon capture equipment and some of them use nuclear power to meet the heat and electricity needs of the reference plant. Also, 2 of these scenarios are created while also producing clean hydrogen through integrated High-Temperature Steam Electrolysis (HTSE). This report offers a detailed techno-economic assessment of different scenarios for a Kraft Pulp Mill, including an analysis of tax credits (section 45V, 45Q, and 48E) provided by the Inflation Reduction Act (IRA) of 2022. The evaluation explores the potential economic benefits and challenges of incorporating different configurations, including nuclear energy, into Kraft Pulp Mill operations, with particular attention to energy efficiency, economic implications, and environmental impact. By assessing both the technical feasibility and economic viability, this analysis aims to identify existing gaps and propose solutions for the successful implementation of nuclear integration. The findings are intended to provide valuable insights for stakeholders considering the adoption of advanced nuclear reactors in the pulp and paper industries.
The United States (U.S.) nuclear-generation fleet stands as a critical national strategic asset, playing a pivotal role in achieving climate goals. Operating on light-water reactor (LWR) technologies, this fleet provides the largest share of U.S. carbon-free electrical generation, ensuring 24/7 clean-energy stability. With a proven track record of reliability while operating at high-capacity factors, consistently above 90%, the existing nuclear fleet serves as a cornerstone for sustainable energy. The Department of Energy’s (DOE’s) Light Water Reactor Sustainability (LWRS), Flexible Plant Operations and Generation pathway addresses U.S. nuclear power plant (NPP) grid integration challenges in the face of evolving energy landscapes. Research at Idaho National Laboratory (INL) highlights the potential synergy between high-temperature steam-electrolysis (HTSE) technology and nuclear steam and electricity during periods of high renewable grid penetration. Large-scale nuclear-integrated hydrogen production through HTSE presents significant potential for decarbonizing such energy-intensive sectors as oil refining, petrochemicals, ammonia, and fertilizers. The strategic advantage lies in the nuclear sector’s capability to deliver clean electrical and/or steam output during periods of low demand. Nuclear-produced hydrogen—with its ability to provide high-purity clean H 2 well below the national standard of 1 kg of CO 2 per kg of H 2 —represents a breakthrough methodology. This emphasizes the crucial role NPPs can fill in addressing the increasing need for clean hydrogen, establishing them as essential contributors to decarbonization. This report specifically delves into hydrogen-generation opportunities from the U.S. Gulf Coast region. This study aims to assess NPP capabilities for hydrogen production and to identify practical nearby industrial and pipeline-operator off-takers for nuclear-integrated hydrogen production as well as to present some specific case-study analysis showing the conditions under which nuclear hydrogen production and sale can be profitable. Also considered in this report is preliminary analysis of nuclear-heat opportunities accessible near Waterford NPP via transportation of hypothetical steam pipelines and heat-exchange equipment.
Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.
Efforts continue to identify the most-economic methods to decarbonize several sectors of the United States (U.S.) economy. Industrial processes such as synfuel synthesis and high value commodity chemicals rely heavily on energy-dense and easily stored and transported fossil fuels, which power and feed their operations. Steam methane reforming (SMR) is a widely used process for producing methanol. In this process, methane (CH 4 ) from natural gas (NG) reacts with steam (H 2 O) over a catalyst at high temperatures (700-1,000°C) to produce syngas, a mixture of hydrogen (H 2 ) and carbon monoxide (CO). The syngas is then converted into methanol (CH 3 OH) through a second catalytic reaction. This method is known for being an efficient and commonly employed pathway for industrial methanol production. The high-temperature heat needed for SMR, which is currently used in the natural-gas-to-methanol process, cannot be supplied by small modular nuclear reactor (SMNR) direct heating; the temperatures required for the SMR process exceed those of the main steam produced by near-market high-temperature gas reactors (HTGRs). For the conventional methanol process, this leaves possible nuclear-integration opportunities that include: (1) blending nuclear hydrogen into the SMR NG fuel, or (2) assessing alternative synthesis routes leveraging nuclear capabilities and steam electrolysis outputs. In the reference methanol plant, SMR provides the methanol-synthesis reactor with H 2 and co. In Case (2), the state-of-the-art reverse water gas shift (RWGS) pathway achieves the same, sourcing carbon from an industrial CO 2 source.
Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation and storage technologies: land-based wind, offshore wind, distributed wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, commercial battery storage, residential battery storage, pumped storage hydropower, nuclear, coal, and natural gas. EIA data for conventional biopower are included for reference. This webinar presentation introduces the 2024 update to the ATB Electricity data and documentation.
Efforts to identify the most-economic methods to decarbonize several sectors of the U.S. economy are underway. Industrial processes such as crude-oil refining rely heavily on energy-dense and easily stored and transported fossil fuels for powering their operations. Refineries use large amounts of energy, primarily derived from fossil sources to separate crude-oil components, break down heavier hydrocarbons into lighter compounds, remove impurities, reform hydrocarbon molecules, and generate steam and electricity for pumps and compressors and other various auxiliary systems. Crude-oil refining operations such as distillation, cracking, desulfurization, reforming, utilities systems and some offsite facilities collectively account for most of the energy consumption. Other operations such as hydrocracking or hydrotreating also require hydrogen for developing hydrogenation reactions which involve substantial heating to keep the reactors at high-temperature and pressure levels. All heat and energy demands are typically provided by natural gas (NG), oil, or other fuels, which makes refinery industry one of the most-difficult sectors to decarbonize. Nuclear power is a viable and energy-dense source of clean electricity, heat, and hydrogen to provide the large, sustainable energy supply that the refining industry demands. The U.S. Department of Energy’s (DOE’s) Integrated Energy Systems (IES) program is working to perform research and development, design, economic siting, and risk analysis. This state-of-the-art work will enable the first on-site demonstrations and commercial deployments of advanced small modular nuclear reactors (SMNRs) integrated with industries such as chemical production, refining, iron and steel making, and more. IES seeks to demonstrate the ability of advanced nuclear reactors to meet the heat and power demands of these industries while reducing carbon emissions in a sustainable and cost-competitive way. The primary objective of this research effort is to analyze industrial-scale SMNR integration intended to decarbonize refining facilities. The foreseen outcome is the provision of reliable, cost-competitive, and sustainable clean energy, alongside a reduction of carbon emissions. Specifically, the focus of this work lies on meeting the reference facilities’ heat and electricity demands with nuclear power while also supplying clean hydrogen via integrated high-temperature steam electrolysis (HTSE). This report presents a comprehensive technical and economic assessment of the integration of advanced nuclear reactors into a reference refinery, leveraging financial incentives from the Inflation Reduction Act (IRA). The evaluation aims to explore the potential economic benefits and challenges associated with incorporating advanced nuclear reactors into refinery operations, particularly in terms of energy efficiency, economic implications and environmental impact. By examining both the technical feasibility and economic viability, this analysis seeks to identify existing gaps and propose solutions for successful nuclear integration implementation. The findings are intended to provide valuable insights for stakeholders considering the adoption of advanced nuclear reactors in the refining sector. A refinery reference-plant was developed, using an open-source refinery model, Petroleum Refinery Lifecycle Inventory Model (PRELIM) and expert assessment, as a base case for comparison with various nuclear integration options. The capacity of 100 kbd/day (KBD) of heavy crude-oil feed was selected to represent a general coking-type refinery with deep conversion capabilities (incorporating heavy-oil upgrading with FCC, coking, and associated hydrotreating process units), using a heavy crude-oil feed, which represents about 70% of U.S. refineries configurations. A summary of all cases considered in this study is shown in Table 1.
These data provide the 2024 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products now include data (Excel workbook, Tableau workbooks, and structured summary csv files), as well as documentation and user engagement via a website, presentation, and webinar. Starting in 2021, the data are cloud optimized and provided in the OEDI data lake. The data for 2015 - 2020 are can be found on the NREL Data Search Page. The website documentation can be found on the ATB Website.
A key contributor to high capital costs and schedule overruns for new nuclear power plants is lack of standardization, driven by site-specific customization and construction of multiple designs by competing vendors rather than commitment to a single standardized program. While advanced reactor vendors typically individually target repeat construction of standardized units, the many competing designs could exacerbate the problem. “Open Architecture”, the open specification of requirements and interfaces for structures, systems and components (SSCs), has been proposed as a means of promoting standardization, by facilitating existing non-nuclear suppliers to enter the industry and/or allowing SSCs to be configured for more than one reactor within the same technology type. Contracting mechanisms that facilitate information sharing and alignment of incentives between stakeholders may complement such an approach. A preliminary scheme is presented for selection of SSCs for which such strategies could be adopted, based on a vendor make/buy decision model and stakeholder interviews. SSCs are categorized according to number of suppliers and their contribution to the reactor’s competitive edge. SSCs with many potential suppliers and a high contribution to competitive edge may be attractive for widening the supply chain via open specification of system requirements and interfaces, e.g., SSCs in the power island. SSCs with few suppliers and low contribution to competitive edge may be potential avenues for common system specification between vendors, e.g., some of the auxiliary SSCs. Potential cost reductions from such strategies will depend upon the size of the build program and the reactor type.
Supporting Data can be downloaded at: https://gain.inl.gov/content/uploads/4/2024/06/INL-RPT-24-77048-R1.xlsx Nuclear energy is a critical cornerstone of the current United States clean energy supply and may play a larger role in the future in support of a transition to a net-zero economy. The current fleet of nuclear reactors predominantly consists of large light-water reactors (LWRs), while many of the reactor designs under consideration are smaller and/or different technologies. Because these new designs have not yet been built, there is a high degree of uncertainty associated with their cost. This complicates energy-planning efforts because cost projections are not always standardized, consistent, and centralized in an easily accessible location. To help support energy planning in the US, this report provides advanced nuclear cost ranges using a transparent methodology along with other relevant information that can be used to help support decision making and energy planning. The purpose of this work was to conduct a methodical process for cost evaluation using only public information that was vetted with the end-goal to provide reference cost projections for nuclear energy. To provide a solid basis for these values, the approach and assumptions are explicitly laid out throughout the report allowing any user of the data to challenge or reconsider them. Because future US nuclear-reactor costs are still unknown due to little recent observed data, the report opted to compile a comprehensive list of bottom-up estimates and evaluate averages/trends within the data to identify reference ranges. This was deemed preferable to opining on the robustness or validity of one cost estimation versus another. To that end, the work evaluated thousands of lines of cost subaccounts from several bottom-up cost estimates. A wide variety of different reactor types captured in the data are of various sizes and technologies. Some of these reactors will be representative of advanced reactors under development while others will not. Thus, the results here are dependent on the data that are available and the accuracy of the estimates that are used. Each bottom-up estimate was reviewed to determine whether it was complete. Incomplete data sets were corrected to ensure an adequate basis of cross-comparison. The report is not without limitations and should be interpreted as an initial step to develop cost ranges for nuclear technology. Ultimately, future work can build upon the methodology with refined cost estimates to reduce uncertainty. US-based overnight capital cost (OCC) estimates were compiled from extensive data sets into ranges for both large and small reactor sizes for 2030. To project the cost declines over time, learning rates were sampled from literature sources. No SMRs were previously built; hence, learning rates based on bottom-up approaches (e.g., by quantifying the impact stemming from fabrication of different components, modular work, site construction, commissioning) were prioritized. For larger reactors, actual learning rates from deployments were used to project future costs (adjusted to account for standardization or lack thereof between designs). Other costs included are fixed and variable operations and maintenance costs. The final variables were capacity factors and ramp rates to support energy planning.
The U.S. Inflation Reduction Act (IRA) of 2022 provides a wide array of tax credits and other incentives for low-carbon energy. The technology-neutral clean generation production tax credit (PTC) (Section 45Y of the U.S. Internal Revenue Code) and the technology-neutral investment tax credit (ITC) (Section 48E) lower the net cost of new electricity generation projects with zero or negative greenhouse gas emission rates. We evaluate the impact of the IRA legislation—specifically the PTC and ITC—on the cost-competitiveness of small modular reactors (SMRs). We use the Argonne Low-carbon Energy Analysis Framework (A-LEAF) model to calculate the capacity factor of an SMR with a range of hypothetical variable operating and maintenance (O&M) costs in the Electric Reliability Council of Texas (ERCOT) electricity market. We selected ERCOT for market modeling because of its competitive structure, available data, and extensive use in prior literature. We use a discounted cash flow model to calculate the SMR’s net present value based on the market prices and capacity factors from A-LEAF, hypothetical ranges of capital and variable O&M costs, and other input parameters, with or without the IRA tax credits. We determine the SMR owner’s optimal choice of PTC or ITC for the hypothetical ranges of capital and variable O&M costs. We also evaluate potential shifts in the SMR owner’s optimal choice of PTC or ITC based on historical patterns of nuclear capital cost overruns in the United States. We also assess the sensitivity of our results to longer PTC period and electricity prices from the New England market, which tend to be higher than electricity prices in ERCOT. We find that even with the IRA tax credits, only SMRs with low capital and variable O&M costs would be economically feasible in the low-price ERCOT market scenario modeled. A longer PTC period and higher-price market such as New England, however, would significantly expand the economic feasibility of SMRs in the United States.