Engineering topics
Publications and source records attributed to Larsen, Levi Morin.
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).
The shipping industry contributes to a substantial quantity of global carbon emissions. Reaching a “Net-Zero World” will ultimately require complete decarbonization of the existing fleet. Nuclear energy may provide a viable solution toward this end goal. To better understand the economic dynamics of relying on nuclear energy to power maritime fleets, cost targets were identified in this study. Two use cases were considered: (1) nuclear energy is used to generate synthetic fuel (termed synfuel) to power maritime propulsion, and (2) nuclear reactors for vessel propulsion. The study found that in both cases realistic cost targets for nuclear reactor costs could be reached. However, option 2 was deemed to be much more competitive overall but with higher technical risks.
The levelized cost of energy (LCOE) and other cost metrics used in energy planning do not account for out-of-market impacts of the technology choice. While a decision-maker at the utility or asset owner level may compare multiple forms of electricity generating technology using LCOE, a decision-maker over energy policy or community stakeholders may be interested in considering impacts beyond those that LCOE measures. This report quantifies economic impacts such as jobs and wage growth across electricity generation technologies then develops an approach to systematically compare socioeconomic metrics across technology choices. To address additional workforce related impacts, this report also compares the typical workforce education requirements and annual income levels for multiple types of electricity generating facilities. The grid scale electricity generating technologies analyzed in this report produce power using conventional hydroelectric dams, coal, natural gas, nuclear reactors, solar PV, land-based wind turbines, geothermal heat, and woody biomass combustion. Although it doesn’t generate electricity itself, the economic impacts associated with battery storage equipment manufacturing and installation were also analyzed.
The United States nuclear reactor fleet consists of 63 pressurized water reactors and 31 boiling water reactors and is a pivotal component in the nation's energy infrastructure, supplying approximately 97 GW e of clean power. With the country's commitment to decarbonization by 2050, these reactors are not only instrumental in decarbonizing the electricity grid but also play a critical role in decarbonizing industrial processes, producing clean fuels, and scaling up CO 2 removal. This report delves into the potential for power uprates in the existing fleet to contribute to these decarbonization efforts, focusing on the expansion of capacity for applications such as hydrogen production and carbon capture and sequestration. Building on previous research, the report explores regional market demands for hydrogen, oxygen, and carbon dioxide, financial implications of oxygen and CO 2 sales from high-temperature steam electrolysis systems, and the potential for direct air capture systems paired with uprated nuclear plants.
The framework developed in this study is provided both as an excel sheet (https://inl.gov/content/uploads/2023/11/Nuclear-Reactor-Cost-Reduction-Pathway-Spreadsheet-Tool.xlsx) and a Python (Jupyter) Notebook (link: https://github.com/accert-dev/ACCERT/tree/main/Cost%20Reduction). Capital cost considerations are one of the primary inhibitors to the large-scale deployment of nuclear power plants. While it is widely accepted that first units will likely be expensive and relatively uncompetitive, it is reasonable to expect that subsequent units, built in relative quick succession, will be cheaper as they benefit from the so-called “learning effects”. However, the large degree of uncertainty associated with this parameter renders it challenging for first movers to invest in the first few expensive units. To resolve this impasse, the U.S. Department of Energy’s Advanced Nuclear Liftoff study advocated for the formation of large, committed order books of plants of the same technology to spread the costs across several units and kickstart the nuclear supply chain. The study also advocated best practices for avoiding overruns and keeping reactors on budget. This report builds on these key recommendations by attempting to quantify specific pathways toward cost reduction for nuclear energy. A capital cost estimation framework was built to untangle the effect of learning into a subset of key cost drivers, referred to as “levers”. Collectively, the choice of these levers is intended to reflect the decision-making of high-level stakeholders like plant owners and the government. In addition to the size of the firm orderbook, these levers included (a) cost drivers that are most often attributed to cost overruns such as architect/engineering (A/E) proficiency, construction proficiency, procurement service proficiency, design completion prior to the start of construction, and design maturity, and (b) cost reduction strategies such as modular construction, cross-site standardization, safety classification of the reactor building, and of the balance of plant. Two advanced reactor designs were leveraged as use cases and bottom-up cost estimates made with assumptions consistent with a well-executed first-of-a-kind project (WE-FOAK, i.e., almost no overruns) were used as baselines for the models. Cost correlations were surveyed from the literature to determine the impact of important variables on projected timelines and costs.
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.