Search NASA⌕ Search

Engineering topics

Lohse, Christopher Shawn

Publications and source records attributed to Lohse, Christopher Shawn.

4 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

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.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Meta-Analysis of Advanced Nuclear Reactor Cost Estimations

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.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Advanced Reactor Supply Chain Assessment (GAIN Report)

Several net-zero scenario evaluations predict a rapid ramp up of nuclear energy in the coming decades. If this materializes, it will most likely strain the supply chains associated with the potential advanced reactor concepts awaiting deployment. To help assess the current and potential capacities of the various advanced reactor supply chains, the Gateway for Accelerated Innovation in Nuclear (GAIN) conducted a survey of companies able to produce components for advanced reactors in the near future (namely for sodium, gas-cooled, and molten salt reactors). Using an aggressive nuclear deployment scenario, the objective was to assess the ability of the various supply chains to meet the considerable demand projections for certain key components (vessels, heat exchangers, pumps, graphite, and sensors) and identify potential challenges. While individual companies were unable to meet the most optimistic nuclear deployment rate projections, it was found that on aggregate, a United States-based supply chain projected that expansion could be ramped up to meet a larger future demand of these components. However, meeting projected demand for several more complex items (namely gas or salt heat exchangers) was found to be more challenging. Deploying new reactors at scale necessitates the production of more and more supply chain components, requiring a ramp up in production. Supply chain companies were surveyed, and respondents appeared less able to meet short term demand (next year) versus longer-term demand projections (5 and 10 years). This reflects the need to obtain orders with adequate lead times (can range from 3 to 30 months). Future demand will need to be met by expanding existing capacity. These expansions will require suppliers to raise capital or secure other types of support (federal loans or grants) to invest in facilities, equipment, and workforce. Individual suppliers indicated financial investments could be in the range of $\$ $100 million to $\$ $1 billion for their own facilities (depending on the type of facility). The biggest risk, according to respondents, related to general uncertainties surrounding the future nuclear industry and whether the potential demand projections will materialize into real demand that is actionable from a business perspective. Businesses do not seem willing to take investments risks without clear orders. If businesses are not able to invest to expand the supply, it will either delay the deployment of advanced nuclear technology, or the supply chain will be met by suppliers outside of the United States. This report only focuses on the domestic supply chain’s ability to meet the various projections stipulated here for the specific assessed components (vessels, heat exchangers, pumps, graphite, and sensors). The report does not cover all reactor designs or all components that may ultimately be needed for any one reactor design. It also does not address whether any specific aspect of the supply chain will be cost competitive in the global market, nor how potential state-backed entities could affect the expansion of a United States-based supply chain. The largest challenges in ramping up capacity among respondents appear to be workforce related. This includes workforce availability, experience, training, and turnover. In addition to facility investment, suppliers will also need to invest heavily in long-term workforce training to meet production goals. This issue is not nuclear-specific, and the expansion of any supply chain will likely face similar challenges. While suppliers evaluated expected normal business demand from other markets outside of nuclear, it is possible that other market segments could expand more than predicted and compete for the same suppliers. One potential market that may compete for the same supplier resources is the United States military, as many of these suppliers support both the commercial nuclear sector as well as the Navy with reactors and components. In summary, suppliers in the United States believe that there is a way to increase production in order to begin meeting the demand which will exist for advanced reactors—as long as appropriate investments can be made in the supply chain in an appropriate timeframe. Based on the capacity projections and lead times, investment will be needed to meet the 5-year and 10-year production targets. Therefore, if significant nuclear deployment is to occur in the 2030s, investment and ramp up of the advanced nuclear supply chain will need to begin in the near future for the United States to successfully deploy these advanced reactors with domestic supply chains.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗