Integration of Solid Oxide Fuel Cell Systems Into Artificial Intelligence Data Centers

Noring, Alex [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)]; Kuffour, Joshua [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)]; Iyengar, Arun [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)]; Hackett, Gregory [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)] (ORCID:0000000341313209)

doi:10.2172/3366075

DOE OSTI · 3366075

Integration of Solid Oxide Fuel Cell Systems Into Artificial Intelligence Data Centers

Noring, Alex [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)]·Kuffour, Joshua [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)]·Iyengar, Arun [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)]·Hackett, Gregory [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)] (ORCID:0000000341313209)

View original source ↗Read source document ↗Export metadata ↓

Abstract

This report presents the results of a techno-economic analysis (TEA) that evaluates the economic benefits of integrating solid oxide fuel cell (SOFC) systems with artificial intelligence (AI) data centers. The analysis was completed in two phases: a scoping-level analysis was performed to identify impactful integration opportunities, followed by a more detailed TEA. Results show that, due to their modularity, SOFC can meet the 99.999% availability requirement of data centers with minimal additional costs. Heat integration via absorption chillers decreases data center electricity consumption at the tradeoff of increased water consumption. Higher SOFC exhaust temperatures are important for achieving larger electricity savings. Finally, power electronics integration with SOFC direct current electricity can reduce electricity consumption by 9 percent and reduce water consumption by 6.4 percent.

Explore related subjects

20 FOSSIL-FUELED POWER PLANTS AI Data Centers artifical intelligence (AI)SOFC solid oxide fuel cell

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Noring, Alex [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)], Kuffour, Joshua [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)], Iyengar, Arun [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)], Hackett, Gregory [National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)] (ORCID:0000000341313209). 2026-03-31. Integration of Solid Oxide Fuel Cell Systems Into Artificial Intelligence Data Centers. https://doi.org/10.2172/3366075

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

DOE OSTI2026

Designing a Robust MEA-Based Post-Combustion Carbon Capture Process with Capture Rate Guarantees

This work presents an application of the nonlinear two-stage robust optimization solver PyROS to the model-based design and operation of a monoethanolamine scrubbing process for CO2 capture under epistemic uncertainty. Through this application, risk-averse process designs are successfully obtained for CO2 capture targets ranging from 90% to over 99%. In particular, the risk-averse solutions for CO2 capture targets of up to 98% are shown to be only marginally more expensive than their nominally optimal counterparts. Thus, the results demonstrate the utility of recently developed nonlinear robust optimization approaches for the solution of large-scale chemical process models under uncertainty.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2026

Optimal Design and Techno-Economic Analysis of 3D-Printed, Intensified Packings for Absorbers and Strippers in Solvent-Based CO 2 Capture

A potential technology for the CO 2 absorption process is utilizing intensified structured packing with embedded cooling/heating channels for continuous heat exchange, which can overcome limitations of discrete methods, such as discrete intercooling and centralized reboilers, to aid in reducing energy consumption and decreasing costs. This work investigates the modeling of intensified packing (IP) for the stripper tower, extending on previous work for the absorber, which distributes heat internally within the column, improving the thermodynamics for the solvent regeneration process. The model includes submodels for steam turbine extraction to produce steam at various qualities as well as a surrogate model for calculating steam enthalpy. A cost model for a plant-scale absorption capture process was developed, allowing for the design of the plant to be optimized, subject to minimizing capture cost using two different power plant flue gas sources. In this optimization, the placement of IP in both towers is optimized to balance the trade-off between enhanced heat transfer and reduced mass transfer volume. For natural gas combined cycle flue gas, the standard process configuration had a minimum cost of $\$$65.40/tonne CO 2 , and considering IP, the minimum capture cost is reduced to $\$$62.73/tonne, with utilization in the stripper column, which reduces yearly costs by up to $\$$2.67 MM/yr. Cooling the absorber through IP, or intercoolers, was only found to be beneficial at higher capture rates, with IP in both towers having a cost of capture of $\$$68.08/tonne at 99.9% capture, a reduction of $\$$12.64/tonne when using only intercoolers at the same capture rate. When capturing from pulverized-coal power plants, the minimum cost of capture when using IP in both towers is $\$$44.18/tonne (at 97% capture), while the standard configuration with and without intercoolers was $\$$45.69 and $\$$47.22 per tonne, respectively. This results in a reduction in yearly costs of $\$$16.98 MM/yr from the base-case configuration. At this higher CO 2 concentration, cooling in the absorber from the IP becomes extremely beneficial, reducing energy consumption by up to 6%.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2026

Transformational Molecular Layer Deposition Tailor-Made Size-Sieving Sorbents for Post-Combustion CO 2 Capture

This report summarizes the carbon capture research and development conducted by The State University of New York at Buffalo (UB), University of South Carolina (USC), GTI Energy (GTI), and Rensselaer Polytechnic Institute (RPI) for U.S. Department of Energy (DOE) project DE-FE0031730 titled “Transformational Molecular Layer Deposition Tailor-made Size-Sieving Sorbents for Post-Combustion CO 2 capture.” The objective of this project was to develop a transformational molecular layer deposition (MLD) tailor-made size-sieving sorbent integrated with a pressure swing adsorption (PSA) cycle schedule that can be installed in new or retrofitted into existing pulverized coal (PC) power plants for CO 2 capture with a cost of electricity at least 30% lower than a supercritical PC power with CO 2 capture, or approximately $\$$30 per tonne of CO 2 captured, and with it being ready for demonstration by 2030.

20 FOSSIL-FUELED POWER PLANTS↗