FuelCell Energy to Host National Laboratory-Supported AI Data Center Power Testbed in Connecticut Manufacturing Facility

Argonne National Laboratory will analyze deployment economics and lifecycle impacts to help identify cost-effective strategies.

Rhea-AI Summary

FuelCell Energy (FCEL) will develop a Connecticut test facility through StabilityMax to evaluate integrated power systems for AI data centers. The three-year project is led by the U.S. Department of Energy’s National Laboratory of the Rockies, with Argonne National Laboratory participating. It will model and validate configurations combining fuel cells, batteries and power electronics against realistic data center demand.

Positive

• Minor pointFuelCell Energy’s participation in three-year StabilityMax adds collaboration with two national laboratories.
• Minor point. Forward-looking: it has not happened yet and may not happen.A planned Connecticut fuel cell test facility will support evaluation of integrated AI data center power systems.

Negative

• None.

Key Figures

Project duration: Three years

Project duration

Three years

StabilityMax collaborative project

Key Terms

power electronics, load profiles, techno-economic analyses, lifecycle analyses

4 terms

power electronics technical

"fuel cells, energy storage, advanced controls, and power electronics"

Power electronics are devices that control and convert electrical energy to make it more useful or efficient. Think of them as the switches and converters in appliances or electric cars that manage how electricity flows, helping save energy and improve performance. They matter because they make modern technology work smoothly and help reduce energy waste.

load profiles technical

"NLR will develop data center load profiles and simulation models"

A load profile is a measured or modeled pattern showing how electrical or energy demand varies over time for a single device, a customer or a group of customers, or an entire region. It describes quantities such as average and peak use and the timing and shape of demand (hourly, daily, seasonal), and utilities and energy planners use load profiles to size equipment, forecast supply needs, and schedule generation; profiles change with weather, customer behavior, and efficiency measures, so they are snapshots or forecasts rather than fixed properties.

techno-economic analyses technical

"Argonne National Laboratory will complement this work with techno-economic"

An evaluation that combines technical performance data and economic inputs to estimate the cost, productivity, and commercial viability of a technology, process, product, or project. A techno-economic analysis models how physical parameters (efficiency, yield, energy use, throughput, required equipment) interact with financial factors (capital costs, operating costs, useful life, financing, and scale) to produce metrics such as unit cost, payback period, or net present value; it typically includes sensitivity or scenario analysis to show how results change when key assumptions vary. The method depends on engineering assumptions and cost estimates, so its conclusions reflect those inputs and uncertainties rather than being exact predictions.

lifecycle analyses technical

"techno-economic and lifecycle analyses to help identify commercially appealing"

Lifecycle analyses are systematic studies, usually following standards such as ISO 14040/14044, that measure the environmental inputs and impacts of a product, process, service, or activity across its full life stages (for example raw-material extraction, manufacturing, transport, use, and disposal or recycling). They work by compiling an inventory of material and energy flows, converting those flows into environmental impact indicators (like greenhouse gas emissions, water use, or pollution), and interpreting results within defined system boundaries; outcomes depend heavily on choices such as the boundaries, data sources and assumed usage patterns, so results are comparative and condition-specific rather than absolute.

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Testbed will model and validate integrated fuel cell, battery, and power electronics configurations against real-world AI data center load demand

DANBURY, Conn., Nov. 10, 2026 (GLOBE NEWSWIRE) -- FuelCell Energy, Inc. (Nasdaq: FCEL) today announced its participation in StabilityMax, a three-year collaborative project led by the U.S. Department of Energy’s National Laboratory of the Rockies (NLR) that will develop and validate integrated power system architectures designed to support the rapidly evolving energy requirements of artificial intelligence (AI) data centers. The project also includes participation from Argonne National Laboratory (ANL).

As AI adoption accelerates, data centers are driving unprecedented demand for electricity and creating rapid fluctuations in power consumption. StabilityMax will develop and validate a testing and modeling framework to evaluate how fuel cells, energy storage, advanced controls, and power electronics can work together to deliver reliable, responsive power for AI data centers.

Under the project, FuelCell Energy will develop a fuel cell test facility in Connecticut, creating a national laboratory-supported testbed for evaluating integrated power solutions for AI data centers.

Combining FuelCell Energy's fuel cell technology and operating experience with NLR's expertise in AI infrastructure modeling and power systems engineering, the initiative will create the tools and insights needed to optimize system designs, validate performance, and support future deployment of integrated power solutions for digital infrastructure.

NLR will develop data center load profiles and simulation models that capture the dynamic power demands of modern computing infrastructure, providing a foundation for evaluating FuelCell Energy's fuel cell technology under realistic operating conditions. Argonne National Laboratory will complement this work with techno-economic and lifecycle analyses to help identify commercially appealing, cost effective deployment strategies.

StabilityMax is part of a broader initiative by NLR to support the growing energy needs of AI-enabled digital infrastructure. Through new modeling tools, planning platforms, and test environments, NLR is helping accelerate the development and deployment of the power systems needed to enable efficient fuel cell-powered data centers.

“AI infrastructure is creating unprecedented demand for reliable, flexible, and resilient power,” said Shankar Achanta, Chief Product and Technology Officer of FuelCell Energy. “StabilityMax brings together FuelCell Energy's operating experience and fuel cell technology with the expertise of leading national laboratories to better understand how integrated power systems can support the evolving needs of AI data centers. The insights gained through this work will help optimize system designs, validate performance under real-world conditions, and support future deployment of fuel cell-based solutions for digital infrastructure.”

“Fuel cells collocated with data centers provide unique solutions to meet the power demands of AI infrastructure,” said Zhiwen Ma, Principal Investigator at NLR. “Through this project, NLR will help demonstrate how integrated fuel cell systems can rapidly respond to data center power needs while limiting impacts to the utility grid and ratepayers.”

The project builds on FuelCell Energy's ongoing development of integrated power solutions for digital infrastructure. Earlier this year, the company announced a collaboration with Siemens to advance a layered architecture approach that combines multiple technologies operating across different timescales to support the evolving power requirements of AI data centers. Insights generated through StabilityMax are expected to further inform system design and deployment strategies for future digital infrastructure applications.

Eric Strayer, FuelCell Energy’s Head of Global Sales, commented, “FuelCell Energy is actively working with customers and partners deploying power solutions for digital infrastructure, and this project will provide valuable data and operating experience that can inform future deployments. As demand for AI infrastructure continues to accelerate and load profiles evolve with each new generation of chips, the insights gained through this work will help refine system designs and deployment strategies for integrating fuel cells, energy storage, and power electronics in data center environments.”

About FuelCell Energy
FuelCell Energy, Inc. (Nasdaq: FCEL) is a U.S. clean energy technology company that delivers continuous, scalable baseload power for mission-critical applications worldwide. Its fuel cell systems generate electricity on-site at the point of use, providing reliable power for data centers, industrial facilities, utilities, and distributed-generation customers. Compact and modular by design, the systems deliver quiet, low-emission power while minimizing impacts on surrounding communities. FuelCell Energy provides proven utility-scale solutions for cleaner, more resilient local energy and has global deployments approaching one gigawatt. Learn more at FuelCellEnergy.com.

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FAQ

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What is FuelCell Energy’s StabilityMax AI data center project?

StabilityMax is a three-year collaborative project to develop and validate integrated power systems for AI data centers. FuelCell Energy will develop a Connecticut test facility, while the National Laboratory of the Rockies leads the project and develops load profiles and simulation models reflecting data center power demands.