(258f) Modeling and Optimization of Electrified Steam Methane Reformer Via Induction Heating (ESMR-IH)

Hydrogen has emerging roles as both an energy storage medium and a clean fuel, motivating the efficiency improvements through electrification of H₂ production processes¹. One pathway is direct electrification of heat supply in Steam Methane Reforming (SMR) via induction heating (IH)², which leverages the electromagnetic properties of catalytic materials to generate heat in situ³. This technology offers several advantages over conventional fossil-fuel-based heating, including integration with renewable electricity², decarbonization potential⁴, rapid thermal response², mitigation of heat transfer limitations⁵, and reduction in reactor geometry⁵. The economic performance of ESMR-IH has potential to exceed that of traditional SMR and water electrolysis processes^6,7. The Technology Readiness Level of such approach is at 4–5, with ongoing research focused on lab-scale demonstrations⁸. Current techno-economic analyses are typically based on simplified models of ESMR that assume constant energy efficiency and equilibrium-based reactions^4,6,9. Advancement toward commercialization necessitates scale-up assessments, detailed geometry and operation design. There remains a lack of rigorous modeling capable of performing integrated unit simulation, process optimization, and performance analysis across scales.

To address this gap, a first-principles, equation-oriented model for ESMR-IH has been developed, incorporating mass, momentum, and heat conservation equations, along with Langmuir-Hinshelwood-Hougen-Watson kinetics¹⁰. The heat conservation is modified to account for internal heat generation of IH, in contrast to conventional SMR models where heat is externally supplied at the reactor boundary. To assess performance of ESMR-IH compared with thermally-constrained SMR, a two-dimensional model assuming angular symmetry is implemented along the axial and radial dimensions. Model calibration is performed via least-squares parameter estimation using experimental methane conversion data. A dimensionless formulation is employed to isolate scaling effects, generalize the system behavior. An economic optimization framework is developed to minimize the levelized cost of H₂. A Trust Region Filter algorithm¹¹ is employed embedding with a surrogate model to enable efficient integration of the rigorous model into the economic optimization of reactor geometry and operating conditions.

This work aims at establishing a comprehensive modeling and optimization framework for ESMR-IH, filling the gaps in performance prediction, design and operation exploration. The framework evaluates the potential commercialization of electrified hydrogen production technologies, and provides a reference for the electrification of endothermic chemical processes.

References

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