Improving Computational Models of Solid Oxide Cells for Industrial Performance Optimization

The current shift towards renewable energy systems relies heavily on the efficient production and utilization of hydrogen. Solid Oxide Cells (SOCs) have emerged as a pivotal technology in this domain, offering high efficiency in both power generation (SOFC) and electrolysis (SOEC) modes.

The transition of the SOC technology from laboratory research to industrial deployment also shifts the focus of SOC modeling methods from mechanistic investigations towards the engineering tasks of system development and process optimization. This dissertation aims at accelerating the deployment of the SOC technology by providing new modeling tools intended to aid the performance optimization of SOC modules and the systems surrounding them. By improving upon existing modeling efforts, more accurate simulations of the physical processes within SOC stacks are enabled without compromising on the computation speed required for engineering tasks.

The research identifies a critical gap in existing modeling frameworks: the trade-off between computational speed and physical fidelity when simulating gas flow in stack manifolds. One of the most prominent issue in this subject area was found to be the lack of reliable data required to parametrize simplified modeling approaches.
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To resolve this, detailed three-dimensional computational fluid dynamics (CFD) simulations are performed on representative U-type internal manifold geometries using OpenFOAM. These simulations reveal that standard friction factors are inadequate to describe the pressure losses in SOC stack manifolds. Consequently, a set of improved closed-form expressions for pressure loss coefficients and Darcy friction factors are developed through analysis of the detailed CFD simulation results. These expressions are integrated into a network model of the flow, enabling the prediction of flow distribution with deviations of less than 5% compared to high-fidelity CFD, but at a fraction of the computational cost.

Utilizing the newly developed expressions for pressure losses throughout the stack and building upon previous multi-scale SOC modeling works, a comprehensive SOC stack model is developed. The model accounts for electrochemical kinetics, thermocatalytic chemistry, charge transport, as well as different mechanisms of mass and heat transport. In addition to the stack flow model, other improvements such as a conservative set of equations for mass transport in gas channels and an iterative scheme for the computation of the cell potential distribution in SOC stacks are introduced. Initially, the model is parametrized and validated through the comparison of button cell simulations and experimental button cell data. High accuracy across various temperatures and gas compositions is demonstrated. The model is subsequently employed to investigate the impact of the manifold on the flow distribution of an SOEC stack operated at elevated current density. Results reveal significant air channel inlet flow velocity variations of 11% around the average having negligible impact on the stack performance compared to a reference case with homogeneous influx.

Finally, the improved modeling framework is applied to a system-level optimization study of multiple power-to-methane (PtM) processes. This last study performs a comparison of PtM processes built from a combination of different electrolysis, methanation and carbon oxide supply technologies. A major focus of this study is to quantify the advantage reaped from integrating different carbon oxide supply technologies to the PtM process. Therefore, the biomass gasification, amine gas treatment and direct air capture processes are coupled to different SOEC stack architectures (electrolyte-supported and cathode-supported) as well as different methanation processes (fixed-bed and three-phase methanation reactors). The results demonstrate that integrating the carbon supply process into a PtM plant provides a significant advantage for all combinations of technologies. The analysis further highlights a strategic trade-off where capital costs of electrolyzers may be significantly reduced by the synergistic interaction between exothermically operated SOECs and the strongly endothermic carbon capture processes.

Overall, this dissertation provides useful and novel tools for the simulations of SOCs which aid in bridging the gap between the detailed analysis of physical phenomena and the engineering of system-level applications. These tools, as well as the insights resulting from their application in dedicated case-studies, provide an improved foundation for the design and optimization of future energy conversion systems that utilize the SOC technology.