(65e) Modular Dynamic Modeling of Electrochemical Reactors

Meeting global climate targets requires significant reductions in greenhouse gas emissions in all sectors. For the chemical industry, this entails a shift from fossil raw materials and energy sources to renewables. In this context, Power-to-X solutions that convert, e.g., water and carbon dioxide into valuable products, are gaining increasing attention [1]. Such solutions also enable sustainable solutions in other sectors by producing synthetic fuels, or supporting the integration of renewables in the power sector by providing load flexibility. The heart of almost all Power-to-X solutions are electrochemical reactors that convert electrical energy into the valuable product or an intermediate. As such, the importance of electrochemical reactors is expected to increase significantly in the future, regarding both the number of applications and their scale.

While modeling of electrochemical reactors has received ample of attention in literature [2], models able to describe dynamics are still rather scarce [3]. However, dynamics of electrochemical reactors (as well as the surrounding processes) play a key role in light of the volatility of renewable power sources. Furthermore, dynamic models could facilitate parameter identification and hence aid understanding of the underlying physical effects by separating slow and fast processes [3]. Finally, the increasing number of applications of electrochemical reactors calls for tools to support rapid development of models for different reaction systems and setups.

In this contribution, we present a library for modular, dynamic modeling and simulation of electrochemical reactors in Modelica. This library extends our previous work on modular modeling of CO₂ electrolyzers [4] to provide improved modularity and flexibility in modeling and cover a broader range of applications. Models are provided that describe the chemistry, mass and energy balances of different components such as flow channels or gas diffusion layers, as well as the electrical circuit of such reactors. The models are either spatially lumped or of intermediate fidelity, i.e., rather coarse one- or two-dimensional spatial discretization to maintain computational tractability for dynamic simulation and optimization of entire reactor setups. Beyond the model structure, we present example applications including water electrolysis and electrochemical hydrogen separation and compression.

References

[1] J. Burre, D. Bongartz, L.C. Brée, K. Roh, A. Mitsos, Chem. Ing. Techn. 92 (2020), 74.

[2] P. Olivier, C. Bourasseau, P.B. Bouamama, Renew. Sustain. Energy Rev. 78 (2017), 280.

[3] B.J.M. Etzold, U. Krewer, S. Thiele, A. Dreizler, E. Klemm, T. Turek, Chem. Eng. J. 424 (2021), 130501.

[4] L.C. Brée, M. Wessling, A. Mitsos, Comput. Chem. Eng. 139 (2020), 106890.