Publisher URL: https://www.scitepress.org/Papers/2022/112633/112633.pdf
Publisher DOI: 10.5220/0011263300003274
Title: Multilinear modeling and simulation of a multi-stack PEM electrolyzer with degradation for control concept comparison
Language: English
Authors: Luxa, Aline 
Jöres, Niklas 
Cateriano Yáñez, Carlos 
Souza, Marina 
Pangalos, Georg 
Schnelle, Leona 
Lichtenberg, Gerwald  
Editor: Wagner, Gerd 
Werner, Frank 
De Rango, Floriano 
Keywords: Multilinear Simulation; Energy Systems; PEM Electrolyzer; Multi-stack Operation; Controller Design; Degradation; Wind Energy
Issue Date: 2022
Publisher: SciTePress
Part of Series: Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2022) 
Volume number: 1
Startpage: 52
Endpage: 62
Conference: International Conference on Simulation and Modeling Methodologies, Technologies and Applications 2022 
Abstract: 
Hybrid energy systems, e.g., with wind energy and hydrogen production, have a high model complexity due to their multi-physics nature, which poses major control challenges for the optimization of plant operation. This work aims at addressing this issues by introducing a highly efficient modeling and simulation framework. A proton exchange membrane (PEM) electrolyzer stack, including degradation and controller, has been modeled using the multilinear class. This class enables the automatic append of individual models, which is used to stack a 100 multi-stack PEM electrolyzer model. Moreover, the multilinear class models can be represented as tensors, which allows for efficient decomposition methods and formats. This is used to considerably enhance the simulation performance of the system, making the simulation of a one year multi-stack electrolyzer operation possible, with a reasonable computational cost. In the simulation, two different high-level control modes are compared regarding overall degradation gain and electrolyzer efficiency. The developed modeling and simulation framework has proven its suitability for big-scale complex models, enabling efficient simulations for controller analysis.
URI: http://hdl.handle.net/20.500.12738/13233
ISBN: 978-989-758-578-4
ISSN: 2184-2841
Institute: Fakultät Life Sciences 
Department Medizintechnik 
Type: Chapter/Article (Proceedings)
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