An adaptive model-based feedforward temperature control of a 100 kW PEM electrolyzer. (March 2022)

• Record Type: Journal Article
• Authors: Keller, R.; Rauls, E.; Hehemann, M.; Müller, M.; Carmo, M.
• Is Part Of: Control engineering practice. Volume 120(2022)
• Publication Date: 2022-03
• Subjects: Feedforward control -- PEM electrolyzer -- Model-based control -- System efficiency -- Stability -- Adaptive control -- Safety; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2021.104992
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: Polymer Electrolyte Membrane (PEM) electrolyzers will play a central role in future power-to-gas plants. Increasing the performance and scaling of PEM electrolyzers to the MW scale represents significant challenges for existing system components, as well as for optimal operational management. In relation to existing control loops, temperature control turns out to be critical. Due to scaling into higher performance classes and highly dynamic load profiles of green energy sources such as wind power and photovoltaics, the disturbance variable current density has an increasing influence on temperature control. The temperature is an essential operating parameter, especially for PEM electrolyzers, to be able to provide optimum efficiency, safety and prevent premature aging or destruction. In this article, we present an adaptive temperature control with a model-based feedforward control based on a model that considers the dependency of the operating parameters current density and stack temperature. In order to demonstrate the reliability and robustness of the control performance, an experimental validation of the adaptive temperature control with feedforward control is carried out on a 100 kW PEM electrolyzer. In this context, a comparison and an evaluation of the control concept to the existing proportional–integral–derivative (PID) control under highly dynamic load changes from wind power and photovoltaics is performed. Finally, the obtained results are discussed with respect to the aspects of optimal operational management.