Evaluation of Fuel Diversity in Solid Oxide Fuel Cell System

Amirpiran Amiri, Shi Tang, Robert Steinberger-Wilckens, Moses O. Tadé

Research output: Contribution to journalArticle

Abstract

Operability of Solid Oxide Fuel Cell (SOFC) on numerous fuels has been widely counted as a leading advantage in literature. In a designed system, however, switching from a fuel to another is not practically a straightforward task as this causes several system performance issues in both dynamic and steady-state modes. In order to demonstrate the system fuel diversity capabilities, these consequences must be well-evaluated by quantifying the characteristic measures for numerous fuel cases and also potential combinations. From this viewpoint, the numerical predictive models play a critical role. This paper aims to investigate the performance of a SOFC system fed by various fuels using a demonstrated system level model. Process configuration and streams results of a real-life SOFC system rig published in literature are used to validate the model. The presented model is capable not only of capturing the system performance measures but also the SOFC internal variable distributions, allowing the multiscale study of fuel switching scenarios. The fuel change impacts on the system are simulated by considering various fuel sources, i.e., natural gas, biogas, and syngas. Moreover, applications of simulated fuel mixtures are assessed. The modelling results show significant concerns about fuel switching in a system in terms of variation of efficiencies, stack internal temperature and current density homogeneity, and environmental issues. Moreover, the results reveal opportunities for multi-fuel design to address the operation and application requirements such as optimisation of the anode off-gas recycling rate and the thermal-to-electrical ratio as well as the system specific greenhouse gases, i.e., g-COx/Wh release.
Original languageEnglish
JournalInternational Journal of Hydrogen Energy
Early online date20 Nov 2018
DOIs
Publication statusE-pub ahead of print - 20 Nov 2018

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© 2018, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

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