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Mathematical modeling and simulation of hydrogen-fueled solid oxide fuel cell system for micro-grid applications - Effect of failure and degradation on transient performance

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  • Eichhorn Colombo, Konrad W.
  • Kharton, Vladislav V.
  • Berto, Filippo
  • Paltrinieri, Nicola

Abstract

We use a detailed solid oxide fuel cell (SOFC) model for micro-grid applications to analyze the effect of failure and degradation on system performance. Design and operational constraints on a component- and system level are presented. A degrees of freedom analysis identifies controlled and manipulated system variables which are important for control. Experimental data are included to model complex degradation phenomena of the SOFC unit. Rather than using a constant value, a spatially distributed degradation rate as function of temperature and current density is used that allows to study trajectory-based performance deterioration. The SOFC unit is assumed to consist of multiple stacks. The failure scenario studied is the loss of one individual SOFC stack, e.g. due to breakage of sealing or a series of fuel cells. Simulations reveal that degradation leads to significant drifts from the design operating point. Moreover, failure of individual stacks may bring the still operating power generation unit into a regime where further failures and accelerated degradation is more likely. It is shown that system design, dimensioning, operation and control are strongly linked. Apart from specific quantitative results perhaps the main practical contribution are the collected constraints and the degrees of freedom analysis.

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  • Eichhorn Colombo, Konrad W. & Kharton, Vladislav V. & Berto, Filippo & Paltrinieri, Nicola, 2020. "Mathematical modeling and simulation of hydrogen-fueled solid oxide fuel cell system for micro-grid applications - Effect of failure and degradation on transient performance," Energy, Elsevier, vol. 202(C).
  • Handle: RePEc:eee:energy:v:202:y:2020:i:c:s0360544220308598
    DOI: 10.1016/j.energy.2020.117752
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    Cited by:

    1. Shan-Jen Cheng & Wen-Ken Li & Te-Jen Chang & Chang-Hung Hsu, 2021. "Data-Driven Prognostics of the SOFC System Based on Dynamic Neural Network Models," Energies, MDPI, vol. 14(18), pages 1-17, September.
    2. Kotowicz, Janusz & Uchman, Wojciech, 2021. "Analysis of the integrated energy system in residential scale: Photovoltaics, micro-cogeneration and electrical energy storage," Energy, Elsevier, vol. 227(C).
    3. Fathy, Ahmed & Rezk, Hegazy, 2022. "Political optimizer based approach for estimating SOFC optimal parameters for static and dynamic models," Energy, Elsevier, vol. 238(PC).

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