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Modeling and analysis of short-period transient response of a single, planar, anode supported, solid oxide fuel cell during load variations

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  • Nerat, Marko

Abstract

The main motivation for this study was to analyze transient responses of a solid oxide fuel cell (SOFC) during load variations, which can possibly cause fuel starvation within porous anode active layer and, consequently, accelerate the degradation rate of the SOFC. Simulation approach was taken into consideration. For this purpose, three-dimensional (3-D) dynamic model of a single, planar, anode supported SOFC was built. The model is also briefly presented in this paper. The paper focuses on detailed transient analysis of current density (J), power density (P), fuel utilization (FU) and electrical conversion efficiency (η) after a step change of voltage (load). The simulation results also give us valuable data about local mass fractions of fuel species that cannot be measured in realistic devices. It is shown that fuel starvation occurs when the J (load) is increased by approximately 100% and FU is above 0.85 at final value of J (when steady state is assumed). Moreover, the time-dependent profile of FU give us guideline for setting appropriate inlet flow rate of fuel to prevent fuel starvation. The results show that a SOFC with very thin (ds = 0.1 mm) porous anode support layer is prone to fuel starvation during large load variation. Using a thicker porous anode support layer (ds = 0.5 mm) is proposed to avoid fuel starvation and, consequently, mitigate the degradation of a realistic SOFC. The P and η of modeled SOFC are also analyzed during large load variations. The η increases with increasing the ds from 0.1 mm to 1.0 mm. The results indicate the improvement of η by appropriate design and control of a realistic SOFC.

Suggested Citation

  • Nerat, Marko, 2017. "Modeling and analysis of short-period transient response of a single, planar, anode supported, solid oxide fuel cell during load variations," Energy, Elsevier, vol. 138(C), pages 728-738.
    • Handle: RePEc:eee:energy:v:138:y:2017:i:c:p:728-738
    DOI: 10.1016/j.energy.2017.07.133
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    References listed on IDEAS

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    1. Barelli, L. & Bidini, G. & Ottaviano, A., 2016. "Solid oxide fuel cell modelling: Electrochemical performance and thermal management during load-following operation," Energy, Elsevier, vol. 115(P1), pages 107-119.
    2. Chen, Shiyi & Lior, Noam & Xiang, Wenguo, 2015. "Coal gasification integration with solid oxide fuel cell and chemical looping combustion for high-efficiency power generation with inherent CO2 capture," Applied Energy, Elsevier, vol. 146(C), pages 298-312.
    3. Xu, Haoran & Chen, Bin & Liu, Jiang & Ni, Meng, 2016. "Modeling of direct carbon solid oxide fuel cell for CO and electricity cogeneration," Applied Energy, Elsevier, vol. 178(C), pages 353-362.
    4. Amedi, Hamid Reza & Bazooyar, Bahamin & Pishvaie, Mahmoud Reza, 2015. "Control of anode supported SOFCs (solid oxide fuel cells): Part I. mathematical modeling and state estimation within one cell," Energy, Elsevier, vol. 90(P1), pages 605-621.
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    Cited by:

    1. Jiang, Jianhua & Shen, Tan & Deng, Zhonghua & Fu, Xiaowei & Li, Jian & Li, Xi, 2018. "High efficiency thermoelectric cooperative control of a stand-alone solid oxide fuel cell system with an air bypass valve," Energy, Elsevier, vol. 152(C), pages 13-26.
    2. Lee, Wooseok & Bae, Yonggyun & Lee, Sanghyeok & Hong, Jongsup, 2024. "Elucidating the dynamic transport phenomena of solid oxide fuel cells according to rapid electrical load change operation," Applied Energy, Elsevier, vol. 359(C).
    3. Li, Bohan & Wang, Chaoyang & Liu, Ming & Fan, Jianlin & Yan, Junjie, 2023. "Transient performance analysis of a solid oxide fuel cell during power regulations with different control strategies based on a 3D dynamic model," Renewable Energy, Elsevier, vol. 218(C).
    4. Zhu, Pengfei & Wu, Zhen & Yang, Yuchen & Wang, Huan & Li, Ruiqing & Yang, Fusheng & Zhang, Zaoxiao, 2023. "The dynamic response of solid oxide fuel cell fueled by syngas during the operating condition variations," Applied Energy, Elsevier, vol. 349(C).
    5. Wei, Ya & Stanford, Russell J., 2019. "Parameter identification of solid oxide fuel cell by Chaotic Binary Shark Smell Optimization method," Energy, Elsevier, vol. 188(C).

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