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Optimal dynamic operation and modeling of parallel connected multi-stacks fuel cells with improved slime mould algorithm

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  • Othman, Ahmed M.
  • El-Fergany, Attia A.

Abstract

In this article, a comprehensive detailed dynamic representation of multi-stacks fuel cells is addressed. This representation is applied and compromised for parallel connected and operated multi-stacks solid-oxide fuel cells (SOFCs), which is considered a hot topic and research challenge. A proposed control system is presented to manage SOFCs parallel stacks sharing and operation. A part of this technical challenge in regards to the parallel operation is to realize equal output voltages with various current values of each cell. An improved slime mould algorithm (ISMA) is proposed to set the operational parameters of parallel operated SOFCs stacks. Digital simulations have validated the proposed system effectiveness with optimal dynamic parameters under various operating scenarios. These scenarios include step-load changes (increase/decrease) under equal and unequal load sharing's plus emergent fault conditions by short-circuit disturbance and protection tripping. Further validations thru comparisons of ISMA's results with the best results of genetic algorithm (GA) as a well-established benchmark algorithm are emphasized. The simulation results show the efficacy of proposed technique and representation to improve the dynamic performance of the underlined system, for example at a particular scenario. Just to figure out the cropped results, it is noted the ability of proposed technique to realize a very smooth dynamic response (overshoot = 2.30e-5 pu and settling time = 0.054 s) compared to those achieved by GA (overshoot = 4.78e-2 pu and settling time = 0.22 s) under fuel cells different shares' scenarios.

Suggested Citation

  • Othman, Ahmed M. & El-Fergany, Attia A., 2021. "Optimal dynamic operation and modeling of parallel connected multi-stacks fuel cells with improved slime mould algorithm," Renewable Energy, Elsevier, vol. 175(C), pages 770-782.
    • Handle: RePEc:eee:renene:v:175:y:2021:i:c:p:770-782
    DOI: 10.1016/j.renene.2021.04.148
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    References listed on IDEAS

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    1. Ferrari, Mario L., 2015. "Advanced control approach for hybrid systems based on solid oxide fuel cells," Applied Energy, Elsevier, vol. 145(C), pages 364-373.
    2. Ahmed M. Agwa & Attia A. El-Fergany & Gamal M. Sarhan, 2019. "Steady-State Modeling of Fuel Cells Based on Atom Search Optimizer," Energies, MDPI, vol. 12(10), pages 1-14, May.
    3. Li Sun & Qingsong Hua & Jiong Shen & Yali Xue & Donghai Li & Kwang Y. Lee, 2017. "A Combined Voltage Control Strategy for Fuel Cell," Sustainability, MDPI, vol. 9(9), pages 1-15, August.
    4. El-Fergany, Attia A., 2018. "Extracting optimal parameters of PEM fuel cells using Salp Swarm Optimizer," Renewable Energy, Elsevier, vol. 119(C), pages 641-648.
    5. Thomas Kadyk & Christopher Winnefeld & Richard Hanke-Rauschenbach & Ulrike Krewer, 2018. "Analysis and Design of Fuel Cell Systems for Aviation," Energies, MDPI, vol. 11(2), pages 1-15, February.
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    Cited by:

    1. Zhou, Su & Zhang, Gang & Fan, Lei & Gao, Jianhua & Pei, Fenglai, 2022. "Scenario-oriented stacks allocation optimization for multi-stack fuel cell systems," Applied Energy, Elsevier, vol. 308(C).
    2. Zhang, Gang & Zhou, Su & Gao, Jianhua & Fan, Lei & Lu, Yanda, 2023. "Stacks multi-objective allocation optimization for multi-stack fuel cell systems," Applied Energy, Elsevier, vol. 331(C).
    3. Zhou, Su & Xie, Zhengchun & Chen, Chunguang & Zhang, Gang & Guo, Junhua, 2022. "Design and energy consumption research of an integrated air supply device for multi-stack fuel cell systems," Applied Energy, Elsevier, vol. 324(C).

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