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Decision process to manage useful life of multi-stacks fuel cell systems under service constraint

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  • Herr, Nathalie
  • Nicod, Jean-Marc
  • Varnier, Christophe
  • Jardin, Louise
  • Sorrentino, Antonella
  • Hissel, Daniel
  • Péra, Marie-Cécile

Abstract

A management of multi-stacks fuel cell systems is proposed to extend systems useful life in a Prognostics and Health Management (PHM) framework. The problem consists in selecting at each time which fuel cell stacks have to run and which output power has to be chosen for each of them to satisfy a load demand as long as possible. Multi-stacks fuel cell system useful life depends not only on each stack useful life, but also on both the schedule and the operating conditions settings that define the contribution of each stack over time. As the impact of variable operating conditions on fuel cell lifetime is not well-known, a simplified representation of fuel cell behavior under wear and tear is used to estimate the available outputs over time and their associated Remaining Useful Lives (RUL). This health state prognostics model is configured to suit to Proton-Exchange Membrane Fuel Cells (PEMFC) specific characteristics. The proposed scheduling process makes use of an optimal approach based on a Mixed Integer Linear Program (MILP). Efficiency of the associated commitment strategy is assessed by comparison with basic intuitive strategies, considering constant and piecewise constant load demand profiles.

Suggested Citation

  • Herr, Nathalie & Nicod, Jean-Marc & Varnier, Christophe & Jardin, Louise & Sorrentino, Antonella & Hissel, Daniel & Péra, Marie-Cécile, 2017. "Decision process to manage useful life of multi-stacks fuel cell systems under service constraint," Renewable Energy, Elsevier, vol. 105(C), pages 590-600.
    • Handle: RePEc:eee:renene:v:105:y:2017:i:c:p:590-600
    DOI: 10.1016/j.renene.2017.01.001
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    References listed on IDEAS

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    1. Zuo, Jian & Cadet, Catherine & Li, Zhongliang & Bérenguer, Christophe & Outbib, Rachid, 2024. "A deterioration-aware energy management strategy for the lifetime improvement of a multi-stack fuel cell system subject to a random dynamic load," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Zuo, Jian & Lv, Hong & Zhou, Daming & Xue, Qiong & Jin, Liming & Zhou, Wei & Yang, Daijun & Zhang, Cunman, 2021. "Deep learning based prognostic framework towards proton exchange membrane fuel cell for automotive application," Applied Energy, Elsevier, vol. 281(C).
    3. Yue, Meiling & Jemei, Samir & Zerhouni, Noureddine & Gouriveau, Rafael, 2021. "Proton exchange membrane fuel cell system prognostics and decision-making: Current status and perspectives," Renewable Energy, Elsevier, vol. 179(C), pages 2277-2294.
    4. Yang, Yang & Xing, Kai & Yan, Minyue & Zhu, Xun & Ye, Dingding & Chen, Rong & Liao, Qiang, 2023. "A potential flexible fuel cell with dual-functional hydrogel based on multi-component crosslinked hybrid polyvinyl alcohol," Energy, Elsevier, vol. 265(C).
    5. Laeun Kwon & Dae-Seung Cho & Changsun Ahn, 2021. "Degradation-Conscious Equivalent Consumption Minimization Strategy for a Fuel Cell Hybrid System," Energies, MDPI, vol. 14(13), pages 1-14, June.
    6. 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).
    7. 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).
    8. Antonio José Calderón & Francisco José Vivas & Francisca Segura & José Manuel Andújar, 2020. "Integration of a Multi-Stack Fuel Cell System in Microgrids: A Solution Based on Model Predictive Control," Energies, MDPI, vol. 13(18), pages 1-24, September.
    9. Zhou, Su & Fan, Lei & Zhang, Gang & Gao, Jianhua & Lu, Yanda & Zhao, Peng & Wen, Chaokai & Shi, Lin & Hu, Zhe, 2022. "A review on proton exchange membrane multi-stack fuel cell systems: architecture, performance, and power management," Applied Energy, Elsevier, vol. 310(C).
    10. 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).
    11. Fan, Lixin & Tu, Zhengkai & Chan, Siew Hwa, 2022. "Technological and Engineering design of a megawatt proton exchange membrane fuel cell system," Energy, Elsevier, vol. 257(C).
    12. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2021. "Prognosis of fuel cell degradation under different applications using wavelet analysis and nonlinear autoregressive exogenous neural network," Renewable Energy, Elsevier, vol. 179(C), pages 802-814.
    13. Abdelkareem, Mohammad Ali & Allagui, Anis & Sayed, Enas Taha & El Haj Assad, M. & Said, Zafar & Elsaid, Khaled, 2019. "Comparative analysis of liquid versus vapor-feed passive direct methanol fuel cells," Renewable Energy, Elsevier, vol. 131(C), pages 563-584.
    14. Nie, Zhigen & Jia, Yuan & Wang, Wanqiong & Chen, Zheng & Outbib, Rachid, 2022. "Co-optimization of speed planning and energy management for intelligent fuel cell hybrid vehicle considering complex traffic conditions," Energy, Elsevier, vol. 247(C).
    15. Hmam, S. & Olivier, J.-C. & Bourguet, S. & Loron, L. & Bernard, N. & Schaeffer, E., 2019. "A cycle-based formulation for the simulation of multi time-scale systems — Application to the modeling of the storage system of a fully electric ferry," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 158(C), pages 403-417.

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