IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v105y2017icp590-600.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148117300010
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2017.01.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dufo-López, Rodolfo & Bernal-Agustín, José L. & Contreras, Javier, 2007. "Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage," Renewable Energy, Elsevier, vol. 32(7), pages 1102-1126.
    2. Azcárate, Cristina & Blanco, Rosa & Mallor, Fermín & Garde, Raquel & Aguado, Mónica, 2012. "Peaking strategies for the management of wind-H2 energy systems," Renewable Energy, Elsevier, vol. 47(C), pages 103-111.
    3. Bigdeli, Nooshin, 2015. "Optimal management of hybrid PV/fuel cell/battery power system: A comparison of optimal hybrid approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 377-393.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. 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).
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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.
    9. 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).
    10. 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).
    11. 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).
    12. 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.
    13. Zuo, Jian & Steiner, Nadia Yousfi & Li, Zhongliang & Hissel, Daniel, 2024. "Health management review for fuel cells: Focus on action phase," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).
    14. 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).
    15. 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).
    16. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hemmati, Reza & Saboori, Hedayat, 2016. "Emergence of hybrid energy storage systems in renewable energy and transport applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 11-23.
    2. Torreglosa, Juan P. & García, Pablo & Fernández, Luis M. & Jurado, Francisco, 2015. "Energy dispatching based on predictive controller of an off-grid wind turbine/photovoltaic/hydrogen/battery hybrid system," Renewable Energy, Elsevier, vol. 74(C), pages 326-336.
    3. Yao, Ganzhou & Luo, Zirong & Lu, Zhongyue & Wang, Mangkuan & Shang, Jianzhong & Guerrerob, Josep M., 2023. "Unlocking the potential of wave energy conversion: A comprehensive evaluation of advanced maximum power point tracking techniques and hybrid strategies for sustainable energy harvesting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    4. Lan, Hai & Wen, Shuli & Hong, Ying-Yi & Yu, David C. & Zhang, Lijun, 2015. "Optimal sizing of hybrid PV/diesel/battery in ship power system," Applied Energy, Elsevier, vol. 158(C), pages 26-34.
    5. Li, Feng & Yuan, Yupeng & Yan, Xinping & Malekian, Reza & Li, Zhixiong, 2018. "A study on a numerical simulation of the leakage and diffusion of hydrogen in a fuel cell ship," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 177-185.
    6. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    7. Wen, Shuli & Lan, Hai & Hong, Ying-Yi & Yu, David C. & Zhang, Lijun & Cheng, Peng, 2016. "Allocation of ESS by interval optimization method considering impact of ship swinging on hybrid PV/diesel ship power system," Applied Energy, Elsevier, vol. 175(C), pages 158-167.
    8. Paliwal, Priyanka & Patidar, N.P. & Nema, R.K., 2014. "Determination of reliability constrained optimal resource mix for an autonomous hybrid power system using Particle Swarm Optimization," Renewable Energy, Elsevier, vol. 63(C), pages 194-204.
    9. Jiang, Yinghua & Kang, Lixia & Liu, Yongzhong, 2019. "A unified model to optimize configuration of battery energy storage systems with multiple types of batteries," Energy, Elsevier, vol. 176(C), pages 552-560.
    10. Erick Alves & Santiago Sanchez & Danilo Brandao & Elisabetta Tedeschi, 2019. "Smart Load Management with Energy Storage for Power Quality Enhancement in Wind-Powered Oil and Gas Applications," Energies, MDPI, vol. 12(15), pages 1-15, August.
    11. Mengjun Ming & Rui Wang & Yabing Zha & Tao Zhang, 2017. "Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm," Energies, MDPI, vol. 10(5), pages 1-15, May.
    12. Milo, Aitor & Gaztañaga, Haizea & Etxeberria-Otadui, Ion & Bacha, Seddik & Rodríguez, Pedro, 2011. "Optimal economic exploitation of hydrogen based grid-friendly zero energy buildings," Renewable Energy, Elsevier, vol. 36(1), pages 197-205.
    13. Caballero, F. & Sauma, E. & Yanine, F., 2013. "Business optimal design of a grid-connected hybrid PV (photovoltaic)-wind energy system without energy storage for an Easter Island's block," Energy, Elsevier, vol. 61(C), pages 248-261.
    14. Talent, Orlando & Du, Haiping, 2018. "Optimal sizing and energy scheduling of photovoltaic-battery systems under different tariff structures," Renewable Energy, Elsevier, vol. 129(PA), pages 513-526.
    15. Fabrizio, Enrico & Seguro, Federico & Filippi, Marco, 2014. "Integrated HVAC and DHW production systems for Zero Energy Buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 515-541.
    16. Nithya Saiprasad & Akhtar Kalam & Aladin Zayegh, 2019. "Triple Bottom Line Analysis and Optimum Sizing of Renewable Energy Using Improved Hybrid Optimization Employing the Genetic Algorithm: A Case Study from India," Energies, MDPI, vol. 12(3), pages 1-23, January.
    17. Gupta, Ajai & Saini, R.P. & Sharma, M.P., 2011. "Modelling of hybrid energy system—Part II: Combined dispatch strategies and solution algorithm," Renewable Energy, Elsevier, vol. 36(2), pages 466-473.
    18. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    19. Bozzi, Silvia & Archetti, Renata & Passoni, Giuseppe, 2014. "Wave electricity production in Italian offshore: A preliminary investigation," Renewable Energy, Elsevier, vol. 62(C), pages 407-416.
    20. Posso, F. & Contreras, A. & Veziroglu, A., 2009. "The use of hydrogen in the rural sector in Venezuela: Technical and financial study of the storage phase," Renewable Energy, Elsevier, vol. 34(5), pages 1234-1240.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:105:y:2017:i:c:p:590-600. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.