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Integration of a Multi-Stack Fuel Cell System in Microgrids: A Solution Based on Model Predictive Control

Author

Listed:
  • Antonio José Calderón

    (Department of Electrical, Electronics Engineering and Automatic, Campus Universitario, University of Extremadura, Av. de Elvas, s/n, 06006 Badajoz, Spain)

  • Francisco José Vivas

    (CITES (Centro de Investigación en Tecnología, Energía y Sostenibilidad), Campus El Carmen, University of Huelva, 21071 Huelva, Spain)

  • Francisca Segura

    (CITES (Centro de Investigación en Tecnología, Energía y Sostenibilidad), Campus El Carmen, University of Huelva, 21071 Huelva, Spain)

  • José Manuel Andújar

    (CITES (Centro de Investigación en Tecnología, Energía y Sostenibilidad), Campus El Carmen, University of Huelva, 21071 Huelva, Spain)

Abstract

This paper proposes a multi-objective model predictive control (MPC) designed for the power management of a multi-stack fuel cell (FC) system integrated into a renewable sources-based microgrid. The main advantage of MPC is the fact that it allows the current timeslot to be optimized while taking future timeslots into account. The multi-objective function solves the problem related to the power dispatch at time that includes criteria to reduce the multi-stack FC degradation, operating and maintenance costs, as well as hydrogen consumption. Regarding the scientific literature, the novelty of this paper lies in the proposal of a generalized MPC controller for a multi-stack FC that can be used independently of the number of stacks that make it up. Although all the stacks that make up the modular FC system are identical, their levels of degradation, in general, will not be. Thus, over time, each stack can present a different behavior. Therefore, the power control strategy cannot be based on an equal distribution according to the nominal power of each stack. On the contrary, the control algorithm should take advantage of the characteristics of the multi-stack FC concept, distributing operation across all the stacks regarding their capacity to produce power/energy, and optimizing the overall performance.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4924-:d:416081
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    References listed on IDEAS

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    1. Petrollese, Mario & Valverde, Luis & Cocco, Daniele & Cau, Giorgio & Guerra, José, 2016. "Real-time integration of optimal generation scheduling with MPC for the energy management of a renewable hydrogen-based microgrid," Applied Energy, Elsevier, vol. 166(C), pages 96-106.
    2. Yoldaş, Yeliz & Önen, Ahmet & Muyeen, S.M. & Vasilakos, Athanasios V. & Alan, İrfan, 2017. "Enhancing smart grid with microgrids: Challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 205-214.
    3. De las Heras, A. & Vivas, F.J. & Segura, F. & Andújar, J.M., 2018. "From the cell to the stack. A chronological walk through the techniques to manufacture the PEFCs core," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 29-45.
    4. Helm, Dieter, 2014. "The European framework for energy and climate policies," Energy Policy, Elsevier, vol. 64(C), pages 29-35.
    5. 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.
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    Cited by:

    1. José-Luis Casteleiro-Roca & Francisco José Vivas & Francisca Segura & Antonio Javier Barragán & Jose Luis Calvo-Rolle & José Manuel Andújar, 2020. "Hybrid Intelligent Modelling in Renewable Energy Sources-Based Microgrid. A Variable Estimation of the Hydrogen Subsystem Oriented to the Energy Management Strategy," Sustainability, MDPI, vol. 12(24), pages 1-18, December.
    2. Mustafa Gokdag, 2022. "Modulated Predictive Control to Improve the Steady-State Performance of NSI-Based Electrification Systems," Energies, MDPI, vol. 15(6), pages 1-19, March.
    3. Segura, F. & Vivas, F.J. & Andújar, J.M. & Martínez, M., 2023. "Hydrogen-powered refrigeration system for environmentally friendly transport and delivery in the food supply chain," Applied Energy, Elsevier, vol. 338(C).

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