IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v119y2018icp641-648.html
   My bibliography  Save this article

Extracting optimal parameters of PEM fuel cells using Salp Swarm Optimizer

Author

Listed:
  • El-Fergany, Attia A.

Abstract

In the last years, significant attentions have been paid in the state-of-the-literature to have precise current/voltage (I/V) polarization curves of polymer exchange membrane fuel cells (PEMFCs). This article presents a novel application of a very recent heuristic-based on technique, namely Salp Swarm Optimizer (SSO) to define the best values of unknown parameters of PEMFC model. The total of square deviations (TSD) between the actual and calculated results represents the objective function. The TSD is minimized by the proposed SSO-based methodology to insignificant values to ensure the concurrence and consistency between measured and estimated voltage points and subjects to set of constraints. Two test case studies of typical commercial stacked PEMFCs, namely NedStack PS6 and BCS 500-W PEM generator are performed to demonstrate the potential of the proposed procedure under various operating scenarios. Moreover, necessary comparisons to other optimizers under same data and conditions are in order. In addition to this, performance measures are made to evaluate the performance of the SSO. The simulations along with comparisons indicate that the proposed SSO-based on method is successfully used to characterize the PEMFC model precisely.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:119:y:2018:i:c:p:641-648
    DOI: 10.1016/j.renene.2017.12.051
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148117312557
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2017.12.051?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. Ali, M. & El-Hameed, M.A. & Farahat, M.A., 2017. "Effective parameters’ identification for polymer electrolyte membrane fuel cell models using grey wolf optimizer," Renewable Energy, Elsevier, vol. 111(C), pages 455-462.
    2. Luo, Xing & Wang, Jihong & Dooner, Mark & Clarke, Jonathan, 2015. "Overview of current development in electrical energy storage technologies and the application potential in power system operation," Applied Energy, Elsevier, vol. 137(C), pages 511-536.
    3. Yang, Shipin & Chellali, Ryad & Lu, Xiaohua & Li, Lijuan & Bo, Cuimei, 2016. "Modeling and optimization for proton exchange membrane fuel cell stack using aging and challenging P systems based optimization algorithm," Energy, Elsevier, vol. 109(C), pages 569-577.
    4. Tafaoli-Masoule, M. & Bahrami, A. & Elsayed, E.M., 2014. "Optimum design parameters and operating condition for maximum power of a direct methanol fuel cell using analytical model and genetic algorithm," Energy, Elsevier, vol. 70(C), pages 643-652.
    5. Abdollahzadeh, M. & Pascoa, J.C. & Ranjbar, A.A. & Esmaili, Q., 2014. "Analysis of PEM (Polymer Electrolyte Membrane) fuel cell cathode two-dimensional modeling," Energy, Elsevier, vol. 68(C), pages 478-494.
    Full references (including those not matched with items on IDEAS)

    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. Xu, Shuhui & Wang, Yong & Wang, Zhi, 2019. "Parameter estimation of proton exchange membrane fuel cells using eagle strategy based on JAYA algorithm and Nelder-Mead simplex method," Energy, Elsevier, vol. 173(C), pages 457-467.
    2. Priya, K. & Sathishkumar, K. & Rajasekar, N., 2018. "A comprehensive review on parameter estimation techniques for Proton Exchange Membrane fuel cell modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 121-144.
    3. Kandidayeni, M. & Macias, A. & Khalatbarisoltani, A. & Boulon, L. & Kelouwani, S., 2019. "Benchmark of proton exchange membrane fuel cell parameters extraction with metaheuristic optimization algorithms," Energy, Elsevier, vol. 183(C), pages 912-925.
    4. El-Hay, E.A. & El-Hameed, M.A. & El-Fergany, A.A., 2019. "Optimized Parameters of SOFC for steady state and transient simulations using interior search algorithm," Energy, Elsevier, vol. 166(C), pages 451-461.
    5. 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.
    6. Ángel Encalada-Dávila & Samir Echeverría & Jordy Santana-Villamar & Gabriel Cedeño & Mayken Espinoza-Andaluz, 2021. "Optimization Algorithms: Optimal Parameters Computation for Modeling the Polarization Curves of a PEFC Considering the Effect of the Relative Humidity," Energies, MDPI, vol. 14(18), pages 1-21, September.
    7. Miguel J. Prieto & Juan Á. Martínez & Rogelio Peón & Lourdes Á. Barcia & Fernando Nuño, 2017. "On the Convenience of Using Simulation Models to Optimize the Control Strategy of Molten-Salt Heat Storage Systems in Solar Thermal Power Plants," Energies, MDPI, vol. 10(7), pages 1-17, July.
    8. Abdin, Z. & Webb, C.J. & Gray, E.MacA., 2016. "PEM fuel cell model and simulation in Matlab–Simulink based on physical parameters," Energy, Elsevier, vol. 116(P1), pages 1131-1144.
    9. Majumder, Suman & De, Krishnarti & Kumar, Praveen & Sengupta, Bodhisattva & Biswas, Pabitra Kumar, 2021. "Techno-commercial analysis of sustainable E-bus-based public transit systems: An Indian case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    10. Ziad Ragab & Ehsan Pashajavid & Sumedha Rajakaruna, 2024. "Optimal Sizing and Economic Analysis of Community Battery Systems Considering Sensitivity and Uncertainty Factors," Energies, MDPI, vol. 17(18), pages 1-20, September.
    11. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    12. Dib, Ghady & Haberschill, Philippe & Rullière, Romuald & Revellin, Rémi, 2021. "Modelling small-scale trigenerative advanced adiabatic compressed air energy storage for building application," Energy, Elsevier, vol. 237(C).
    13. Guo, Cong & Xu, Yujie & Zhang, Xinjing & Guo, Huan & Zhou, Xuezhi & Liu, Chang & Qin, Wei & Li, Wen & Dou, Binlin & Chen, Haisheng, 2017. "Performance analysis of compressed air energy storage systems considering dynamic characteristics of compressed air storage," Energy, Elsevier, vol. 135(C), pages 876-888.
    14. Salva, J. Antonio & Iranzo, Alfredo & Rosa, Felipe & Tapia, Elvira, 2016. "Validation of cell voltage and water content in a PEM (polymer electrolyte membrane) fuel cell model using neutron imaging for different operating conditions," Energy, Elsevier, vol. 101(C), pages 100-112.
    15. Alexandru Ciocan & Cosmin Ungureanu & Alin Chitu & Elena Carcadea & George Darie, 2020. "Electrical Longboard for Everyday Urban Commuting," Sustainability, MDPI, vol. 12(19), pages 1-14, September.
    16. Ameen, Muhammad Tahir & Ma, Zhiwei & Smallbone, Andrew & Norman, Rose & Roskilly, Anthony Paul, 2023. "Demonstration system of pumped heat energy storage (PHES) and its round-trip efficiency," Applied Energy, Elsevier, vol. 333(C).
    17. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    18. Jonathan Fahlbeck & Håkan Nilsson & Saeed Salehi, 2021. "Flow Characteristics of Preliminary Shutdown and Startup Sequences for a Model Counter-Rotating Pump-Turbine," Energies, MDPI, vol. 14(12), pages 1-17, June.
    19. Abdollahzadeh, M. & Ribeirinha, P. & Boaventura, M. & Mendes, A., 2018. "Three-dimensional modeling of PEMFC with contaminated anode fuel," Energy, Elsevier, vol. 152(C), pages 939-959.
    20. Sandro Sitompul & Goro Fujita, 2021. "Impact of Advanced Load-Frequency Control on Optimal Size of Battery Energy Storage in Islanded Microgrid System," Energies, MDPI, vol. 14(8), pages 1-18, April.

    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:119:y:2018:i:c:p:641-648. 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.