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A steady-state electrical model of a microbial fuel cell through multiple-cycle polarization curves

Author

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  • Serra, P.M.D.
  • Espírito-Santo, A.
  • Magrinho, M.

Abstract

The use of Microbial Fuel Cells as power sources in rural or remote locations can solve issues related with power availability and wastewater cleaning. Furthermore, the application of such technology in wireless smart sensors applied to wastewater treatment plants can also help in water quality monitoring, increasing the process autonomy and reliability. A trustworthy power source needs to have a predictable and repeatable behavior, which cannot be achieved without adequate models and supporting hardware for energy regulation and storage. The work herein described proposes a steady-state model, represented by an electric circuit made of passive components. This model was first applied to a specific 28 mL air-cathode Microbial Fuel Cells working with artificial wastewater and using graphite brush anodes. Afterwards, the model was further validated by applying it to a larger reactor and to other bibliographic records. The goal of the study is to propose a method for finding a Microbial Fuel Cell model to be used with maximum power point tracking research, guaranteeing the best-case scenario for Microbial Fuel Cell operation as a power source. The reactors used in this study were analyzed by relating time and voltage development, both in colonization and in polarization studies. A mathematical relationship model was developed and proposed allowing to separate MFC's behavior, concerning energy production, in to meaningful components. From the experimental data the method was used to obtain a two-component circuit model that describes the power behavior of this specific Microbial Fuel Cell topology. The same method can be used to described other MFC.

Suggested Citation

  • Serra, P.M.D. & Espírito-Santo, A. & Magrinho, M., 2020. "A steady-state electrical model of a microbial fuel cell through multiple-cycle polarization curves," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    • Handle: RePEc:eee:rensus:v:117:y:2020:i:c:s1364032119306471
    DOI: 10.1016/j.rser.2019.109439
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    Citations

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    Cited by:

    1. En-Jui Liu & Yi-Hsuan Hung & Che-Wun Hong, 2021. "Improved Metaheuristic Optimization Algorithm Applied to Hydrogen Fuel Cell and Photovoltaic Cell Parameter Extraction," Energies, MDPI, vol. 14(3), pages 1-16, January.
    2. Narayanamoorthy, Samayan & Ramya, L. & Kalaiselvan, Samayan & Kureethara, Joseph Varghese & Kang, Daekook, 2021. "Use of DEMATEL and COPRAS method to select best alternative fuel for control of impact of greenhouse gas emissions," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    3. Van Limbergen, T. & Bonné, R. & Hustings, J. & Valcke, R. & Thijs, S. & Vangronsveld, J. & Manca, J.V., 2022. "Plant microbial fuel cells from the perspective of photovoltaics: Efficiency, power, and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    4. Theofilos Kamperidis & Asimina Tremouli & Antonis Peppas & Gerasimos Lyberatos, 2022. "A 2D Modelling Approach for Predicting the Response of a Two-Chamber Microbial Fuel Cell to Substrate Concentration and Electrolyte Conductivity Changes," Energies, MDPI, vol. 15(4), pages 1-15, February.
    5. Song, Ke & Wang, Yimin & Ding, Yuhang & Xu, Hongjie & Mueller-Welt, Philip & Stuermlinger, Tobias & Bause, Katharina & Ehrmann, Christopher & Weinmann, Hannes W. & Schaefer, Jens & Fleischer, Juergen , 2022. "Assembly techniques for proton exchange membrane fuel cell stack: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).

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