Issue |
E3S Web Conf.
Volume 334, 2022
EFC21 - European Fuel Cells and Hydrogen Piero Lunghi Conference
|
|
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Article Number | 08011 | |
Number of page(s) | 8 | |
Section | Microbial & Enzymatic Biolectrochemical Systems | |
DOI | https://doi.org/10.1051/e3sconf/202233408011 | |
Published online | 10 January 2022 |
Performance assessment of stacked air-cathode microbial fuel cells under series and parallel electrical connections
1 Univerisity of Naples “Parthenope”, Naples, Italy
2 Department of Industrial Engineering, University of Salerno, Salerno, Italy
* Corresponding author: simona.dimicco@studenti.uniparthenope.it
Microbial fuel cells (MFCs) are playing an important role in the context of sustainable energy development. They represent a sustainable approach to harvest electricity from biodegradable materials. However, harvesting energy from MFCs represents a critical issue because of the low output voltage and power produced. Realizing stacked configurations may involve an increase in MFCs performances in terms of output voltage, current and electric power.
In this paper, two stacked configurations under different electrical connection modes have been designed, developed, modeled and tested. The stacked MFCs consist of 4 reactors (28 mL x4) that are connected in series, and parallel-series modes. Three different tests have been carried out, which involves: 1) performing the polarization and power curves by applying decreasing resistances; 2) assessment of the electric behavior of each reactor over time at a fixed resistance, 3) performing the polarization and power curves by applying increasing resistances. Moreover, a numerical model for predicting the transient behavior of the electrical quantities for one reactor, has been developed and validated by using the experimental data. As expected, the results highlighted that the parallel-series configuration assures the highest volumetric power density compared to the series configuration, reaching the maximum value of 1248.5 mW/m3 (139.8 µW) at 0.291 mA. Eventually, by comparing the numerical and the experimental data, it has been demonstrated that the developed model is able to predict the reactor’s electrical trend with a good accuracy.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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