Table · dataset · 2025
Predicting Electrolyzer Performance under Forced Periodic Operation using Nonlinear Frequency Response Method
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Industrial-scale electrolyzers are supplied by power converters with a mixture of DC current and superimposed current ripple.
Description
Therefore, electrolyzers are inevitably operated in a forced periodic regime. On the other hand, pulsed electrolysis, as a type of forced periodic operation, emerged as an attractive process intensification strategy.
While the negative impact of the current ripple on the electrolyzer performance was reported, the positive impact of pulsed electrolysis was claimed. However, since both regimes are types of forced periodic operation, a similar effect is expected. To clarify this, we suggest the nonlinear frequency response (NFR) method for evaluation of the performance of a proton exchange membrane water electrolyzer (PEMWE) in forced periodic operation.
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The NFR method demonstrates a voltage decrease and power consumption increase during forced periodic operation of PEMWE in comparison to the steady-state operation, agreeing remarkably well with experiments and numerical simulations. Furthermore, the NFR method reveals that the voltage decrease is a consequence of the system's nonlinear kinetics, and the power requirements are influenced by both linear and nonlinear phenomena.
Linear contributions tend to increase power requirements, while nonlinear contributions decrease them. However, regardless of the operating conditions, linear contributions prevail, leading to increased power consumption during forced periodic operation. At the usual operating current densities, ohmic contributions dominate the PEMWE power increase.
Overall, the NFR method proves advantageous for analyzing forced periodic operations, providing an analytical tool to calculate the electrolyzer's losses during such conditions and guide system design, especially of the supplying power converter.
Links
Where it is published
- Dataverse dataset page edmond.mpg.de/dataset.xhtml?persistentId=doi%3A10.17617%2F3.FEEHJO ↗
landing page · from edmond mpdl mpg de
- DOI doi.org/10.17617/3.feehjo ↗
DOI / persistent id · from edmond mpdl mpg de
Catalogue records · 1
- Dataverse API edmond.mpg.de/api/datasets/:persistentId/?persistentId=doi%3A10.17617%2F3.FE… ↗
metadata API · from edmond mpdl mpg de
Topics
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- Astronomy & Astrophysics · Chemistry · Chemistry · Computer Science & AI · Earth & Environmental Science · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Materials Science · Medicine & Health · Ocean & Atmospheric Science · Physics · Social Science
- Inferred from text
- Chemical engineering 70%
Provenance · 2 source records, 24 field assertions
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|---|---|---|---|
| Edmond | doi:10.17617/3.FEEHJO | 10 d ago | JSON v1 |
| Edmond | doi:10.17617/3.FEEHJO | 8 d ago | JSON v1 |
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