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Part 1: Document Description
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Citation |
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Title: |
Data from dynamic wind profile long-term operation of alkaline and PEM water electrolysis with extraction of performance data in Python |
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Identification Number: |
doi:10.26165/JUELICH-DATA/PYGQTO |
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Distributor: |
Jülich DATA |
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Date of Distribution: |
2025-04-14 |
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Version: |
2 |
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Bibliographic Citation: |
Zerressen, Sarah, 2025, "Data from dynamic wind profile long-term operation of alkaline and PEM water electrolysis with extraction of performance data in Python", https://doi.org/10.26165/JUELICH-DATA/PYGQTO, Jülich DATA, V2 |
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Citation |
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Title: |
Data from dynamic wind profile long-term operation of alkaline and PEM water electrolysis with extraction of performance data in Python |
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Identification Number: |
doi:10.26165/JUELICH-DATA/PYGQTO |
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Authoring Entity: |
Zerressen, Sarah (IET-4) |
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Distributor: |
Jülich DATA |
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Access Authority: |
Zerressen, Sarah |
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Depositor: |
Zerressen, Sarah |
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Date of Deposit: |
2024-12-10 |
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Study Scope |
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Keywords: |
Chemistry, Engineering |
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Abstract: |
We created a semi-synthetic wind profile from wind turbine data and converted it to current and potential profiles for PEM and alkaline water electrolysis cells with a maximum power output of 40 and 4 W respectively. Then we conducted dynamic electrolysis with these profiles for up to 961 h with PEMWE and AWE single cells. The data obtained from the dynamic operation are included in the dataset. We applied two analysis methods to our datasets in Python to extract performance data from the electrolysis cells like I-V-curves, current density dependent cell voltage changes and resistances. The Python code is also part of the dataset. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Identification Number: |
10.1016/j.ijhydene.2025.03.387 |
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Bibliographic Citation: |
Pape, S.-V.; Zerressen, S.; Seidler, M. F.; Keller, R.; Lohmann-Richters, F.; Müller, M.; Apfel, U.-P.; Mechler, A. K.; Glüsen, A., Performance data extraction from dynamic long-term operation of proton exchange membrane and alkaline water electrolysis cells. Int. J. Hydrogen Energy 2025, 127, 51-63. |
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AWE_dyn_wind_interruption.csv |
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Notes: |
text/csv |
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AWE_dyn_wind_no_interruption.csv |
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text/csv |
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AWE_recorded_curves.csv |
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text/csv |
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documentation.zip |
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application/zip |
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DynEx.cpython-312.pyc |
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application/octet-stream |
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DynEx.py |
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text/x-python |
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PEM_dyn_wind_data.csv |
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Notes: |
text/csv |
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PEM_recorded_data.csv |
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Notes: |
text/csv |
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readme.txt |
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Notes: |
text/plain |
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simple_example.py |
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Notes: |
text/x-python |
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Turbine_Power_SemiSynthetic.csv |
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Notes: |
text/csv |