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@BertoGBG BertoGBG commented Nov 2, 2024

Closes # (if applicable).

Changes proposed in this Pull Request

Checklist

  • Code changes are sufficiently documented; i.e. new functions contain docstrings and further explanations may be given in doc.
  • Data source for new technologies is clearly stated.
  • Newly introduced dependencies are added to environment.yaml (if applicable).
  • A note for the release notes doc/release_notes.rst of the upcoming release is included.
  • I consent to the release of this PR's code under the GPLv3 license.

adjust units in sheets 105. wrong formatting from DEA in investment and energy content
added: 
1) biochar pyrolysis
  - added in the list of technolgies, excel_sheet to read from DEA and parameters.
   - added a new function: "biochar_pyrolysis_harmonise_dea", which retrived data from DEA and applies simple operations to return efficencies and investments on the   desidered basis
   - modified function "order_data" to add the units corresponding to biochar pyrolysis. 

2) electrolysis at small scale (10 MW)
    - no changes to functions, it follows the same approach of standard AEC
added biochar pyrolysis (original DEA data only from 2025) 
and AEC electrolysis at small scale
added biochar pyrolysis (original DEA data only from 2025) 
and AEC electrolysis at small scale
added biochar pyrolysis (original DEA data only from 2025) 
and AEC electrolysis at small scale
@BertoGBG
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BertoGBG commented Nov 2, 2024

This pull request adds pyrolysis for biochar production from the DEA technology catalogue.

@BertoGBG
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BertoGBG commented Nov 2, 2024

this pull request adds pyrolysis for biochar production to the technology-data.

@lisazeyen
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thanks @BertoGBG !

@lisazeyen lisazeyen merged commit bc3af05 into PyPSA:master Nov 3, 2024

# normalizing costs to biochar output
df_divid = pd.concat((df.iloc[df.index.str.contains("Biochar Output")],
df.iloc[df.index.str.contains("Heat Output")]), axis=0).sum(axis=0, skipna=False)
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As far as I understand your code, you change "Heat output" to x % with the df_sum*100 operation in line 892, while Biochar Output is still 0.4. Do you not need to adjust that as well?

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3 participants