2025 EcoDynElec Update

This section describes the main updates and changes made to the datasets and scripts of the EcoDynElec project in 2025.

SwissGrid

Data type: Quarter-hourly data covering net and raw electricity consumption in Switzerland, national generation, and cross-border exchanges with several European countries.

Downloading: Manual download from SwissGrid. Download the .xlsx or .xls files for all available years (e.g., 2016 → 20XX).

Update: The data update is performed by executing the update_all function located in ecodynelec/update.py.

Important: you must specify the path to the folder containing all yearly files (every downloaded year). The module will not work properly if one or more yearly files are missing.

Expected folder structure:

EcoDynElec/
├── ...
├── support_files/
│   └── swissgrid_data/
│       ├── EnergieUebersichtCH-2016.xlsx
│       ├── EnergieUebersichtCH-2017.xlsx
│       ├── ...
│       └── EnergieUebersichtCH-2024.xlsx

OFEN (SFOE)

Data type: Monthly data on national electricity production (hydropower, nuclear, thermal, renewable, etc.). Since 2024, wind and solar photovoltaic production (for years 2020–2024) have been added.

Downloading: Available on SFOE – Swiss Electricity Statistics. Make sure to save the files following the structure below:

EcoDynElec/
├── ...
├── support_files/
│   └── ofen_data/
│       ├── 2022.pdf
│       ├── 2023.pdf
│       ├── 2024.pdf
│       └── ...

Update: The sfoe_extracting.py module automates the update of SFOE PDF files for SFOE_data.csv. Currently, only the 2022 and 2024 reports are processed by the function. If 2025 data become available, the SFOE_extracting function must be adapted accordingly. It is also essential to download all PDF files from 2022 onward to ensure the proper functioning of the application. The SFOE data are also used by the auxiliary.py module to determine the Swiss residual share. The read_ofen_pdf_file function has been optimized and updated for the 2023 and 2024 reports. Make sure to extend or adapt it accordingly for future years.

ENTSO-E

Data type: Quarter-hourly data: - AggregatedGenerationPerType - PhysicalFlows

Downloading: Data are retrieved via FileZilla, following the procedure described in Downloading ENTSO-E data

Warning

The variables Energy_storage_IT and Other_renewable_IT have been newly added to the ENTSO-E datasets. Previously, these categories were ignored, and their corresponding impact values in Unit_Impact_Vector.csv were set to 0. It is now necessary to update the associated impact values according to the model’s requirements.

Energy Charts

Data type: Daily data (in GWh) for Swiss electricity production — including hydropower, biogas, biomass, waste incineration, wind, photovoltaic, and other sources.

Downloading: Available on Energy Charts Make sure to save the files following the structure below:

EcoDynElec/
├── ...
├── support_files/
│   └── ec_data/
│       ├── energy-charts_Production_nette_d'électricité_en_Suisse_2020.csv
│       ├── energy-charts_Production_nette_d'électricité_en_Suisse_2021.csv
│       ├── energy-charts_Production_nette_d'électricité_en_Suisse_2023.csv
│       └── ...

Pronovo

Data type: Quarter-hourly production data by technology (PV, wind, biomass, hydropower). Since 2023, data are provided on a quarterly basis, with a distinction between A+ (auxiliary consumption) and A- (actual production). In EcoDynElec, only the values labeled with A− are used.

Downloading: Available on Pronovo Make sure to save the files following the structure below:

EcoDynElec/
├── prod_2020
├── prod_2021/
│       ├── Profils_courbe_de_charge_01.2020.csv
│       ├── Profils_courbe_de_charge_02.2020.csv
│       └── ...
├── prod_2023
│       ├── 202303_CH_Total_Quartal_def.csv
│       ├── 202306_CH_Total_Quartal_def.csv
│       └── ...
├── ...

Residual model update procedure

To update the Residual_model.xlsx file:

  1. Run the extract_ofen_typical_days_for_residual function separately. This function internally calls the updated read_ofen_pdf_file. It will generate a dictionary output for the selected year, which must be converted into a DataFrame and saved as a .csv file.

  2. Open the generated CSV file and copy its content next to the existing data in Residual_model.xlsx located in support_files/.

  3. Repeat the same procedure for ENTSO-E data using the extract_entsoe_daily_generation_for_residuals function. Copy and paste the new data in the same way.

  4. Ensure that all relevant Excel formulas have been extended to cover the new data range — particularly those related to: - the ENTSO-E mapping, - comparison: percentage difference, and - comparison: absolute difference. These calculations are used when generating the Share_residual.csv file.

  5. Once everything has been verified, run the update_all function. It will automatically export the updated data from Residual_model.xlsx into Share_residual.csv.

Timezone alignment and end-of-year gap

The Swissgrid, Pronovo, and Energy Charts datasets are originally provided in GMT+1 (local time, without explicit timezone information). To ensure consistency and interoperability across all sources, these time series are systematically converted to UTC.

However, this alignment introduces a one-hour forward shift in the timestamps. Unless the data extends slightly beyond December 31st (e.g., into January 1st of the following year), this shift creates a missing hour at the very end of the last year (from 31/12 23:45 to 01/01 00:45 in UTC).

This gap does not impact the functioning of the application. Nevertheless, starting from the 2025 update, a few additional data points from early 2025 have been downloaded and integrated into the processing pipeline for Swissgrid, Pronovo, and Energy Charts, ensuring complete yearly coverage.