auxiliary
Module containing a collection of functions to load side-datasets that may be required during the execution of ecodynelec proceses.
- ecodynelec.preprocessing.auxiliary.clear_ambiguous_dates(sg)[source]
Function to clear ambiguous dates in SwissGrid raw data
- ecodynelec.preprocessing.auxiliary.get_default_file(name, level=0, max_level=3)[source]
Function to return the absolute path of default files. The function uses the location of the current auxiliary.py file but assumes no structure in EcoDynElec. It only searches the structure upward
- ecodynelec.preprocessing.auxiliary.load_ch_enr_model(ch_enr_model_path, start, end, freq)[source]
Load the CH energy production data from the given path and returns a dataframe with the same format as the processed ENTSO-E production and exchange data.
- Parameters:
ch_enr_model_path (str) – Path to the CH energy production data, generated with EcoDynElec-EnrModel
start (str) – Start date of the data to load
end (str) – End date of the data to load
freq (str) – Frequency of the data to return (from H to Y)
- Returns:
A dataframe with the same format as the processed ENTSO-E production and exchange data, containing the CH energy production data for the given period
- Return type:
pd.DataFrame
- ecodynelec.preprocessing.auxiliary.load_gap_content(path_gap, start=None, end=None, freq='H', enr_prod_residual_ch=None)[source]
Function that defines the relative composition of the swiss residual production. The function is very file format specific. If enr_prod_residual_ch is not None, it will be subtracted from the “other” residual production before computing the relative composition of each category.
- Parameters:
path_gap (str) – Path to the file containing residual content information. The file must contain absolute values for each category, for each time step (if not, use updating.update_residual_share to update the file).
start (default to None) – starting date, as datetime or str
end (default to None) – ending date, as datetime or str
freq (str, default to “H”) – frequency to resample the data to
enr_prod_residual_ch (default to None) – Delta between the renewable electricity production of EcoDynElec-EnrModel and the production given by the ENTSO-E data. If not None, the total will be subtracted from the “other” residual category.
- Returns:
table with relative residual production composition for each time step.
- Return type:
pandas.DataFrame
- ecodynelec.preprocessing.auxiliary.load_grid_losses(network_loss_path, start=None, end=None)[source]
Function that loads network grid losses and returns a pandas DataFrame with the fraction of network loss in the transmitted electricity for each month.
- ecodynelec.preprocessing.auxiliary.load_rawEntso(mix_data, freq='H')[source]
Function that can load an existing production and exchange matrix in a CSV file
- ecodynelec.preprocessing.auxiliary.load_swissGrid(path_sg, start=None, end=None, freq='H')[source]
Function to load production and cross-border flows information from Swiss Grid. Data used many times along the algorithm.
- Parameters:
path_sg (str) – path to the file with Swiss Grid information
start (str, default None) – starting date, as datetime or str
end (str, default None) – ending date, as datetime or str
freq (str, default to ‘H’) – frequency to resample the SwissGrid data to
- Returns:
table of SwissGrid information in MWh
- Return type:
pandas.DataFrame
- ecodynelec.preprocessing.auxiliary.load_useful_countries(path_neighbour, ctry)[source]
Function to load a list of countries directly or indirectly involved in the computation. Countries directly involved are passed as arguments. Countries indirectly involved are their neighbours. These indirectly involved countries help building the import from ‘other’ countries.
- ecodynelec.preprocessing.auxiliary.post_process_2017(columns)[source]
Helper to fix the 2017 data read from the OFEN pdf file
- ecodynelec.preprocessing.auxiliary.post_process_2022(columns)[source]
Helper to fix the 2022 data read from the OFEN pdf file
- ecodynelec.preprocessing.auxiliary.post_process_2023(columns)[source]
Helper to fix the 2023 data read from the OFEN pdf file
- ecodynelec.preprocessing.auxiliary.post_process_2024(columns)[source]
Helper to fix the 2024 data read from the OFEN pdf file
- ecodynelec.preprocessing.auxiliary.read_ofen_pdf_file(file, post_process_fun, page=31)[source]
Reads an ofen pdf file and extracts a dictionary of typical days with their electricity mix. Supports years from 2017 to 2024. Not tested after. A post-processing function should be provided to fix the data read from the pdf file. This function depends on the year of the data because the format of the pdf file changes between years. Four post-processing functions are provided above for 2017, 2022, 2023 and 2024.
- Parameters:
file (str) – Path to the pdf file to read
post_process_fun (function) – Function to apply to the data read from the pdf file Takes a list of columns as input and returns the modified list of columns
page (int) – Page of the pdf file to read (default: 31)