Import and Export

Import and Export#

PyPSA can handle several different data formats, such as CSV, netCDF and HDF5 files. It is also possible to build a pypsa.Network within a Python script. There is limited functionality to import from Pypower and Pandapower.

Adding components#

Networks can also be built step-by-step for each component by calling pypsa.Network.add() to add a single or multiple components.

To add multiple components whose static attributes are given in a pandas DataFrame, use pypsa.Network.import_components_from_dataframe()

To import time-varying information use pypsa.Network.import_series_from_dataframe()

Removing components#

Components can be removed with pypsa.Network.remove().

Multiple components can be removed by calling pypsa.Network.mremove().

CSV import and export#

Create a folder with CSVs for each component type (e.g. generators.csv, storage_units.csv), then a CSV for each time-dependent variable (e.g. generators-p_max_pu.csv, loads-p_set.csv). Then run pypsa.Network.import_from_csv_folder() to import the network.

Note

It is not necessary to add every single column, only those where values differ from the defaults listed in Components. All empty values/columns are filled with the defaults.

A loaded network can be exported as a folder of csv files with pypsa.Network.export_to_csv_folder().

netCDF import and export#

netCDF files take up less space than CSV files and are faster to load.

netCDF is also preferred over HDF5 because netCDF is structured more cleanly, is easier to use from other programming languages, can limit float precision to save space and supports lazy loading.

To export network and components to a netCDF file run pypsa.Network.export_to_netcdf().

To import network data from netCDF file run pypsa.Network.import_from_netcdf().

HDF5 import and export#

To export the network to an HDF store, run pypsa.Network.export_to_hdf5().

To import network data from an HDF5 store, run pypsa.Network.import_from_hdf5().

Pypower import#

To import a network from Pypower’s ppc dictionary/numpy.array format version 2, run the function pypsa.Network.import_from_pypower_ppc().

Pandapower import#

Warning

Not all pandapower data is supported.

To import a network from pandapower, run the function pypsa.Network.import_from_pandapower_net().

Cloud object storage import and export#

CSV, netCDF and HDF5 files in cloud object storage can be imported and exported by installing the cloudpathlib package. This is available through the [cloudpath] optional dependency, installable via pip install 'pypsa[cloudpath]'.

cloudpathlib supports AWS S3 (s3://), Google Cloud Storage (gs://) and Azure Blob Storage (az://) as cloud object storage providers.

from pypsa import Network
n = Network('examples/ac-dc-meshed/ac-dc-data')
n.export_to_csv_folder('s3://my-s3-bucket/ac-dc-data')
n = Network('s3://my-s3-bucket/ac-dc-data')
n.export_to_netcdf('gs://my-gs-bucket/ac-dc-data.nc')
n = Network('gs://my-gs-bucket/ac-dc-data.nc')
n.export_to_hdf5('az://my-az-bucket/ac-dc-data.h5')
n = Network('az://my-az-bucket/ac-dc-data.h5')
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