edisgo.network.overlying_grid
¶
Module Contents¶
Classes¶
Data container for requirements from the overlying grid. |
Functions¶
|
Distributes overlying grid requirements to components in grid. |
- class edisgo.network.overlying_grid.OverlyingGrid(**kwargs)[source]¶
Data container for requirements from the overlying grid.
The requirements from the overlying grid are used as constraints for flexibilities.
- renewables_curtailment¶
Curtailment of fluctuating renewables per time step in MW.
- Type:
- storage_units_active_power¶
Aggregated dispatch of storage units per time step in MW.
- Type:
- storage_units_soc¶
State of charge of storage units per time step in p.u.. The state of charge at time step t here constitutes the state of charge at the beginning of time step t.
- Type:
- dsm_active_power¶
Aggregated demand side management utilisation per time step in MW.
- Type:
- electromobility_active_power¶
Aggregated charging demand at all charging sites in grid per time step in MW.
- Type:
- heat_pump_decentral_active_power¶
Aggregated demand of flexible decentral heat pumps per time step in MW.
- Type:
- thermal_storage_units_decentral_soc¶
State of charge of decentral thermal storage units in p.u..
- Type:
- heat_pump_central_active_power¶
Aggregated demand of flexible central heat pumps per time step in MW.
- Type:
- thermal_storage_units_central_soc¶
State of charge of central thermal storage units per district heating area (in columns as string of integer, i.e. “130” instead of “130.0”) and time step (in index) in p.u.. The state of charge at time step t here constitutes the state of charge at the beginning of time step t.
- Type:
- feedin_district_heating¶
Other thermal feed-in into district heating per district heating area (in columns as string of integer, i.e. “130” instead of “130.0”) and time step (in index) in MW.
- Type:
- reduce_memory(attr_to_reduce=None, to_type='float32')[source]¶
Reduces size of time series data to save memory.
- to_csv(directory, reduce_memory=False, **kwargs)[source]¶
Saves data in object to csv.
- Parameters:
directory (str) – Directory to save data in.
reduce_memory (bool, optional) – If True, size of time series data is reduced using
reduce_memory
. Optional parameters ofreduce_memory
can be passed as kwargs to this function. Default: False.kwargs – Kwargs may contain arguments of
reduce_memory
.
- from_csv(data_path, dtype=None, from_zip_archive=False, **kwargs)[source]¶
Restores data in object from csv files.
- Parameters:
- resample(method: str = 'ffill', freq: str | pandas.Timedelta = '15min')[source]¶
Resamples all time series to a desired resolution.
See
resample_timeseries
for more information.- Parameters:
method (str, optional) – See
resample_timeseries
for more information.freq (str, optional) – See
resample_timeseries
for more information.
- edisgo.network.overlying_grid.distribute_overlying_grid_requirements(edisgo_obj)[source]¶
Distributes overlying grid requirements to components in grid.
Overlying grid requirements for e.g. electromobility charging are distributed to all charging points where cars are parked, and for DSM to all DSM loads based on their available load increase and decrease at each time step.