flixopt.flow_system

This module contains the FlowSystem class, which is used to collect instances of many other classes by the end User.

Attributes

Classes

FlowSystem

FlowSystem(timesteps: DatetimeIndex, hours_of_last_timestep: Optional[float] = None, hours_of_previous_timesteps: Optional[Union[int, float, ndarray]] = None)

A FlowSystem organizes the high level Elements (Components & Effects).

Parameters:

Name	Type	Description	Default
timesteps	DatetimeIndex	The timesteps of the model.	required
hours_of_last_timestep	Optional[float]	The duration of the last time step. Uses the last time interval if not specified	None
hours_of_previous_timesteps	Optional[Union[int, float, ndarray]]	The duration of previous timesteps. If None, the first time increment of time_series is used. This is needed to calculate previous durations (for example consecutive_on_hours). If you use an array, take care that its long enough to cover all previous values!	None

Functions

from_dict classmethod

from_dict(data: Dict) -> FlowSystem

Load a FlowSystem from a dictionary.

Parameters:

Name	Type	Description	Default
data	Dict	Dictionary containing the FlowSystem data.	required

from_netcdf classmethod

from_netcdf(path: Union[str, Path])

Load a FlowSystem from a netcdf file

add_elements

add_elements(*elements: Element) -> None

Add Components(Storages, Boilers, Heatpumps, ...), Buses or Effects to the FlowSystem

Parameters:

Name	Type	Description	Default
*elements	Element	childs of Element like Boiler, HeatPump, Bus,... modeling Elements	()

to_json

to_json(path: Union[str, Path])

Saves the flow system to a json file. This not meant to be reloaded and recreate the object, but rather used to document or compare the flow_system to others.

Parameters:

Name	Type	Description	Default
path	Union[str, Path]	The path to the json file.	required

as_dict

as_dict(data_mode: Literal['data', 'name', 'stats'] = 'data') -> Dict

Convert the object to a dictionary representation.

as_dataset

as_dataset(constants_in_dataset: bool = False) -> xr.Dataset

Convert the FlowSystem to a xarray Dataset.

Parameters:

Name	Type	Description	Default
constants_in_dataset	bool	If True, constants are included as Dataset variables.	False

to_netcdf

to_netcdf(path: Union[str, Path], compression: int = 0, constants_in_dataset: bool = True)

Saves the FlowSystem to a netCDF file. Args: path: The path to the netCDF file. compression: The compression level to use when saving the file. constants_in_dataset: If True, constants are included as Dataset variables.

plot_network

plot_network(path: Union[bool, str, Path] = 'flow_system.html', controls: Union[bool, List[Literal['nodes', 'edges', 'layout', 'interaction', 'manipulation', 'physics', 'selection', 'renderer']]] = True, show: bool = False) -> Optional[pyvis.network.Network]

Visualizes the network structure of a FlowSystem using PyVis, saving it as an interactive HTML file.

Parameters:

Name	Type	Description	Default
path	Union[bool, str, Path]	Path to save the HTML visualization. - False: Visualization is created but not saved. - str or Path: Specifies file path (default: 'flow_system.html').	'flow_system.html'
controls	Union[bool, List[Literal['nodes', 'edges', 'layout', 'interaction', 'manipulation', 'physics', 'selection', 'renderer']]]	UI controls to add to the visualization. - True: Enables all available controls. - List: Specify controls, e.g., ['nodes', 'layout']. - Options: 'nodes', 'edges', 'layout', 'interaction', 'manipulation', 'physics', 'selection', 'renderer'.	True
show	bool	Whether to open the visualization in the web browser.	False

Returns: - Optional[pyvis.network.Network]: The Network instance representing the visualization, or None if pyvis is not installed.

Examples:

>>> flow_system.plot_network()
>>> flow_system.plot_network(show=False)
>>> flow_system.plot_network(path='output/custom_network.html', controls=['nodes', 'layout'])

Notes: - This function requires pyvis. If not installed, the function prints a warning and returns None. - Nodes are styled based on type (e.g., circles for buses, boxes for components) and annotated with node information.

create_time_series

create_time_series(name: str, data: Optional[Union[NumericData, TimeSeriesData, TimeSeries]], needs_extra_timestep: bool = False) -> Optional[TimeSeries]

Tries to create a TimeSeries from NumericData Data and adds it to the time_series_collection If the data already is a TimeSeries, nothing happens and the TimeSeries gets reset and returned If the data is a TimeSeriesData, it is converted to a TimeSeries, and the aggregation weights are applied. If the data is None, nothing happens.

create_effect_time_series

create_effect_time_series(label_prefix: Optional[str], effect_values: EffectValuesUser, label_suffix: Optional[str] = None) -> Optional[EffectTimeSeries]

Transform EffectValues to EffectTimeSeries. Creates a TimeSeries for each key in the nested_values dictionary, using the value as the data.

The resulting label of the TimeSeries is the label of the parent_element, followed by the label of the Effect in the nested_values and the label_suffix. If the key in the EffectValues is None, the alias 'Standard_Effect' is used

Functions