flixOpt.features
This module contains the features of the flixOpt framework. Features extend the functionality of Elements.
Classes
InvestmentModel
InvestmentModel(element: Union[Flow, Storage], invest_parameters: InvestParameters, defining_variable: [VariableTS], relative_bounds_of_defining_variable: Tuple[Numeric, Numeric], fixed_relative_profile: Optional[Numeric] = None, label: str = 'Investment', on_variable: Optional[VariableTS] = None)
Bases: ElementModel
Class for modeling an investment
If fixed relative profile is used, the relative bounds are ignored
Functions
OnOffModel
OnOffModel(element: Element, on_off_parameters: OnOffParameters, defining_variables: List[VariableTS], defining_bounds: List[Tuple[Numeric, Numeric]], label: str = 'OnOff')
Bases: ElementModel
Class for modeling the on and off state of a variable If defining_bounds are given, creates sufficient lower bounds
defining_bounds: a list of Numeric, that can be used to create the bound for On/Off more efficiently
Functions
get_consecutive_duration
classmethod
get_consecutive_duration(binary_values: Union[int, ndarray], dt_in_hours: Union[int, float, ndarray]) -> Skalar
Returns the current consecutive duration in hours, computed from binary values. If only one binary value is availlable, the last dt_in_hours is used. Of both binary_values and dt_in_hours are arrays, checks that the length of dt_in_hours has at least as many elements as the last consecutive duration in binary_values.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
binary_values
|
(int, ndarray)
|
An int or 1D binary array containing only |
required |
dt_in_hours
|
(int, float, ndarray)
|
The duration of each time step in hours. |
required |
Returns:
| Type | Description |
|---|---|
ndarray
|
The duration of the binary variable in hours. |
Raises:
| Type | Description |
|---|---|
TypeError
|
If the length of binary_values and dt_in_hours is not equal, but None is a scalar. |
SegmentModel
MultipleSegmentsModel
MultipleSegmentsModel(element: Element, sample_points: Dict[Variable, List[Tuple[Numeric, Numeric]]], can_be_outside_segments: Optional[Union[bool, Variable]], as_time_series: bool = True, label: str = 'MultipleSegments')
Bases: ElementModel
can_be_outside_segments: True -> Variable gets created; False or None -> No Variable gets_created; Variable -> the Variable gets used
Functions
ShareAllocationModel
ShareAllocationModel(element: Element, label: str, shares_are_time_series: bool, total_max: Optional[Skalar] = None, total_min: Optional[Skalar] = None, max_per_hour: Optional[Numeric] = None, min_per_hour: Optional[Numeric] = None)
Bases: ElementModel
SingleShareModel
SingleShareModel(element: Element, name: str, variable: Optional[Variable], factor: Numeric, share_as_sum: bool)
Bases: ElementModel
Holds a Variable and an Equation. Summands can be added to the Equation. Used to publish Shares
PreventSimultaneousUsageModel
PreventSimultaneousUsageModel(element: Element, variables: List[VariableTS], label: str = 'PreventSimultaneousUsage')
Bases: ElementModel
Prevents multiple Multiple Binary variables from being 1 at the same time
Only 'classic type is modeled for now (# "classic" -> alle Flows brauchen Binärvariable:) In 'new', the binary Variables need to be forced beforehand, which is not that straight forward... --> TODO maybe