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flixopt.interface

This module contains classes to collect Parameters for the Investment and OnOff decisions. These are tightly connected to features.py

Attributes

Classes

Piece 

Piece(start: NumericData, end: NumericData)

Bases: Interface

Define a Piece, which is part of a Piecewise object.

Parameters:

Name Type Description Default
start NumericData

The x-values of the piece.

 required
end NumericData

The end of the piece.

 required

Functions

infos 
infos(use_numpy: bool = True, use_element_label: bool = False) -> Dict

Generate a dictionary representation of the object's constructor arguments. Excludes default values and empty dictionaries and lists. Converts data to be compatible with JSON.

Parameters:

Name Type Description Default
use_numpy bool

Whether to convert NumPy arrays to lists. Defaults to True. If True, numeric numpy arrays (np.ndarray) are preserved as-is. If False, they are converted to lists.

 True
use_element_label bool

Whether to use the element label instead of the infos of the element. Defaults to False. Note that Elements used as keys in dictionaries are always converted to their labels.

 False

Returns:

Type Description
Dict

A dictionary representation of the object's constructor arguments.
to_json 
to_json(path: Union[str, Path])

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

Parameters:

Name Type Description Default
path Union[str, Path]

The path to the json file.

 required
to_dict 
to_dict() -> Dict

Convert the object to a dictionary representation.

from_dict classmethod 
from_dict(data: Dict) -> Interface

Create an instance from a dictionary representation.

Parameters:

Name Type Description Default
data Dict

Dictionary containing the data for the object.

 required

Piecewise 

Piecewise(pieces: List[Piece])

Bases: Interface

Define a Piecewise, consisting of a list of Pieces.

Parameters:

Name Type Description Default
pieces List[Piece]

The pieces of the piecewise.

 required

Functions

infos 
infos(use_numpy: bool = True, use_element_label: bool = False) -> Dict

Generate a dictionary representation of the object's constructor arguments. Excludes default values and empty dictionaries and lists. Converts data to be compatible with JSON.

Parameters:

Name Type Description Default
use_numpy bool

Whether to convert NumPy arrays to lists. Defaults to True. If True, numeric numpy arrays (np.ndarray) are preserved as-is. If False, they are converted to lists.

 True
use_element_label bool

Whether to use the element label instead of the infos of the element. Defaults to False. Note that Elements used as keys in dictionaries are always converted to their labels.

 False

Returns:

Type Description
Dict

A dictionary representation of the object's constructor arguments.
to_json 
to_json(path: Union[str, Path])

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

Parameters:

Name Type Description Default
path Union[str, Path]

The path to the json file.

 required
to_dict 
to_dict() -> Dict

Convert the object to a dictionary representation.

from_dict classmethod 
from_dict(data: Dict) -> Interface

Create an instance from a dictionary representation.

Parameters:

Name Type Description Default
data Dict

Dictionary containing the data for the object.

 required

PiecewiseConversion 

PiecewiseConversion(piecewises: Dict[str, Piecewise])

Bases: Interface

Define a piecewise conversion between multiple Flows. --> "gaps" can be expressed by a piece not starting at the end of the prior piece: [(1,3), (4,5)] --> "points" can expressed as piece with same begin and end: [(3,3), (4,4)]

Parameters:

Name Type Description Default
piecewises Dict[str, Piecewise]

Dict of Piecewises defining the conversion factors. flow labels as keys, piecewise as values

 required

Functions

infos 
infos(use_numpy: bool = True, use_element_label: bool = False) -> Dict

Generate a dictionary representation of the object's constructor arguments. Excludes default values and empty dictionaries and lists. Converts data to be compatible with JSON.

Parameters:

Name Type Description Default
use_numpy bool

Whether to convert NumPy arrays to lists. Defaults to True. If True, numeric numpy arrays (np.ndarray) are preserved as-is. If False, they are converted to lists.

 True
use_element_label bool

Whether to use the element label instead of the infos of the element. Defaults to False. Note that Elements used as keys in dictionaries are always converted to their labels.

 False

Returns:

Type Description
Dict

A dictionary representation of the object's constructor arguments.
to_json 
to_json(path: Union[str, Path])

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

Parameters:

Name Type Description Default
path Union[str, Path]

The path to the json file.

 required
to_dict 
to_dict() -> Dict

Convert the object to a dictionary representation.

from_dict classmethod 
from_dict(data: Dict) -> Interface

Create an instance from a dictionary representation.

Parameters:

Name Type Description Default
data Dict

Dictionary containing the data for the object.

 required

PiecewiseEffects 

PiecewiseEffects(piecewise_origin: Piecewise, piecewise_shares: Dict[str, Piecewise])

Bases: Interface

Define piecewise effects related to a variable.

Parameters:

Name Type Description Default
piecewise_origin Piecewise

Piecewise of the related variable

 required
piecewise_shares Dict[str, Piecewise]

Piecewise defining the shares to different Effects

 required

Functions

infos 
infos(use_numpy: bool = True, use_element_label: bool = False) -> Dict

Generate a dictionary representation of the object's constructor arguments. Excludes default values and empty dictionaries and lists. Converts data to be compatible with JSON.

Parameters:

Name Type Description Default
use_numpy bool

Whether to convert NumPy arrays to lists. Defaults to True. If True, numeric numpy arrays (np.ndarray) are preserved as-is. If False, they are converted to lists.

 True
use_element_label bool

Whether to use the element label instead of the infos of the element. Defaults to False. Note that Elements used as keys in dictionaries are always converted to their labels.

 False

Returns:

Type Description
Dict

A dictionary representation of the object's constructor arguments.
to_json 
to_json(path: Union[str, Path])

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

Parameters:

Name Type Description Default
path Union[str, Path]

The path to the json file.

 required
to_dict 
to_dict() -> Dict

Convert the object to a dictionary representation.

from_dict classmethod 
from_dict(data: Dict) -> Interface

Create an instance from a dictionary representation.

Parameters:

Name Type Description Default
data Dict

Dictionary containing the data for the object.

 required

InvestParameters 

InvestParameters(fixed_size: Optional[Union[int, float]] = None, minimum_size: Union[int, float] = 0, maximum_size: Optional[Union[int, float]] = None, optional: bool = True, fix_effects: Optional[EffectValuesUserScalar] = None, specific_effects: Optional[EffectValuesUserScalar] = None, piecewise_effects: Optional[PiecewiseEffects] = None, divest_effects: Optional[EffectValuesUserScalar] = None)

Bases: Interface

collects arguments for invest-stuff

Parameters:

Name Type Description Default
fix_effects Optional[EffectValuesUserScalar]

Fixed investment costs if invested. (Attention: Annualize costs to chosen period!)

 None
divest_effects Optional[EffectValuesUserScalar]

Fixed divestment costs (if not invested, e.g., demolition costs or contractual penalty).

 None
fixed_size Optional[Union[int, float]]

Determines if the investment size is fixed.

 None
optional bool

If True, investment is not forced.

 True
specific_effects Optional[EffectValuesUserScalar]

Specific costs, e.g., in €/kW_nominal or €/m²_nominal. Example: {costs: 3, CO2: 0.3} with costs and CO2 representing an Object of class Effect (Attention: Annualize costs to chosen period!)

 None
piecewise_effects Optional[PiecewiseEffects]

Linear piecewise relation [invest_pieces, cost_pieces]. Example 1: [ [5, 25, 25, 100], # size in kW {costs: [50,250,250,800], # € PE: [5, 25, 25, 100] # kWh_PrimaryEnergy } ] Example 2 (if only standard-effect): [ [5, 25, 25, 100], # kW # size in kW [50,250,250,800] # value for standart effect, typically € ] # € (Attention: Annualize costs to chosen period!) (Args 'specific_effects' and 'fix_effects' can be used in parallel to Investsizepieces)

 None
minimum_size Union[int, float]

Min nominal value (only if: size_is_fixed = False).

 0
maximum_size Optional[Union[int, float]]

Max nominal value (only if: size_is_fixed = False).

 None

Functions

infos 
infos(use_numpy: bool = True, use_element_label: bool = False) -> Dict

Generate a dictionary representation of the object's constructor arguments. Excludes default values and empty dictionaries and lists. Converts data to be compatible with JSON.

Parameters:

Name Type Description Default
use_numpy bool

Whether to convert NumPy arrays to lists. Defaults to True. If True, numeric numpy arrays (np.ndarray) are preserved as-is. If False, they are converted to lists.

 True
use_element_label bool

Whether to use the element label instead of the infos of the element. Defaults to False. Note that Elements used as keys in dictionaries are always converted to their labels.

 False

Returns:

Type Description
Dict

A dictionary representation of the object's constructor arguments.
to_json 
to_json(path: Union[str, Path])

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

Parameters:

Name Type Description Default
path Union[str, Path]

The path to the json file.

 required
to_dict 
to_dict() -> Dict

Convert the object to a dictionary representation.

from_dict classmethod 
from_dict(data: Dict) -> Interface

Create an instance from a dictionary representation.

Parameters:

Name Type Description Default
data Dict

Dictionary containing the data for the object.

 required

OnOffParameters 

OnOffParameters(effects_per_switch_on: Optional[EffectValuesUser] = None, effects_per_running_hour: Optional[EffectValuesUser] = None, on_hours_total_min: Optional[int] = None, on_hours_total_max: Optional[int] = None, consecutive_on_hours_min: Optional[NumericData] = None, consecutive_on_hours_max: Optional[NumericData] = None, consecutive_off_hours_min: Optional[NumericData] = None, consecutive_off_hours_max: Optional[NumericData] = None, switch_on_total_max: Optional[int] = None, force_switch_on: bool = False)

Bases: Interface

Bundles information about the on and off state of an Element. If no parameters are given, the default is to create a binary variable for the on state without further constraints or effects and a variable for the total on hours.

Parameters:

Name Type Description Default
effects_per_switch_on Optional[EffectValuesUser]

cost of one switch from off (var_on=0) to on (var_on=1), unit i.g. in Euro

 None
effects_per_running_hour Optional[EffectValuesUser]

costs for operating, i.g. in € per hour

 None
on_hours_total_min Optional[int]

min. overall sum of operating hours.

 None
on_hours_total_max Optional[int]

max. overall sum of operating hours.

 None
consecutive_on_hours_min Optional[NumericData]

min sum of operating hours in one piece (last on-time period of timeseries is not checked and can be shorter)

 None
consecutive_on_hours_max Optional[NumericData]

max sum of operating hours in one piece

 None
consecutive_off_hours_min Optional[NumericData]

min sum of non-operating hours in one piece (last off-time period of timeseries is not checked and can be shorter)

 None
consecutive_off_hours_max Optional[NumericData]

max sum of non-operating hours in one piece

 None
switch_on_total_max Optional[int]

max nr of switchOn operations

 None
force_switch_on bool

force creation of switch on variable, even if there is no switch_on_total_max

 False

Attributes

use_off property 
use_off: bool

Determines wether the OFF Variable is needed or not

use_consecutive_on_hours property 
use_consecutive_on_hours: bool

Determines wether a Variable for consecutive off hours is needed or not

use_consecutive_off_hours property 
use_consecutive_off_hours: bool

Determines wether a Variable for consecutive off hours is needed or not

use_switch_on property 
use_switch_on: bool

Determines wether a Variable for SWITCH-ON is needed or not

Functions

infos 
infos(use_numpy: bool = True, use_element_label: bool = False) -> Dict

Generate a dictionary representation of the object's constructor arguments. Excludes default values and empty dictionaries and lists. Converts data to be compatible with JSON.

Parameters:

Name Type Description Default
use_numpy bool

Whether to convert NumPy arrays to lists. Defaults to True. If True, numeric numpy arrays (np.ndarray) are preserved as-is. If False, they are converted to lists.

 True
use_element_label bool

Whether to use the element label instead of the infos of the element. Defaults to False. Note that Elements used as keys in dictionaries are always converted to their labels.

 False

Returns:

Type Description
Dict

A dictionary representation of the object's constructor arguments.
to_json 
to_json(path: Union[str, Path])

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

Parameters:

Name Type Description Default
path Union[str, Path]

The path to the json file.

 required
to_dict 
to_dict() -> Dict

Convert the object to a dictionary representation.

from_dict classmethod 
from_dict(data: Dict) -> Interface

Create an instance from a dictionary representation.

Parameters:

Name Type Description Default
data Dict

Dictionary containing the data for the object.

 required

Functions