flixOpt.interface
This module contains classes to collect Parameters for the Investment and OnOff decisions. These are tightly connected to features.py
Classes
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: Union[Dict, int, float] = None, specific_effects: Union[Dict, int, float] = None, effects_in_segments: Optional[Tuple[List[Tuple[Skalar, Skalar]], Dict[Effect, List[Tuple[Skalar, Skalar]]]]] = None, divest_effects: Union[Dict, int, float] = None)
Bases: Interface
collects arguments for invest-stuff
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
fix_effects
|
None or scalar
|
Fixed investment costs if invested. (Attention: Annualize costs to chosen period!) |
None
|
divest_effects
|
None or scalar
|
Fixed divestment costs (if not invested, e.g., demolition costs or contractual penalty). |
None
|
fixed_size
|
(int, float)
|
Determines if the investment size is fixed. |
None
|
optional
|
bool
|
If True, investment is not forced. |
True
|
specific_effects
|
scalar or Dict[Effect: Union[int, float, np.ndarray]
|
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
|
effects_in_segments
|
list or List[ List[Union[int,float]], Dict[cEffecType: Union[List[Union[int,float]]
|
Linear relation in segments [invest_segments, cost_segments]. 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 InvestsizeSegments) |
None
|
minimum_size
|
scalar
|
Min nominal value (only if: size_is_fixed = False). |
0
|
maximum_size
|
(scalar, Optional)
|
Max nominal value (only if: size_is_fixed = False). |
None
|
Functions
infos
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:
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.
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.
Returns: Dict: A dictionary representation of the object's constructor arguments.
OnOffParameters
OnOffParameters(effects_per_switch_on: Union[Dict, Numeric] = None, effects_per_running_hour: Union[Dict, Numeric] = None, on_hours_total_min: Optional[int] = None, on_hours_total_max: Optional[int] = None, consecutive_on_hours_min: Optional[Numeric] = None, consecutive_on_hours_max: Optional[Numeric] = None, consecutive_off_hours_min: Optional[Numeric] = None, consecutive_off_hours_max: Optional[Numeric] = None, switch_on_total_max: Optional[int] = None, force_switch_on: bool = False)
Bases: Interface
on_off_parameters class for modeling 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
|
(scalar, array, TimeSeriesData)
|
cost of one switch from off (var_on=0) to on (var_on=1), unit i.g. in Euro |
None
|
effects_per_running_hour
|
scalar or TS
|
costs for operating, i.g. in € per hour |
None
|
on_hours_total_min
|
scalar
|
min. overall sum of operating hours. |
None
|
on_hours_total_max
|
scalar
|
max. overall sum of operating hours. |
None
|
consecutive_on_hours_min
|
scalar
|
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
|
scalar
|
max sum of operating hours in one piece |
None
|
consecutive_off_hours_min
|
scalar
|
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
|
scalar
|
max sum of non-operating hours in one piece |
None
|
switch_on_total_max
|
integer
|
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_consecutive_on_hours
property
Determines wether a Variable for consecutive off hours is needed or not
use_consecutive_off_hours
property
Determines wether a Variable for consecutive off hours is needed or not
use_switch_on
property
Determines wether a Variable for SWITCH-ON is needed or not
Functions
infos
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:
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.
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.
Returns: Dict: A dictionary representation of the object's constructor arguments.