Skip to content

flixopt.elements

This module contains the basic elements of the flixopt framework.

Attributes

Classes

Component 

Component(
    label: str,
    inputs: Optional[List[Flow]] = None,
    outputs: Optional[List[Flow]] = None,
    on_off_parameters: Optional[OnOffParameters] = None,
    prevent_simultaneous_flows: Optional[List[Flow]] = None,
    meta_data: Optional[Dict] = None,
)

Bases: Element

A Component contains incoming and outgoing Flows. It defines how these Flows interact with each other. The On or Off state of the Component is defined by all its Flows. Its on, if any of its FLows is On. It's mathematically advisable to define the On/Off state in a FLow rather than a Component if possible, as this introduces less binary variables to the Model Constraints to the On/Off state are defined by the on_off_parameters.

Parameters:

Name Type Description Default
label str

The label of the Element. Used to identify it in the FlowSystem

 required
inputs Optional[List[Flow]]

input flows.

 None
outputs Optional[List[Flow]]

output flows.

 None
on_off_parameters Optional[OnOffParameters]

Information about on and off state of Component. Component is On/Off, if all connected Flows are On/Off. This induces an On-Variable (binary) in all Flows! If possible, use OnOffParameters in a single Flow instead to keep the number of binary variables low. See class OnOffParameters.

 None
prevent_simultaneous_flows Optional[List[Flow]]

Define a Group of Flows. Only one them can be on at a time. Induces On-Variable in all Flows! If possible, use OnOffParameters in a single Flow instead.

 None
meta_data Optional[Dict]

used to store more information about the Element. Is not used internally, but saved in the results. Only use python native types.

 None

Functions

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

Bus 

Bus(
    label: str,
    excess_penalty_per_flow_hour: Optional[NumericDataTS] = 100000.0,
    meta_data: Optional[Dict] = None,
)

Bases: Element

A Bus represents a nodal balance between the flow rates of its incoming and outgoing Flows.

Parameters:

Name Type Description Default
label str

The label of the Element. Used to identify it in the FlowSystem

 required
excess_penalty_per_flow_hour Optional[NumericDataTS]

excess costs / penalty costs (bus balance compensation) (none/ 0 -> no penalty). The default is 1e5. (Take care: if you use a timeseries (no scalar), timeseries is aggregated if calculation_type = aggregated!)

 100000.0
meta_data Optional[Dict]

used to store more information about the Element. Is not used internally, but saved in the results. Only use python native types.

 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

Connection 

Connection()

This class is not yet implemented!

Functions

Flow 

Flow(
    label: str,
    bus: str,
    size: Union[Scalar, InvestParameters] = None,
    fixed_relative_profile: Optional[NumericDataTS] = None,
    relative_minimum: NumericDataTS = 0,
    relative_maximum: NumericDataTS = 1,
    effects_per_flow_hour: Optional[EffectValuesUser] = None,
    on_off_parameters: Optional[OnOffParameters] = None,
    flow_hours_total_max: Optional[Scalar] = None,
    flow_hours_total_min: Optional[Scalar] = None,
    load_factor_min: Optional[Scalar] = None,
    load_factor_max: Optional[Scalar] = None,
    previous_flow_rate: Optional[NumericData] = None,
    meta_data: Optional[Dict] = None,
)

Bases: Element

A Flow moves energy (or material) between a Bus and a Component in a predefined direction. The flow-rate is the main optimization variable of the Flow.

Parameters:

Name Type Description Default
label str

The label of the FLow. Used to identify it in the FlowSystem. Its full_label consists of the label of the Component and the label of the Flow.

 required
bus str

blabel of the bus the flow is connected to.

 required
size Union[Scalar, InvestParameters]

size of the flow. If InvestmentParameters is used, size is optimized. If size is None, a default value is used.

 None
relative_minimum NumericDataTS

min value is relative_minimum multiplied by size

 0
relative_maximum NumericDataTS

max value is relative_maximum multiplied by size. If size = max then relative_maximum=1

 1
load_factor_min Optional[Scalar]

minimal load factor general: avg Flow per nominalVal/investSize (e.g. boiler, kW/kWh=h; solarthermal: kW/m²; def: :math:load\_factor:= sumFlowHours/ (nominal\_val \cdot \Delta t_{tot})

 None
load_factor_max Optional[Scalar]

maximal load factor (see minimal load factor)

 None
effects_per_flow_hour Optional[EffectValuesUser]

operational costs, costs per flow-"work"

 None
on_off_parameters Optional[OnOffParameters]

If present, flow can be "off", i.e. be zero (only relevant if relative_minimum > 0) Therefore a binary var "on" is used. Further, several other restrictions and effects can be modeled through this On/Off State (See OnOffParameters)

 None
flow_hours_total_max Optional[Scalar]

maximum flow-hours ("flow-work") (if size is not const, maybe load_factor_max is the better choice!)

 None
flow_hours_total_min Optional[Scalar]

minimum flow-hours ("flow-work") (if size is not predefined, maybe load_factor_min is the better choice!)

 None
fixed_relative_profile Optional[NumericDataTS]

fixed relative values for flow (if given). flow_rate(t) := fixed_relative_profile(t) * size(t) With this value, the flow_rate is no optimization-variable anymore. (relative_minimum and relative_maximum are ignored) used for fixed load or supply profiles, i.g. heat demand, wind-power, solarthermal If the load-profile is just an upper limit, use relative_maximum instead.

 None
previous_flow_rate Optional[NumericData]

previous flow rate of the flow. Used to determine if and how long the flow is already on / off. If None, the flow is considered to be off for one timestep.

 None
meta_data Optional[Dict]

used to store more information about the Element. Is not used internally, but saved in the results. Only use python native types.

 None

Functions

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
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

FlowModel 

FlowModel(model: SystemModel, element: Flow)

Bases: ElementModel

Attributes

flow_rate_bounds_on property 
flow_rate_bounds_on: Tuple[NumericData, NumericData]

Returns absolute flow rate bounds. Important for OnOffModel

flow_rate_lower_bound_relative property 
flow_rate_lower_bound_relative: NumericData

Returns the lower bound of the flow_rate relative to its size

flow_rate_upper_bound_relative property 
flow_rate_upper_bound_relative: NumericData

Returns the upper bound of the flow_rate relative to its size

flow_rate_lower_bound property 
flow_rate_lower_bound: NumericData

Returns the minimum bound the flow_rate can reach. Further constraining might be done in OnOffModel and InvestmentModel

flow_rate_upper_bound property 
flow_rate_upper_bound: NumericData

Returns the maximum bound the flow_rate can reach. Further constraining might be done in OnOffModel and InvestmentModel

label_full property 
label_full: str

Used to construct the names of variables and constraints

Functions

add 
add(
    item: Union[Variable, Constraint, Model], short_name: Optional[str] = None
) -> Union[linopy.Variable, linopy.Constraint, Model]

Add a variable, constraint or sub-model to the model

Parameters:

Name Type Description Default
item Union[Variable, Constraint, Model]

The variable, constraint or sub-model to add to the model

 required
short_name Optional[str]

The short name of the variable, constraint or sub-model. If not provided, the full name is used.

 None

ComponentModel 

ComponentModel(model: SystemModel, element: Component)

Bases: ElementModel

Attributes

label_full property 
label_full: str

Used to construct the names of variables and constraints

Functions

do_modeling 
do_modeling()

Initiates all FlowModels

add 
add(
    item: Union[Variable, Constraint, Model], short_name: Optional[str] = None
) -> Union[linopy.Variable, linopy.Constraint, Model]

Add a variable, constraint or sub-model to the model

Parameters:

Name Type Description Default
item Union[Variable, Constraint, Model]

The variable, constraint or sub-model to add to the model

 required
short_name Optional[str]

The short name of the variable, constraint or sub-model. If not provided, the full name is used.

 None

Functions