Cairn API documentation

CairnAPI

class cairn.CairnAPI

Bases: pybind11_object

class ESettingsLimited

Bases: pybind11_object

Members:

all

mandatory

optional

used

all = <ESettingsLimited.all: 0>

mandatory = <ESettingsLimited.mandatory: 1>

property name

optional = <ESettingsLimited.optional: 2>

used = <ESettingsLimited.used: 3>

property value

close_study(self: cairn.bin.cairn.CairnAPI) → None: close the current study

component_type(self: cairn.bin.cairn.CairnAPI, model: str) → str: returns the type of a given model

create_study(self: cairn.bin.cairn.CairnAPI, arg0: str) → CairnAPI::OptimProblemAPI: creates study with a given name

read_study(self: cairn.bin.cairn.CairnAPI, fileName: str) → CairnAPI::OptimProblemAPI: reads a study from file

all = <ESettingsLimited.all: 0>

property all_models

property carrier_types

property component_types

mandatory = <ESettingsLimited.mandatory: 1>

optional = <ESettingsLimited.optional: 2>

property solvers

used = <ESettingsLimited.used: 3>

OptimProblem

class cairn.OptimProblem

Bases: pybind11_object

OptimProblem class.

add_label(self: cairn.bin.cairn.OptimProblem, arg0: str) → None: add a label to the problem

add_link(self: cairn.bin.cairn.OptimProblem, arg0: CairnAPI::MilpPortAPI, arg1: CairnAPI::BusAPI) → None: adds a link between two given ports

add_timeseries(self: cairn.bin.cairn.OptimProblem, arg0: str) → None: adds a given timeseries file

create_bus(self: cairn.bin.cairn.OptimProblem, arg0: str, arg1: str, arg2: CairnAPI::EnergyVectorAPI) → CairnAPI::BusAPI: creates and returns a new bus with a given name, model and energy carrier, e.g., create_bus(‘H2_Bus’, ‘NodeLaw’, vH2)

create_component(self: cairn.bin.cairn.OptimProblem, arg0: str, arg1: str) → CairnAPI::MilpComponentAPI: creates and returns a new component with a given name and model, e.g., create_component(‘Elec_Grid’, ‘GridFree’)

create_energy_carrier(self: cairn.bin.cairn.OptimProblem, arg0: str, arg1: str) → CairnAPI::EnergyVectorAPI: creates and returns a new energy carrier with a given name and type, e.g., create_energy_carrier(‘H2’, ‘FluidH2’)

export_parameters(self: cairn.bin.cairn.OptimProblem, filename: str = '', optionsMap: collections.abc.Mapping[str, bool] = {}) → None: exports the study parameters to a csv file

export_plan(self: cairn.bin.cairn.OptimProblem, filename: str = '', solNb: SupportsInt = 0) → None: exports PLAN results to a csv file

get_all_indicators_values(self: cairn.bin.cairn.OptimProblem, range: str = 'PLAN') → dict[str, float | int | str | list[str] | list[float] | list[int]]: returns the indicators of all components for a given range, by default PLAN value

get_bus(self: cairn.bin.cairn.OptimProblem, arg0: str) → CairnAPI::BusAPI: returns a given bus

get_component(self: cairn.bin.cairn.OptimProblem, arg0: str) → CairnAPI::MilpComponentAPI: returns a given component

get_components(self: cairn.bin.cairn.OptimProblem, category: str = '') → list[str]: returns all the components of the optim problem specifying the category if needed

get_energy_carrier(self: cairn.bin.cairn.OptimProblem, arg0: str) → CairnAPI::EnergyVectorAPI: returns a given energy carrier

get_indicator_value(self: cairn.bin.cairn.OptimProblem, name: str, range: str = 'PLAN') → float: returns the result of a given TecEco indicator for a given range, by default PLAN value

get_indicators_values(self: cairn.bin.cairn.OptimProblem, range: str = 'PLAN') → dict[str, float | int | str | list[str] | list[float] | list[int]]: returns the TecEco indicators for a given range, by default PLAN value

get_object(self: cairn.bin.cairn.OptimProblem, arg0: str) → CairnAPI::ObjectAPI: returns a given object

get_simulation_control(self: cairn.bin.cairn.OptimProblem) → CairnAPI::SimulationControlAPI: return SimulationControl

get_solver(self: cairn.bin.cairn.OptimProblem) → CairnAPI::SolverAPI: return Solver

get_tech_eco_analysis(self: cairn.bin.cairn.OptimProblem) → CairnAPI::TecEcoAnalysisAPI: return TecEcoAnalysis

remove_bus(self: cairn.bin.cairn.OptimProblem, arg0: CairnAPI::BusAPI) → None: removes a given bus

remove_component(self: cairn.bin.cairn.OptimProblem, arg0: CairnAPI::MilpComponentAPI) → None: removes a geiven component from the optim problem

remove_energy_carrier(self: cairn.bin.cairn.OptimProblem, arg0: CairnAPI::EnergyVectorAPI) → None: removes a given energy carrier from the optim problem

remove_label(self: cairn.bin.cairn.OptimProblem, arg0: str) → None: remove a label from the problem

remove_link(self: cairn.bin.cairn.OptimProblem, arg0: CairnAPI::MilpPortAPI, arg1: CairnAPI::BusAPI) → None: removes a given link

run(self: cairn.bin.cairn.OptimProblem, resultsPath: str = '') → CairnAPI::SolutionAPI: runs the optim problem

save_study(self: cairn.bin.cairn.OptimProblem, filename: str, mode: str = '') → None: saves a study with a given name (it can also take a mode to position the components e.g. gradient)

property buses

property components

property energy_carriers: returns all the energy carriers of the optim problem

property indicators

property indicators_shortnames

property indicators_units

property labels: get/set the labels of the problem

property links

property objects

property optimized_components

CairnObject

class cairn.CairnObject

Bases: pybind11_object

Object class.

get_setting_value(self: cairn.bin.cairn.CairnObject, arg0: str) → float | int | str | list[str] | list[float] | list[int]: returns the value of a given parameter

get_settings(self: cairn.bin.cairn.CairnObject, setLimited: cairn.bin.cairn.CairnAPI.ESettingsLimited = <ESettingsLimited.all: 0>) → list[str]: returns a list of all (by default), used, optional or mandatory parameter names

rename(self: cairn.bin.cairn.CairnObject, arg0: str) → None: rename EnergyVector component

set_setting_value(self: cairn.bin.cairn.CairnObject, name: str, value: SupportsFloat | SupportsInt | str | collections.abc.Sequence[str] | collections.abc.Sequence[SupportsFloat] | collections.abc.Sequence[SupportsInt], verify: bool = True) → None: sets the value of a given parameter

property name

property objectType

property setting_values: get/set all parameters as a dictionary

property settings: returns a list of all parameter names

property show_config: returns ShowConfig of a given parameter. The parameter is displayed in the GUI when this ShowConfig is selected in the DataFilter

property show_configs: returns a list of all ShowConfigs which is used in the GUI DataFilter

EnergyVector

class cairn.EnergyVector

Bases: CairnObject

EnergyCarrier class. The constructor takes several arguments: arg1: OptimProblemAPI aProblem, the study where the EnergyVector will be added arg2: string aName to give the name of the energy vector arg3: string aType to give the type of the energy vector (list available thanks to property carrier_types of CairnAPI)

property type

Bus

class cairn.Bus

Bases: CairnObject

Bus class. The constructor takes several arguments: arg1: OptimProblemAPI aProblem, the study where the Bus will be added arg2: string aName to give the name of the bus arg3: string aModelName to give the model. Available Bus models are NodeLaw, NodeEquality and ManualObjective arg4: string aEnergyVector to give the energy vector of the bus

get_indicator_value(self: cairn.bin.cairn.Bus, name: str, range: str = 'PLAN') → float: returns the result of a given indicator for a given range, by default PLAN value

get_indicators_values(self: cairn.bin.cairn.Bus, range: str = 'PLAN') → dict[str, float | int | str | list[str] | list[float] | list[int]]: returns the indicators for a given range, by default PLAN value

get_label_value(self: cairn.bin.cairn.Bus, arg0: str) → str: return the value of a given label

get_var_value(self: cairn.bin.cairn.Bus, arg0: str) → float | int | str | list[str] | list[float] | list[int]: returns the result of a given IO for the optimal solution

get_var_values(self: cairn.bin.cairn.Bus) → dict[str, float | int | str | list[str] | list[float] | list[int]]: returns the result of all IOs for the optimal solution

set_label_value(self: cairn.bin.cairn.Bus, arg0: str, arg1: str) → None: set the value of a given label

property indicators

property indicators_shortnames

property indicators_units

property label_values: get/set all label values as a dictionary

property model_class

property type

property variables

Port

class cairn.Port

Bases: CairnObject

Port class. The constructor takes several arguments: arg1: MilpComponentAPI aComponent which will own the port arg2: string aName to give the name of the port arg3: EnergyVectorAPI aEnergyVector to give the energy vector of the port arg3 (optional): string aDirection (Input, Output or DataExchange) to set the direction of the port arg3 (optional): string aVariable to set the variable of the port

set_carrier(self: cairn.bin.cairn.Port, arg0: cairn.bin.cairn.EnergyVector) → None: sets the energy carrier of the port (takes componenet not name)

property carrier_name: return the name of energy carrier

Component

class cairn.Component

Bases: CairnObject

Component class. The constructor takes several arguments: arg1: OptimProblemAPI aProblem, the study where the component will be added arg2: string aName to give the name of the component arg3: string aModelName to give the model (list available thanks to property all_models of CairnAPI). Note that, to create componenets NodeLaw, NodeEquality and ManualObjective use BusAPI

add_port(self: cairn.bin.cairn.Component, name: str, carrier: cairn.bin.cairn.EnergyVector, direction: str = 'DATAEXCHANGE', variable: str = '', reinitializeCompo: bool = True) → cairn.bin.cairn.Port: creates a new port for the component

get_indicator_value(self: cairn.bin.cairn.Component, name: str, range: str = 'PLAN') → float: returns the result of a given indicator for a given range, by default PLAN value

get_indicators_values(self: cairn.bin.cairn.Component, range: str = 'PLAN') → dict[str, float | int | str | list[str] | list[float] | list[int]]: returns the indicators for a given range, by default PLAN value

get_label_value(self: cairn.bin.cairn.Component, arg0: str) → str: return the value of a given label

get_port(self: cairn.bin.cairn.Component, arg0: str) → cairn.bin.cairn.Port: returns a given port from the component

get_timeseries_vector(self: cairn.bin.cairn.Component, arg0: str) → float | int | str | list[str] | list[float] | list[int]: returns the vector value of a given timeseries parameter

get_var_value(self: cairn.bin.cairn.Component, arg0: str) → float | int | str | list[str] | list[float] | list[int]: returns the result of a given IO for the optimal solution

get_var_values(self: cairn.bin.cairn.Component) → dict[str, float | int | str | list[str] | list[float] | list[int]]: returns the result of all IOs for the optimal solution

remove_port(self: cairn.bin.cairn.Component, arg0: cairn.bin.cairn.Port, arg1: bool) → bool: removes a given port from the component

set_label_value(self: cairn.bin.cairn.Component, arg0: str, arg1: str) → None: set the value of a given label

set_timeseries_vector(self: cairn.bin.cairn.Component, arg0: str, arg1: collections.abc.Sequence[SupportsFloat]) → None: sets the vector value of a given timeseries parameter

property default_ports: returns the list of default port names

property dim_param: return the parameter used for dimensionning

property direction: return the direction based on the default port. Valid only for components of types Grid and SourceLoad.

property indicators

property indicators_shortnames

property indicators_units

property is_optimized

property label_values: get/set all label values as a dictionary

property model_class

property optimal_size_expression: returns the name of optimal size (MaxSize) variable. Note, it works only after configuring the carriers of default ports.

property ports: returns the list of all port names

property type

property variables

Solution

class cairn.Solution

Bases: pybind11_object

Solution class.

get_ts_results(self: cairn.bin.cairn.Solution, arg0: SupportsInt) → dict[str, list[float | int | str | list[str] | list[float] | list[int]]]: returns the output ts results

property nb_solutions: returns the number of solutions found

property status: returns the status of the run

cairn toolbox

cairn.run_sensitivity(problem, df_sens, max_time=-1, indicators=Empty DataFrame Columns: [] Index: []): runs sensitivity study of a given problem with a given input dataframe (2 header rows: 1st row: name of the component, 2nd row: name of the parameter and one sensitivity study per row) for an optional maximal duration of each run. arg1: cairn problem arg2: dataframe containing sensitivity studies to be conducted arg3: maximal duration of each sensitivity study (optional) arg4: pandas dataframe of two colums Model and Indicator of KPI to save during sensitivity (file PLAN) :meta public:

cairn.set_param(problem, header_col, value)

cairn.copy_component(problem, component, new_name, connexions=True)

Make a copy of a component, with its parameters and connexions (optional).

Parameters:

problem (cairn.OptimProblem) – The problem that will be modified
component (str) – The name of component to duplicate
new_name (str) – The name of the duplicated component
connexions (bool) – If true, the ports and links are also duplicated.

Returns:

compo2 – The new component.

Return type:

cairn.Component