Energy model optimization parameters

The energy model optimization parameters specify the parameters for the myopic optimization function.

In order to perform a myopic optimization, the following parameter must be given:

• start_year: Year of the first optimization.

In addition, at least two of the following parameters must also be specified:

• end_year: Year of the last optimization.

• number_of_steps: Number of optimization runs excluding the start year.

• years_per_step: Number of years represented by one optimization run.

The following parameters are optional, but both must be provided if the CO2 reduction is used:

• CO2_reference: CO2 emission reference value to which the reduction should be applied to.

• CO2_reduction_targets: CO2 reduction targets for all optimization periods, in percentages. If specified, the length of the list must equal the number of optimization steps, and a sink component named ‘CO2 to environment’ is required.

pydantic model ensysmod.schemas.EnergyModelOptimizationCreate

Attributes to receive via API on creation of a model optimization parameter.

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

field start_year: int [Required]

Year of the first optimization

Constraints:

• ge = 0

field end_year: int | None = None

Year of the last optimization

field number_of_steps: int | None = None

Number of optimization runs excluding the start year

field years_per_step: int | None = None

Number of years represented by one optimization run

field CO2_reference: float | None = None

CO2 emission reference value to which the reduction should be applied to

Constraints:

• ge = 0

field CO2_reduction_targets: list[float] | None = None

CO2 reduction targets for all optimization periods, in percentages. If specified, the length of the list must equal the number of optimization steps, and a sink component named ‘CO2 to environment’ is required.