battery_optimizer.uk.mel_mil

Functions

create_melmil_result_from_dataframe(...[, trace])
optimize_mel_mil_request(request)

Classes

BMPosition(*, time_from, time_to, power_MW)
BOA(*, BOATimepoints)
BOATimepoint(*, time_from, power_kW)
BaselinePoint(*, time_from, power_kW[, ...])
MELMILResult(*, request_id[, problem_type, ...])

class battery_optimizer.uk.mel_mil.BMPosition(*, time_from, time_to, power_MW)

Bases: BaseModel

Parameters:

• time_from (datetime)

• time_to (datetime)

• power_MW (float)

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

power_MW: float

time_from: datetime

time_to: datetime

class battery_optimizer.uk.mel_mil.BOA(*, BOATimepoints)

Bases: BaseModel

Parameters:

BOATimepoints (list[BOATimepoint])

BOATimepoints: list[BOATimepoint]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class battery_optimizer.uk.mel_mil.BOATimepoint(*, time_from, power_kW)

Bases: BaseModel

Parameters:

• time_from (datetime)

• power_kW (float)

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

power_kW: float

time_from: datetime

class battery_optimizer.uk.mel_mil.BaselinePoint(*, time_from, power_kW, expected_soc_fraction=None)

Bases: BaseModel

Parameters:

• time_from (datetime)

• power_kW (float)

• expected_soc_fraction (float | None)

expected_soc_fraction: float | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

power_kW: float

time_from: datetime

class battery_optimizer.uk.mel_mil.MELMILResult(*, request_id, problem_type=ProblemType.MELMIL, asset_id, request_creation_time, result_creation_time, mel, mil, request, trace=None)

Bases: BaseModel

Parameters:

• request_id (str)

• problem_type (ProblemType)

• asset_id (str | int)

• request_creation_time (datetime)

• result_creation_time (datetime)

• mel (list[BMPosition])

• mil (list[BMPosition])

• request (UKRequest | dict)

• trace (Any)

asset_id: str | int

mel: list[BMPosition]

mil: list[BMPosition]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

problem_type: ProblemType

request: UKRequest | dict

request_creation_time: datetime

request_id: str

result_creation_time: datetime

trace: Any

battery_optimizer.uk.mel_mil.create_melmil_result_from_dataframe(request_id, problem_type, asset_id, request_creation_time, mel_df, mil_df, request, trace=None)

Parameters:

• request_id (str)

• problem_type (ProblemType)

• asset_id (str | int)

• request_creation_time (datetime)

• mel_df (DataFrame)

• mil_df (DataFrame)

• request (UKRequest | dict)

• trace (Any)

Return type:

MELMILResult

battery_optimizer.uk.mel_mil.optimize_mel_mil_request(request)