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31bd2de18b
Extend single_test_optimization.py to be able to use real world data from new prediction classes. - .venv/bin/python single_test_optimization.py --real_world --verbose Can also be run with profiling "--profile". Add single_test_prediction.py to fetch predictions from remote prediction providers - .venv/bin/python single_test_prediction.py --verbose --provider-id PVForecastAkkudoktor | more - .venv/bin/python single_test_prediction.py --verbose --provider-id LoadAkkudoktor | more - .venv/bin/python single_test_prediction.py --verbose --provider-id ElecPriceAkkudoktor | more - .venv/bin/python single_test_prediction.py --verbose --provider-id BrightSky | more - .venv/bin/python single_test_prediction.py --verbose --provider-id ClearOutside | more Can also be run with profiling "--profile". single_test_optimization.py is an example on how to retrieve prediction data for optimization and use it to set up the optimization parameters. Changes: - load: Only one load provider at a time (vs. 5 before) Bug fixes: - prediction: only use providers that are enabled to retrieve or set data. - prediction: fix pre pendulum format strings - dataabc: Prevent error when resampling data with no datasets. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
70 lines
2.8 KiB
Python
70 lines
2.8 KiB
Python
"""Retrieves pvforecast forecast data from an import file.
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This module provides classes and mappings to manage pvforecast data obtained from
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an import file, including support for various pvforecast attributes such as temperature,
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humidity, cloud cover, and solar irradiance. The data is mapped to the `PVForecastDataRecord`
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format, enabling consistent access to forecasted and historical pvforecast attributes.
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"""
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from pathlib import Path
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from typing import Optional, Union
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from pydantic import Field, field_validator
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from akkudoktoreos.config.configabc import SettingsBaseModel
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from akkudoktoreos.prediction.predictionabc import PredictionImportProvider
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from akkudoktoreos.prediction.pvforecastabc import PVForecastProvider
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from akkudoktoreos.utils.logutil import get_logger
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logger = get_logger(__name__)
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class PVForecastImportCommonSettings(SettingsBaseModel):
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"""Common settings for pvforecast data import from file or JSON string."""
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pvforecastimport_file_path: Optional[Union[str, Path]] = Field(
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default=None, description="Path to the file to import pvforecast data from."
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)
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pvforecastimport_json: Optional[str] = Field(
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default=None,
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description="JSON string, dictionary of PV forecast float value lists."
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"Keys are 'pvforecast_dc_power', 'pvforecast_ac_power'.",
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)
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# Validators
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@field_validator("pvforecastimport_file_path", mode="after")
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@classmethod
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def validate_pvforecastimport_file_path(
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cls, value: Optional[Union[str, Path]]
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) -> Optional[Path]:
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if value is None:
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return None
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if isinstance(value, str):
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value = Path(value)
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"""Ensure file is available."""
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value.resolve()
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if not value.is_file():
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raise ValueError(f"Import file path '{value}' is not a file.")
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return value
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class PVForecastImport(PVForecastProvider, PredictionImportProvider):
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"""Fetch PV forecast data from import file or JSON string.
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PVForecastImport is a singleton-based class that retrieves pvforecast forecast data
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from a file or JSON string and maps it to `PVForecastDataRecord` fields. It manages the forecast
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over a range of hours into the future and retains historical data.
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"""
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@classmethod
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def provider_id(cls) -> str:
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"""Return the unique identifier for the PVForecastImport provider."""
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return "PVForecastImport"
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def _update_data(self, force_update: Optional[bool] = False) -> None:
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if self.config.pvforecastimport_file_path is not None:
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self.import_from_file(self.config.pvforecastimport_file_path, key_prefix="pvforecast")
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if self.config.pvforecastimport_json is not None:
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self.import_from_json(self.config.pvforecastimport_json, key_prefix="pvforecast")
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