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https://github.com/Akkudoktor-EOS/EOS.git
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70 lines
2.8 KiB
Python
70 lines
2.8 KiB
Python
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"""Retrieves load forecast data from Akkudoktor load profiles."""
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from pathlib import Path
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from typing import Optional
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import numpy as np
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from pydantic import Field
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from akkudoktoreos.config.configabc import SettingsBaseModel
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from akkudoktoreos.prediction.loadabc import LoadProvider
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from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
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from akkudoktoreos.utils.logutil import get_logger
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logger = get_logger(__name__)
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class LoadAkkudoktorCommonSettings(SettingsBaseModel):
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"""Common settings for load data import from file."""
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loadakkudoktor_year_energy: Optional[float] = Field(
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default=None, description="Yearly energy consumption (kWh)."
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)
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class LoadAkkudoktor(LoadProvider):
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"""Fetch Load forecast data from Akkudoktor load profiles."""
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@classmethod
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def provider_id(cls) -> str:
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"""Return the unique identifier for the LoadAkkudoktor provider."""
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return "LoadAkkudoktor"
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def load_data(self) -> np.ndarray:
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"""Loads data from the Akkudoktor load file."""
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load_file = Path(__file__).parent.parent.joinpath("data/load_profiles.npz")
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data_year_energy = None
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try:
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file_data = np.load(load_file)
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profile_data = np.array(
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list(zip(file_data["yearly_profiles"], file_data["yearly_profiles_std"]))
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)
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data_year_energy = profile_data * self.config.loadakkudoktor_year_energy
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# pprint(self.data_year_energy)
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except FileNotFoundError:
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error_msg = f"Error: File {load_file} not found."
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logger.error(error_msg)
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raise FileNotFoundError(error_msg)
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except Exception as e:
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error_msg = f"An error occurred while loading data: {e}"
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logger.error(error_msg)
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raise ValueError(error_msg)
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return data_year_energy
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def _update_data(self, force_update: Optional[bool] = False) -> None:
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"""Adds the load means and standard deviations."""
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data_year_energy = self.load_data()
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for load in self.loads():
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attr_load_mean = f"{load}_mean"
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attr_load_std = f"{load}_std"
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date = self.start_datetime
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for i in range(self.config.prediction_hours):
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# Extract mean and standard deviation for the given day and hour
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# Day indexing starts at 0, -1 because of that
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hourly_stats = data_year_energy[date.day_of_year - 1, :, date.hour]
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self.update_value(date, attr_load_mean, hourly_stats[0])
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self.update_value(date, attr_load_std, hourly_stats[1])
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date += to_duration("1 hour")
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# We are working on fresh data (no cache), report update time
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self.update_datetime = to_datetime(in_timezone=self.config.timezone)
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