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Fix BrightSky weather prediction

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- Get weather data with fully specified end_date datetime argument to not miss data.
- Make preciptable water records generation robust against missing temperature
  or humidity values.

Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
This commit is contained in:
Bobby Noelte
2025-01-22 23:47:28 +01:00
parent 694655311f
commit c8cad0f277
6 changed files with 1665 additions and 9622 deletions
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52
src/akkudoktoreos/prediction/weatherbrightsky.py
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@@ -7,7 +7,7 @@ format, enabling consistent access to forecasted and historical weather attribut
"""
import json
from typing import Dict, List, Optional, Tuple
from typing import Dict, List, Optional, Tuple, Union
import pandas as pd
import pvlib
@@ -16,14 +16,14 @@ import requests
from akkudoktoreos.core.cache import cache_in_file
from akkudoktoreos.core.logging import get_logger
from akkudoktoreos.prediction.weatherabc import WeatherDataRecord, WeatherProvider
from akkudoktoreos.utils.datetimeutil import to_datetime
from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
logger = get_logger(__name__)
WheaterDataBrightSkyMapping: List[Tuple[str, Optional[str], Optional[float]]] = [
WheaterDataBrightSkyMapping: List[Tuple[str, Optional[str], Optional[Union[str, float]]]] = [
# brightsky_key, description, corr_factor
("timestamp", "DateTime", None),
("timestamp", "DateTime", "to datetime in timezone"),
("precipitation", "Precipitation Amount (mm)", 1),
("pressure_msl", "Pressure (mb)", 1),
("sunshine", None, None),
@@ -96,8 +96,8 @@ class WeatherBrightSky(WeatherProvider):
ValueError: If the API response does not include expected `weather` data.
"""
source = "https://api.brightsky.dev"
date = to_datetime(self.start_datetime, as_string="YYYY-MM-DD")
last_date = to_datetime(self.end_datetime, as_string="YYYY-MM-DD")
date = to_datetime(self.start_datetime, as_string=True)
last_date = to_datetime(self.end_datetime, as_string=True)
response = requests.get(
f"{source}/weather?lat={self.config.general.latitude}&lon={self.config.general.longitude}&date={date}&last_date={last_date}&tz={self.config.general.timezone}"
)
@@ -133,7 +133,8 @@ class WeatherBrightSky(WeatherProvider):
error_msg = f"No WeatherDataRecord key for '{description}'"
logger.error(error_msg)
raise ValueError(error_msg)
return self.key_to_series(key)
series = self.key_to_series(key)
return series
def _description_from_series(self, description: str, data: pd.Series) -> None:
"""Update a weather data with a pandas Series based on its description.
@@ -170,7 +171,7 @@ class WeatherBrightSky(WeatherProvider):
brightsky_data = self._request_forecast(force_update=force_update) # type: ignore
# Get key mapping from description
brightsky_key_mapping: Dict[str, Tuple[Optional[str], Optional[float]]] = {}
brightsky_key_mapping: Dict[str, Tuple[Optional[str], Optional[Union[str, float]]]] = {}
for brightsky_key, description, corr_factor in WheaterDataBrightSkyMapping:
if description is None:
brightsky_key_mapping[brightsky_key] = (None, None)
@@ -192,7 +193,10 @@ class WeatherBrightSky(WeatherProvider):
value = brightsky_record[brightsky_key]
corr_factor = item[1]
if value and corr_factor:
value = value * corr_factor
if corr_factor == "to datetime in timezone":
value = to_datetime(value, in_timezone=self.config.general.timezone)
else:
value = value * corr_factor
setattr(weather_record, key, value)
self.insert_by_datetime(weather_record)
@@ -216,14 +220,30 @@ class WeatherBrightSky(WeatherProvider):
self._description_from_series(description, dhi)
# Add Preciptable Water (PWAT) with a PVLib method.
description = "Temperature (°C)"
temperature = self._description_to_series(description)
description = "Relative Humidity (%)"
humidity = self._description_to_series(description)
key = WeatherDataRecord.key_from_description("Temperature (°C)")
assert key
temperature = self.key_to_array(
key=key,
start_datetime=self.start_datetime,
end_datetime=self.end_datetime,
interval=to_duration("1 hour"),
)
key = WeatherDataRecord.key_from_description("Relative Humidity (%)")
assert key
humidity = self.key_to_array(
key=key,
start_datetime=self.start_datetime,
end_datetime=self.end_datetime,
interval=to_duration("1 hour"),
)
data = pvlib.atmosphere.gueymard94_pw(temperature, humidity)
pwat = pd.Series(
data=pvlib.atmosphere.gueymard94_pw(temperature, humidity), index=temperature.index
data=data,
index=pd.DatetimeIndex(
pd.date_range(
start=self.start_datetime, end=self.end_datetime, freq="1h", inclusive="left"
)
),
)
description = "Preciptable Water (cm)"
self._description_from_series(description, pwat)