"""Provides feed-in tariff data from the dvhub.online price API.""" import time from datetime import datetime from typing import Any, Optional import pandas as pd import requests from loguru import logger from pydantic import Field from akkudoktoreos.config.configabc import SettingsBaseModel from akkudoktoreos.core.cache import cache_in_file from akkudoktoreos.prediction.feedintariffabc import FeedInTariffProvider from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration class FeedInTariffDvhubOnlineCommonSettings(SettingsBaseModel): """Common settings for the dvhub.online feed-in tariff provider.""" base_url: str = Field( default="https://dvhub.online", json_schema_extra={ "description": "Base URL of the dvhub.online price API.", "examples": ["https://dvhub.online"], }, ) zone: str = Field( default="DE-LU", json_schema_extra={ "description": "Bidding zone passed to the dvhub.online price API.", "examples": ["DE-LU"], }, ) class FeedInTariffDvhubOnline(FeedInTariffProvider): """Fetch dvhub.online day-ahead market prices as feed-in tariff data. dvhub.online serves EPEX day-ahead prices (15-minute slots, EUR/MWh) via ``GET /api/prices?start=YYYY-MM-DD&end=YYYY-MM-DD&zone=DE-LU``. The raw market price is stored as ``feed_in_tariff_wh`` (EUR/Wh) — like ``FeedInTariffEnergyCharts`` this intentionally adds no import charges or VAT, so the series is the direct-marketing revenue the optimizer needs. Only published slots are stored. Automatic optimization requires real tariff coverage for the GENETIC or GENETIC0 control horizon. """ highest_orig_datetime: Optional[datetime] = None def historic_hours_min(self) -> int: """Day-ahead source without seasonal extrapolation — keep two days.""" return 48 @classmethod def provider_id(cls) -> str: """Return the unique identifier for the dvhub.online feed-in tariff provider.""" return "FeedInTariffDvhubOnline" def _provider_settings(self) -> FeedInTariffDvhubOnlineCommonSettings: settings = self.config.feedintariff.dvhubonline if settings is None: return FeedInTariffDvhubOnlineCommonSettings() return settings @cache_in_file(with_ttl="1 hour") def _request_forecast(self, start_date: str, end_date: str) -> dict[str, Any]: """Fetch market prices from the dvhub.online price API.""" settings = self._provider_settings() url = ( f"{settings.base_url}/api/prices?start={start_date}&end={end_date}&zone={settings.zone}" ) # Retry transient network problems with a short backoff (same pattern # as FeedInTariffEnergyCharts): (connect, read) timeout tuple. max_attempts = 3 last_exc: Optional[Exception] = None for attempt in range(1, max_attempts + 1): try: response = requests.get( url, headers={"accept": "application/json"}, timeout=(5, 60) ) logger.debug(f"Response from {url}: {response}") response.raise_for_status() data = response.json() if not isinstance(data, dict) or not isinstance(data.get("data"), list): raise ValueError(f"Unexpected dvhub.online price API response shape from {url}") self.update_datetime = to_datetime(in_timezone=self.config.general.timezone) return data except ( requests.exceptions.Timeout, requests.exceptions.ConnectionError, ) as exc: last_exc = exc logger.warning( "dvhub.online price request attempt {}/{} failed: {}", attempt, max_attempts, exc, ) if attempt < max_attempts: time.sleep(2 * attempt) raise last_exc # type: ignore[misc] def _parse_data(self, dvhub_data: dict[str, Any]) -> pd.Series: """dvhub.online entries {ts, price[EUR/MWh]} -> Series of EUR/Wh.""" series_data = pd.Series(dtype=float) for entry in dvhub_data.get("data", []): try: orig_datetime = to_datetime(entry["ts"], in_timezone=self.config.general.timezone) price_eur_per_mwh = float(entry["price"]) except (KeyError, TypeError, ValueError) as exc: logger.warning("Skipping malformed dvhub.online price entry {}: {}", entry, exc) continue series_data.at[orig_datetime] = price_eur_per_mwh / 1_000_000 return series_data async def _update_data(self, force_update: Optional[bool] = False) -> None: """Update feed-in tariff forecast data from dvhub.online.""" if not self.ems_start_datetime: raise ValueError(f"Start DateTime not set: {self.ems_start_datetime}") start_date = to_datetime( self.ems_start_datetime - to_duration("2 days"), as_string="YYYY-MM-DD" ) end_date = to_datetime(self.end_datetime, as_string="YYYY-MM-DD") dvhub_data = self._request_forecast( start_date=start_date, end_date=end_date, force_update=force_update ) # type: ignore[call-arg] series_data = self._parse_data(dvhub_data) if series_data.empty: raise ValueError("No dvhub.online feed-in tariff data available") await self.key_from_series("feed_in_tariff_wh", series_data) self.highest_orig_datetime = series_data.index.max()