mirror of
https://github.com/Akkudoktor-EOS/EOS.git
synced 2026-10-09 07:56:40 +00:00
Andreas
a2f4ef6f54
The optimizer treated the end of `optimization.horizon_hours` as the end of the world: energy left in the battery there was worth a single configured price per kWh, so it either dumped the battery into the last hours or hoarded it, depending on that one number. The horizon is now two spans. `horizon_hours` still receives every control command. The new `optimization.tail_horizon_hours` (default 48 h) is a pure lookahead that never produces a command. In AUTO terminal-value mode a deterministic dynamic program solves that tail backwards on a 101-point SoC grid using the production battery and inverter models - SoC bounds, power caps, conversion losses, configured charge and export rates, direct-marketing permission and LCOS on delivered DC energy - and the existing AUTO proxy supplies the continuation value at the tail end. Genetic fitness reads the resulting curve. `tail_horizon_hours: 0` restores the plain proxy at the control end, FIXED is unchanged. The forecast budget is reported, never enforced by refusal: a tail that does not fit is shortened to what the forecast covers and reported as `effective_tail_hours`, and a control horizon that does not fit is warned about at configuration time and rejected by the optimizer at run time, which knows which series ran out. `prediction.hours` defaults to 72 so the new defaults fit out of the box; existing shorter configurations keep starting. Control arrays and warm-start genomes now begin at the run timestamp rather than midnight, flagged by `controls_start_at_now` so the adapters still read older solutions. `forecast_interval_seconds` declares the resolution of shortened native quarter-hour inputs. Required forecasts are no longer silently replaced by demo providers. A missing PV, price, load, feed-in or weather forecast used to rewrite the configured provider and retry, so a run could quietly optimize against invented data. Missing values now stay missing, and provider values are held only within their own source interval instead of being extended indefinitely. Also fixes a config update that could leave EOS half-updated: the merged candidate is validated before the singleton is reinitialized. Four provider tests that hard-coded the old 48 h prediction default are rewritten to derive their expectations from the configured horizon.
132 lines
4.6 KiB
Python
132 lines
4.6 KiB
Python
"""Tests for the native quarter-hour Tibber feed-in tariff provider."""
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import json
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from unittest.mock import Mock, patch
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import pytest
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from akkudoktoreos.core.coreabc import get_ems
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from akkudoktoreos.optimization.genetic.geneticparams import (
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MARKET_PRICE_FEED_IN_TARIFF_PROVIDERS,
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)
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from akkudoktoreos.prediction.elecpricetibber import TibberGraphQLResponse
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from akkudoktoreos.prediction.feedintarifftibber import FeedInTariffTibber
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from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
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def _point(starts_at: str, energy: float, total: float = 0.40) -> dict[str, object]:
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return {"startsAt": starts_at, "energy": energy, "total": total}
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def _payload(points: list[dict[str, object]]) -> dict[str, object]:
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return {
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"data": {
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"viewer": {
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"homes": [
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{
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"id": "home-1",
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"currentSubscription": {
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"priceInfo": {"today": points[:4], "tomorrow": points[4:]},
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"priceInfoRange": {"nodes": points},
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},
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}
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]
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}
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}
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}
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@pytest.fixture
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def quarter_hour_points():
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return [
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_point(f"2026-07-15T0{index // 4}:{(index % 4) * 15:02d}:00+02:00", 0.10 + index / 100)
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for index in range(8)
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]
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@pytest.fixture
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def provider(config_eos):
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FeedInTariffTibber.reset_instance()
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config_eos.merge_settings_from_dict(
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{
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"elecprice": {"tibber": {"access_token": "token-123", "home_id": "home-1"}},
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"feedintariff": {
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"direct_marketing_enabled": True,
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"provider": "FeedInTariffTibber",
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},
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"prediction": {"hours": 2},
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"optimization": {"horizon_hours": 2, "tail_horizon_hours": 0},
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}
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)
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value = FeedInTariffTibber()
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value.highest_orig_datetime = None
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value.records.clear()
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get_ems().set_start_datetime(
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to_datetime("2026-07-15T00:00:00+02:00", in_timezone="Europe/Berlin")
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)
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return value
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def test_provider_is_registered_and_used_for_direct_marketing(provider, config_eos):
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assert provider.enabled()
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assert "FeedInTariffTibber" in config_eos.feedintariff.providers
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assert "FeedInTariffTibber" in MARKET_PRICE_FEED_IN_TARIFF_PROVIDERS
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def test_parse_uses_energy_component_at_native_quarter_hour_resolution(
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provider, quarter_hour_points
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):
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response = TibberGraphQLResponse.model_validate(_payload(quarter_hour_points))
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series = provider._parse_data(response)
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assert series.tolist() == pytest.approx([(0.10 + index / 100) / 1000 for index in range(8)])
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assert series.index.to_series().diff().dropna().dt.total_seconds().unique().tolist() == [900.0]
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@patch("requests.post")
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def test_request_is_strictly_quarter_hourly_and_requests_energy(
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mock_post, provider, quarter_hour_points
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):
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response = Mock()
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response.content = json.dumps(_payload(quarter_hour_points)).encode()
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response.raise_for_status = Mock()
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mock_post.return_value = response
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provider._request_forecast(force_update=True)
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query = mock_post.call_args.kwargs["json"]["query"]
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assert "priceInfo(resolution: QUARTER_HOURLY)" in " ".join(query.split())
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assert "priceInfoRange(resolution: QUARTER_HOURLY" in " ".join(query.split())
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assert "energy" in query
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assert mock_post.call_args.kwargs["headers"]["Authorization"] == "Bearer token-123"
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def test_update_keeps_four_distinct_prices_per_hour(provider, quarter_hour_points, monkeypatch):
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response = TibberGraphQLResponse.model_validate(_payload(quarter_hour_points))
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monkeypatch.setattr(provider, "_request_forecast", lambda **_: response)
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provider._update_data(force_update=True)
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start = to_datetime("2026-07-15T00:00:00+02:00", in_timezone="Europe/Berlin")
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prices = provider.key_to_array(
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key="feed_in_tariff_wh",
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start_datetime=start,
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end_datetime=start + to_duration("2 hours"),
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interval=to_duration("15 minutes"),
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fill_method="ffill",
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)
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assert prices.tolist() == pytest.approx([(0.10 + index / 100) / 1000 for index in range(8)])
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def test_update_rejects_hourly_tibber_data(provider, monkeypatch):
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hourly = [
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_point("2026-07-15T00:00:00+02:00", 0.10),
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_point("2026-07-15T01:00:00+02:00", 0.11),
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]
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response = TibberGraphQLResponse.model_validate(_payload(hourly))
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monkeypatch.setattr(provider, "_request_forecast", lambda **_: response)
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with pytest.raises(ValueError, match="requires native 15-minute prices"):
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provider._update_data(force_update=True)
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