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7f2ac9098c
Fügt einen Direktvermarktungs-Modus (feedintariff.direct_marketing_enabled) hinzu, der den Börsenpreis als Einspeisevergütung nutzt und aktive Batterie-Entladung ins Netz (battery_grid_export_allowed) sowie DC-Charge-Bypass optimiert. - FeedInTariffEnergyCharts-Provider (Börsen-Einspeisetarif inkl. Prognose) - Inverter: DC/AC-Wirkungsgrade und Batterie-Grid-Export in process_energy - Genetik: Export-/DC-Charge-Zustände, Restwert-Bewertung des Akkus - Solution-Result: neues Feld Feed_in_tariff (verwendeter Tarif je Stunde) - Tests für neue Provider, Solution und Simulation Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
import pandas as pd
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import pytest
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from akkudoktoreos.server import eos as eos_server
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class _FakeEms:
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async def run(self, **kwargs):
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return None
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class _FakePrediction:
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def __init__(self):
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self.key_to_series_kwargs = None
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def key_to_series(self, **kwargs):
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self.key_to_series_kwargs = kwargs
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start = pd.Timestamp(kwargs["start_datetime"].isoformat())
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index = pd.date_range(start=start, periods=8, freq="15min")
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values = [1.0, 3.0, 5.0, 7.0, 10.0, 14.0, 18.0, 22.0]
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return pd.Series(values, index=index, name=kwargs["key"])
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@pytest.mark.asyncio
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async def test_strompreis_endpoint_averages_quarter_hour_prices(monkeypatch, config_eos):
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"""Deprecated /strompreis aggregates 15-minute spot prices to hourly means."""
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prediction = _FakePrediction()
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monkeypatch.setattr(eos_server, "get_ems", lambda: _FakeEms())
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monkeypatch.setattr(eos_server, "get_prediction", lambda: prediction)
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result = await eos_server.fastapi_strompreis()
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assert result[:3] == [4.0, 16.0, 16.0]
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assert len(result) == 48
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assert prediction.key_to_series_kwargs["key"] == "elecprice_marketprice_wh"
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