feat: Direktvermarktung mit Batterie-Netzeinspeisung

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>

tests/test_strompreis_endpoint.py

@@ -0,0 +1,36 @@
+import pandas as pd
+import pytest
+
+from akkudoktoreos.server import eos as eos_server
+
+
+class _FakeEms:
+    async def run(self, **kwargs):
+        return None
+
+
+class _FakePrediction:
+    def __init__(self):
+        self.key_to_series_kwargs = None
+
+    def key_to_series(self, **kwargs):
+        self.key_to_series_kwargs = kwargs
+        start = pd.Timestamp(kwargs["start_datetime"].isoformat())
+        index = pd.date_range(start=start, periods=8, freq="15min")
+        values = [1.0, 3.0, 5.0, 7.0, 10.0, 14.0, 18.0, 22.0]
+        return pd.Series(values, index=index, name=kwargs["key"])
+
+
+@pytest.mark.asyncio
+async def test_strompreis_endpoint_averages_quarter_hour_prices(monkeypatch, config_eos):
+    """Deprecated /strompreis aggregates 15-minute spot prices to hourly means."""
+    prediction = _FakePrediction()
+
+    monkeypatch.setattr(eos_server, "get_ems", lambda: _FakeEms())
+    monkeypatch.setattr(eos_server, "get_prediction", lambda: prediction)
+
+    result = await eos_server.fastapi_strompreis()
+
+    assert result[:3] == [4.0, 16.0, 16.0]
+    assert len(result) == 48
+    assert prediction.key_to_series_kwargs["key"] == "elecprice_marketprice_wh"