feat(pvforecast): add adaptive per-plane PV learning and diagnostics (#1422)

PV arrays with different orientations and curtailment need separate plant calibration and weather correction. This opt-in provider publishes normal EOS AC/DC forecast keys at 15-minute resolution.

- Preserve daily per-plane energy/shape calibration and validated short-term local/trend selection. Curtailment-sensitive arrays require a fresh release flag or an explicitly configured learning guard.
-  Add switchable empirical solar-angle response relative to separate eligible reference arrays, removing their common weather error. This learns angular residuals, not physical angles or a measured geometric horizon.
-  Archive actually received weather model inputs, first local receipt and frozen per-member PV candidates. Returned past weather is excluded; unknown source issuance remains explicit. Learn model weights and forecast-regime bias separately at 2–6, 6–24 and 24–48 hours.
- New long-horizon candidates remain in shadow until their genuinely issued outputs improve equal-day MAE by the configured margin, win on at least 60% of validation days and pass a matched-support energy-bias guard. Insufficient evidence retains calibration. Daily yields still require complete local days, including DST.
- Expose fitted parameters, independent training/validation day counts, errors, selected methods and persistence in the existing status API, with additional normal prediction keys for Grafana. Retain physical DC through angular/weather corrections an  enforce individual inverter AC limits.

Co-authored-by: Normann <github@koldrack.com>
Co-authored-by: Christin <chrissi@von-perbandt.de>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: YMT <yn276364@dal.ca>
Co-authored-by: sarankumar1325 <120080287+sarankumar1325@users.noreply.github.com>

tests/test_prediction.py

@@ -27,6 +27,9 @@ from akkudoktoreos.prediction.prediction import (
     Prediction,
     PredictionCommonSettings,
 )
+from akkudoktoreos.prediction.pvakkuadapt import (
+    PVForecastAdaptiveAkkudoktor,
+)
 from akkudoktoreos.prediction.pvforecastakkudoktor import PVForecastAkkudoktor
 from akkudoktoreos.prediction.pvforecastforecastsolar import PVForecastForecastSolar
 from akkudoktoreos.prediction.pvforecasthomeassistant import PVForecastHomeAssistant
@@ -75,6 +78,7 @@ def forecast_providers():
         LoadImport(),
         LoadVrm(),
         PVForecastAkkudoktor(),
+        PVForecastAdaptiveAkkudoktor(),
         PVForecastForecastSolar(),
         PVForecastHomeAssistant(),
         PVForecastImport(),
@@ -138,19 +142,23 @@ def test_provider_sequence(prediction):
     assert isinstance(prediction.providers[21], LoadImport)
     assert isinstance(prediction.providers[22], LoadVrm)
     assert isinstance(prediction.providers[23], PVForecastAkkudoktor)
-    assert isinstance(prediction.providers[24], PVForecastForecastSolar)
-    assert isinstance(prediction.providers[25], PVForecastHomeAssistant)
-    assert isinstance(prediction.providers[26], PVForecastImport)
-    assert isinstance(prediction.providers[27], PVForecastPVLib)
-    assert isinstance(prediction.providers[28], PVForecastPVNode)
-    assert isinstance(prediction.providers[29], PVForecastSolcast)
-    assert isinstance(prediction.providers[30], PVForecastVrm)
+    assert isinstance(prediction.providers[24], PVForecastAdaptiveAkkudoktor)
+    assert isinstance(prediction.providers[25], PVForecastForecastSolar)
+    assert isinstance(prediction.providers[26], PVForecastHomeAssistant)
+    assert isinstance(prediction.providers[27], PVForecastImport)
+    assert isinstance(prediction.providers[28], PVForecastPVLib)
+    assert isinstance(prediction.providers[29], PVForecastPVNode)
+    assert isinstance(prediction.providers[30], PVForecastSolcast)
+    assert isinstance(prediction.providers[31], PVForecastVrm)
 
 
 def test_provider_by_id(prediction, forecast_providers):
     """Test that provider_by_id method returns the correct provider."""
     for provider in forecast_providers:
-        assert prediction.provider_by_id(provider.provider_id()).provider_id() == provider.provider_id()
+        assert (
+            prediction.provider_by_id(provider.provider_id()).provider_id()
+            == provider.provider_id()
+        )
 
 
 def test_prediction_repr(prediction):