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_database.py

@@ -10,7 +10,7 @@ import shutil
 import tempfile
 import time
 from pathlib import Path
-from typing import AsyncIterator, Optional, Type
+from typing import Any, AsyncIterator, Optional, Type, cast
 
 import pytest
 import pytest_asyncio
@@ -876,3 +876,26 @@ class TestPerformance:
         assert loaded == n
         print(f"\nLoaded {n} records in {load_duration:.2f}s "
               f"({n / load_duration:.0f} rec/s)")
+
+@pytest.mark.asyncio
+async def test_sqlite_bulk_operations_rollback_as_one_transaction(config_eos):
+    import sqlite3
+
+    config_eos.database.provider = "SQLite"
+    db = get_database()
+    await db.open()
+    try:
+        await db.save_records([(b"first", b"original"), (b"second", b"other")], namespace="atomic")
+        with pytest.raises(sqlite3.ProgrammingError):
+            await db.save_records(
+                [(b"first", b"changed"), (b"bad", cast(Any, object()))], namespace="atomic"
+            )
+        assert dict([row async for row in db.iterate_records(namespace="atomic")]) == {
+            b"first": b"original",
+            b"second": b"other",
+        }
+        with pytest.raises(sqlite3.ProgrammingError):
+            await db.delete_records([b"first", cast(Any, object())], namespace="atomic")
+        assert await db.count_records(namespace="atomic") == 2
+    finally:
+        await db.close()