Fix daily planner: pass forecast + budget to plan_day()

backend/workers/daily_planner.py

@@ -33,16 +33,69 @@ logging.basicConfig(
 log = logging.getLogger("daily_planner")
 
 
+def _get_forecast(target: date):
+    """Build 96-slot (15-min) forecast arrays from IMS cache or defaults."""
+    try:
+        from src.data.ims_client import IMSClient
+        import pandas as pd
+
+        client = IMSClient()
+        df = client.load_cached()
+        if df.empty:
+            raise ValueError("No IMS cache available")
+
+        # Get the most recent day's pattern as a proxy for tomorrow
+        df["hour"] = pd.to_datetime(df["timestamp_utc"]).dt.hour
+        # Build 96 slots of temp and GHI
+        temps = []
+        ghis = []
+        for slot in range(96):
+            h = slot // 4
+            # Use mean values per hour from recent data
+            hour_data = df[df["hour"] == h]
+            t = hour_data["air_temperature_c"].mean() if "air_temperature_c" in df.columns and not hour_data.empty else 25.0
+            g = hour_data["ghi_w_m2"].mean() if "ghi_w_m2" in df.columns and not hour_data.empty else 0.0
+            temps.append(float(t) if not pd.isna(t) else 25.0)
+            ghis.append(float(g) if not pd.isna(g) else 0.0)
+        return temps, ghis
+    except Exception as exc:
+        log.warning("Could not build forecast from IMS: %s — using defaults", exc)
+        # Default: sinusoidal temperature and GHI profile for Sde Boker
+        import math
+        temps = []
+        ghis = []
+        for slot in range(96):
+            h = slot / 4  # fractional hour
+            # Temp: 18°C at night, peaks ~35°C at 14:00
+            t = 26.5 + 8.5 * math.sin(math.pi * (h - 6) / 12) if 6 <= h <= 18 else 20.0
+            # GHI: 0 at night, peaks ~900 W/m² at noon
+            g = max(0, 900 * math.sin(math.pi * (h - 6) / 12)) if 6 <= h <= 18 else 0.0
+            temps.append(round(t, 1))
+            ghis.append(round(g, 1))
+        return temps, ghis
+
+
 def main():
     from src.day_ahead_planner import DayAheadPlanner
     from src.data.redis_cache import get_redis
-    from config.settings import DAILY_PLAN_PATH
+    from config.settings import DAILY_PLAN_PATH, MAX_ENERGY_REDUCTION_PCT
 
     target = date.today()
     log.info("Computing day-ahead plan for %s", target)
 
+    # Build forecast inputs
+    forecast_temps, forecast_ghi = _get_forecast(target)
+
+    # Compute a reasonable daily budget (5% of ~25 kWh potential = ~1.25 kWh)
+    daily_budget_kwh = 25.0 * MAX_ENERGY_REDUCTION_PCT / 100.0
+
     planner = DayAheadPlanner()
-    plan = planner.plan(target_date=target)
+    plan = planner.plan_day(
+        target_date=target,
+        forecast_temps=forecast_temps,
+        forecast_ghi=forecast_ghi,
+        daily_budget_kwh=daily_budget_kwh,
+    )
 
     plan_dict = plan.to_dict() if hasattr(plan, "to_dict") else {"raw": str(plan)}
     plan_dict["_computed_at"] = datetime.now(timezone.utc).isoformat()