feat: add raw profile data for Solar 8760 column

- Add load_wind_profile_25y to loader.py
- Store raw profile (0-1 normalized) in hourly_solar_profile
- Solar 8760 shows raw profile values from CSV file
- Compute averages at day/month/year levels from profile

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

packages/engine/src/remodel_engine/catalog/loader.py

@@ -115,3 +115,12 @@ def load_wind_profile(location_id: str) -> np.ndarray:
     if data.shape[0] != 8760:
         raise ValueError(f"Wind profile {path} has {data.shape[0]} rows, expected 8760")
     return data.astype(np.float64)
+
+
+def load_wind_profile_25y(location_id: str) -> np.ndarray:
+    """Return 25-year wind profile array: (25 * 8760,) = (219000,).
+
+    Uses the 8760-hour profile expanded with leap year handling.
+    """
+    source = load_wind_profile(location_id)
+    return _expand_to_25_years(source)

packages/engine/src/remodel_engine/scenarios/runner.py

@@ -13,7 +13,7 @@ Pipeline order:
 from __future__ import annotations
 
 import time
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 
 from remodel_engine.capex.cost_items import ProjectCapacity, compute_capex
 from remodel_engine.capex.idc import compute_idc
@@ -72,12 +72,15 @@ class _PipelineResult:
     total_curtailed_mwh: float | None = None
     total_mcp_revenue_cr: float | None = None
     # Hourly generation: 25 years × 8760 hours = 219,000 values
-    solar_hourly: list[float] = None  # type: ignore[assignment]
+    solar_hourly: list[float] = field(default_factory=list)  # type: ignore[assignment]
-    wind_hourly: list[float] = None  # type: ignore[assignment]
+    wind_hourly: list[float] = field(default_factory=list)  # type: ignore[assignment]
     # Capacity values for hourly display
     solar_dc_mwp: float = 0.0
     wind_mw: float = 0.0
     solar_ac_mw: float = 0.0  # type: ignore[assignment]
+    # Raw profile data (0-1 normalized values from CSV)
+    solar_profile_25y: list[float] = field(default_factory=list)  # type: ignore[assignment]
+    wind_profile_25y: list[float] = field(default_factory=list)  # type: ignore[assignment]
 
 
 def _run_pipeline(inputs: ScenarioInput, tariff: float) -> _PipelineResult:
@@ -93,6 +96,9 @@ def _run_pipeline(inputs: ScenarioInput, tariff: float) -> _PipelineResult:
     solar_dc_mwp = 0.0
     solar_ac_mw = 0.0
     wind_mw = 0.0
+    # Raw profile data (0-1 normalized)
+    solar_profile_25y: list[float] = []
+    wind_profile_25y: list[float] = []
 
     if inputs.solar is not None:
         sol_df = simulate_solar(inputs.solar)
@@ -103,6 +109,9 @@ def _run_pipeline(inputs: ScenarioInput, tariff: float) -> _PipelineResult:
         solar_y1_cuf = float(annual_cuf(sol_df, inputs.solar.capacity_ac_mw).iloc[0])
         solar_dc_mwp = inputs.solar.capacity_dc_mwp
         solar_ac_mw = inputs.solar.capacity_ac_mw
+        # Get raw profile (normalized 0-1) from loader
+        from remodel_engine.catalog.loader import load_solar_profile_25y
+        solar_profile_25y = load_solar_profile_25y(inputs.solar.location_id).tolist()
         # Store all 25 years hourly - convert DataFrame to flat list
         for year in range(25):
             year_data = sol_df[sol_df["year"] == year + 1]["ac_power_mw"].tolist()
@@ -118,6 +127,9 @@ def _run_pipeline(inputs: ScenarioInput, tariff: float) -> _PipelineResult:
         ]
         wind_y1_plf = float(annual_plf(wnd_df, inputs.wind.capacity_mw).iloc[0])
         wind_mw = inputs.wind.capacity_mw
+        # Get raw profile from loader
+        from remodel_engine.catalog.loader import load_wind_profile_25y
+        wind_profile_25y = load_wind_profile_25y(inputs.wind.location_id).tolist()
         # Store all 25 years hourly - convert DataFrame to flat list
         for year in range(25):
             year_data = wnd_df[wnd_df["year"] == year + 1]["ac_power_mw"].tolist()
@@ -327,6 +339,8 @@ def _run_pipeline(inputs: ScenarioInput, tariff: float) -> _PipelineResult:
         solar_dc_mwp=solar_dc_mwp,
         solar_ac_mw=solar_ac_mw,
         wind_mw=wind_mw,
+        solar_profile_25y=solar_profile_25y,
+        wind_profile_25y=wind_profile_25y,
     )
 
 
@@ -557,15 +571,16 @@ def run_scenario(inputs: ScenarioInput) -> ScenarioResult:
             idx = year * 8760 + hour_idx
             solar_val = pipe.solar_hourly[idx] if pipe.solar_hourly and idx < len(pipe.solar_hourly) else 0.0
             wind_val = pipe.wind_hourly[idx] if pipe.wind_hourly and idx < len(pipe.wind_hourly) else 0.0
+            # Raw profile values from CSV (0-1 normalized)
+            solar_profile_val = pipe.solar_profile_25y[idx] if pipe.solar_profile_25y and idx < len(pipe.solar_profile_25y) else 0.0
+            wind_profile_val = pipe.wind_profile_25y[idx] if pipe.wind_profile_25y and idx < len(pipe.wind_profile_25y) else 0.0
             total_re = solar_val + wind_val
             hourly_total_re.append(total_re)
             hourly_client_end.append(total_re * loss_factor)
             hourly_load.append(client_load_mw)
-            # Profile data: actual generation / capacity = normalized profile value
+            # Raw profile (0-1) for Solar 8760 column, final output for Solar MW column
-            # Store: for solar = solar_val (which is DC output), for wind = wind_val
+            hourly_solar_profile.append(solar_profile_val)
-            # User can compute: profile = solar_val / solar_dc_mwp
+            hourly_wind_profile.append(wind_profile_val)
-            hourly_solar_profile.append(solar_val)
-            hourly_wind_profile.append(wind_val)
 
     return ScenarioResult(
         inputs=inputs,