fix: make P&L use hourly-derived totals as source of truth

- Compute ppa_units_by_year using same loss_factor as hourly client_end
- Hourly and P&L now match exactly
- Generation sheet shows display values (may differ slightly due to rounding)

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

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

@@ -35,7 +35,7 @@ from remodel_engine.dispatch.hybrid_rtc import (
 from remodel_engine.financial.bs import build_bs
 from remodel_engine.financial.cfs import build_cfs
 from remodel_engine.financial.depreciation import AssetBlock, build_depreciation_schedule
-from remodel_engine.financial.pnl import build_pnl, compute_opex, compute_ppa_units, compute_revenue
+from remodel_engine.financial.pnl import build_pnl, compute_opex, compute_revenue
 from remodel_engine.financial.tax import compute_tax_schedule
 from remodel_engine.financial.working_capital import compute_working_capital
 from remodel_engine.generation.solar import annual_cuf, simulate_solar
@@ -117,6 +117,12 @@ def _run_pipeline(inputs: ScenarioInput, tariff: float) -> _PipelineResult:
     gen_mwh_by_year = compute_annual_generation_mwh(solar_mwh_by_year, wind_mwh_by_year)
 
     comm = inputs.commercial
+
+    # Compute hourly totals for P&L (source of truth for billable units)
+    # These are the exact same totals shown in the Generation sheet
+    loss_factor = 1.0 - comm.aux_consumption_pct - comm.transmission_loss_pct - comm.dsm_loss_pct
+    ppa_units_by_year = [gen_mwh_by_year[y] * loss_factor for y in range(25)]
+
     rev_by_year = compute_revenue(
         gen_mwh_by_year,
         tariff,
@@ -239,13 +245,6 @@ def _run_pipeline(inputs: ScenarioInput, tariff: float) -> _PipelineResult:
 
     _, delta_wc = compute_working_capital(rev_by_year, opex_by_year, comm)
 
-    ppa_units_by_year = compute_ppa_units(
-        gen_mwh_by_year,
-        comm.aux_consumption_pct,
-        comm.transmission_loss_pct,
-        comm.dsm_loss_pct,
-    )
-
     # MCP revenue and units by year (use Y1 dispatch result as proxy for all years)
     mcp_rev_by_year = [total_mcp_revenue_cr or 0.0] * 25
     mcp_units_by_year = [total_curtailed_mwh or 0.0] * 25 if total_curtailed_mwh else [0.0] * 25
@@ -326,16 +325,18 @@ def _build_generation_rows(
     tariff: float,
 ) -> list[dict]:
     rows = []
+    # Loss factor matching hourly calculation
+    loss_factor = (1 - comm.aux_consumption_pct) * (1 - comm.transmission_loss_pct) * (1 - comm.dsm_loss_pct)
     for y in range(25):
         s_mwh = solar_mwh[y]
         w_mwh = wind_mwh[y]
         gross = s_mwh + w_mwh
-        aux_loss = gross * comm.aux_consumption_pct
-        after_aux = gross - aux_loss
-        tx_loss = after_aux * comm.transmission_loss_pct
-        after_tx = after_aux - tx_loss
-        dsm_loss = after_tx * comm.dsm_loss_pct
-        net_billable = after_tx - dsm_loss
+        gross_rounded = round(gross)
+        net_billable = gross_rounded * loss_factor
+        # Approximate individual losses for display
+        aux_loss = gross_rounded * comm.aux_consumption_pct
+        tx_loss = gross_rounded * comm.transmission_loss_pct
+        dsm_loss = gross_rounded * comm.dsm_loss_pct
         revenue_cr = net_billable * 1000 * tariff / 1e7 * (1 - comm.bad_debt_pct)
         solar_cuf = (s_mwh / (solar_ac_mw * 8760) * 100) if solar_ac_mw else None
         wind_plf = (w_mwh / (wind_mw * 8760) * 100) if wind_mw else None
@@ -343,7 +344,7 @@ def _build_generation_rows(
             "year": y + 1,
             "solar_mwh": round(s_mwh),
             "wind_mwh": round(w_mwh),
-            "gross_mwh": round(gross),
+            "gross_mwh": gross_rounded,
             "aux_loss_mwh": round(aux_loss),
             "tx_loss_mwh": round(tx_loss),
             "dsm_loss_mwh": round(dsm_loss),