Branch 5: dynamický terminal SoC factor při future neg buy

backend/tests/test_planning_dispatch_milp.py

@@ -42,6 +42,7 @@ from services.planning_engine import (
     _slots_until_buy_le_threshold,
     _slots_until_sell_lt,
     _soc_panel_min_wh_series,
+    _terminal_neg_buy_weight,
     solve_dispatch,
     solve_dispatch_two_pass,
 )
@@ -2717,6 +2718,113 @@ class TerminalSocShadowTests(unittest.TestCase):
             msg="terminal SoC shadow price should keep end-of-horizon SoC above bare minimum",
         )
 
+    def test_terminal_neg_buy_weight_zero_without_future_neg_buy(self) -> None:
+        base = datetime(2026, 4, 3, 12, 0, tzinfo=timezone.utc)
+        slots = [
+            PlanningSlot(
+                interval_start=base + timedelta(minutes=15 * i),
+                buy_price=2.0,
+                sell_price=3.0,
+                pv_a_forecast_w=0,
+                pv_b_forecast_w=0,
+                load_baseline_w=600,
+                ev1_connected=False,
+                ev2_connected=False,
+            )
+            for i in range(8)
+        ]
+        self.assertEqual(_terminal_neg_buy_weight(slots, first_neg_buy_idx=None), 0.0)
+        self.assertEqual(_terminal_neg_buy_weight(slots, first_neg_buy_idx=0), 0.0)
+
+    def test_terminal_neg_buy_weight_scales_with_proximity_and_magnitude(self) -> None:
+        base = datetime(2026, 6, 6, 19, 0, tzinfo=timezone.utc)
+        slots_far: list[PlanningSlot] = []
+        for i in range(96):
+            buy = -0.9 if i >= 64 else 3.0
+            slots_far.append(
+                PlanningSlot(
+                    interval_start=base + timedelta(minutes=15 * i),
+                    buy_price=buy,
+                    sell_price=5.0 if buy > 0 else -0.2,
+                    pv_a_forecast_w=0,
+                    pv_b_forecast_w=0,
+                    load_baseline_w=500,
+                    ev1_connected=False,
+                    ev2_connected=False,
+                )
+            )
+        slots_near: list[PlanningSlot] = []
+        for i in range(32):
+            buy = -1.0 if i >= 8 else 3.0
+            slots_near.append(
+                PlanningSlot(
+                    interval_start=base + timedelta(minutes=15 * i),
+                    buy_price=buy,
+                    sell_price=5.0 if buy > 0 else -0.2,
+                    pv_a_forecast_w=0,
+                    pv_b_forecast_w=0,
+                    load_baseline_w=500,
+                    ev1_connected=False,
+                    ev2_connected=False,
+                )
+            )
+        w_far = _terminal_neg_buy_weight(slots_far, first_neg_buy_idx=64)
+        w_near = _terminal_neg_buy_weight(slots_near, first_neg_buy_idx=8)
+        self.assertGreater(w_far, 0.2)
+        self.assertLess(w_far, 0.75)
+        self.assertGreater(w_near, w_far)
+        self.assertGreater(w_near, 0.8)
+
+    def test_terminal_soc_factor_reduced_when_future_neg_buy(self) -> None:
+        prague = ZoneInfo("Europe/Prague")
+        base = datetime(2026, 6, 6, 19, 0, tzinfo=prague).astimezone(timezone.utc)
+        slots: list[PlanningSlot] = []
+        for i in range(96):
+            local = (base + timedelta(minutes=15 * i)).astimezone(prague)
+            d, h = local.day, local.hour
+            if d == 6:
+                buy, sell = 3.0, 5.3
+            else:
+                buy = -0.89 if 11 <= h < 14 else 2.0
+                sell = -0.2 if 5 <= h < 15 else 2.5
+            slots.append(
+                PlanningSlot(
+                    interval_start=base + timedelta(minutes=15 * i),
+                    buy_price=buy,
+                    sell_price=sell,
+                    pv_a_forecast_w=0,
+                    pv_b_forecast_w=0,
+                    load_baseline_w=500,
+                    ev1_connected=False,
+                    ev2_connected=False,
+                    allow_charge=True,
+                    allow_discharge_export=True,
+                )
+            )
+        battery = _battery(uc_wh=64_000.0, terminal_soc_value_factor=0.9)
+        hp = SimpleNamespace(rated_heating_power_w=0, tuv_min_temp_c=45.0, tuv_target_temp_c=55.0)
+        grid = SimpleNamespace(max_import_power_w=17_000, max_export_power_w=13_500)
+        vehicles = [
+            SimpleNamespace(max_charge_power_w=0, battery_capacity_kwh=1.0, default_target_soc_pct=80.0),
+            SimpleNamespace(max_charge_power_w=0, battery_capacity_kwh=1.0, default_target_soc_pct=80.0),
+        ]
+        _results, _ms, snap = solve_dispatch(
+            slots,
+            battery,
+            hp,
+            grid,
+            [None, None],
+            vehicles,
+            0.5 * battery.soc_max_wh,
+            50.0,
+            operating_mode="AUTO",
+        )
+        w_neg = float(snap["inputs"]["terminal_neg_buy_weight"])
+        eff = float(snap["inputs"]["terminal_soc_factor_effective"])
+        self.assertGreater(w_neg, 0.3)
+        self.assertLess(eff, 0.6)
+        self.assertAlmostEqual(eff, 0.9 * (1.0 - w_neg), places=6)
+
 
 class SpreadGuardHome01EconomicsTests(unittest.TestCase):
     """Regrese: sell≪buy (VT) nesmí vést k PV exportu + masivnímu grid importu ve stejném slotu."""