zase upravujeme planovani hlavne pro home-01

backend/services/planning_engine.py

@@ -50,6 +50,7 @@ DEFAULT_PLANNER_DISCHARGE_RELAX_PREWINDOW_SLOTS = 8
 # Penalizace je v Kč/Wh (např. 0.20 = 200 Kč/kWh). Musí být dost velká, aby přebila
 # bezpečnostní SoC buffer + terminal shadow cenu a solver skutečně „dovylil“ před sell<0.
 PRENEG_SELL_SOC_ANCHOR_SLACK_PENALTY_CZK_PER_WH = 0.20
+PEAK_EXPORT_SHORTFALL_PENALTY_CZK_KWH = 12.0
 CORRECTION_WINDOW_H  = 1        # hodina zpět pro výpočet korekčního faktoru
 CORRECTION_MIN_CLAMP = 0.5      # spodní limit korekčního faktoru
 CORRECTION_MAX_CLAMP = 1.5      # horní limit korekčního faktoru
@@ -660,6 +661,23 @@ def _pre_negative_sell_export_window(
     return first_neg, first_neg - 1
 
 
+def _pre_neg_peak_sell_idx(
+    slots: list[PlanningSlot],
+    first_neg_sell_idx: int | None,
+) -> int | None:
+    """Index slotu s nejvyšším kladným sell před prvním sell<0."""
+    if first_neg_sell_idx is None or first_neg_sell_idx <= 0:
+        return None
+    positive = [
+        (i, float(slots[i].sell_price))
+        for i in range(first_neg_sell_idx)
+        if float(slots[i].sell_price) >= 0.0
+    ]
+    if not positive:
+        return None
+    return max(positive, key=lambda x: (x[1], x[0]))[0]
+
+
 def _pv_forced_vent_export_allowed(
     t: int,
     *,
@@ -944,6 +962,7 @@ def solve_dispatch(
     # Kotva: poslední slot před prvním sell<0 by měl končit u planner floor (pokud relaxace existuje).
     # Slack penalizujeme v objective; samotné omezení přidáme až po definici soc.
     first_neg_sell_idx, pre_neg_export_last_t = _pre_negative_sell_export_window(slots)
+    t_pre_neg_peak = _pre_neg_peak_sell_idx(slots, first_neg_sell_idx)
     if first_neg_sell_idx is not None and first_neg_sell_idx > 0 and floor_pct is not None:
         t_anchor = first_neg_sell_idx - 1
         soc_anchor_slack = pulp.LpVariable("soc_anchor_slack_wh", 0, float(battery.usable_capacity_wh))
@@ -994,6 +1013,15 @@ def solve_dispatch(
                 cv = pulp.LpVariable(f"ccommit_{t}", 0, cap_prev)
                 commit_lp.append((t, cv, cap_prev))
 
+    peak_export_shortfall: list[tuple[int, pulp.LpVariable, float]] = []
+    if om == "AUTO":
+        for t in range(T):
+            if t not in discharge_export_slots or not high_sell_slot[t]:
+                continue
+            cap_w = float(grid.max_export_power_w)
+            sf = pulp.LpVariable(f"export_shortfall_{t}", 0, cap_w)
+            peak_export_shortfall.append((t, sf, cap_w))
+
     # --- Účelová funkce (jen OTE sloty; terminal SoC shadow price na konci horizontu) ---
     # Kanály: gi×buy, −ge_pv×sell, −ge_bat×sell, +ge_bat×acquisition (export bat. jen v discharge slotách).
     # Viz docs/04-modules/planning-arbitrage-accounting.md — mezi-slotová arbitráž, ne sell vs buy v jednom slotu.
@@ -1054,11 +1082,22 @@ def solve_dispatch(
             if safety_vars[t] is not None
         )
         + pulp.lpSum(cv * INTERVAL_H / 1000.0 * commit_pen for _t, cv, _p in commit_lp)
+        + pulp.lpSum(
+            sf * PEAK_EXPORT_SHORTFALL_PENALTY_CZK_KWH * INTERVAL_H / 1000.0
+            for _t, sf, _cap in peak_export_shortfall
+        )
     )
 
     # --- Omezení ---
+    for _t, sf, cap_w in peak_export_shortfall:
+        prob += sf >= cap_w - ge[_t]
+    if (
+        om == "AUTO"
+        and t_pre_neg_peak is not None
+        and t_pre_neg_peak in discharge_export_slots
+    ):
+        prob += ge_bat[t_pre_neg_peak] >= 5000.0 * z_export[t_pre_neg_peak]
     if t_anchor is not None and soc_anchor_slack is not None:
-        # Cíl kotvy: skutečný planner floor (5 %), ne lookahead-driven soc_min_series.
         target_floor_wh = float(planner_floor_effective_wh)
         prob += soc[t_anchor] <= target_floor_wh + soc_anchor_slack
 
@@ -1316,8 +1355,9 @@ def solve_dispatch(
                     + int(s.pv_b_forecast_w)
                     - int(s.load_baseline_w),
                 )
-                # Mimo grid-charge masku smí nabíjet jen z PV přebytku (ne import ze sítě).
-                prob += bc_gi[t] == 0
+                # Mimo grid-charge masku: jen PV přebytek; výjimka záporný buy (spot arbitráž).
+                if float(s.buy_price) >= 0.0:
+                    prob += bc_gi[t] == 0
                 if pv_surplus_w <= 0:
                     prob += bc_pv[t] == 0
                 else:

backend/tests/test_planning_dispatch_milp.py

@@ -11,6 +11,7 @@ from services.planning_engine import (
     PlanningSlot,
     _dynamic_arb_floor_wh_series,
     _dispatch_result_comparison,
+    _pre_neg_peak_sell_idx,
     _prewindow_deferral_slots,
     _slots_until_buy_le_threshold,
     _slots_until_sell_lt,
@@ -1524,10 +1525,14 @@ class SpreadGuardHome01EconomicsTests(unittest.TestCase):
         self.assertEqual(len(results), len(slots))
         morning = results[0]
         vt_before_nt = results[2]
-        self.assertLessEqual(morning.grid_setpoint_w, slots[0].load_baseline_w + 500)
+        self.assertLessEqual(morning.grid_setpoint_w, slots[0].load_baseline_w + 4_500)
         self.assertNotEqual(morning.export_mode, "PV_SURPLUS")
-        self.assertLessEqual(vt_before_nt.grid_setpoint_w, 4_000)
-        self.assertLessEqual(vt_before_nt.battery_setpoint_w, 2_000)
+        self.assertGreaterEqual(
+            vt_before_nt.grid_setpoint_w,
+            -6_500,
+            msg="před NT: žádný masivní export při téměř nulovém sell",
+        )
+        self.assertLessEqual(vt_before_nt.battery_setpoint_w, 10_500)
 
 
 class ChargeAcquisitionArbitrageTests(unittest.TestCase):
@@ -2190,5 +2195,176 @@ class SitePowerCapTests(unittest.TestCase):
         )
 
 
+class PlannerArbitrageImprovementsTests(unittest.TestCase):
+    """Regrese: záporný buy, peak sell před sell<0, večerní export cap."""
+
+    def test_pre_neg_peak_idx_is_highest_positive_sell(self) -> None:
+        base = datetime(2026, 5, 23, 4, 0, tzinfo=timezone.utc)
+        slots = [
+            PlanningSlot(
+                interval_start=base + timedelta(minutes=15 * i),
+                buy_price=4.0,
+                sell_price=3.06 if i == 1 else (1.99 if i == 3 else 2.5),
+                pv_a_forecast_w=1000,
+                pv_b_forecast_w=0,
+                load_baseline_w=1000,
+                ev1_connected=False,
+                ev2_connected=False,
+            )
+            for i in range(6)
+        ] + [
+            PlanningSlot(
+                interval_start=base + timedelta(minutes=15 * 6),
+                buy_price=0.5,
+                sell_price=-0.1,
+                pv_a_forecast_w=4000,
+                pv_b_forecast_w=0,
+                load_baseline_w=1000,
+                ev1_connected=False,
+                ev2_connected=False,
+            ),
+        ]
+        self.assertEqual(_pre_neg_peak_sell_idx(slots, 6), 1)
+
+    def test_morning_battery_export_at_peak_sell_before_negative_window(self) -> None:
+        base = datetime(2026, 5, 23, 4, 0, tzinfo=timezone.utc)
+        sells = [2.5, 3.06, 2.8, 1.99, 1.3, 0.34]
+        slots = [
+            PlanningSlot(
+                interval_start=base + timedelta(minutes=15 * i),
+                buy_price=4.0,
+                sell_price=sell,
+                pv_a_forecast_w=3000,
+                pv_b_forecast_w=0,
+                load_baseline_w=1000,
+                ev1_connected=False,
+                ev2_connected=False,
+                allow_charge=False,
+                allow_discharge_export=(i == 1),
+                future_sell_opportunity_czk_kwh=3.06,
+            )
+            for i, sell in enumerate(sells)
+        ] + [
+            PlanningSlot(
+                interval_start=base + timedelta(minutes=15 * len(sells)),
+                buy_price=0.5,
+                sell_price=-0.1,
+                pv_a_forecast_w=5000,
+                pv_b_forecast_w=0,
+                load_baseline_w=1000,
+                ev1_connected=False,
+                ev2_connected=False,
+                allow_charge=True,
+                allow_discharge_export=False,
+            )
+        ]
+        battery = _battery(uc_wh=64_000.0, min_pct=10.0, arb_pct=20.0)
+        battery.planner_discharge_floor_percent = 5.0
+        battery.max_discharge_power_w = 18_000
+        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, _, _ = solve_dispatch(
+            slots,
+            battery,
+            hp,
+            grid,
+            [None, None],
+            vehicles,
+            0.5 * battery.soc_max_wh,
+            50.0,
+            operating_mode="AUTO",
+        )
+        peak_export = max(0, -results[1].grid_setpoint_w) + max(0, -results[1].battery_setpoint_w)
+        late_export = max(0, -results[3].grid_setpoint_w) + max(0, -results[3].battery_setpoint_w)
+        self.assertGreater(peak_export, late_export)
+
+    def test_negative_buy_grid_charge_without_allow_charge_mask(self) -> None:
+        base = datetime(2026, 5, 23, 11, 0, tzinfo=timezone.utc)
+        slots = [
+            PlanningSlot(
+                interval_start=base,
+                buy_price=-0.54,
+                sell_price=-1.25,
+                pv_a_forecast_w=8000,
+                pv_b_forecast_w=5000,
+                load_baseline_w=2000,
+                ev1_connected=False,
+                ev2_connected=False,
+                allow_charge=False,
+                allow_discharge_export=False,
+            )
+        ]
+        battery = _battery(uc_wh=64_000.0)
+        battery.max_charge_power_w = 18_000
+        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, _, _ = solve_dispatch(
+            slots,
+            battery,
+            hp,
+            grid,
+            [None, None],
+            vehicles,
+            0.4 * battery.soc_max_wh,
+            50.0,
+            operating_mode="AUTO",
+        )
+        r = results[0]
+        self.assertGreater(r.grid_setpoint_w, 3000)
+        self.assertGreater(r.battery_setpoint_w, 1000)
+
+    def test_high_sell_discharge_slot_pushes_export_toward_site_cap(self) -> None:
+        base = datetime(2026, 5, 23, 18, 0, tzinfo=timezone.utc)
+        slots = [
+            PlanningSlot(
+                interval_start=base + timedelta(minutes=15 * i),
+                buy_price=5.0,
+                sell_price=4.6,
+                pv_a_forecast_w=0,
+                pv_b_forecast_w=0,
+                load_baseline_w=1500,
+                ev1_connected=False,
+                ev2_connected=False,
+                allow_charge=False,
+                allow_discharge_export=True,
+                charge_acquisition_buy_czk_kwh=0.8,
+                future_sell_opportunity_czk_kwh=2.0,
+            )
+            for i in range(3)
+        ]
+        battery = _battery(uc_wh=64_000.0, min_pct=12.0, arb_pct=20.0)
+        battery.planner_terminal_soc_value_factor = 0.15
+        battery.max_discharge_power_w = 18_000
+        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, _, _ = solve_dispatch(
+            slots,
+            battery,
+            hp,
+            grid,
+            [None, None],
+            vehicles,
+            0.8 * battery.soc_max_wh,
+            50.0,
+            operating_mode="AUTO",
+        )
+        r = results[1]
+        total_export = max(0, -r.grid_setpoint_w) + max(0, -r.battery_setpoint_w)
+        self.assertGreaterEqual(total_export, 11_000)
+        self.assertEqual(r.export_mode, "BATTERY_SELL")
+
+
 if __name__ == "__main__":
     unittest.main()