dalsi pokusy

backend/tests/test_planning_charge_slot_selection.py

@@ -211,6 +211,10 @@ def _select_charge_slots(
             grid_pm += 1
         grid_filled_wh += cum
 
+        for t, s in enumerate(slots):
+            if float(s.buy_price) < 0:
+                selected.add(t)
+
     pv_layer_cap = max(charge_target_wh - grid_filled_wh, 0.0)
     pv_candidates: list[tuple[int, float, float]] = []
     for t, s in enumerate(slots):
@@ -279,6 +283,33 @@ def _select_discharge_export_slots(
             break
         selected.add(t)
         cum += per_slot_wh
+
+    max_sell = max((float(s.sell_price) for s in slots), default=0.0)
+    if max_sell > 0:
+        for t, s in enumerate(slots):
+            if float(s.sell_price) >= max_sell - degrad and float(s.sell_price) > sell_min:
+                selected.add(t)
+
+    first_neg = next(
+        (i for i, s in enumerate(slots) if float(s.sell_price) < 0),
+        None,
+    )
+    preneg_min_soc = min_soc_wh + max(per_slot_wh, 1000.0)
+    if (
+        first_neg is not None
+        and first_neg > 0
+        and current_soc_wh >= preneg_min_soc
+    ):
+        neg_day = _prague_date(slots[first_neg])
+        positive = [
+            i
+            for i in range(first_neg)
+            if float(slots[i].sell_price) >= 0 and _prague_date(slots[i]) == neg_day
+        ]
+        if positive:
+            peak_t = max(positive, key=lambda i: (float(slots[i].sell_price), i))
+            selected.add(peak_t)
+
     return selected