246 lines
9.0 KiB
Python
246 lines
9.0 KiB
Python
"""Pre-selection nabíjecích slotů (anti-micro-cycling) – referenční Python.
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Logika je v DB: ems.fn_load_planning_slots_full. Tento soubor drží kopii algoritmu
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pro rychlé unit testy bez PostgreSQL.
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Algoritmus (aktuální):
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A) PV-surplus sloty (pv_surplus > 0): ranking dle sell_price ASC,
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vyberou se nejlevnější, dokud kumulativní PV surplus nepokryje
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charge target (energy_to_fill × charge_buf). Zbylé → PV do sítě.
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B) Non-PV sloty (pv_surplus <= 0): AM/PM rozpočet 50/50,
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OTE-first priorita (is_predicted_price=false před true),
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poté seřazené dle buy_price ASC.
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"""
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from __future__ import annotations
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import unittest
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from datetime import datetime, timezone, timedelta
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from types import SimpleNamespace
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from zoneinfo import ZoneInfo
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from services.planning_engine import INTERVAL_H, PlanningSlot
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_PRAGUE = ZoneInfo("Europe/Prague")
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def _select_charge_slots(
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slots: list[PlanningSlot],
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battery: SimpleNamespace,
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current_soc_wh: float,
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) -> set[int]:
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"""Kopie logiky z ems.fn_load_planning_slots_full (charge mask)."""
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charge_buf = float(getattr(battery, "charge_slot_buffer", 0) or 0)
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if charge_buf <= 0:
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return set(range(len(slots)))
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energy_to_fill = float(battery.soc_max_wh) - float(current_soc_wh)
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if energy_to_fill <= 0:
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return set(range(len(slots)))
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eta = float(getattr(battery, "charge_efficiency", 1.0) or 1.0)
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max_p_w = float(getattr(battery, "max_charge_power_w", 0.0) or 0.0)
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per_slot_full_wh = max_p_w * eta * INTERVAL_H
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charge_target_wh = max(energy_to_fill, 0) * charge_buf
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# AM/PM budget
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n_am = sum(1 for s in slots if _prague_hour(s) < 12)
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n_pm = len(slots) - n_am
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if n_am <= 0:
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chg_am = 0.0
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chg_pm = charge_target_wh
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elif n_pm <= 0:
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chg_am = charge_target_wh
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chg_pm = 0.0
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else:
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chg_am = charge_target_wh / 2.0
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chg_pm = charge_target_wh - chg_am
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selected: set[int] = set()
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# A) PV-surplus: cheapest sell_price first
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pv_candidates: list[tuple[int, float, float]] = []
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for t, s in enumerate(slots):
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pv_surplus_w = max(0, s.pv_a_forecast_w + s.pv_b_forecast_w - s.load_baseline_w)
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if pv_surplus_w > 0:
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pv_candidates.append((t, float(s.sell_price), float(pv_surplus_w)))
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pv_candidates.sort(key=lambda x: (x[1], x[0]))
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cum = 0.0
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for t, _sell, pv_surplus_w in pv_candidates:
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if cum >= charge_target_wh:
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break
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selected.add(t)
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cum += min(pv_surplus_w, max_p_w) * eta * INTERVAL_H
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# B) Non-PV: AM budget (OTE-first)
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am_candidates = [
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(t, getattr(slots[t], "is_predicted_price", False), float(slots[t].buy_price))
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for t in range(len(slots))
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if t not in selected
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and max(0, slots[t].pv_a_forecast_w + slots[t].pv_b_forecast_w - slots[t].load_baseline_w) <= 0
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and _prague_hour(slots[t]) < 12
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]
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am_candidates.sort(key=lambda x: (int(x[1]), x[2], x[0]))
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cum = 0.0
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for t, _pred, _price in am_candidates:
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if cum >= chg_am or per_slot_full_wh <= 0:
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break
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selected.add(t)
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cum += per_slot_full_wh
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# B) Non-PV: PM budget (OTE-first)
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pm_candidates = [
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(t, getattr(slots[t], "is_predicted_price", False), float(slots[t].buy_price))
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for t in range(len(slots))
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if t not in selected
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and max(0, slots[t].pv_a_forecast_w + slots[t].pv_b_forecast_w - slots[t].load_baseline_w) <= 0
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and _prague_hour(slots[t]) >= 12
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]
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pm_candidates.sort(key=lambda x: (int(x[1]), x[2], x[0]))
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cum = 0.0
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for t, _pred, _price in pm_candidates:
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if cum >= chg_pm or per_slot_full_wh <= 0:
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break
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selected.add(t)
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cum += per_slot_full_wh
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return selected
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def _prague_hour(s: PlanningSlot) -> int:
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dt = s.interval_start
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if dt.tzinfo is None:
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dt = dt.replace(tzinfo=timezone.utc)
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return dt.astimezone(_PRAGUE).hour
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def _slot(
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*,
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buy: float,
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sell: float = 1.0,
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pv: int = 0,
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load: int = 2_000,
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hour_utc: int = 12,
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predicted: bool = False,
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) -> PlanningSlot:
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return PlanningSlot(
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interval_start=datetime(2026, 5, 19, hour_utc, 0, tzinfo=timezone.utc),
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buy_price=buy,
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sell_price=sell,
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pv_a_forecast_w=0,
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pv_b_forecast_w=pv,
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load_baseline_w=load,
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ev1_connected=False,
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ev2_connected=False,
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is_predicted_price=predicted,
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)
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def _battery(
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*,
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charge_buf: float = 1.3,
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uc_wh: float = 64_000.0,
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soc_max_pct: float = 95.0,
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max_charge_w: float = 18_000.0,
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charge_eff: float = 0.95,
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) -> SimpleNamespace:
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return SimpleNamespace(
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usable_capacity_wh=uc_wh,
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soc_max_wh=soc_max_pct / 100.0 * uc_wh,
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max_charge_power_w=max_charge_w,
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charge_efficiency=charge_eff,
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charge_slot_buffer=charge_buf,
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)
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class SelectChargeSlotsTests(unittest.TestCase):
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def test_buffer_zero_returns_all_slots(self) -> None:
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slots = [_slot(buy=3.0) for _ in range(4)]
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battery = _battery(charge_buf=0.0)
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out = _select_charge_slots(slots, battery, current_soc_wh=0.0)
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self.assertEqual(out, set(range(4)))
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def test_returns_all_when_battery_is_full(self) -> None:
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slots = [_slot(buy=0.1) for _ in range(3)]
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battery = _battery()
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out = _select_charge_slots(
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slots, battery, current_soc_wh=battery.soc_max_wh + 1.0
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)
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self.assertEqual(out, set(range(3)))
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def test_pv_surplus_cheapest_sell_price_selected(self) -> None:
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"""PV-surplus sloty s nejnižší sell_price se vybírají přednostně."""
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slots = [
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_slot(buy=1.0, sell=2.0, pv=8_000, load=2_000),
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_slot(buy=1.0, sell=5.0, pv=8_000, load=2_000),
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_slot(buy=1.0, sell=3.0, pv=8_000, load=2_000),
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]
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battery = _battery(
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charge_buf=1.3, uc_wh=1_000.0, soc_max_pct=100.0, max_charge_w=6_000.0
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)
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out = _select_charge_slots(slots, battery, current_soc_wh=0.0)
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self.assertIn(0, out, "Cheapest sell_price PV slot must be selected")
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self.assertNotIn(1, out, "Expensive sell_price PV slot should be excluded")
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def test_non_pv_slots_selected_with_am_pm_budget(self) -> None:
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"""Non-PV sloty se vybírají dle buy_price v rámci AM/PM rozpočtu."""
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slots = [
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_slot(buy=0.5, hour_utc=4), # AM slot, cheap
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_slot(buy=3.0, hour_utc=5), # AM slot, expensive
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_slot(buy=0.4, hour_utc=14), # PM slot, cheap
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_slot(buy=9.9, hour_utc=15), # PM slot, expensive
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]
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battery = _battery(
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charge_buf=1.3, uc_wh=5_000.0, soc_max_pct=100.0, max_charge_w=18_000.0
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)
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out = _select_charge_slots(slots, battery, current_soc_wh=0.0)
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self.assertIn(0, out, "Cheapest AM slot must be selected")
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self.assertIn(2, out, "Cheapest PM slot must be selected")
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def test_ote_slots_prioritized_over_predicted(self) -> None:
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"""OTE sloty (is_predicted_price=false) mají přednost před predikovanými."""
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slots = [
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_slot(buy=3.56, hour_utc=13, predicted=False), # OTE, dražší
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_slot(buy=2.00, hour_utc=13, predicted=True), # predicted, levnější
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]
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battery = _battery(
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charge_buf=1.3, uc_wh=3_000.0, soc_max_pct=100.0, max_charge_w=18_000.0
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)
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out = _select_charge_slots(slots, battery, current_soc_wh=0.0)
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self.assertIn(0, out, "OTE slot must be selected even if pricier than predicted")
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def test_does_not_exclude_slot_just_because_pv_below_load(self) -> None:
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"""Regrese: sloty bez PV-surplus se vybírají přes AM/PM grid budget."""
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slots = [
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_slot(buy=0.4, pv=3_320, load=3_747, hour_utc=13),
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_slot(buy=0.42, pv=2_116, load=3_747, hour_utc=13),
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_slot(buy=0.44, pv=1_649, load=3_747, hour_utc=13),
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_slot(buy=0.47, pv=1_276, load=3_747, hour_utc=13),
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]
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battery = _battery()
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out = _select_charge_slots(slots, battery, current_soc_wh=0.2 * battery.usable_capacity_wh)
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for idx in (0, 1, 2, 3):
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self.assertIn(idx, out)
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def test_long_horizon_pv_surplus_does_not_exhaust_grid_budget(self) -> None:
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"""Regrese: v 96h horizontu nesmí PV-surplus sloty „vyžrat" grid rozpočet."""
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cheap_grid = [_slot(buy=0.4 + 0.01 * i, pv=0, load=2_000) for i in range(40)]
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pv_days = [_slot(buy=1.5, sell=1.5, pv=10_000, load=2_000) for _ in range(100)]
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slots = cheap_grid + pv_days
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battery = _battery(
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charge_buf=1.3, uc_wh=64_000.0, soc_max_pct=95.0, max_charge_w=18_000.0
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)
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out = _select_charge_slots(slots, battery, current_soc_wh=0.2 * battery.usable_capacity_wh)
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grid_selected = sum(1 for i in range(len(cheap_grid)) if i in out)
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self.assertGreaterEqual(
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grid_selected,
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5,
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"V dlouhém horizontu s mnoha PV-surplus sloty musí zůstat dostatek "
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"grid slotů povolených pro nabíjení z levného importu.",
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)
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if __name__ == "__main__":
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unittest.main()
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