3b5f07b66e
Hloubková diagnóza EV potvrdila: oportunitní ekonomika via-baterie je v LP
správně, ale okraje lhaly nebo byly nevykonatelné:
- V099 + R__039: ems.ev_session.opportunistic_value_czk_kwh (NULL = zdědit
z asset_vehicle, 0 = vypnout pro session); headroom_wh z max(target_soc,
soc_at_connect) — „nenabíjet" (nízký target) už paradoxně NEzvětšuje
oportunistickou vrstvu; vehicles JSON nese min_power_w wallboxu.
- R__015: patch klíč opportunistic_value_czk_kwh (validace >= 0).
- solver_v2: (a) deadline suma range(t_dl) — slot začínající v deadline už
nepatří „do deadline"; (b) Σ ev_direct <= gi + PV (fyzikální split);
(c) binárka ev_on → setpoint ∈ {0} ∪ [min_power_w, max] (konec 400–900 W
nevykonatelných setpointů); (d) bez session EV == 0 (stop-session i golden
fixtures — žádné pumpování při buy<0); dekompozice total == needed − unmet
+ opp i pro needed = 0; (e) battery_arbitrage_czk = via_bat kWh × oportunitní
cena (min sell exportního slotu téhož pražského dne, jinak terminal value)
místo konstantní 0. Oportunismus PO deadline zůstává POVOLENÝ (rozhodnutí:
auto často doma, odjezd řeší rolling replan).
- R__033: fn_plan_current_bundle.intervals + ev1/ev2_via_bat_w (UI nemá cenit
EV kWh z baterie slotovým buy).
Golden gate beze změny snapshotů (v1 nedotčen, fixtures bez EV sessions);
solver_v2_eval před/po identický (CELKEM −1283.5 Kč, Δ −221.9 vs v1);
tests/test_solver_v2.py +7 testů; plná sada 310 passed / 4 xfailed.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
473 lines
21 KiB
Python
473 lines
21 KiB
Python
"""solver_v2 (čisté jádro): tvrdá pravidla, režimy, EV deadline, arbitráž (bez DB)."""
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from __future__ import annotations
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import unittest
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from datetime import datetime, timedelta, timezone
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from types import SimpleNamespace
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from services.planning.solver_v2 import solve_dispatch_v2
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from services.planning.types import PlanningSlot
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def _slot(
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base: datetime,
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i: int,
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*,
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buy: float,
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sell: float,
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pv_a: int = 0,
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pv_b: int = 0,
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load: int = 1000,
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ev1: bool = False,
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) -> PlanningSlot:
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return PlanningSlot(
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interval_start=base + timedelta(minutes=15 * i),
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buy_price=buy,
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sell_price=sell,
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pv_a_forecast_w=pv_a,
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pv_b_forecast_w=pv_b,
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load_baseline_w=load,
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ev1_connected=ev1,
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ev2_connected=False,
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)
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def _battery(uc_wh: float = 20_000.0) -> SimpleNamespace:
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return SimpleNamespace(
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usable_capacity_wh=uc_wh,
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min_soc_wh=0.12 * uc_wh,
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arb_floor_wh=0.20 * uc_wh,
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reserve_soc_wh=0.20 * uc_wh,
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soc_max_wh=0.95 * uc_wh,
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charge_efficiency=0.95,
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discharge_efficiency=0.95,
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degradation_cost_czk_kwh=0.5,
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max_charge_power_w=8000,
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max_discharge_power_w=8000,
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planner_terminal_soc_value_factor=0.8,
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)
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def _grid(block_neg: bool = False, gen_cutoff: bool = False) -> SimpleNamespace:
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return SimpleNamespace(
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max_import_power_w=17_000,
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max_export_power_w=13_500,
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block_export_on_negative_sell=block_neg,
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deye_gen_microinverter_cutoff_enabled=gen_cutoff,
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)
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_HP = SimpleNamespace(rated_heating_power_w=0, tuv_min_temp_c=45.0, tuv_target_temp_c=55.0)
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_VEHICLES = [
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SimpleNamespace(max_charge_power_w=11_000, battery_capacity_kwh=60.0, default_target_soc_pct=80.0),
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SimpleNamespace(max_charge_power_w=0, battery_capacity_kwh=1.0, default_target_soc_pct=80.0),
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]
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_BASE = datetime(2026, 6, 10, 0, 0, tzinfo=timezone.utc)
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def _solve(
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slots,
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*,
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battery=None,
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grid=None,
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ev_sessions=(None, None),
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soc0=None,
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mode="AUTO",
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vehicles=None,
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):
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bat = battery or _battery()
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return solve_dispatch_v2(
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slots,
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bat,
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_HP,
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grid or _grid(),
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list(ev_sessions),
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vehicles if vehicles is not None else _VEHICLES,
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soc0 if soc0 is not None else 0.5 * bat.usable_capacity_wh,
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50.0,
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operating_mode=mode,
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)
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class HardRulesTests(unittest.TestCase):
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def test_negative_buy_blocks_export(self) -> None:
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slots = [_slot(_BASE, i, buy=-2.0, sell=1.5, pv_a=6000, load=500) for i in range(8)]
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results, _, _ = _solve(slots)
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for r in results:
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self.assertGreaterEqual(r.grid_setpoint_w, 0, "buy<0 → žádný export (pumpa)")
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def test_block_export_on_negative_sell(self) -> None:
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slots = [_slot(_BASE, i, buy=2.0, sell=-0.5, pv_a=8000, load=500) for i in range(8)]
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results, _, _ = _solve(slots, grid=_grid(block_neg=True))
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for r in results:
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self.assertGreaterEqual(r.grid_setpoint_w, 0, "KV1: sell<0 → ge=0")
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def test_negative_sell_prefers_charge_or_curtail_over_paid_export(self) -> None:
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slots = [_slot(_BASE, i, buy=2.0, sell=-1.0, pv_a=8000, load=500) for i in range(8)]
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results, _, _ = _solve(slots)
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paid_export = sum(-r.grid_setpoint_w for r in results if r.grid_setpoint_w < 0)
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self.assertEqual(paid_export, 0, "spot: za export při sell<0 se platí → ekonomika ho vyloučí")
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def test_battery_export_requires_arb_floor(self) -> None:
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bat = _battery()
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slots = [_slot(_BASE, i, buy=1.0, sell=8.0, load=500) for i in range(8)]
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results, _, _ = _solve(slots, battery=bat, soc0=0.5 * bat.usable_capacity_wh)
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for r in results:
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if r.grid_setpoint_w < 0 and r.battery_setpoint_w < 0:
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self.assertGreaterEqual(
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r.battery_soc_target / 100.0 * bat.usable_capacity_wh,
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bat.arb_floor_wh - 1.0,
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"export z baterie nesmí podlézt arb floor",
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)
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def test_curtailment_only_pv_a(self) -> None:
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# extrémně záporný sell bez block_export: pole B nelze omezit, A ano
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slots = [_slot(_BASE, i, buy=2.0, sell=-3.0, pv_a=5000, pv_b=4000, load=300) for i in range(8)]
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bat = _battery(uc_wh=2000.0) # malá baterie, ať se přebytek nevejde
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results, _, _ = _solve(slots, battery=bat, soc0=0.9 * 2000.0)
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self.assertTrue(any(r.pv_a_curtailed_w > 0 for r in results), "A se curtailuje")
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for r in results:
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self.assertLessEqual(r.pv_a_curtailed_w, 5000, "curtail max = výroba A")
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class ArbitrageTests(unittest.TestCase):
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def test_cheap_night_charge_expensive_evening_discharge(self) -> None:
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slots = [_slot(_BASE, i, buy=1.0, sell=0.5, load=1000) for i in range(16)]
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slots += [_slot(_BASE, 16 + i, buy=8.0, sell=7.0, load=1000) for i in range(16)]
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results, _, _ = _solve(slots)
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charged = sum(r.battery_setpoint_w for r in results[:16] if r.battery_setpoint_w > 0)
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discharged = sum(-r.battery_setpoint_w for r in results[16:] if r.battery_setpoint_w < 0)
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self.assertGreater(charged, 0, "levná noc → nabíjet")
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self.assertGreater(discharged, 0, "drahý večer → vybíjet")
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class OperatingModeTests(unittest.TestCase):
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def _slots(self):
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return [_slot(_BASE, i, buy=1.0, sell=6.0, pv_a=3000, load=1000) for i in range(8)]
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def test_preserve_locks_battery(self) -> None:
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results, _, _ = _solve(self._slots(), mode="PRESERVE")
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for r in results:
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self.assertEqual(r.battery_setpoint_w, 0)
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def test_charge_cheap_no_export_no_discharge(self) -> None:
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results, _, _ = _solve(self._slots(), mode="CHARGE_CHEAP")
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for r in results:
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self.assertGreaterEqual(r.grid_setpoint_w, 0)
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self.assertGreaterEqual(r.battery_setpoint_w, 0)
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def test_self_sustain_import_capped_to_load(self) -> None:
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results, _, _ = _solve(self._slots(), mode="SELF_SUSTAIN")
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for r in results:
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self.assertLessEqual(r.grid_setpoint_w, 1000, "import ≤ baseline load")
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class NightReserveTests(unittest.TestCase):
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def test_night_discharge_respects_buffer(self) -> None:
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# noc: vysoký sell, žádné PV; buffer 2000 Wh nad min → plán nesmí
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# kalkulovat s vybitím pod min+buffer (sell < buy ⇒ slack se nevyplatí)
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bat = _battery()
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slots = []
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for i in range(16):
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s = _slot(_BASE, i, buy=6.0, sell=4.5, load=800)
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s.night_baseload_buffer_wh = 2000.0
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slots.append(s)
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results, _, _ = _solve(slots, battery=bat, soc0=0.6 * bat.usable_capacity_wh)
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floor_pct = (bat.min_soc_wh + 2000.0) / bat.usable_capacity_wh * 100.0
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for r in results:
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self.assertGreaterEqual(r.battery_soc_target, floor_pct - 0.6)
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def test_extreme_sell_spike_may_sell_reserve(self) -> None:
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# sell výrazně nad buy → racionální polštář prodat (placený slack)
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bat = _battery()
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slots = []
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for i in range(16):
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s = _slot(_BASE, i, buy=2.0, sell=12.0, load=300)
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s.night_baseload_buffer_wh = 2000.0
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slots.append(s)
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results, _, _ = _solve(slots, battery=bat, soc0=0.6 * bat.usable_capacity_wh)
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min_soc_pct = min(r.battery_soc_target for r in results)
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floor_pct = (bat.min_soc_wh + 2000.0) / bat.usable_capacity_wh * 100.0
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self.assertLess(min_soc_pct, floor_pct - 1.0, "spike má polštář vyprodat")
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def test_start_below_buffer_is_feasible(self) -> None:
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bat = _battery()
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slots = []
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for i in range(8):
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s = _slot(_BASE, i, buy=6.0, sell=1.0, load=1500)
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s.night_baseload_buffer_wh = 3000.0
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slots.append(s)
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results, _, _ = _solve(slots, battery=bat, soc0=bat.min_soc_wh + 500.0)
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self.assertEqual(len(results), 8)
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class DaytimeSafetyRampTests(unittest.TestCase):
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def test_morning_tops_up_reserve_before_selling(self) -> None:
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# KV1 scénář: ráno baterie u dna, fixní buy 6.35 >> sell 2.5, PV jede;
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# s rampou (target 30 % usable) musí nejdřív dotáhnout rezervu, ne prodávat
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bat = _battery()
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bat.planner_safety_soc_risk_factor = 0.05
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target_wh = 0.30 * bat.usable_capacity_wh
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slots = []
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for i in range(16):
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s = _slot(_BASE, i, buy=6.35, sell=2.5, pv_a=6000, load=800)
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s.safety_soc_target_wh = target_wh
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slots.append(s)
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results, _, _ = _solve(slots, battery=bat, soc0=0.11 * bat.usable_capacity_wh)
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soc_pct = [r.battery_soc_target for r in results]
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first_reach = next((i for i, v in enumerate(soc_pct) if v >= 29.5), None)
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self.assertIsNotNone(first_reach, "rampa má dotáhnout na rezervu")
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exported_before = sum(
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-r.grid_setpoint_w for r in results[:first_reach] if r.grid_setpoint_w < 0
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)
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self.assertLess(
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exported_before, 500 * max(1, first_reach),
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"před dosažením rezervy se nemá významně prodávat",
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)
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def test_sell_spike_beats_ramp(self) -> None:
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# extrémní sell nad buy → deficit je racionální podstoupit
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bat = _battery()
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bat.planner_safety_soc_risk_factor = 0.05
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slots = []
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for i in range(16):
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s = _slot(_BASE, i, buy=2.0, sell=14.0, pv_a=2000, load=300)
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s.safety_soc_target_wh = 0.5 * bat.usable_capacity_wh
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slots.append(s)
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results, _, _ = _solve(slots, battery=bat, soc0=0.45 * bat.usable_capacity_wh)
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total_export = sum(-r.grid_setpoint_w for r in results if r.grid_setpoint_w < 0)
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self.assertGreater(total_export, 5000, "spike má vyprodat i pod target")
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class PvRiskFrontloadTests(unittest.TestCase):
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def test_neg_window_charges_asap(self) -> None:
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# sell<0 okno, PV >> load, prázdnější baterie: s frontload prémií musí
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# nabíjení běžet plným tempem od začátku (ne odložené na konec okna)
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bat = _battery()
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bat.planner_pv_risk_frontload_czk_kwh = 0.05
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slots = [_slot(_BASE, i, buy=2.0, sell=-0.5, pv_a=12000, load=500) for i in range(12)]
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results, _, _ = _solve(slots, battery=bat, soc0=0.2 * bat.usable_capacity_wh)
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# max tempo: 8 kW × 0.25 h × 0.95 eff = 1.9 kWh/slot = 9.5 p.b. na 20 kWh
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soc_mid = results[3].battery_soc_target
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self.assertGreaterEqual(
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soc_mid, 20.0 + 4 * 9.0,
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"frontload: prvni 4 sloty maji nabijet plnym vykonem",
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)
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class EvOpportunisticTests(unittest.TestCase):
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def _session(self, needed=4000.0, headroom=20000.0, opp=1.0):
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return SimpleNamespace(
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target_deadline=_BASE + timedelta(hours=2),
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energy_needed_wh=needed,
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headroom_wh=headroom,
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opportunistic_value_czk_kwh=opp,
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)
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def test_negative_prices_fill_beyond_target(self) -> None:
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# buy<0 celé okno → nad target se vyplatí brát (hodnota 1 Kč/kWh + platí ti síť)
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slots = [_slot(_BASE, i, buy=-1.0, sell=-0.5, ev1=True, load=300) for i in range(16)]
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results, _, snap = _solve(slots, ev_sessions=(self._session(), None))
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delivered = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results)
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self.assertGreater(delivered, 4000.0 + 2000.0, "měkký cíl má nasávat")
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self.assertLessEqual(delivered, 4000.0 + 20000.0 + 1.0, "strop headroom")
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self.assertGreater(snap["objective_terms"]["ev_opp_wh"][0], 0)
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def test_normal_prices_no_opportunistic(self) -> None:
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# běžné ceny (buy 3) > hodnota 1 Kč/kWh → jen tvrdý cíl
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slots = [_slot(_BASE, i, buy=3.0, sell=2.0, ev1=True, load=300) for i in range(16)]
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results, _, snap = _solve(slots, ev_sessions=(self._session(), None))
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delivered = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results)
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self.assertLess(delivered, 4000.0 + 200.0)
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self.assertLess(snap["objective_terms"]["ev_opp_wh"][0], 100.0)
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def test_cheap_sell_prefers_car_over_grid(self) -> None:
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# sell 0.3 < opp 1.0, plná domácí baterka, velký PV přebytek
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# → přebytek do auta, ne za babku do sítě
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bat = _battery()
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slots = [_slot(_BASE, i, buy=3.0, sell=0.3, pv_a=9000, load=500, ev1=True) for i in range(16)]
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results, _, snap = _solve(
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slots, battery=bat, soc0=bat.soc_max_wh, # baterka plná
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ev_sessions=(self._session(needed=2000.0, headroom=25000.0), None),
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)
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delivered = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results)
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exported = sum(-r.grid_setpoint_w * 0.25 for r in results if r.grid_setpoint_w < 0)
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self.assertGreater(delivered, 15000.0, "přebytek má téct do auta")
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self.assertLess(exported, delivered, "prodej za 0.3 nemá vyhrát nad autem")
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def test_total_energy_capped_even_at_negative_buy(self) -> None:
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# fix latentního bugu: bez headroom (opp=0) nesmí buy<0 pumpovat nad needed
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slots = [_slot(_BASE, i, buy=-2.0, sell=-1.0, ev1=True, load=300) for i in range(16)]
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sess = self._session(needed=3000.0, headroom=0.0, opp=0.0)
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results, _, _ = _solve(slots, ev_sessions=(sess, None))
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delivered = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results)
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self.assertLessEqual(delivered, 3000.0 + 1.0)
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class EvAccountingTests(unittest.TestCase):
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"""EV účtování 2026-06-12: deadline boundary, stop-session, fyzikální split,
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min. výkon wallboxu, opp po deadline, battery_arbitrage_czk reporting."""
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def test_deadline_boundary_slot_excluded(self) -> None:
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# slot začínající přesně v deadline (slot 4) už do deadline nepatří;
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# levné sloty 4..7 nesmí krýt tvrdý cíl (dřív off-by-one t_dl+1)
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slots = [
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_slot(_BASE, i, buy=5.0 if i < 4 else 0.5, sell=0.2, ev1=True)
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for i in range(8)
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]
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session = SimpleNamespace(
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target_deadline=_BASE + timedelta(hours=1), # = start slotu 4
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energy_needed_wh=4000.0,
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headroom_wh=0.0,
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opportunistic_value_czk_kwh=0.0,
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)
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results, _, snap = _solve(slots, ev_sessions=(session, None))
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before = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results[:4])
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after = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results[4:])
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self.assertGreaterEqual(before, 4000.0 - 1.0, "tvrdý cíl jen sloty PŘED deadline")
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self.assertLessEqual(after, 1.0, "slot v deadline a dál nekryje tvrdý cíl")
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self.assertEqual(snap["objective_terms"]["ev_unmet_wh"], [0.0])
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def test_stop_session_zero_everywhere(self) -> None:
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# needed 0 + opp 0 (stop-session) → EV nula i při záporných cenách
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slots = [_slot(_BASE, i, buy=-2.0, sell=-1.0, ev1=True, load=300) for i in range(8)]
|
||
session = SimpleNamespace(
|
||
target_deadline=_BASE + timedelta(hours=2),
|
||
energy_needed_wh=0.0,
|
||
headroom_wh=0.0,
|
||
opportunistic_value_czk_kwh=0.0,
|
||
)
|
||
results, _, _ = _solve(slots, ev_sessions=(session, None))
|
||
for r in results:
|
||
self.assertEqual(r.ev1_setpoint_w or 0, 0)
|
||
|
||
def test_no_session_zero_even_at_negative_buy(self) -> None:
|
||
# připojené auto BEZ session nemá mandát nabíjet (golden fixtures)
|
||
slots = [_slot(_BASE, i, buy=-2.0, sell=-1.0, ev1=True, load=300) for i in range(8)]
|
||
results, _, _ = _solve(slots, ev_sessions=(None, None))
|
||
for r in results:
|
||
self.assertEqual(r.ev1_setpoint_w or 0, 0)
|
||
|
||
def test_ev_direct_within_grid_plus_pv(self) -> None:
|
||
# fyzikální split: direct (= setpoint − via_bat) nesmí překročit gi + PV
|
||
slots = [
|
||
_slot(_BASE, i, buy=2.0, sell=1.0, pv_a=(3000 if i < 4 else 0), ev1=True)
|
||
for i in range(12)
|
||
]
|
||
bat = _battery()
|
||
session = SimpleNamespace(
|
||
target_deadline=_BASE + timedelta(hours=3),
|
||
energy_needed_wh=10000.0,
|
||
headroom_wh=0.0,
|
||
opportunistic_value_czk_kwh=0.0,
|
||
)
|
||
results, _, _ = _solve(
|
||
slots, battery=bat, soc0=0.9 * bat.usable_capacity_wh,
|
||
ev_sessions=(session, None),
|
||
)
|
||
for i, r in enumerate(results):
|
||
direct = (r.ev1_setpoint_w or 0) - r.ev1_via_bat_w
|
||
gi_w = max(0, r.grid_setpoint_w)
|
||
pv_w = slots[i].pv_a_forecast_w + slots[i].pv_b_forecast_w
|
||
self.assertLessEqual(direct, gi_w + pv_w + 2, f"slot {i}: direct > gi+pv")
|
||
|
||
def test_min_power_setpoints_zero_or_above_min(self) -> None:
|
||
# wallbox min 1380 W (6 A): setpoint ∈ {0} ∪ [1380, max] — žádné 400–900 W
|
||
vehicles = [
|
||
SimpleNamespace(
|
||
max_charge_power_w=11_000, min_power_w=1380,
|
||
battery_capacity_kwh=60.0, default_target_soc_pct=80.0,
|
||
),
|
||
_VEHICLES[1],
|
||
]
|
||
# ceny nutí rozprostřít malé množství energie → bez binárky by vyšlo ~86 W/slot
|
||
slots = [_slot(_BASE, i, buy=2.0 + 0.01 * i, sell=1.0, ev1=True) for i in range(8)]
|
||
session = SimpleNamespace(
|
||
target_deadline=_BASE + timedelta(hours=2),
|
||
energy_needed_wh=690.0, # 2 sloty × 1380 W × 0.25 h
|
||
headroom_wh=0.0,
|
||
opportunistic_value_czk_kwh=0.0,
|
||
)
|
||
results, _, _ = _solve(slots, ev_sessions=(session, None), vehicles=vehicles)
|
||
delivered = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results)
|
||
self.assertGreaterEqual(delivered, 690.0 - 1.0)
|
||
for i, r in enumerate(results):
|
||
sp = r.ev1_setpoint_w or 0
|
||
self.assertTrue(
|
||
sp == 0 or sp >= 1379,
|
||
f"slot {i}: setpoint {sp} W je pod minimem wallboxu",
|
||
)
|
||
|
||
def test_opportunistic_after_deadline_allowed(self) -> None:
|
||
# ROZHODNUTO 2026-06-12: opp vrstva NENÍ omezená deadline — záporné ceny
|
||
# po deadline smí téct do auta (odjezd řeší rolling replan)
|
||
slots = [
|
||
_slot(_BASE, i, buy=(3.0 if i < 4 else -1.5), sell=(1.0 if i < 4 else -0.5),
|
||
ev1=True, load=300)
|
||
for i in range(16)
|
||
]
|
||
session = SimpleNamespace(
|
||
target_deadline=_BASE + timedelta(hours=1), # slot 4
|
||
energy_needed_wh=2000.0,
|
||
headroom_wh=20000.0,
|
||
opportunistic_value_czk_kwh=1.0,
|
||
)
|
||
results, _, snap = _solve(slots, ev_sessions=(session, None))
|
||
after_deadline = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results[4:])
|
||
total = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results)
|
||
self.assertGreater(after_deadline, 0.0, "opp po deadline musí zůstat povolené")
|
||
self.assertLessEqual(total, 2000.0 + 20000.0 + 1.0, "strop needed + headroom")
|
||
self.assertGreater(snap["objective_terms"]["ev_opp_wh"][0], 0.0)
|
||
|
||
def test_battery_arbitrage_reported_for_via_bat(self) -> None:
|
||
# EV kryté z baterie (noc, drahý buy, plná baterie) → via_bat > 0 a
|
||
# battery_arbitrage_czk nese oportunitní cenu (ne konstantní 0)
|
||
bat = _battery()
|
||
slots = [_slot(_BASE, i, buy=8.0, sell=1.0, ev1=True, load=300) for i in range(8)]
|
||
session = SimpleNamespace(
|
||
target_deadline=_BASE + timedelta(hours=2),
|
||
energy_needed_wh=6000.0,
|
||
headroom_wh=0.0,
|
||
opportunistic_value_czk_kwh=0.0,
|
||
)
|
||
results, _, _ = _solve(
|
||
slots, battery=bat, soc0=bat.soc_max_wh, ev_sessions=(session, None)
|
||
)
|
||
via = sum(r.ev1_via_bat_w for r in results)
|
||
self.assertGreater(via, 0, "drahý buy + plná baterie → EV z baterie")
|
||
arb = sum(r.battery_arbitrage_czk for r in results)
|
||
self.assertGreater(arb, 0.0, "via_bat sloty musí reportovat oportunitní Kč")
|
||
for r in results:
|
||
if r.ev1_via_bat_w == 0:
|
||
self.assertEqual(r.battery_arbitrage_czk, 0.0)
|
||
|
||
|
||
class EvDeadlineTests(unittest.TestCase):
|
||
def test_ev_energy_delivered_before_deadline(self) -> None:
|
||
slots = [_slot(_BASE, i, buy=2.0 if i < 8 else 6.0, sell=1.0, ev1=True) for i in range(16)]
|
||
session = SimpleNamespace(
|
||
target_deadline=_BASE + timedelta(hours=4), # slot 16 → vše do konce
|
||
energy_needed_wh=8000.0,
|
||
)
|
||
results, _, snap = _solve(slots, ev_sessions=(session, None))
|
||
delivered = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results)
|
||
self.assertGreaterEqual(delivered, 8000.0 - 1.0)
|
||
self.assertEqual(snap["objective_terms"]["ev_unmet_wh"], [0.0])
|
||
# levné sloty (0–7) mají dodat většinu energie
|
||
cheap = sum((r.ev1_setpoint_w or 0) * 0.25 for r in results[:8])
|
||
self.assertGreater(cheap, 4000.0, "EV nabíjí přednostně v levných slotech")
|
||
|
||
def test_ev_unreachable_deadline_uses_paid_slack(self) -> None:
|
||
slots = [_slot(_BASE, i, buy=2.0, sell=1.0, ev1=(i == 0)) for i in range(8)]
|
||
session = SimpleNamespace(
|
||
target_deadline=_BASE + timedelta(minutes=15),
|
||
energy_needed_wh=50_000.0, # nesplnitelné za 1 slot
|
||
)
|
||
results, _, snap = _solve(slots, ev_sessions=(session, None))
|
||
self.assertGreater(snap["objective_terms"]["ev_unmet_wh"][0], 0.0, "slack místo infeasible")
|
||
|
||
|
||
if __name__ == "__main__":
|
||
unittest.main()
|