mirror of
https://github.com/Akkudoktor-EOS/EOS.git
synced 2026-08-31 12:46:38 +00:00
71 lines
2.6 KiB
Python
71 lines
2.6 KiB
Python
import pytest
|
|
|
|
from akkudoktoreos.prediction.interpolator import get_eos_load_interpolator
|
|
|
|
|
|
def test_quarter_hour_energy_is_converted_back_to_same_mean_power():
|
|
"""Splitting hourly energy must not change the minute-load probability lookup."""
|
|
interpolator = get_eos_load_interpolator()
|
|
hourly_load_wh = 800.0
|
|
hourly_pv_wh = 1200.0
|
|
slot_duration_h = 0.25
|
|
|
|
hourly = interpolator.calculate_expected_direct_consumption(hourly_load_wh, hourly_pv_wh)
|
|
quarter_hour = interpolator.calculate_expected_direct_consumption(
|
|
(hourly_load_wh / 4) / slot_duration_h,
|
|
(hourly_pv_wh / 4) / slot_duration_h,
|
|
)
|
|
|
|
assert quarter_hour == pytest.approx(hourly)
|
|
|
|
|
|
def test_load_above_probability_grid_uses_highest_supported_distribution():
|
|
"""Out-of-range household load must not make self-consumption jump to zero."""
|
|
interpolator = get_eos_load_interpolator()
|
|
|
|
at_boundary = interpolator.calculate_self_consumption(3450.0, 5000.0)
|
|
above_boundary = interpolator.calculate_self_consumption(4000.0, 5000.0)
|
|
|
|
assert above_boundary == pytest.approx(at_boundary)
|
|
assert above_boundary > 0.99
|
|
|
|
|
|
def test_expected_direct_consumption_accounts_for_subhourly_load_variation():
|
|
"""Expected overlap must be below the optimistic overlap of interval means."""
|
|
interpolator = get_eos_load_interpolator()
|
|
|
|
direct_power_w = interpolator.calculate_expected_direct_consumption(800.0, 1200.0)
|
|
|
|
assert direct_power_w == pytest.approx(621.0, abs=2.0)
|
|
assert 0.0 < direct_power_w < 800.0
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
("mean_load_power_w", "pv_power_w"),
|
|
[(800.0, 1200.0), (1000.0, 500.0), (1500.0, 1500.0)],
|
|
)
|
|
def test_expected_direct_consumption_produces_conservative_energy_balance(
|
|
mean_load_power_w, pv_power_w
|
|
):
|
|
"""Direct use, residual load and surplus must conserve both mean powers."""
|
|
interpolator = get_eos_load_interpolator()
|
|
|
|
direct_power_w = interpolator.calculate_expected_direct_consumption(
|
|
mean_load_power_w, pv_power_w
|
|
)
|
|
residual_load_w = mean_load_power_w - direct_power_w
|
|
pv_surplus_w = pv_power_w - direct_power_w
|
|
|
|
assert 0.0 <= direct_power_w <= min(mean_load_power_w, pv_power_w)
|
|
assert direct_power_w + residual_load_w == pytest.approx(mean_load_power_w)
|
|
assert direct_power_w + pv_surplus_w == pytest.approx(pv_power_w)
|
|
|
|
|
|
def test_expected_direct_consumption_preserves_forecast_mean_at_high_pv():
|
|
"""A PV level above every normalized load bin covers the complete mean load."""
|
|
interpolator = get_eos_load_interpolator()
|
|
|
|
direct_power_w = interpolator.calculate_expected_direct_consumption(3000.0, 10000.0)
|
|
|
|
assert direct_power_w == pytest.approx(3000.0)
|