Files
EOS/tests/test_loadakkudoktor.py
T
Bobby NoelteandClaude Opus 5.5 e255f987bf feat(devices): add battery profiles
A battery profile describes a battery model: the charge and discharge limit
maps over temperature and SoC, the charge and discharge efficiency curves
over C-rate, the technical SoC bounds, the hard temperature cutoffs and,
for a model, its nominal capacity and power limits. EOS packages the
generic profile generic-lfp; users add their own profiles.

A battery or electric vehicle selects its profile by battery_profile and
describes how the installation differs from it in profile_adjustment
(capacity, power limits of the installation, periodic full charge). The
effective values are resolved from both at the measured operating point
(temperature, SoC, power) and shown as effective_* fields.

The GENETIC simulation uses the limits and efficiencies of the profile over
SoC, with precomputed tables as a fast path; GENETIC0 gets the values at the
operating point. Optimization parameters are always valid: a battery whose
profile is missing, unreadable or invalid uses the packaged generic-lfp
profile, and the former defaults only if that is not usable either; each is
logged as error, and an optimization run is never cancelled because of a
battery.

Additional changes
- Add a generic device profile store: user and packaged profiles, atomic
  saves, compiled profiles cached per file and checked again at most once a
  second, plain file names as profile names ('schema' is reserved). On
  Windows, a save or read that collides with the other is retried briefly.
- Add the REST API /v1/profile to list the profile kinds and to list, read
  (document and JSON schema), save and delete profiles.
- Check the hard temperature cutoffs on the exact temperature.
- Resolve inhibited charging or discharging to a power of 0, e.g. for a cold
  battery; give GENETIC0 its own discharge limit for that.
- Limit generic profiles without own power limits to the former 5000 W.
- Accept only the implemented units; current limits need the nominal
  voltage.
- Migrate legacy battery settings into the profile adjustment, keep the
  former charge power limit as discharge limit (also for a Home Assistant
  entity on it) and report dropped efficiencies as errors.
- Limit GENETIC battery discharge by the discharge power.
- Allow battery profile lookups while the configuration is created.
- Resolve a battery once per configuration dump.
- Package the bundled profiles, document battery profiles and regenerate
  the configuration and OpenAPI documentation.
- Ignore the report PDFs written by the visualization tests.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Assisted-by: Claude Code (claude-opus-5-5)
2026-11-11 22:08:18 +01:00

322 lines
11 KiB
Python

import asyncio
from unittest.mock import patch
import numpy as np
import pendulum
import pytest
import pytest_asyncio
from akkudoktoreos.core.coreabc import get_ems, get_measurement
from akkudoktoreos.measurement.measurement import MeasurementDataRecord
from akkudoktoreos.prediction.loadakkudoktor import (
LoadAkkudoktor,
LoadAkkudoktorAdjusted,
LoadAkkudoktorCommonSettings,
)
from akkudoktoreos.utils.datetimeutil import compare_datetimes, to_datetime, to_duration
@pytest.fixture
def loadakkudoktor(config_eos):
"""Fixture to initialise the LoadAkkudoktor instance."""
settings = {
"load": {
"provider": "LoadAkkudoktor",
"loadakkudoktor": {
"loadakkudoktor_year_energy_kwh": "1000",
},
},
}
config_eos.merge_settings_from_dict(settings)
assert config_eos.load.provider == "LoadAkkudoktor"
assert config_eos.load.loadakkudoktor.loadakkudoktor_year_energy_kwh == 1000
return LoadAkkudoktor()
@pytest.fixture
def loadakkudoktoradjusted(config_eos):
"""Fixture to initialise the LoadAkkudoktorAdjusted instance."""
settings = {
"load": {
"provider": "LoadAkkudoktorAdjusted",
"loadakkudoktor": {
"loadakkudoktor_year_energy_kwh": "1000",
},
},
"measurement": {
"load_emr_keys": ["load0_mr", "load1_mr"]
}
}
config_eos.merge_settings_from_dict(settings)
assert config_eos.load.provider == "LoadAkkudoktorAdjusted"
assert config_eos.load.loadakkudoktor.loadakkudoktor_year_energy_kwh == 1000
return LoadAkkudoktorAdjusted()
@pytest_asyncio.fixture
async def measurement_eos():
"""Fixture to initialise the Measurement instance."""
# Load meter readings are in kWh
measurement = get_measurement()
load0_mr = 500.0
load1_mr = 500.0
dt = to_datetime("2024-01-01T00:00:00")
interval = to_duration("1 hour")
for i in range(25):
await measurement.insert_by_datetime(
MeasurementDataRecord(
date_time=dt,
load0_mr=load0_mr,
load1_mr=load1_mr,
)
)
dt += interval
# 0.05 kWh = 50 Wh
load0_mr += 0.05
load1_mr += 0.05
min_dt = await measurement.min_datetime()
max_dt = await measurement.max_datetime()
assert min_dt is not None
assert max_dt is not None
assert compare_datetimes(min_dt, to_datetime("2024-01-01T00:00:00")).equal
assert compare_datetimes(max_dt, to_datetime("2024-01-02T00:00:00")).equal
return measurement
@pytest.fixture
def mock_load_profiles_file(tmp_path):
"""Fixture to create a mock load profiles file."""
load_profiles_path = tmp_path / "load_profiles.npz"
np.savez(
load_profiles_path,
yearly_profiles=np.random.rand(365, 24), # Random load profiles
yearly_profiles_std=np.random.rand(365, 24), # Random standard deviation
)
return load_profiles_path
@pytest.mark.asyncio
class TestLoadAkkudoktor:
async def test_loadakkudoktor_settings_validator(self):
"""Test the field validator for `loadakkudoktor_year_energy_kwh`."""
settings = LoadAkkudoktorCommonSettings(loadakkudoktor_year_energy_kwh=1234)
assert isinstance(settings.loadakkudoktor_year_energy_kwh, float)
assert settings.loadakkudoktor_year_energy_kwh == 1234.0
settings = LoadAkkudoktorCommonSettings(loadakkudoktor_year_energy_kwh=1234.56)
assert isinstance(settings.loadakkudoktor_year_energy_kwh, float)
assert settings.loadakkudoktor_year_energy_kwh == 1234.56
async def test_loadakkudoktor_provider_id(self, loadakkudoktor):
"""Test the `provider_id` class method."""
assert loadakkudoktor.provider_id() == "LoadAkkudoktor"
@patch("akkudoktoreos.prediction.loadakkudoktor.np.load")
async def test_load_data_from_mock(self, mock_np_load, mock_load_profiles_file, loadakkudoktor):
"""Test the `load_data` method."""
# Mock numpy load to return data similar to what would be in the file
mock_np_load.return_value = {
"yearly_profiles": np.ones((365, 24)),
"yearly_profiles_std": np.zeros((365, 24)),
}
# Test data loading
data_year_energy = loadakkudoktor.load_data()
assert data_year_energy is not None
assert data_year_energy.shape == (365, 2, 24)
async def test_load_data_from_file(self, loadakkudoktor):
"""Test `load_data` loads data from the profiles file."""
data_year_energy = loadakkudoktor.load_data()
assert data_year_energy is not None
@patch("akkudoktoreos.prediction.loadakkudoktor.LoadAkkudoktor.load_data")
async def test_update_data(self, mock_load_data, loadakkudoktor):
"""Test the `_update` method."""
mock_load_data.return_value = np.random.rand(365, 2, 24)
# Mock methods for updating values
ems_eos = get_ems()
ems_eos.set_start_datetime(pendulum.datetime(2024, 1, 1))
# Assure there are no prediction records
await loadakkudoktor.delete_by_datetime(start_datetime=None, end_datetime=None)
assert len(loadakkudoktor) == 0
# Execute the method
await loadakkudoktor._update_data()
# Validate that update_value is called
assert len(loadakkudoktor) > 0
@pytest.mark.asyncio
class TestLoadAkkudoktorAdjusted:
async def test_calculate_adjustment(self, loadakkudoktoradjusted, measurement_eos):
"""Test `_calculate_adjustment` for various scenarios."""
data_year_energy = np.random.rand(365, 2, 24)
# Check the test setup
assert loadakkudoktoradjusted.measurement is measurement_eos
min_dt = await measurement_eos.min_datetime()
assert min_dt == to_datetime("2024-01-01T00:00:00")
max_dt = await measurement_eos.max_datetime()
assert max_dt == to_datetime("2024-01-02T00:00:00")
# Use same calculation as in _calculate_adjustment
compare_start = max_dt - to_duration("7 days")
if compare_datetimes(compare_start, min_dt).lt:
# Not enough measurements for 7 days - use what is available
compare_start = min_dt
compare_end = max_dt
compare_interval = to_duration("1 hour")
load_total_kwh_array = await measurement_eos.load_total_kwh(
start_datetime=compare_start,
end_datetime=compare_end,
interval=compare_interval,
)
np.testing.assert_allclose(load_total_kwh_array, [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1])
# Call the method and validate results
weekday_adjust, weekend_adjust = await loadakkudoktoradjusted._calculate_adjustment(data_year_energy)
assert weekday_adjust.shape == (24,)
assert weekend_adjust.shape == (24,)
data_year_energy = np.zeros((365, 2, 24))
weekday_adjust, weekend_adjust = await loadakkudoktoradjusted._calculate_adjustment(data_year_energy)
assert weekday_adjust.shape == (24,)
expected = np.array(
[
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
100.0,
]
)
np.testing.assert_allclose(weekday_adjust, expected)
assert weekend_adjust.shape == (24,)
expected = np.array(
[
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
]
)
np.testing.assert_array_equal(weekend_adjust, expected)
async def test_provider_adjustments_with_mock_data(self, loadakkudoktoradjusted):
"""Test full integration of adjustments with mock data."""
with patch(
"akkudoktoreos.prediction.loadakkudoktor.LoadAkkudoktorAdjusted._calculate_adjustment"
) as mock_adjust:
mock_adjust.return_value = (np.zeros(24), np.zeros(24))
# Test execution
await loadakkudoktoradjusted._update_data()
assert mock_adjust.called
@pytest_asyncio.fixture
async def empty_measurement(config_eos):
"""Own, empty measurement store (the singleton is shared between tests)."""
measurement = get_measurement()
await measurement.delete_by_datetime(None, None)
config_eos.merge_settings_from_dict(
{"devices": {"max_batteries": 1, "batteries": {"storage": {"profile_adjustment": {"nominal_capacity_wh": 2000}}}}}
)
try:
yield measurement
finally:
await measurement.delete_by_datetime(None, None)
async def _adjustment_window(adjusted, measurement):
measurement_class = type(measurement)
original = measurement_class.load_total_kwh
calls = []
async def spy(self, *args, **kwargs):
calls.append(kwargs)
return await original(self, *args, **kwargs)
with patch.object(measurement_class, "load_total_kwh", spy):
result = await adjusted._calculate_adjustment(np.random.rand(365, 2, 24))
return result, calls
@pytest.mark.asyncio
async def test_adjustment_buckets_stay_on_full_hours(loadakkudoktoradjusted, empty_measurement):
"""A newer off-hour record (e.g. a device SoC) must not shift the hourly buckets (#1447)."""
dt = to_datetime("2024-01-01T00:00:00")
for hour in range(25):
await empty_measurement.update_value(dt.add(hours=hour), "load0_mr", 500.0 + hour)
await empty_measurement.update_value(
to_datetime("2024-01-02T00:11:00"), "storage-soc-factor", 0.42
)
_, calls = await _adjustment_window(loadakkudoktoradjusted, empty_measurement)
assert calls
assert calls[0]["start_datetime"] == to_datetime("2024-01-01T00:00:00")
assert calls[0]["end_datetime"] == to_datetime("2024-01-02T00:00:00")
@pytest.mark.asyncio
@pytest.mark.parametrize(
"records",
[
[("14:15", "load0_mr", 1000.0), ("14:26", "storage-soc-factor", 0.42)],
[("14:11", "storage-soc-factor", 0.42)],
],
)
async def test_adjustment_within_first_hour_returns_zero(
loadakkudoktoradjusted, empty_measurement, records
):
"""Less than one full hour of data yields no adjustment instead of an error."""
for time, key, value in records:
await empty_measurement.update_value(to_datetime(f"2026-08-01T{time}:00"), key, value)
(weekday, weekend), calls = await _adjustment_window(loadakkudoktoradjusted, empty_measurement)
assert calls == []
assert not weekday.any() and not weekend.any()