fix(adapter): stamp Home Assistant device states with run time, not slot start (#1452)

* fix(adapter): stamp Home Assistant device states with run time, not slot start The Home Assistant adapter stored every reading with ems_start_datetime, which set_start_datetime() rounds down to the optimization slot (e.g. 14:00 for a run at 14:11). The GENETIC configuration request checks SoC freshness against the unrounded observation_datetime with measurement_max_age_seconds (default 300 s). Any run starting more than five minutes into a slot therefore discarded the freshly read SoC and optimized with 0 % initial SoC. Stamp device state measurements (device_measurement_entity_ids, e.g. SoC) with observation_datetime instead. Not to_datetime(): a reading taken a few seconds after the observation time would be rejected as a future sample. Meter readings (load, grid import/export, PV) keep the slot start, because their energy is aggregated per slot. With device states at their real time, a record holding only some keys can now be the newest one (e.g. the Home Assistant battery SoC while the EV SoC or a cycle count comes through the measurement API). Readers therefore skip records without the value they need: - GENETIC SoC and completed appliance cycles: such a record no longer hides a fresh value (the cycle count case aborted the optimization). This also covers a meter reading at the slot start that is newer than a SoC supplied through the measurement API. Values stored as pandas NA count as missing instead of raising TypeError; an explicit NaN stays an invalid sample. - GENETIC0 SoC: looks up the reading nearest to observation_datetime instead of the slot start, skipping records without SoC and converting only the selected sample. Before, a run late in the slot (14:40 in the 14:00 slot) would pick the previous run's reading (13:40). This also fixes SoC values PUT via the REST API with their real time. LoadAkkudoktorAdjusted anchored its hourly comparison window on the newest record of any key. An off-hour device state would shift every bucket (e.g. to :11) against hour-aligned meter readings; the window now starts and ends on full hours, and less than one full hour of data yields no adjustment instead of an error. (15-minute slot starts and SoC values PUT with their real time had the same effect before.) Regenerated openapi.json and docs/_generated/openapi.md (version only). Fixes #1447 Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01EYWR1HVM8a8src23xuyL3T * test(genetic0): use pv_battery instead of deprecated pv_akku mypy flags attribute access on the pv_akku computed field (attr-defined), which failed the pre-commit check of the PR. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01EYWR1HVM8a8src23xuyL3T --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-29 09:11:57 +00:00 · 2026-10-26 07:14:00 +01:00
parent 5249b389f5
commit 58b968562e
10 changed files with 470 additions and 18 deletions
@@ -0,0 +1,160 @@
+"""GENETIC0 must use the SoC read during the run, not an older reading (#1447)."""
+
+from unittest.mock import AsyncMock, Mock, patch
+
+import numpy as np
+import pandas as pd
+import pytest
+import pytest_asyncio
+
+from akkudoktoreos.core.coreabc import get_ems, get_measurement
+from akkudoktoreos.optimization.genetic0.genetic0params import (
+    Genetic0OptimizationParameters,
+)
+from akkudoktoreos.utils.datetimeutil import to_datetime
+
+
+@pytest_asyncio.fixture
+async def isolated_measurement(config_eos):
+    """Keep synthetic records out of the process-wide measurement singleton."""
+    measurement = get_measurement()
+    await measurement.delete_by_datetime(None, None)
+    try:
+        yield measurement
+    finally:
+        await measurement.delete_by_datetime(None, None)
+
+
+@pytest.mark.asyncio
+async def test_soc_read_late_in_slot_beats_previous_reading(config_eos, isolated_measurement):
+    config_eos.merge_settings_from_dict(
+        {
+            "prediction": {"hours": 48},
+            "optimization": {"genetic0": {"horizon_hours": 24}},
+            "elecfee": {"provider": None},
+            "devices": {
+                "max_batteries": 1,
+                "max_electric_vehicles": 0,
+                "max_inverters": 1,
+                "max_home_appliances": 0,
+                "batteries": {"storage": {"capacity_wh": 2000, "max_charge_power_w": 1000}},
+                "inverters": {"inverter": {"battery_id": "storage", "max_power_w": 1000}},
+            },
+        }
+    )
+    # A run at 14:40 belongs to the 14:00 slot. The previous run (13:40) is closer
+    # to the slot start than the reading taken now.
+    run_time = to_datetime("2026-08-01T14:40:00+00:00")
+    get_ems().set_start_datetime(run_time)
+    measurement = isolated_measurement
+    await measurement.update_value(run_time.subtract(hours=1), "storage-soc-factor", 0.10)
+    await measurement.update_value(run_time, "storage-soc-factor", 0.42)
+
+    tariff = pd.Series(
+        0.00008, index=pd.date_range("2026-08-01T00:00:00Z", periods=72 * 4, freq="15min")
+    )
+
+    async def read_array(**kwargs):
+        return np.full(48, 0.0003)
+
+    prediction = Mock(
+        update_data=AsyncMock(),
+        key_to_array=AsyncMock(side_effect=read_array),
+        key_to_raw_series=AsyncMock(return_value=tariff),
+    )
+    with patch.object(Genetic0OptimizationParameters, "prediction", prediction):
+        parameters = await Genetic0OptimizationParameters.prepare()
+
+    assert parameters is not None
+    assert parameters.pv_battery is not None
+    assert parameters.pv_battery.initial_soc_percentage == 42
+
+
+@pytest.mark.asyncio
+async def test_meter_only_record_does_not_mask_soc(config_eos, isolated_measurement):
+    config_eos.merge_settings_from_dict(
+        {
+            "prediction": {"hours": 48},
+            "optimization": {"genetic0": {"horizon_hours": 24}},
+            "elecfee": {"provider": None},
+            "measurement": {"load_emr_keys": ["load_meter"]},
+            "devices": {
+                "max_batteries": 1,
+                "max_electric_vehicles": 0,
+                "max_inverters": 1,
+                "max_home_appliances": 0,
+                "batteries": {"storage": {"capacity_wh": 2000, "max_charge_power_w": 1000}},
+                "inverters": {"inverter": {"battery_id": "storage", "max_power_w": 1000}},
+            },
+        }
+    )
+    run_time = to_datetime("2026-08-01T14:40:00+00:00")
+    get_ems().set_start_datetime(run_time)
+    measurement = isolated_measurement
+    # SoC through the measurement API at 13:30, the adapter's meter reading at the
+    # slot start (14:00); the run at 14:40 must still find the SoC.
+    await measurement.update_value(run_time.subtract(minutes=70), "storage-soc-factor", 0.42)
+    await measurement.update_value(get_ems().start_datetime, "load_meter", 1234.5)
+
+    tariff = pd.Series(
+        0.00008, index=pd.date_range("2026-08-01T00:00:00Z", periods=72 * 4, freq="15min")
+    )
+
+    async def read_array(**kwargs):
+        return np.full(48, 0.0003)
+
+    prediction = Mock(
+        update_data=AsyncMock(),
+        key_to_array=AsyncMock(side_effect=read_array),
+        key_to_raw_series=AsyncMock(return_value=tariff),
+    )
+    with patch.object(Genetic0OptimizationParameters, "prediction", prediction):
+        parameters = await Genetic0OptimizationParameters.prepare()
+
+    assert parameters is not None
+    assert parameters.pv_battery is not None
+    assert parameters.pv_battery.initial_soc_percentage == 42
+
+
+@pytest.mark.asyncio
+async def test_older_missing_value_does_not_spoil_current_soc(config_eos, isolated_measurement):
+    config_eos.merge_settings_from_dict(
+        {
+            "prediction": {"hours": 48},
+            "optimization": {"genetic0": {"horizon_hours": 24}},
+            "elecfee": {"provider": None},
+            "devices": {
+                "max_batteries": 1,
+                "max_electric_vehicles": 0,
+                "max_inverters": 1,
+                "max_home_appliances": 0,
+                "batteries": {"storage": {"capacity_wh": 2000, "max_charge_power_w": 1000}},
+                "inverters": {"inverter": {"battery_id": "storage", "max_power_w": 1000}},
+            },
+        }
+    )
+    run_time = to_datetime("2026-08-01T14:40:00+00:00")
+    get_ems().set_start_datetime(run_time)
+    measurement = isolated_measurement
+    # An older reading stored as pandas NA (e.g. a JSON null in a Float64 series).
+    await measurement.update_value(run_time.subtract(hours=1), "storage-soc-factor", pd.NA)
+    await measurement.update_value(run_time, "storage-soc-factor", 0.42)
+
+    tariff = pd.Series(
+        0.00008, index=pd.date_range("2026-08-01T00:00:00Z", periods=72 * 4, freq="15min")
+    )
+
+    async def read_array(**kwargs):
+        return np.full(48, 0.0003)
+
+    prediction = Mock(
+        update_data=AsyncMock(),
+        key_to_array=AsyncMock(side_effect=read_array),
+        key_to_raw_series=AsyncMock(return_value=tariff),
+    )
+    with patch.object(Genetic0OptimizationParameters, "prediction", prediction):
+        parameters = await Genetic0OptimizationParameters.prepare()
+
+    assert parameters is not None
+    assert parameters.pv_battery is not None
+    assert parameters.pv_battery.initial_soc_percentage == 42