mirror of
https://github.com/Akkudoktor-EOS/EOS.git
synced 2026-11-13 09:13:30 +01:00
Bobby NoelteandClaude Opus 5.5
faf37abfe7
An inverter profile describes the technical data of an inverter model: its nominal AC power, the DC→AC and AC→DC efficiency curves over the load fraction (AC power relative to the nominal power), the AC charge power limit of the model, whether that limit also limits PV charging, and an optional power derating over the ambient temperature. Curves are read linearly and clamped at their ends, so every lookup yields a value. The packaged profile generic-hybrid has typical hybrid inverter efficiencies, no nominal power (the inverter device has to provide it) and full power up to 45 degC. Inverter settings name their profile (inverter_profile, default generic-hybrid) and hold the differences of the unit in profile_adjustment: nominal_power_w (replaces the profile value, required for a generic profile), max_power_w and max_ac_charge_power_w (installation limits that can only lower; an AC charge limit of 0 disables AC charging). The effective parameters are resolved at the ambient temperature of the inverter, given by the new measurement key <device_id>-temperature-degc (45 degC without a fresh value); the power derating lowers the maximum power and the AC charge limit. Optimization parameters are always valid: the GENETIC and GENETIC0 parameter preparation resolve the inverter with resolve_current_operating_parameters_or_defaults, which never raises. An unusable profile gives the generic-hybrid profile, a missing nominal power the fallback of 10000 W, an inverter derated to zero power the parameters at 45 degC, and no usable profile at all the profile adjustment with constant efficiency; each is logged as error. The GENETIC inverter takes the AC→DC efficiency curve of the profile, solved exactly on each linear piece of the curve (about 2 % longer runs); GENETIC0 keeps constant efficiencies and no longer replaces the configured inverters with the demo inverter; a battery, electric vehicle or inverter that cannot be prepared is left out of the GENETIC0 run, never replaced by a demo device. Configurations migrate: max_power_w becomes profile_adjustment.nominal_power_w, max_ac_charge_power_w moves into the adjustment, an ac_to_dc_efficiency of 0 keeps AC charging disabled, and the efficiency fields are dropped with an error log, as for batteries, so the profile efficiencies apply. Home Assistant config paths follow. Additional changes - Move the curve algorithms of the battery profile into profilecurve, so battery and inverter profiles share them; the battery profile keeps its document format and classes. - Move ProfileBaseModel, the strict base of profile documents, into profilestore. - Serve inverter profiles through the profile REST API. Refuse to delete a profile that a configured device uses and that has no packaged profile to revert to (409). - Share the measurement access of the device settings in devicemeasurement. - Rename check_battery_profiles to check_device_profiles; the device profile check at configuration setup covers inverters, too. - Document inverter profiles, their configuration, defaults and sharing; regenerate the configuration and OpenAPI documentation. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Assisted-by: Claude Code (claude-opus-5-5)
318 lines
15 KiB
Python
318 lines
15 KiB
Python
"""Tests for the inverter device settings resolved from inverter profiles."""
|
|
|
|
import dataclasses
|
|
import math
|
|
from typing import Any, Optional
|
|
|
|
import pytest
|
|
|
|
from akkudoktoreos.devices.profile.inverterprofile import (
|
|
InverterProfile,
|
|
InverterProfileSettings,
|
|
)
|
|
from akkudoktoreos.devices.profile.profilecurve import PrecomputedCurve
|
|
from akkudoktoreos.devices.profile.profilestore import get_profile_store
|
|
from akkudoktoreos.devices.settings import invertermeasurement
|
|
from akkudoktoreos.devices.settings.inverterresolution import (
|
|
INVERTER_DEFAULT_TEMPERATURE_DEGC,
|
|
InverterOperatingPoint,
|
|
InverterResolutionError,
|
|
)
|
|
from akkudoktoreos.devices.settings.invertersettings import (
|
|
INVERTER_DEFAULT_PROFILE,
|
|
InverterCommonSettings,
|
|
InverterProfileAdjustment,
|
|
)
|
|
|
|
|
|
def make_settings(**adjustment: Any) -> InverterCommonSettings:
|
|
return InverterCommonSettings(
|
|
device_id="inverter1",
|
|
battery_id="battery1",
|
|
profile_adjustment=InverterProfileAdjustment(**adjustment),
|
|
)
|
|
|
|
|
|
@pytest.fixture
|
|
def generic(config_eos) -> InverterProfile:
|
|
"""The packaged generic hybrid inverter profile."""
|
|
return get_profile_store().get(InverterProfileSettings, "generic-hybrid")
|
|
|
|
|
|
@pytest.fixture
|
|
def use_profile(monkeypatch):
|
|
"""Let all inverter settings use the given compiled profile."""
|
|
|
|
def _use(profile: InverterProfile) -> None:
|
|
monkeypatch.setattr(InverterCommonSettings, "get_inverter_profile", lambda self: profile)
|
|
|
|
return _use
|
|
|
|
|
|
@pytest.fixture
|
|
def measured(monkeypatch) -> dict[str, Optional[float]]:
|
|
"""Measured values by key for the inverter measurement access."""
|
|
values: dict[str, Optional[float]] = {}
|
|
|
|
async def fake_get_measured_value(key: str, target_datetime: Any) -> Optional[float]:
|
|
return values.get(key)
|
|
|
|
monkeypatch.setattr(invertermeasurement, "get_measured_value", fake_get_measured_value)
|
|
return values
|
|
|
|
|
|
class TestDefaults:
|
|
def test_default_profile(self):
|
|
settings = InverterCommonSettings(device_id="inverter1")
|
|
assert settings.inverter_profile == INVERTER_DEFAULT_PROFILE == "generic-hybrid"
|
|
assert settings.profile_adjustment.model_dump() == InverterProfileAdjustment().model_dump()
|
|
|
|
def test_generic_profile_needs_a_nominal_power(self, generic):
|
|
settings = InverterCommonSettings(device_id="inverter1")
|
|
with pytest.raises(InverterResolutionError, match="inverter1.*nominal_power_w"):
|
|
settings.resolve_operating_parameters()
|
|
assert settings.effective_nominal_power_w is None
|
|
assert settings.effective_max_power_w is None
|
|
errors, warnings = settings.check_profile()
|
|
assert len(errors) == 1 and "inverter1" in errors[0]
|
|
assert warnings == []
|
|
|
|
@pytest.mark.parametrize(
|
|
"adjustment",
|
|
[{"nominal_power_w": 0}, {"max_power_w": 0}, {"max_ac_charge_power_w": -1}],
|
|
)
|
|
def test_rejects_invalid_adjustment(self, adjustment):
|
|
with pytest.raises(ValueError):
|
|
InverterProfileAdjustment(**adjustment)
|
|
|
|
|
|
class TestResolution:
|
|
def test_reference_point_is_45_degc(self, generic):
|
|
settings = make_settings(nominal_power_w=10000)
|
|
parameters = settings.resolve_operating_parameters()
|
|
assert parameters.temperature_degC == INVERTER_DEFAULT_TEMPERATURE_DEGC == 45.0
|
|
# The generic profile is not derated at 45 degC.
|
|
assert parameters.power_fraction == pytest.approx(1.0)
|
|
assert parameters.nominal_power_w == pytest.approx(10000)
|
|
assert parameters.max_power_w == pytest.approx(10000)
|
|
assert parameters.max_ac_charge_power_w == pytest.approx(10000)
|
|
assert settings.effective_max_power_w == pytest.approx(10000)
|
|
|
|
def test_efficiencies_come_from_the_profile(self, generic):
|
|
settings = make_settings(nominal_power_w=10000)
|
|
parameters = settings.resolve_operating_parameters()
|
|
# DC→AC at the reference load fraction 0.06 of the maximum power.
|
|
assert parameters.dc_to_ac_efficiency == pytest.approx(generic.dc_to_ac_efficiency_at(0.06))
|
|
# AC→DC at the AC charge limit, here the full nominal power.
|
|
assert parameters.ac_to_dc_efficiency == pytest.approx(generic.ac_to_dc_efficiency_at(1.0))
|
|
assert settings.effective_dc_to_ac_efficiency == pytest.approx(
|
|
parameters.dc_to_ac_efficiency
|
|
)
|
|
assert settings.effective_ac_to_dc_efficiency == pytest.approx(
|
|
parameters.ac_to_dc_efficiency
|
|
)
|
|
|
|
def test_derating_at_the_operating_point(self, generic):
|
|
settings = make_settings(nominal_power_w=10000)
|
|
parameters = settings.resolve_operating_parameters(InverterOperatingPoint(60.0))
|
|
assert parameters.power_fraction == pytest.approx(0.6)
|
|
assert parameters.max_power_w == pytest.approx(6000)
|
|
assert parameters.max_ac_charge_power_w == pytest.approx(6000)
|
|
|
|
def test_curves_are_over_the_load_fraction_of_the_maximum_power(self, generic):
|
|
settings = make_settings(nominal_power_w=10000)
|
|
parameters = settings.resolve_operating_parameters(InverterOperatingPoint(60.0))
|
|
# 3000 W are 0.3 of the nominal and 0.5 of the derated maximum power.
|
|
curve = PrecomputedCurve.from_points(
|
|
[x for x, _ in parameters.dc_to_ac_efficiency_curve],
|
|
[y for _, y in parameters.dc_to_ac_efficiency_curve],
|
|
)
|
|
assert curve.lookup(0.5) == pytest.approx(generic.dc_to_ac_efficiency_at(0.3))
|
|
# The curve ends at the maximum power, 0.6 of the nominal power.
|
|
assert parameters.dc_to_ac_efficiency_curve[-1] == pytest.approx(
|
|
(1.0, generic.dc_to_ac_efficiency_at(0.6))
|
|
)
|
|
assert all(0.0 <= x <= 1.0 for x, _ in parameters.dc_to_ac_efficiency_curve)
|
|
|
|
def test_curve_keeps_two_points_when_heavily_limited(self, generic):
|
|
# 400 W are below the first breakpoint (0.05 of 10 kW = 500 W).
|
|
settings = make_settings(nominal_power_w=10000, max_power_w=400)
|
|
curve = settings.resolve_operating_parameters().dc_to_ac_efficiency_curve
|
|
assert [x for x, _ in curve] == [0.0, 1.0]
|
|
assert [y for _, y in curve] == pytest.approx([0.88, 0.88])
|
|
settings.to_genetic_param()
|
|
|
|
def test_no_power_at_the_operating_point(self, generic):
|
|
settings = make_settings(nominal_power_w=10000)
|
|
with pytest.raises(InverterResolutionError, match="allows no power"):
|
|
settings.resolve_operating_parameters(InverterOperatingPoint(70.0))
|
|
|
|
def test_installation_limits_only_lower(self, generic):
|
|
settings = make_settings(nominal_power_w=10000, max_power_w=8000, max_ac_charge_power_w=3000)
|
|
parameters = settings.resolve_operating_parameters()
|
|
assert parameters.max_power_w == pytest.approx(8000)
|
|
assert parameters.max_ac_charge_power_w == pytest.approx(3000)
|
|
assert parameters.ac_to_dc_efficiency == pytest.approx(generic.ac_to_dc_efficiency_at(0.3))
|
|
assert settings.check_profile() == ([], [])
|
|
|
|
def test_derating_below_the_installation_limit(self, generic):
|
|
settings = make_settings(nominal_power_w=10000, max_power_w=8000)
|
|
parameters = settings.resolve_operating_parameters(InverterOperatingPoint(60.0))
|
|
assert parameters.max_power_w == pytest.approx(6000)
|
|
|
|
def test_zero_ac_charge_limit_disables_ac_charging(self, generic):
|
|
settings = make_settings(nominal_power_w=10000, max_ac_charge_power_w=0)
|
|
parameters = settings.resolve_operating_parameters()
|
|
assert parameters.max_ac_charge_power_w == 0
|
|
assert math.isfinite(parameters.ac_to_dc_efficiency)
|
|
assert settings.to_genetic_param().max_ac_charge_power_w == 0
|
|
|
|
def test_model_ac_charge_limit_is_derated(self, generic, use_profile):
|
|
use_profile(dataclasses.replace(generic, nominal_power_w=10000, max_ac_charge_power_w=5000))
|
|
settings = make_settings()
|
|
assert settings.resolve_operating_parameters().max_ac_charge_power_w == pytest.approx(5000)
|
|
derated = settings.resolve_operating_parameters(InverterOperatingPoint(60.0))
|
|
assert derated.max_ac_charge_power_w == pytest.approx(3000)
|
|
|
|
def test_profile_nominal_power_and_adjustment(self, generic, use_profile):
|
|
use_profile(dataclasses.replace(generic, nominal_power_w=6000))
|
|
assert make_settings().effective_nominal_power_w == pytest.approx(6000)
|
|
assert make_settings(nominal_power_w=8000).effective_nominal_power_w == pytest.approx(8000)
|
|
|
|
def test_missing_profile(self, config_eos):
|
|
settings = InverterCommonSettings(
|
|
device_id="inverter1",
|
|
inverter_profile="does-not-exist",
|
|
profile_adjustment=InverterProfileAdjustment(nominal_power_w=10000),
|
|
)
|
|
with pytest.raises(InverterResolutionError, match="does-not-exist.*not usable"):
|
|
settings.resolve_operating_parameters()
|
|
assert settings.effective_max_power_w is None
|
|
errors, _ = settings.check_profile()
|
|
assert "does-not-exist" in errors[0]
|
|
|
|
def test_warns_about_limits_without_effect(self, generic):
|
|
settings = make_settings(nominal_power_w=5000, max_power_w=8000, max_ac_charge_power_w=6000)
|
|
errors, warnings = settings.check_profile()
|
|
assert errors == []
|
|
assert len(warnings) == 2
|
|
assert "profile_adjustment.max_power_w" in warnings[0]
|
|
assert "profile_adjustment.max_ac_charge_power_w" in warnings[1]
|
|
|
|
|
|
class TestMeasurement:
|
|
def test_temperature_measurement_key(self):
|
|
settings = make_settings(nominal_power_w=10000)
|
|
assert settings.measurement_key_temperature_degc == "inverter1-temperature-degc"
|
|
assert "inverter1-temperature-degc" in settings.measurement_keys
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_measured_temperature(self, measured):
|
|
measured["inverter1-temperature-degc"] = 52.5
|
|
point = await make_settings().measure_operating_point()
|
|
assert point == InverterOperatingPoint(temperature_degC=52.5)
|
|
|
|
@pytest.mark.asyncio
|
|
@pytest.mark.parametrize("value", [None, float("nan"), float("inf")])
|
|
async def test_missing_temperature_defaults_to_45_degc(self, measured, value):
|
|
measured["inverter1-temperature-degc"] = value
|
|
point = await make_settings().measure_operating_point()
|
|
assert point.temperature_degC == 45.0
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_resolution_at_the_measured_temperature(self, generic, measured):
|
|
settings = make_settings(nominal_power_w=10000)
|
|
measured["inverter1-temperature-degc"] = 60.0
|
|
parameters = await settings.resolve_current_operating_parameters()
|
|
assert parameters.max_power_w == pytest.approx(6000)
|
|
|
|
|
|
class TestConversion:
|
|
def test_genetic_parameters(self, generic):
|
|
settings = make_settings(nominal_power_w=10000, max_ac_charge_power_w=4000)
|
|
parameters = settings.resolve_operating_parameters(InverterOperatingPoint(60.0))
|
|
genetic = settings.to_genetic_param(parameters)
|
|
assert genetic.device_id == "inverter1"
|
|
assert genetic.battery_id == "battery1"
|
|
assert genetic.max_power_wh == pytest.approx(6000)
|
|
assert genetic.max_ac_charge_power_w == pytest.approx(4000)
|
|
assert genetic.dc_to_ac_efficiency == pytest.approx(parameters.dc_to_ac_efficiency)
|
|
assert genetic.ac_to_dc_efficiency == pytest.approx(parameters.ac_to_dc_efficiency)
|
|
assert genetic.dc_to_ac_efficiency_curve == [
|
|
tuple(point) for point in parameters.dc_to_ac_efficiency_curve
|
|
]
|
|
assert genetic.ac_charge_limits_total_charge is False
|
|
|
|
def test_genetic0_parameters(self, generic):
|
|
settings = make_settings(nominal_power_w=10000)
|
|
genetic0 = settings.to_genetic0_param()
|
|
assert genetic0.max_power_wh == pytest.approx(10000)
|
|
assert genetic0.dc_to_ac_efficiency == pytest.approx(settings.effective_dc_to_ac_efficiency)
|
|
assert genetic0.ac_to_dc_efficiency == pytest.approx(settings.effective_ac_to_dc_efficiency)
|
|
|
|
|
|
@pytest.fixture
|
|
def logged_errors():
|
|
"""Collect the messages logged at ERROR level."""
|
|
from loguru import logger
|
|
|
|
messages: list[str] = []
|
|
sink_id = logger.add(lambda message: messages.append(message.record["message"]), level="ERROR")
|
|
yield messages
|
|
logger.remove(sink_id)
|
|
|
|
|
|
class TestOptimizationDefaults:
|
|
"""The parameter preparation of the optimizations never fails (defaults with an error log)."""
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_derated_to_zero_uses_the_reference_temperature(
|
|
self, generic, measured, logged_errors
|
|
):
|
|
"""generic-hybrid derates to 0 W at 65 degC; the run gets the 45 degC parameters."""
|
|
settings = make_settings(nominal_power_w=10000)
|
|
measured["inverter1-temperature-degc"] = 70.0
|
|
parameters = await settings.resolve_current_operating_parameters_or_defaults()
|
|
assert parameters.max_power_w == pytest.approx(10000)
|
|
assert parameters.temperature_degC == INVERTER_DEFAULT_TEMPERATURE_DEGC
|
|
assert len(logged_errors) == 1
|
|
assert "allows no power at 70.0 degC" in logged_errors[0]
|
|
# The conversion gets valid parameters.
|
|
assert settings.to_genetic_param(parameters).max_power_wh == pytest.approx(10000)
|
|
|
|
def test_missing_nominal_power_gives_the_fallback(self, generic, logged_errors):
|
|
parameters = make_settings().resolve_operating_parameters_or_defaults()
|
|
assert parameters.nominal_power_w == pytest.approx(10000)
|
|
assert len(logged_errors) == 1
|
|
assert "nominal power 10000 W" in logged_errors[0]
|
|
|
|
def test_unusable_profile_uses_the_generic_profile(self, generic, logged_errors):
|
|
settings = InverterCommonSettings(
|
|
device_id="inverter1",
|
|
battery_id="battery1",
|
|
inverter_profile="does-not-exist",
|
|
profile_adjustment=InverterProfileAdjustment(nominal_power_w=8000),
|
|
)
|
|
parameters = settings.resolve_operating_parameters_or_defaults()
|
|
assert parameters.nominal_power_w == pytest.approx(8000)
|
|
assert parameters.dc_to_ac_efficiency < 1.0 # from the generic profile curves
|
|
assert len(logged_errors) == 1
|
|
assert f"inverter profile '{INVERTER_DEFAULT_PROFILE}'" in logged_errors[0]
|
|
|
|
@pytest.mark.parametrize("error", [FileNotFoundError, PermissionError, IsADirectoryError])
|
|
def test_without_any_usable_profile(self, monkeypatch, logged_errors, error):
|
|
def missing(document_type, name, **options):
|
|
raise error(f"Inverter profile '{name}' is not readable")
|
|
|
|
monkeypatch.setattr(get_profile_store(), "get", missing)
|
|
settings = make_settings(nominal_power_w=8000, max_power_w=6000)
|
|
parameters = settings.resolve_operating_parameters_or_defaults()
|
|
assert parameters.max_power_w == pytest.approx(6000)
|
|
assert parameters.dc_to_ac_efficiency == pytest.approx(1.0)
|
|
assert len(logged_errors) == 1
|
|
assert "constant efficiency 1" in logged_errors[0]
|
|
|
|
def test_report_false_logs_nothing(self, generic, logged_errors):
|
|
make_settings().resolve_operating_parameters_or_defaults(report=False)
|
|
assert logged_errors == []
|