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)

tests/test_genetic0params.py

@@ -158,7 +158,9 @@ class TestGenetic0MeasuredSOC:
                     "max_electric_vehicles": 0,
                     "max_inverters": 1,
                     "max_home_appliances": 0,
-                    "batteries": {"storage": {"capacity_wh": 2000, "max_charge_power_w": 1000}},
+                    "batteries": {
+                        "storage": {"profile_adjustment": {"nominal_capacity_wh": 2000, "max_charge_power_w": 1000}}
+                    },
                     "inverters": {"inverter": {"battery_id": "storage", "max_power_w": 1000}},
                 },
             }
@@ -203,7 +205,9 @@ class TestGenetic0MeasuredSOC:
                     "max_electric_vehicles": 0,
                     "max_inverters": 1,
                     "max_home_appliances": 0,
-                    "batteries": {"storage": {"capacity_wh": 2000, "max_charge_power_w": 1000}},
+                    "batteries": {
+                        "storage": {"profile_adjustment": {"nominal_capacity_wh": 2000, "max_charge_power_w": 1000}}
+                    },
                     "inverters": {"inverter": {"battery_id": "storage", "max_power_w": 1000}},
                 },
             }
@@ -247,7 +251,9 @@ class TestGenetic0MeasuredSOC:
                     "max_electric_vehicles": 0,
                     "max_inverters": 1,
                     "max_home_appliances": 0,
-                    "batteries": {"storage": {"capacity_wh": 2000, "max_charge_power_w": 1000}},
+                    "batteries": {
+                        "storage": {"profile_adjustment": {"nominal_capacity_wh": 2000, "max_charge_power_w": 1000}}
+                    },
                     "inverters": {"inverter": {"battery_id": "storage", "max_power_w": 1000}},
                 },
             }
@@ -277,3 +283,106 @@ class TestGenetic0MeasuredSOC:
         assert parameters is not None
         assert parameters.pv_battery is not None
         assert parameters.pv_battery.initial_soc_percentage == 42
+
+
+class TestGenetic0DemoData:
+    """Demo device data used when no battery / electric vehicle is configured."""
+
+    @pytest.mark.asyncio
+    async def test_demo_devices_use_nominal_capacity(self, config_eos):
+        config_eos.merge_settings_from_dict(
+            {
+                "prediction": {"hours": 48},
+                "optimization": {"genetic0": {"horizon_hours": 24}},
+                "elecfee": {"provider": None},
+                "devices": {
+                    "max_batteries": 1,
+                    "max_electric_vehicles": 1,
+                    "max_inverters": 0,
+                    "max_home_appliances": 0,
+                    "batteries": None,
+                    "electric_vehicles": None,
+                },
+            }
+        )
+        get_ems().set_start_datetime(to_datetime("2026-08-01T14:00:00+00:00"))
+        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
+        # The demo capacities must reach the profile adjustment of the settings;
+        # the generic default profile provides no capacity of its own.
+        assert config_eos.devices.batteries["battery1"].profile_adjustment.nominal_capacity_wh == 8000
+        assert (
+            config_eos.devices.electric_vehicles["ev1"].profile_adjustment.nominal_capacity_wh
+            == 50000
+        )
+        assert parameters.pv_battery is not None
+        assert parameters.pv_battery.capacity_wh == 8000
+        assert parameters.ev is not None
+        assert parameters.ev.capacity_wh == 50000
+
+    @pytest.mark.asyncio
+    async def test_battery_configuration_error_uses_defaults_not_demo_data(self, config_eos):
+        """A misconfigured battery keeps its configuration, with defaults for the rest."""
+        from loguru import logger
+
+        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": 0,
+                    "max_home_appliances": 0,
+                    # generic-lfp provides no capacity and the adjustment none either.
+                    "batteries": {"storage": {"min_soc_percentage": 20}},
+                    "electric_vehicles": None,
+                },
+            }
+        )
+        get_ems().set_start_datetime(to_datetime("2026-08-01T14:00:00+00:00"))
+        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),
+        )
+        messages: list[str] = []
+        sink_id = logger.add(
+            lambda message: messages.append(message.record["message"]), level="ERROR"
+        )
+        try:
+            with patch.object(Genetic0OptimizationParameters, "prediction", prediction):
+                parameters = await Genetic0OptimizationParameters.prepare()
+        finally:
+            logger.remove(sink_id)
+        assert parameters is not None
+        assert parameters.pv_battery is not None
+        # The configured battery, not the demo battery: its own SoC minimum.
+        assert parameters.pv_battery.device_id == "storage"
+        assert parameters.pv_battery.min_soc_percentage == 20
+        assert parameters.pv_battery.capacity_wh == 8000
+        assert any(
+            "Battery 'storage'" in m and "nominal capacity 8000 Wh" in m for m in messages
+        )