Cleanup: parameters: extra=forbid, optimize: battery, inverter optional (#361)

* Cleanup: parameters: extra=forbid, optimize: battery, inverter optional

 * Don't allow extra fields for parameters/REST-API (at least for now while
   changing API).
 * Allow both battery and inverter to be set optionally (atm optional
   battery not implemented, no API constraints).
 * inverter: Remove default max_power_wh
 * single_test_optimization: Add more cli-parameters

* Workflow docker-build: Don't try to authenticate for PRs

 * Secrets are not available anyway for forks.

src/akkudoktoreos/class_home_appliance.py

@@ -1,64 +0,0 @@
-import numpy as np
-from pydantic import BaseModel, Field
-
-
-class HomeApplianceParameters(BaseModel):
-    consumption_wh: int = Field(
-        gt=0,
-        description="An integer representing the energy consumption of a household device in watt-hours.",
-    )
-    duration_h: int = Field(
-        gt=0,
-        description="An integer representing the usage duration of a household device in hours.",
-    )
-
-
-class HomeAppliance:
-    def __init__(self, parameters: HomeApplianceParameters, hours: int):
-        self.hours = hours  # Total duration for which the planning is done
-        self.consumption_wh = (
-            parameters.consumption_wh
-        )  # Total energy consumption of the device in kWh
-        self.duration_h = parameters.duration_h  # Duration of use in hours
-        self.load_curve = np.zeros(self.hours)  # Initialize the load curve with zeros
-
-    def set_starting_time(self, start_hour: int, global_start_hour: int = 0) -> None:
-        """Sets the start time of the device and generates the corresponding load curve.
-
-        :param start_hour: The hour at which the device should start.
-        """
-        self.reset()
-        # Check if the duration of use is within the available time frame
-        if start_hour + self.duration_h > self.hours:
-            raise ValueError("The duration of use exceeds the available time frame.")
-        if start_hour < global_start_hour:
-            raise ValueError("The start time is earlier than the available time frame.")
-
-        # Calculate power per hour based on total consumption and duration
-        power_per_hour = self.consumption_wh / self.duration_h  # Convert to watt-hours
-
-        # Set the power for the duration of use in the load curve array
-        self.load_curve[start_hour : start_hour + self.duration_h] = power_per_hour
-
-    def reset(self) -> None:
-        """Resets the load curve."""
-        self.load_curve = np.zeros(self.hours)
-
-    def get_load_curve(self) -> np.ndarray:
-        """Returns the current load curve."""
-        return self.load_curve
-
-    def get_load_for_hour(self, hour: int) -> float:
-        """Returns the load for a specific hour.
-
-        :param hour: The hour for which the load is queried.
-        :return: The load in watts for the specified hour.
-        """
-        if hour < 0 or hour >= self.hours:
-            raise ValueError("The specified hour is outside the available time frame.")
-
-        return self.load_curve[hour]
-
-    def get_latest_starting_point(self) -> int:
-        """Returns the latest possible start time at which the device can still run completely."""
-        return self.hours - self.duration_h

src/akkudoktoreos/core/ems.py

@@ -8,7 +8,7 @@ from typing_extensions import Self
 
 from akkudoktoreos.core.coreabc import ConfigMixin, PredictionMixin, SingletonMixin
 from akkudoktoreos.core.logging import get_logger
-from akkudoktoreos.core.pydantic import PydanticBaseModel
+from akkudoktoreos.core.pydantic import ParametersBaseModel, PydanticBaseModel
 from akkudoktoreos.devices.battery import Battery
 from akkudoktoreos.devices.generic import HomeAppliance
 from akkudoktoreos.devices.inverter import Inverter
@@ -18,7 +18,7 @@ from akkudoktoreos.utils.utils import NumpyEncoder
 logger = get_logger(__name__)
 
 
-class EnergieManagementSystemParameters(PydanticBaseModel):
+class EnergieManagementSystemParameters(ParametersBaseModel):
     pv_prognose_wh: list[float] = Field(
         description="An array of floats representing the forecasted photovoltaic output in watts for different time intervals."
     )
@@ -50,7 +50,7 @@ class EnergieManagementSystemParameters(PydanticBaseModel):
         return self
 
 
-class SimulationResult(PydanticBaseModel):
+class SimulationResult(ParametersBaseModel):
     """This object contains the results of the simulation and provides insights into various parameters over the entire forecast period."""
 
     Last_Wh_pro_Stunde: list[Optional[float]] = Field(description="TBD")

src/akkudoktoreos/core/pydantic.py

@@ -478,3 +478,7 @@ class PydanticDateTimeSeries(PydanticBaseModel):
             dtype=str(series.dtype),
             tz=tz,
         )
+
+
+class ParametersBaseModel(PydanticBaseModel):
+    model_config = ConfigDict(extra="forbid")

src/akkudoktoreos/devices/battery.py

@@ -4,6 +4,7 @@ import numpy as np
 from pydantic import BaseModel, Field, field_validator
 
 from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.core.pydantic import ParametersBaseModel
 from akkudoktoreos.devices.devicesabc import DeviceBase
 from akkudoktoreos.utils.utils import NumpyEncoder
 
@@ -24,7 +25,7 @@ def initial_soc_percentage_field(description: str) -> int:
     return Field(default=0, ge=0, le=100, description=description)
 
 
-class BaseBatteryParameters(BaseModel):
+class BaseBatteryParameters(ParametersBaseModel):
     """Base class for battery parameters with fields for capacity, efficiency, and state of charge."""
 
     capacity_wh: int = Field(

src/akkudoktoreos/devices/generic.py

@@ -1,15 +1,16 @@
 from typing import Optional
 
 import numpy as np
-from pydantic import BaseModel, Field
+from pydantic import Field
 
 from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.core.pydantic import ParametersBaseModel
 from akkudoktoreos.devices.devicesabc import DeviceBase
 
 logger = get_logger(__name__)
 
 
-class HomeApplianceParameters(BaseModel):
+class HomeApplianceParameters(ParametersBaseModel):
     consumption_wh: int = Field(
         gt=0,
         description="An integer representing the energy consumption of a household device in watt-hours.",

src/akkudoktoreos/devices/inverter.py

@@ -1,17 +1,18 @@
 from typing import Optional
 
-from pydantic import BaseModel, Field
+from pydantic import Field
 from scipy.interpolate import RegularGridInterpolator
 
 from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.core.pydantic import ParametersBaseModel
 from akkudoktoreos.devices.battery import Battery
 from akkudoktoreos.devices.devicesabc import DeviceBase
 
 logger = get_logger(__name__)
 
 
-class InverterParameters(BaseModel):
-    max_power_wh: float = Field(default=10000, gt=0)
+class InverterParameters(ParametersBaseModel):
+    max_power_wh: float = Field(gt=0)
 
 
 class Inverter(DeviceBase):

src/akkudoktoreos/optimization/genetic.py

@@ -6,7 +6,7 @@ from typing import Any, Optional
 
 import numpy as np
 from deap import algorithms, base, creator, tools
-from pydantic import BaseModel, Field, field_validator, model_validator
+from pydantic import Field, field_validator, model_validator
 from typing_extensions import Self
 
 from akkudoktoreos.core.coreabc import (
@@ -16,6 +16,7 @@ from akkudoktoreos.core.coreabc import (
 )
 from akkudoktoreos.core.ems import EnergieManagementSystemParameters, SimulationResult
 from akkudoktoreos.core.logging import get_logger
+from akkudoktoreos.core.pydantic import ParametersBaseModel
 from akkudoktoreos.devices.battery import (
     Battery,
     ElectricVehicleParameters,
@@ -30,10 +31,10 @@ from akkudoktoreos.utils.utils import NumpyEncoder
 logger = get_logger(__name__)
 
 
-class OptimizationParameters(BaseModel):
+class OptimizationParameters(ParametersBaseModel):
     ems: EnergieManagementSystemParameters
-    pv_akku: SolarPanelBatteryParameters
-    inverter: InverterParameters = InverterParameters()
+    pv_akku: Optional[SolarPanelBatteryParameters]
+    inverter: Optional[InverterParameters]
     eauto: Optional[ElectricVehicleParameters]
     dishwasher: Optional[HomeApplianceParameters] = None
     temperature_forecast: Optional[list[Optional[float]]] = Field(
@@ -60,7 +61,7 @@ class OptimizationParameters(BaseModel):
         return start_solution
 
 
-class OptimizeResponse(BaseModel):
+class OptimizeResponse(ParametersBaseModel):
     """**Note**: The first value of "Last_Wh_per_hour", "Netzeinspeisung_Wh_per_hour", and "Netzbezug_Wh_per_hour", will be set to null in the JSON output and represented as NaN or None in the corresponding classes' data returns. This approach is adopted to ensure that the current hour's processing remains unchanged."""
 
     ac_charge: list[float] = Field(
@@ -565,11 +566,13 @@ class optimization_problem(ConfigMixin, DevicesMixin, EnergyManagementSystemMixi
         )
 
         # Initialize PV and EV batteries
-        akku = Battery(
-            parameters.pv_akku,
-            hours=self.config.prediction_hours,
-        )
-        akku.set_charge_per_hour(np.full(self.config.prediction_hours, 1))
+        akku: Optional[Battery] = None
+        if parameters.pv_akku:
+            akku = Battery(
+                parameters.pv_akku,
+                hours=self.config.prediction_hours,
+            )
+            akku.set_charge_per_hour(np.full(self.config.prediction_hours, 1))
 
         eauto: Optional[Battery] = None
         if parameters.eauto:
@@ -595,11 +598,13 @@ class optimization_problem(ConfigMixin, DevicesMixin, EnergyManagementSystemMixi
         )
 
         # Initialize the inverter and energy management system
-        inverter = Inverter(
-            sc,
-            parameters.inverter,
-            akku,
-        )
+        inverter: Optional[Inverter] = None
+        if parameters.inverter:
+            inverter = Inverter(
+                sc,
+                parameters.inverter,
+                akku,
+            )
         self.ems.set_parameters(
             parameters.ems,
             inverter=inverter,