renamed haushaltsgeräte to home appliance (#196)

* * rename Haushaltsgeraete to home appliance
* renamed strafe to penalty (optimization problem)

Signed-off-by: Jürgen Eckel <juergen.eckel@gmail.com>

* removed penalty renaming

Signed-off-by: Jürgen Eckel <juergen.eckel@gmail.com>

* renamed one variable

Signed-off-by: Jürgen Eckel <juergen.eckel@gmail.com>

* * renamed variable names and methods of the home appliance class

* renamed missed method names

* fixed renamed variable

* renamed object

* adjusted to latest repo changes

* renamed file to class_home_applianc.py

* renamed method

---------

Signed-off-by: Jürgen Eckel <juergen.eckel@gmail.com>
Signed-off-by: Jürgen Eckel <juergen@riddleandcode.com>

.pre-commit-config.yaml

@@ -9,6 +9,8 @@ repos:
       - id: check-yaml
       - id: end-of-file-fixer
       - id: trailing-whitespace
+      - id: check-merge-conflict
+        exclude: '\.rst$'  # Exclude .rst files
   - repo: https://github.com/PyCQA/isort
     rev: 5.13.2
     hooks:

docs/akkudoktoreos/openapi.json

@@ -496,27 +496,27 @@
         "type": "object",
         "title": "HTTPValidationError"
       },
-      "HaushaltsgeraetParameters": {
+      "HomeApplianceParameters": {
         "properties": {
-          "verbrauch_wh": {
+          "consumption_wh": {
             "type": "integer",
             "exclusiveMinimum": 0.0,
-            "title": "Verbrauch Wh",
+            "title": "Consumption Wh",
             "description": "An integer representing the energy consumption of a household device in watt-hours."
           },
-          "dauer_h": {
+          "duration_h": {
             "type": "integer",
             "exclusiveMinimum": 0.0,
-            "title": "Dauer H",
+            "title": "Duration H",
             "description": "An integer representing the usage duration of a household device in hours."
           }
         },
         "type": "object",
         "required": [
-          "verbrauch_wh",
+          "consumption_wh",
-          "dauer_h"
+          "duration_h"
         ],
-        "title": "HaushaltsgeraetParameters"
+        "title": "HomeApplianceParameters"
       },
       "OptimizationParameters": {
         "properties": {
@@ -535,10 +535,10 @@
           "eauto": {
             "$ref": "#/components/schemas/EAutoParameters"
           },
-          "spuelmaschine": {
+          "dishwasher": {
             "anyOf": [
               {
-                "$ref": "#/components/schemas/HaushaltsgeraetParameters"
+                "$ref": "#/components/schemas/HomeApplianceParameters"
               },
               {
                 "type": "null"
@@ -624,7 +624,7 @@
             "title": "Start Solution",
             "description": "An array of binary values (0 or 1) representing a possible starting solution for the simulation."
           },
-          "spuelstart": {
+          "washingstart": {
             "anyOf": [
               {
                 "type": "integer"
@@ -633,7 +633,7 @@
                 "type": "null"
               }
             ],
-            "title": "Spuelstart",
+            "title": "Washingstart",
             "description": "Can be `null` or contain an object representing the start of washing (if applicable)."
           }
         },
@@ -782,7 +782,7 @@
             "title": "Gesamtkosten Euro",
             "description": "The total costs in euros."
           },
-          "Haushaltsgeraet_wh_pro_stunde": {
+          "Home_appliance_wh_per_hour": {
             "items": {
               "anyOf": [
                 {
@@ -794,7 +794,7 @@
               ]
             },
             "type": "array",
-            "title": "Haushaltsgeraet Wh Pro Stunde",
+            "title": "Home Appliance Wh Per Hour",
             "description": "The energy consumption of a household appliance in watt-hours per hour."
           },
           "Kosten_Euro_pro_Stunde": {
@@ -882,7 +882,7 @@
           "Gesamtbilanz_Euro",
           "Gesamteinnahmen_Euro",
           "Gesamtkosten_Euro",
-          "Haushaltsgeraet_wh_pro_stunde",
+          "Home_appliance_wh_per_hour",
           "Kosten_Euro_pro_Stunde",
           "Netzbezug_Wh_pro_Stunde",
           "Netzeinspeisung_Wh_pro_Stunde",

single_test_optimization.py

@@ -267,11 +267,11 @@ parameters = OptimizationParameters(
             # Current SOC of the electric car (%)
             "start_soc_prozent": 5,
         },
-        # "spuelmaschine": {
+        # "dishwasher": {
         #     # Household appliance consumption (Wh)
-        #     "verbrauch_wh": 5000,
+        #     "consumption_wh": 5000,
         #     # Duration of appliance usage (hours)
-        #     "dauer_h": 0,
+        #     "duration_h": 0,
         # },
         # Temperature forecast (48 hours)
         "temperature_forecast": temperature_forecast,

src/akkudoktoreos/class_home_appliance.py

@@ -0,0 +1,64 @@
+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=None):
+        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, global_start_hour=0):
+        """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):
+        """Resets the load curve."""
+        self.load_curve = np.zeros(self.hours)
+
+    def get_load_curve(self):
+        """Returns the current load curve."""
+        return self.load_curve
+
+    def get_load_for_hour(self, hour):
+        """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):
+        """Returns the latest possible start time at which the device can still run completely."""
+        return self.hours - self.duration_h

src/akkudoktoreos/devices/generic.py

@@ -2,53 +2,53 @@ import numpy as np
 from pydantic import BaseModel, Field
 
 
-class HaushaltsgeraetParameters(BaseModel):
+class HomeApplianceParameters(BaseModel):
-    verbrauch_wh: int = Field(
+    consumption_wh: int = Field(
         gt=0,
         description="An integer representing the energy consumption of a household device in watt-hours.",
     )
-    dauer_h: int = Field(
+    duration_h: int = Field(
         gt=0,
         description="An integer representing the usage duration of a household device in hours.",
     )
 
 
-class Haushaltsgeraet:
+class HomeAppliance:
-    def __init__(self, parameters: HaushaltsgeraetParameters, hours=24):
+    def __init__(self, parameters: HomeApplianceParameters, hours=None):
         self.hours = hours  # Total duration for which the planning is done
-        self.verbrauch_wh = (
+        self.consumption_wh = (
-            parameters.verbrauch_wh  # Total energy consumption of the device in kWh
+            parameters.consumption_wh
-        )
+        )  # Total energy consumption of the device in kWh
-        self.dauer_h = parameters.dauer_h  # Duration of use in hours
+        self.duration_h = parameters.duration_h  # Duration of use in hours
-        self.lastkurve = np.zeros(self.hours)  # Initialize the load curve with zeros
+        self.load_curve = np.zeros(self.hours)  # Initialize the load curve with zeros
 
-    def set_startzeitpunkt(self, start_hour, global_start_hour=0):
+    def set_starting_time(self, start_hour, global_start_hour=0):
         """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.dauer_h > self.hours:
+        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
-        leistung_pro_stunde = self.verbrauch_wh / self.dauer_h  # Convert to watt-hours
+        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.lastkurve[start_hour : start_hour + self.dauer_h] = leistung_pro_stunde
+        self.load_curve[start_hour : start_hour + self.duration_h] = power_per_hour
 
     def reset(self):
         """Resets the load curve."""
-        self.lastkurve = np.zeros(self.hours)
+        self.load_curve = np.zeros(self.hours)
 
-    def get_lastkurve(self):
+    def get_load_curve(self):
         """Returns the current load curve."""
-        return self.lastkurve
+        return self.load_curve
 
-    def get_last_fuer_stunde(self, hour):
+    def get_load_for_hour(self, hour):
         """Returns the load for a specific hour.
 
         :param hour: The hour for which the load is queried.
@@ -57,8 +57,8 @@ class Haushaltsgeraet:
         if hour < 0 or hour >= self.hours:
             raise ValueError("The specified hour is outside the available time frame.")
 
-        return self.lastkurve[hour]
+        return self.load_curve[hour]
 
-    def spaetestmoeglicher_startzeitpunkt(self):
+    def get_latest_starting_point(self):
         """Returns the latest possible start time at which the device can still run completely."""
-        return self.hours - self.dauer_h
+        return self.hours - self.duration_h

src/akkudoktoreos/devices/heatpump.py

@@ -125,15 +125,15 @@ if __name__ == "__main__":
     start_innentemperatur = 15  # Initial indoor temperature
     isolationseffizienz = 0.8  # Insulation efficiency
     gewuenschte_innentemperatur = 20  # Desired indoor temperature
-    wp = Heatpump(max_heizleistung, 24)  # Initialize heat pump with prediction hours
+    hp = Heatpump(max_heizleistung, 24)  # Initialize heat pump with prediction hours
 
     # Print COP for various outside temperatures
-    print(wp.calculate_cop(-10), " ", wp.calculate_cop(0), " ", wp.calculate_cop(10))
+    print(hp.calculate_cop(-10), " ", hp.calculate_cop(0), " ", hp.calculate_cop(10))
 
     # 24 hours of outside temperatures (example values)
     temperaturen = [ 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -1, -2, -3, -4, -5, -6, -7, -8, -9, -10, -5, -2, 5, ]  # fmt: skip
 
     # Calculate the 24-hour power data
-    leistungsdaten = wp.simulate_24h(temperaturen)
+    leistungsdaten = hp.simulate_24h(temperaturen)
 
     print(leistungsdaten)

src/akkudoktoreos/optimization/genetic.py

@@ -8,7 +8,7 @@ from typing_extensions import Self
 
 from akkudoktoreos.config import AppConfig
 from akkudoktoreos.devices.battery import EAutoParameters, PVAkku, PVAkkuParameters
-from akkudoktoreos.devices.generic import Haushaltsgeraet, HaushaltsgeraetParameters
+from akkudoktoreos.devices.generic import HomeAppliance, HomeApplianceParameters
 from akkudoktoreos.devices.inverter import Wechselrichter, WechselrichterParameters
 from akkudoktoreos.prediction.ems import (
     EnergieManagementSystem,
@@ -22,7 +22,7 @@ class OptimizationParameters(BaseModel):
     pv_akku: PVAkkuParameters
     wechselrichter: WechselrichterParameters = WechselrichterParameters()
     eauto: EAutoParameters
-    spuelmaschine: Optional[HaushaltsgeraetParameters] = None
+    dishwasher: Optional[HomeApplianceParameters] = None
     temperature_forecast: list[float] = Field(
         "An array of floats representing the temperature forecast in degrees Celsius for different time intervals."
     )
@@ -86,7 +86,7 @@ class SimulationResult(BaseModel):
     )
     Gesamteinnahmen_Euro: float = Field(description="The total revenues in euros.")
     Gesamtkosten_Euro: float = Field(description="The total costs in euros.")
-    Haushaltsgeraet_wh_pro_stunde: list[Optional[float]] = Field(
+    Home_appliance_wh_per_hour: list[Optional[float]] = Field(
         description="The energy consumption of a household appliance in watt-hours per hour."
     )
     Kosten_Euro_pro_Stunde: list[Optional[float]] = Field(
@@ -120,7 +120,7 @@ class SimulationResult(BaseModel):
 #    Gesamtbilanz_Euro: float = Field(description="The total simulated balance in euros.")
 #    Gesamteinnahmen_Euro: float = Field(description="The total simulated income in euros.")
 #    Gesamtkosten_Euro: float = Field(description="The total simulated costs in euros.")
-#    Haushaltsgeraet_wh_pro_stunde: list[Optional[float]] = Field(
+#    Home_appliance_wh_per_hour: list[Optional[float]] = Field(
 #        description="An array of floats representing the simulated energy consumption of a household appliance in watt-hours per hour."
 #    )
 #    Kosten_Euro_pro_Stunde: list[Optional[float]] = Field(
@@ -158,7 +158,7 @@ class OptimizeResponse(BaseModel):
         None,
         description="An array of binary values (0 or 1) representing a possible starting solution for the simulation.",
     )
-    spuelstart: Optional[int] = Field(
+    washingstart: Optional[int] = Field(
         None,
         description="Can be `null` or contain an object representing the start of washing (if applicable).",
     )
@@ -285,7 +285,7 @@ class optimization_problem:
             individual[self.prediction_hours : self.prediction_hours * 2] = ev_charge_part_mutated
 
         # Step 3: Mutate appliance start times if household appliances are part of the optimization
-        if self.opti_param["haushaltsgeraete"] > 0:
+        if self.opti_param["home_appliance"] > 0:
             # Extract the appliance part (typically a single value for the start hour)
             appliance_part = [individual[-1]]
 
@@ -311,7 +311,7 @@ class optimization_problem:
             ]
 
         # Add the start time of the household appliance if it's being optimized
-        if self.opti_param["haushaltsgeraete"] > 0:
+        if self.opti_param["home_appliance"] > 0:
             individual_components += [self.toolbox.attr_int()]
 
         return creator.Individual(individual_components)
@@ -333,12 +333,12 @@ class optimization_problem:
             else None
         )
 
-        spuelstart_int = (
+        washingstart_int = (
             individual[-1]
-            if self.opti_param and self.opti_param.get("haushaltsgeraete", 0) > 0
+            if self.opti_param and self.opti_param.get("home_appliance", 0) > 0
             else None
         )
-        return discharge_hours_bin, eautocharge_hours_float, spuelstart_int
+        return discharge_hours_bin, eautocharge_hours_float, washingstart_int
 
     def setup_deap_environment(self, opti_param: dict[str, Any], start_hour: int) -> None:
         """Set up the DEAP environment with fitness and individual creation rules."""
@@ -410,11 +410,11 @@ class optimization_problem:
         This is an internal function.
         """
         ems.reset()
-        discharge_hours_bin, eautocharge_hours_index, spuelstart_int = self.split_individual(
+        discharge_hours_bin, eautocharge_hours_index, washingstart_int = self.split_individual(
             individual
         )
-        if self.opti_param.get("haushaltsgeraete", 0) > 0:
+        if self.opti_param.get("home_appliance", 0) > 0:
-            ems.set_haushaltsgeraet_start(spuelstart_int, global_start_hour=start_hour)
+            ems.set_home_appliance_start(washingstart_int, global_start_hour=start_hour)
 
         ac, dc, discharge = self.decode_charge_discharge(discharge_hours_bin)
 
@@ -557,12 +557,12 @@ class optimization_problem:
         eauto.set_charge_per_hour(np.full(self.prediction_hours, 1))
 
         # Initialize household appliance if applicable
-        spuelmaschine = (
+        dishwasher = (
-            Haushaltsgeraet(
+            HomeAppliance(
-                parameters=parameters.spuelmaschine,
+                parameters=parameters.dishwasher,
                 hours=self.prediction_hours,
             )
-            if parameters.spuelmaschine is not None
+            if parameters.dishwasher is not None
             else None
         )
 
@@ -572,12 +572,12 @@ class optimization_problem:
             self._config.eos,
             parameters.ems,
             eauto=eauto,
-            haushaltsgeraet=spuelmaschine,
+            home_appliance=dishwasher,
             wechselrichter=wr,
         )
 
         # Setup the DEAP environment and optimization process
-        self.setup_deap_environment({"haushaltsgeraete": 1 if spuelmaschine else 0}, start_hour)
+        self.setup_deap_environment({"home_appliance": 1 if dishwasher else 0}, start_hour)
         self.toolbox.register(
             "evaluate",
             lambda ind: self.evaluate(ind, ems, parameters, start_hour, worst_case),
@@ -586,7 +586,7 @@ class optimization_problem:
 
         # Perform final evaluation on the best solution
         o = self.evaluate_inner(start_solution, ems, start_hour)
-        discharge_hours_bin, eautocharge_hours_float, spuelstart_int = self.split_individual(
+        discharge_hours_bin, eautocharge_hours_float, washingstart_int = self.split_individual(
             start_solution
         )
         if self.optimize_ev:
@@ -622,7 +622,7 @@ class optimization_problem:
             "Einnahmen_Euro_pro_Stunde",
             "EAuto_SoC_pro_Stunde",
             "Verluste_Pro_Stunde",
-            "Haushaltsgeraet_wh_pro_stunde",
+            "Home_appliance_wh_per_hour",
         ]
 
         # Loop through each key in the list
@@ -649,6 +649,6 @@ class optimization_problem:
             "result": o,
             "eauto_obj": ems.eauto.to_dict(),
             "start_solution": start_solution,
-            "spuelstart": spuelstart_int,
+            "washingstart": washingstart_int,
             # "simulation_data": o,
         }

src/akkudoktoreos/prediction/ems.py

@@ -7,7 +7,7 @@ from typing_extensions import Self
 
 from akkudoktoreos.config import EOSConfig
 from akkudoktoreos.devices.battery import PVAkku
-from akkudoktoreos.devices.generic import Haushaltsgeraet
+from akkudoktoreos.devices.generic import HomeAppliance
 from akkudoktoreos.devices.inverter import Wechselrichter
 
 
@@ -47,7 +47,7 @@ class EnergieManagementSystem:
         config: EOSConfig,
         parameters: EnergieManagementSystemParameters,
         eauto: Optional[PVAkku] = None,
-        haushaltsgeraet: Optional[Haushaltsgeraet] = None,
+        home_appliance: Optional[HomeAppliance] = None,
         wechselrichter: Optional[Wechselrichter] = None,
     ):
         self.akku = wechselrichter.akku
@@ -60,7 +60,7 @@ class EnergieManagementSystem:
             else np.full(len(self.gesamtlast), parameters.einspeiseverguetung_euro_pro_wh, float)
         )
         self.eauto = eauto
-        self.haushaltsgeraet = haushaltsgeraet
+        self.home_appliance = home_appliance
         self.wechselrichter = wechselrichter
         self.ac_charge_hours = np.full(config.prediction_hours, 0)
         self.dc_charge_hours = np.full(config.prediction_hours, 1)
@@ -78,8 +78,8 @@ class EnergieManagementSystem:
     def set_ev_charge_hours(self, ds: List[int]) -> None:
         self.ev_charge_hours = ds
 
-    def set_haushaltsgeraet_start(self, ds: List[int], global_start_hour: int = 0) -> None:
+    def set_home_appliance_start(self, ds: List[int], global_start_hour: int = 0) -> None:
-        self.haushaltsgeraet.set_startzeitpunkt(ds, global_start_hour=global_start_hour)
+        self.home_appliance.set_starting_time(ds, global_start_hour=global_start_hour)
 
     def reset(self) -> None:
         self.eauto.reset()
@@ -114,7 +114,7 @@ class EnergieManagementSystem:
         akku_soc_pro_stunde = np.full((total_hours), np.nan)
         eauto_soc_pro_stunde = np.full((total_hours), np.nan)
         verluste_wh_pro_stunde = np.full((total_hours), np.nan)
-        haushaltsgeraet_wh_pro_stunde = np.full((total_hours), np.nan)
+        home_appliance_wh_per_hour = np.full((total_hours), np.nan)
 
         # Set initial state
         akku_soc_pro_stunde[0] = self.akku.ladezustand_in_prozent()
@@ -127,10 +127,10 @@ class EnergieManagementSystem:
             # Accumulate loads and PV generation
             verbrauch = self.gesamtlast[stunde]
             verluste_wh_pro_stunde[stunde_since_now] = 0.0
-            if self.haushaltsgeraet:
+            if self.home_appliance:
-                ha_load = self.haushaltsgeraet.get_last_fuer_stunde(stunde)
+                ha_load = self.home_appliance.get_load_for_hour(stunde)
                 verbrauch += ha_load
-                haushaltsgeraet_wh_pro_stunde[stunde_since_now] = ha_load
+                home_appliance_wh_per_hour[stunde_since_now] = ha_load
 
             # E-Auto handling
             if self.eauto and self.ev_charge_hours[stunde] > 0:
@@ -193,7 +193,7 @@ class EnergieManagementSystem:
             "Gesamtkosten_Euro": np.nansum(kosten_euro_pro_stunde),
             "Verluste_Pro_Stunde": verluste_wh_pro_stunde,
             "Gesamt_Verluste": np.nansum(verluste_wh_pro_stunde),
-            "Haushaltsgeraet_wh_pro_stunde": haushaltsgeraet_wh_pro_stunde,
+            "Home_appliance_wh_per_hour": home_appliance_wh_per_hour,
         }
 
         return out

src/akkudoktoreos/visualize.py

@@ -112,7 +112,7 @@ def visualisiere_ergebnisse(
         )
         plt.plot(
             hours,
-            ergebnisse["Haushaltsgeraet_wh_pro_stunde"],
+            ergebnisse["Home_appliance_wh_per_hour"],
             label="Household Device (Wh)",
             marker="o",
             linestyle="--",

tests/test_class_ems.py

@@ -3,7 +3,7 @@ import pytest
 
 from akkudoktoreos.config import AppConfig
 from akkudoktoreos.devices.battery import EAutoParameters, PVAkku, PVAkkuParameters
-from akkudoktoreos.devices.generic import Haushaltsgeraet, HaushaltsgeraetParameters
+from akkudoktoreos.devices.generic import HomeAppliance, HomeApplianceParameters
 from akkudoktoreos.devices.inverter import Wechselrichter, WechselrichterParameters
 from akkudoktoreos.prediction.ems import (
     EnergieManagementSystem,
@@ -28,14 +28,14 @@ def create_ems_instance(tmp_config: AppConfig) -> EnergieManagementSystem:
     wechselrichter = Wechselrichter(WechselrichterParameters(max_leistung_wh=10000), akku)
 
     # Household device (currently not used, set to None)
-    home_appliance = Haushaltsgeraet(
+    home_appliance = HomeAppliance(
-        HaushaltsgeraetParameters(
+        HomeApplianceParameters(
-            verbrauch_wh=2000,
+            consumption_wh=2000,
-            dauer_h=2,
+            duration_h=2,
         ),
         hours=prediction_hours,
     )
-    home_appliance.set_startzeitpunkt(2)
+    home_appliance.set_starting_time(2)
 
     # Example initialization of electric car battery
     eauto = PVAkku(
@@ -212,7 +212,7 @@ def create_ems_instance(tmp_config: AppConfig) -> EnergieManagementSystem:
             gesamtlast=gesamtlast,
         ),
         eauto=eauto,
-        haushaltsgeraet=home_appliance,
+        home_appliance=home_appliance,
         wechselrichter=wechselrichter,
     )
 
@@ -270,7 +270,7 @@ def test_simulation(create_ems_instance):
         "Gesamtkosten_Euro",
         "Verluste_Pro_Stunde",
         "Gesamt_Verluste",
-        "Haushaltsgeraet_wh_pro_stunde",
+        "Home_appliance_wh_per_hour",
     ]
 
     for key in expected_keys:
@@ -338,18 +338,18 @@ def test_simulation(create_ems_instance):
 
     # Check home appliances
     assert (
-        sum(ems.haushaltsgeraet.get_lastkurve()) == 2000
+        sum(ems.home_appliance.get_load_curve()) == 2000
-    ), "The sum of 'ems.haushaltsgeraet.get_lastkurve()' should be 2000."
+    ), "The sum of 'ems.home_appliance.get_load_curve()' should be 2000."
 
     assert (
         np.nansum(
             np.where(
-                np.equal(result["Haushaltsgeraet_wh_pro_stunde"], None),
+                np.equal(result["Home_appliance_wh_per_hour"], None),
                 np.nan,
-                np.array(result["Haushaltsgeraet_wh_pro_stunde"]),
+                np.array(result["Home_appliance_wh_per_hour"]),
             )
         )
         == 2000
-    ), "The sum of 'Haushaltsgeraet_wh_pro_stunde' should be 2000."
+    ), "The sum of 'Home_appliance_wh_per_hour' should be 2000."
 
     print("All tests passed successfully.")

tests/test_class_ems_2.py

@@ -3,7 +3,7 @@ import pytest
 
 from akkudoktoreos.config import AppConfig
 from akkudoktoreos.devices.battery import EAutoParameters, PVAkku, PVAkkuParameters
-from akkudoktoreos.devices.generic import Haushaltsgeraet, HaushaltsgeraetParameters
+from akkudoktoreos.devices.generic import HomeAppliance, HomeApplianceParameters
 from akkudoktoreos.devices.inverter import Wechselrichter, WechselrichterParameters
 from akkudoktoreos.prediction.ems import (
     EnergieManagementSystem,
@@ -28,14 +28,14 @@ def create_ems_instance(tmp_config: AppConfig) -> EnergieManagementSystem:
     wechselrichter = Wechselrichter(WechselrichterParameters(max_leistung_wh=10000), akku)
 
     # Household device (currently not used, set to None)
-    home_appliance = Haushaltsgeraet(
+    home_appliance = HomeAppliance(
-        HaushaltsgeraetParameters(
+        HomeApplianceParameters(
-            verbrauch_wh=2000,
+            consumption_wh=2000,
-            dauer_h=2,
+            duration_h=2,
         ),
         hours=prediction_hours,
     )
-    home_appliance.set_startzeitpunkt(2)
+    home_appliance.set_starting_time(2)
 
     # Example initialization of electric car battery
     eauto = PVAkku(
@@ -117,7 +117,7 @@ def create_ems_instance(tmp_config: AppConfig) -> EnergieManagementSystem:
             gesamtlast=gesamtlast,
         ),
         eauto=eauto,
-        haushaltsgeraet=home_appliance,
+        home_appliance=home_appliance,
         wechselrichter=wechselrichter,
     )
 
@@ -182,7 +182,7 @@ def test_simulation(create_ems_instance):
         "Gesamtkosten_Euro",
         "Verluste_Pro_Stunde",
         "Gesamt_Verluste",
-        "Haushaltsgeraet_wh_pro_stunde",
+        "Home_appliance_wh_per_hour",
     ]
 
     for key in expected_keys:

tests/testdata/optimize_input_2.json

@@ -37,9 +37,9 @@
         "start_soc_prozent": 5,
         "min_soc_prozent": 80
     },
-    "spuelmaschine" :{
+    "dishwasher" :{
-        "verbrauch_wh": 5000,
+        "consumption_wh": 5000,
-        "dauer_h": 2
+        "duration_h": 2
     },
     "temperature_forecast": [
       18.3, 17.8, 16.9, 16.2, 15.6, 15.1, 14.6, 14.2, 14.3, 14.8, 15.7, 16.7, 17.4,

tests/testdata/optimize_result_1.json

@@ -475,7 +475,7 @@
           0.0
       ],
       "Gesamt_Verluste": 1859.6205371900821,
-      "Haushaltsgeraet_wh_pro_stunde": [
+      "Home_appliance_wh_per_hour": [
           null,
           null,
           null,
@@ -727,5 +727,5 @@
       1,
       1
   ],
-  "spuelstart": null
+  "washingstart": null
 }

tests/testdata/optimize_result_2.json

@@ -40,7 +40,8 @@
       957.818181818182, 447.0, 1152.0, 843.0, 846.7933884297522, 345.0, 276.0, 309.0, 0.0, 0.0, 0.0, 0.0, 124.41545454545451, 141.38119834710756, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 69.12409090909085, 0.0, 78.55010330578523, 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, 100.08954545454549, 80.85954545454547
     ],
     "Gesamt_Verluste": 5771.031508264463,
-    "Haushaltsgeraet_wh_pro_stunde": [
+
+    "Home_appliance_wh_per_hour": [
       0.0, 0.0, 0.0, 2500.0, 2500.0, 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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
     ]
   },
@@ -62,5 +63,5 @@
   "start_solution": [
     0, 0, 4, 3, 1, 3, 1, 5, 6, 4, 1, 3, 6, 4, 6, 0, 6, 6, 0, 0, 3, 4, 1, 3, 2, 4, 4, 2, 3, 2, 1, 0, 2, 4, 1, 0, 6, 6, 2, 0, 4, 3, 3, 2, 6, 4, 1, 1, 0, 1, 5, 1, 2, 4, 6, 6, 5, 0, 2, 1, 6, 5, 6, 3, 2, 6, 6, 1, 1, 1, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 13
   ],
-  "spuelstart": 13
+  "washingstart": 13
 }

tests/testdata/optimize_result_2_full.json

@@ -40,7 +40,7 @@
       957.818181818182, 2.817272727272737, 672.0, 1152.0, 1152.0, 660.994834710744, 276.0, 276.0, 33.0, 0.0, 0.0, 0.0, 0.0, 0.0, 70.41409090909087, 118.37045454545455, 94.68272727272722, 83.01681818181817, 75.86045454545456, 66.66681818181814, 69.12409090909085, 109.0704545454546, 109.96227272727276, 47.952272727272714, 15.439199999999985, 53.855999999999995, 159.6443999999999, 21.032399999999996, 710.3921528925632, 0.0, 0.0, 0.0, 0.0, 35.132727272727266, 77.27590909090907, 134.59227272727276, 100.08954545454549, 80.85954545454547
     ],
     "Gesamt_Verluste": 7416.064896694217,
-    "Haushaltsgeraet_wh_pro_stunde": [
+    "Home_appliance_wh_per_hour": [
       0.0, 0.0, 0.0, 2500.0, 2500.0, 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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
     ]
   },
@@ -62,5 +62,5 @@
   "start_solution": [
     3, 2, 6, 3, 5, 4, 1, 5, 4, 6, 1, 1, 2, 6, 6, 6, 6, 6, 1, 2, 2, 6, 5, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 6, 2, 2, 2, 6, 1, 1, 1, 1, 1, 0, 5, 3, 1, 1, 2, 0, 1, 0, 6, 2, 0, 6, 6, 6, 5, 2, 2, 3, 6, 1, 5, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 13
   ],
-  "spuelstart": 13
+  "washingstart": 13
 }

tests/testdata/visualize_input_1.json

@@ -90,7 +90,7 @@
       100.08954545454549, 0.0
     ],
     "Gesamt_Verluste": 6563.160567638104,
-    "Haushaltsgeraet_wh_pro_stunde": [
+    "Home_appliance_wh_per_hour": [
       null,
       null,
       null,