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Data prefetch for ems (#418)
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* Pre-fetch data * maintanance and extend tests * comment clean up * nansum usage (to be save)
This commit is contained in:
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@ -1,4 +1,4 @@
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from typing import Any, ClassVar, Dict, Optional, Union
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from typing import Any, ClassVar, Optional
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import numpy as np
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import numpy as np
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from numpydantic import NDArray, Shape
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from numpydantic import NDArray, Shape
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@ -186,7 +186,7 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
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len(self.load_energy_array), parameters.einspeiseverguetung_euro_pro_wh, float
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len(self.load_energy_array), parameters.einspeiseverguetung_euro_pro_wh, float
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)
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)
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)
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)
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if inverter is not None:
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if inverter:
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self.battery = inverter.battery
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self.battery = inverter.battery
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else:
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else:
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self.battery = None
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self.battery = None
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@ -198,7 +198,7 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
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self.ev_charge_hours = np.full(self.config.prediction_hours, 0.0)
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self.ev_charge_hours = np.full(self.config.prediction_hours, 0.0)
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def set_akku_discharge_hours(self, ds: np.ndarray) -> None:
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def set_akku_discharge_hours(self, ds: np.ndarray) -> None:
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if self.battery is not None:
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if self.battery:
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self.battery.set_discharge_per_hour(ds)
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self.battery.set_discharge_per_hour(ds)
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def set_akku_ac_charge_hours(self, ds: np.ndarray) -> None:
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def set_akku_ac_charge_hours(self, ds: np.ndarray) -> None:
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@ -211,7 +211,7 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
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self.ev_charge_hours = ds
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self.ev_charge_hours = ds
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def set_home_appliance_start(self, ds: int, global_start_hour: int = 0) -> None:
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def set_home_appliance_start(self, ds: int, global_start_hour: int = 0) -> None:
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if self.home_appliance is not None:
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if self.home_appliance:
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self.home_appliance.set_starting_time(ds, global_start_hour=global_start_hour)
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self.home_appliance.set_starting_time(ds, global_start_hour=global_start_hour)
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def reset(self) -> None:
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def reset(self) -> None:
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@ -276,53 +276,50 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
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return self.simulate(start_hour)
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return self.simulate(start_hour)
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def simulate(self, start_hour: int) -> dict[str, Any]:
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def simulate(self, start_hour: int) -> dict[str, Any]:
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"""hour.
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"""Simulate energy usage and costs for the given start hour.
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akku_soc_pro_stunde begin of the hour, initial hour state!
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akku_soc_pro_stunde begin of the hour, initial hour state!
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last_wh_pro_stunde integral of last hour (end state)
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last_wh_pro_stunde integral of last hour (end state)
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"""
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"""
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# Check for simulation integrity
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# Check for simulation integrity
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missing_data = []
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required_attrs = [
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"load_energy_array",
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if self.load_energy_array is None:
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"pv_prediction_wh",
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missing_data.append("Load Curve")
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"elect_price_hourly",
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if self.pv_prediction_wh is None:
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"ev_charge_hours",
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missing_data.append("PV Forecast")
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"ac_charge_hours",
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if self.elect_price_hourly is None:
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"dc_charge_hours",
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missing_data.append("Electricity Price")
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"elect_revenue_per_hour_arr",
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if self.ev_charge_hours is None:
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]
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missing_data.append("EV Charge Hours")
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missing_data = [
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if self.ac_charge_hours is None:
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attr.replace("_", " ").title() for attr in required_attrs if getattr(self, attr) is None
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missing_data.append("AC Charge Hours")
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]
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if self.dc_charge_hours is None:
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missing_data.append("DC Charge Hours")
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if self.elect_revenue_per_hour_arr is None:
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missing_data.append("Feed-in Tariff")
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if missing_data:
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if missing_data:
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error_msg = "Mandatory data missing - " + ", ".join(missing_data)
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logger.error("Mandatory data missing - %s", ", ".join(missing_data))
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logger.error(error_msg)
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raise ValueError(f"Mandatory data missing: {', '.join(missing_data)}")
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raise ValueError(error_msg)
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else:
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# make mypy happy
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assert self.load_energy_array is not None
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assert self.pv_prediction_wh is not None
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assert self.elect_price_hourly is not None
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assert self.ev_charge_hours is not None
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assert self.ac_charge_hours is not None
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assert self.dc_charge_hours is not None
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assert self.elect_revenue_per_hour_arr is not None
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load_energy_array = self.load_energy_array
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# Pre-fetch data
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load_energy_array = np.array(self.load_energy_array)
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pv_prediction_wh = np.array(self.pv_prediction_wh)
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elect_price_hourly = np.array(self.elect_price_hourly)
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ev_charge_hours = np.array(self.ev_charge_hours)
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ac_charge_hours = np.array(self.ac_charge_hours)
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dc_charge_hours = np.array(self.dc_charge_hours)
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elect_revenue_per_hour_arr = np.array(self.elect_revenue_per_hour_arr)
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if not (
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# Fetch objects
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len(load_energy_array) == len(self.pv_prediction_wh) == len(self.elect_price_hourly)
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battery = self.battery
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):
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assert battery # to please mypy
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error_msg = f"Array sizes do not match: Load Curve = {len(load_energy_array)}, PV Forecast = {len(self.pv_prediction_wh)}, Electricity Price = {len(self.elect_price_hourly)}"
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ev = self.ev
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home_appliance = self.home_appliance
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inverter = self.inverter
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if not (len(load_energy_array) == len(pv_prediction_wh) == len(elect_price_hourly)):
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error_msg = f"Array sizes do not match: Load Curve = {len(load_energy_array)}, PV Forecast = {len(pv_prediction_wh)}, Electricity Price = {len(elect_price_hourly)}"
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logger.error(error_msg)
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logger.error(error_msg)
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raise ValueError(error_msg)
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raise ValueError(error_msg)
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# Optimized total hours calculation
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end_hour = len(load_energy_array)
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end_hour = len(load_energy_array)
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total_hours = end_hour - start_hour
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total_hours = end_hour - start_hour
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@ -332,116 +329,110 @@ class EnergieManagementSystem(SingletonMixin, ConfigMixin, PredictionMixin, Pyda
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consumption_energy_per_hour = np.full((total_hours), np.nan)
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consumption_energy_per_hour = np.full((total_hours), np.nan)
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costs_per_hour = np.full((total_hours), np.nan)
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costs_per_hour = np.full((total_hours), np.nan)
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revenue_per_hour = np.full((total_hours), np.nan)
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revenue_per_hour = np.full((total_hours), np.nan)
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soc_per_hour = np.full((total_hours), np.nan) # Hour End State
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soc_per_hour = np.full((total_hours), np.nan)
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soc_ev_per_hour = np.full((total_hours), np.nan)
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soc_ev_per_hour = np.full((total_hours), np.nan)
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losses_wh_per_hour = np.full((total_hours), np.nan)
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losses_wh_per_hour = np.full((total_hours), np.nan)
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home_appliance_wh_per_hour = np.full((total_hours), np.nan)
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home_appliance_wh_per_hour = np.full((total_hours), np.nan)
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electricity_price_per_hour = np.full((total_hours), np.nan)
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electricity_price_per_hour = np.full((total_hours), np.nan)
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# Set initial state
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# Set initial state
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if self.battery:
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soc_per_hour[0] = battery.current_soc_percentage()
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soc_per_hour[0] = self.battery.current_soc_percentage()
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if ev:
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if self.ev:
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soc_ev_per_hour[0] = ev.current_soc_percentage()
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soc_ev_per_hour[0] = self.ev.current_soc_percentage()
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for hour in range(start_hour, end_hour):
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for hour in range(start_hour, end_hour):
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hour_since_now = hour - start_hour
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hour_idx = hour - start_hour
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# save begin states
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# save begin states
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if self.battery:
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soc_per_hour[hour_idx] = battery.current_soc_percentage()
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soc_per_hour[hour_since_now] = self.battery.current_soc_percentage()
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else:
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if ev:
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soc_per_hour[hour_since_now] = 0.0
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soc_ev_per_hour[hour_idx] = ev.current_soc_percentage()
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if self.ev:
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soc_ev_per_hour[hour_since_now] = self.ev.current_soc_percentage()
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# Accumulate loads and PV generation
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# Accumulate loads and PV generation
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consumption = self.load_energy_array[hour]
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consumption = load_energy_array[hour]
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losses_wh_per_hour[hour_since_now] = 0.0
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losses_wh_per_hour[hour_idx] = 0.0
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# Home appliances
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# Home appliances
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if self.home_appliance:
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if home_appliance:
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ha_load = self.home_appliance.get_load_for_hour(hour)
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ha_load = home_appliance.get_load_for_hour(hour)
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consumption += ha_load
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consumption += ha_load
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home_appliance_wh_per_hour[hour_since_now] = ha_load
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home_appliance_wh_per_hour[hour_idx] = ha_load
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# E-Auto handling
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# E-Auto handling
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if self.ev:
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if ev and ev_charge_hours[hour] > 0:
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if self.ev_charge_hours[hour] > 0:
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loaded_energy_ev, verluste_eauto = ev.charge_energy(
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loaded_energy_ev, verluste_eauto = self.ev.charge_energy(
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None, hour, relative_power=ev_charge_hours[hour]
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None, hour, relative_power=self.ev_charge_hours[hour]
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)
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)
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consumption += loaded_energy_ev
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consumption += loaded_energy_ev
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losses_wh_per_hour[hour_idx] += verluste_eauto
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losses_wh_per_hour[hour_since_now] += verluste_eauto
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# Process inverter logic
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# Process inverter logic
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energy_feedin_grid_actual, energy_consumption_grid_actual, losses, eigenverbrauch = (
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energy_feedin_grid_actual = energy_consumption_grid_actual = losses = eigenverbrauch = (
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0.0,
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0.0
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0.0,
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0.0,
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0.0,
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)
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)
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if self.battery:
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self.battery.set_charge_allowed_for_hour(self.dc_charge_hours[hour], hour)
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hour_ac_charge = ac_charge_hours[hour]
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if self.inverter:
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hour_dc_charge = dc_charge_hours[hour]
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energy_produced = self.pv_prediction_wh[hour]
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hourly_electricity_price = elect_price_hourly[hour]
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hourly_energy_revenue = elect_revenue_per_hour_arr[hour]
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battery.set_charge_allowed_for_hour(hour_dc_charge, hour)
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if inverter:
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energy_produced = pv_prediction_wh[hour]
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(
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(
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energy_feedin_grid_actual,
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energy_feedin_grid_actual,
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energy_consumption_grid_actual,
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energy_consumption_grid_actual,
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losses,
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losses,
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eigenverbrauch,
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eigenverbrauch,
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) = self.inverter.process_energy(energy_produced, consumption, hour)
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) = inverter.process_energy(energy_produced, consumption, hour)
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# AC PV Battery Charge
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# AC PV Battery Charge
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if self.battery and self.ac_charge_hours[hour] > 0.0:
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if hour_ac_charge > 0.0:
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self.battery.set_charge_allowed_for_hour(1, hour)
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battery.set_charge_allowed_for_hour(1, hour)
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battery_charged_energy_actual, battery_losses_actual = self.battery.charge_energy(
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battery_charged_energy_actual, battery_losses_actual = battery.charge_energy(
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None, hour, relative_power=self.ac_charge_hours[hour]
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None, hour, relative_power=hour_ac_charge
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)
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)
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# print(hour, " ", battery_charged_energy_actual, " ",self.ac_charge_hours[hour]," ",self.battery.current_soc_percentage())
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consumption += battery_charged_energy_actual
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consumption += battery_losses_actual
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energy_consumption_grid_actual += battery_charged_energy_actual
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energy_consumption_grid_actual += battery_losses_actual
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losses_wh_per_hour[hour_since_now] += battery_losses_actual
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feedin_energy_per_hour[hour_since_now] = energy_feedin_grid_actual
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total_battery_energy = battery_charged_energy_actual + battery_losses_actual
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consumption_energy_per_hour[hour_since_now] = energy_consumption_grid_actual
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consumption += total_battery_energy
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losses_wh_per_hour[hour_since_now] += losses
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energy_consumption_grid_actual += total_battery_energy
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loads_energy_per_hour[hour_since_now] = consumption
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losses_wh_per_hour[hour_idx] += battery_losses_actual
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electricity_price_per_hour[hour_since_now] = self.elect_price_hourly[hour]
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# Update hourly arrays
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feedin_energy_per_hour[hour_idx] = energy_feedin_grid_actual
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consumption_energy_per_hour[hour_idx] = energy_consumption_grid_actual
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losses_wh_per_hour[hour_idx] += losses
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loads_energy_per_hour[hour_idx] = consumption
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electricity_price_per_hour[hour_idx] = hourly_electricity_price
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# Financial calculations
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# Financial calculations
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costs_per_hour[hour_since_now] = (
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costs_per_hour[hour_idx] = energy_consumption_grid_actual * hourly_electricity_price
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energy_consumption_grid_actual * self.elect_price_hourly[hour]
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revenue_per_hour[hour_idx] = energy_feedin_grid_actual * hourly_energy_revenue
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)
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revenue_per_hour[hour_since_now] = (
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energy_feedin_grid_actual * self.elect_revenue_per_hour_arr[hour]
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)
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# Total cost and return
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total_cost = np.nansum(costs_per_hour)
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gesamtkosten_euro = np.nansum(costs_per_hour) - np.nansum(revenue_per_hour)
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total_losses = np.nansum(losses_wh_per_hour)
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total_revenue = np.nansum(revenue_per_hour)
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# Prepare output dictionary
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# Prepare output dictionary
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out: Dict[str, Union[np.ndarray, float]] = {
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return {
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"Last_Wh_pro_Stunde": loads_energy_per_hour,
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"Last_Wh_pro_Stunde": loads_energy_per_hour,
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"Netzeinspeisung_Wh_pro_Stunde": feedin_energy_per_hour,
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"Netzeinspeisung_Wh_pro_Stunde": feedin_energy_per_hour,
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"Netzbezug_Wh_pro_Stunde": consumption_energy_per_hour,
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"Netzbezug_Wh_pro_Stunde": consumption_energy_per_hour,
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"Kosten_Euro_pro_Stunde": costs_per_hour,
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"Kosten_Euro_pro_Stunde": costs_per_hour,
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"akku_soc_pro_stunde": soc_per_hour,
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"akku_soc_pro_stunde": soc_per_hour,
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"Einnahmen_Euro_pro_Stunde": revenue_per_hour,
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"Einnahmen_Euro_pro_Stunde": revenue_per_hour,
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"Gesamtbilanz_Euro": gesamtkosten_euro,
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"Gesamtbilanz_Euro": total_cost - total_revenue,
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"EAuto_SoC_pro_Stunde": soc_ev_per_hour,
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"EAuto_SoC_pro_Stunde": soc_ev_per_hour,
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"Gesamteinnahmen_Euro": np.nansum(revenue_per_hour),
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"Gesamteinnahmen_Euro": total_revenue,
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"Gesamtkosten_Euro": np.nansum(costs_per_hour),
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"Gesamtkosten_Euro": total_cost,
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"Verluste_Pro_Stunde": losses_wh_per_hour,
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"Verluste_Pro_Stunde": losses_wh_per_hour,
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"Gesamt_Verluste": np.nansum(losses_wh_per_hour),
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"Gesamt_Verluste": total_losses,
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"Home_appliance_wh_per_hour": home_appliance_wh_per_hour,
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"Home_appliance_wh_per_hour": home_appliance_wh_per_hour,
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"Electricity_price": electricity_price_per_hour,
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"Electricity_price": electricity_price_per_hour,
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}
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}
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return out
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# Initialize the Energy Management System, it is a singleton.
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# Initialize the Energy Management System, it is a singleton.
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ems = EnergieManagementSystem()
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ems = EnergieManagementSystem()
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@ -6,6 +6,7 @@ import pytest
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from akkudoktoreos.core.ems import (
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from akkudoktoreos.core.ems import (
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EnergieManagementSystem,
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EnergieManagementSystem,
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EnergieManagementSystemParameters,
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EnergieManagementSystemParameters,
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SimulationResult,
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get_ems,
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get_ems,
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)
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)
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from akkudoktoreos.devices.battery import (
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from akkudoktoreos.devices.battery import (
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@ -182,6 +183,7 @@ def test_simulation(create_ems_instance):
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# Assertions to validate results
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# Assertions to validate results
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assert result is not None, "Result should not be None"
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assert result is not None, "Result should not be None"
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assert isinstance(result, dict), "Result should be a dictionary"
|
assert isinstance(result, dict), "Result should be a dictionary"
|
||||||
|
assert SimulationResult(**result) is not None
|
||||||
assert "Last_Wh_pro_Stunde" in result, "Result should contain 'Last_Wh_pro_Stunde'"
|
assert "Last_Wh_pro_Stunde" in result, "Result should contain 'Last_Wh_pro_Stunde'"
|
||||||
|
|
||||||
"""
|
"""
|
||||||
@ -240,7 +242,7 @@ def test_simulation(create_ems_instance):
|
|||||||
|
|
||||||
assert (
|
assert (
|
||||||
abs(result["Netzeinspeisung_Wh_pro_Stunde"][10] - 3946.93) < 1e-3
|
abs(result["Netzeinspeisung_Wh_pro_Stunde"][10] - 3946.93) < 1e-3
|
||||||
), "'Netzeinspeisung_Wh_pro_Stunde[11]' should be 4000."
|
), "'Netzeinspeisung_Wh_pro_Stunde[11]' should be 3946.93."
|
||||||
|
|
||||||
assert (
|
assert (
|
||||||
abs(result["Netzeinspeisung_Wh_pro_Stunde"][11] - 0.0) < 1e-3
|
abs(result["Netzeinspeisung_Wh_pro_Stunde"][11] - 0.0) < 1e-3
|
||||||
@ -251,6 +253,78 @@ def test_simulation(create_ems_instance):
|
|||||||
), "'akku_soc_pro_stunde[20]' should be 10."
|
), "'akku_soc_pro_stunde[20]' should be 10."
|
||||||
assert (
|
assert (
|
||||||
abs(result["Last_Wh_pro_Stunde"][20] - 6050.98) < 1e-3
|
abs(result["Last_Wh_pro_Stunde"][20] - 6050.98) < 1e-3
|
||||||
), "'Netzeinspeisung_Wh_pro_Stunde[11]' should be 0.0."
|
), "'Last_Wh_pro_Stunde[20]' should be 6050.98."
|
||||||
|
|
||||||
print("All tests passed successfully.")
|
print("All tests passed successfully.")
|
||||||
|
|
||||||
|
|
||||||
|
def test_set_parameters(create_ems_instance):
|
||||||
|
"""Test the set_parameters method of EnergieManagementSystem."""
|
||||||
|
ems = create_ems_instance
|
||||||
|
|
||||||
|
# Check if parameters are set correctly
|
||||||
|
assert ems.load_energy_array is not None, "load_energy_array should not be None"
|
||||||
|
assert ems.pv_prediction_wh is not None, "pv_prediction_wh should not be None"
|
||||||
|
assert ems.elect_price_hourly is not None, "elect_price_hourly should not be None"
|
||||||
|
assert (
|
||||||
|
ems.elect_revenue_per_hour_arr is not None
|
||||||
|
), "elect_revenue_per_hour_arr should not be None"
|
||||||
|
|
||||||
|
|
||||||
|
def test_set_akku_discharge_hours(create_ems_instance):
|
||||||
|
"""Test the set_akku_discharge_hours method of EnergieManagementSystem."""
|
||||||
|
ems = create_ems_instance
|
||||||
|
discharge_hours = np.full(ems.config.prediction_hours, 1.0)
|
||||||
|
ems.set_akku_discharge_hours(discharge_hours)
|
||||||
|
assert np.array_equal(
|
||||||
|
ems.battery.discharge_array, discharge_hours
|
||||||
|
), "Discharge hours should be set correctly"
|
||||||
|
|
||||||
|
|
||||||
|
def test_set_akku_ac_charge_hours(create_ems_instance):
|
||||||
|
"""Test the set_akku_ac_charge_hours method of EnergieManagementSystem."""
|
||||||
|
ems = create_ems_instance
|
||||||
|
ac_charge_hours = np.full(ems.config.prediction_hours, 1.0)
|
||||||
|
ems.set_akku_ac_charge_hours(ac_charge_hours)
|
||||||
|
assert np.array_equal(
|
||||||
|
ems.ac_charge_hours, ac_charge_hours
|
||||||
|
), "AC charge hours should be set correctly"
|
||||||
|
|
||||||
|
|
||||||
|
def test_set_akku_dc_charge_hours(create_ems_instance):
|
||||||
|
"""Test the set_akku_dc_charge_hours method of EnergieManagementSystem."""
|
||||||
|
ems = create_ems_instance
|
||||||
|
dc_charge_hours = np.full(ems.config.prediction_hours, 1.0)
|
||||||
|
ems.set_akku_dc_charge_hours(dc_charge_hours)
|
||||||
|
assert np.array_equal(
|
||||||
|
ems.dc_charge_hours, dc_charge_hours
|
||||||
|
), "DC charge hours should be set correctly"
|
||||||
|
|
||||||
|
|
||||||
|
def test_set_ev_charge_hours(create_ems_instance):
|
||||||
|
"""Test the set_ev_charge_hours method of EnergieManagementSystem."""
|
||||||
|
ems = create_ems_instance
|
||||||
|
ev_charge_hours = np.full(ems.config.prediction_hours, 1.0)
|
||||||
|
ems.set_ev_charge_hours(ev_charge_hours)
|
||||||
|
assert np.array_equal(
|
||||||
|
ems.ev_charge_hours, ev_charge_hours
|
||||||
|
), "EV charge hours should be set correctly"
|
||||||
|
|
||||||
|
|
||||||
|
def test_reset(create_ems_instance):
|
||||||
|
"""Test the reset method of EnergieManagementSystem."""
|
||||||
|
ems = create_ems_instance
|
||||||
|
ems.reset()
|
||||||
|
assert ems.ev.current_soc_percentage() == 100, "EV SOC should be reset to initial value"
|
||||||
|
assert (
|
||||||
|
ems.battery.current_soc_percentage() == 80
|
||||||
|
), "Battery SOC should be reset to initial value"
|
||||||
|
|
||||||
|
|
||||||
|
def test_simulate_start_now(create_ems_instance):
|
||||||
|
"""Test the simulate_start_now method of EnergieManagementSystem."""
|
||||||
|
ems = create_ems_instance
|
||||||
|
result = ems.simulate_start_now()
|
||||||
|
assert result is not None, "Result should not be None"
|
||||||
|
assert isinstance(result, dict), "Result should be a dictionary"
|
||||||
|
assert "Last_Wh_pro_Stunde" in result, "Result should contain 'Last_Wh_pro_Stunde'"
|
||||||
|
Loading…
x
Reference in New Issue
Block a user