from pathlib import Path import numpy as np import pytest from akkudoktoreos.config import AppConfig from akkudoktoreos.devices.battery import EAutoParameters, PVAkku, PVAkkuParameters from akkudoktoreos.devices.generic import HomeAppliance, HomeApplianceParameters from akkudoktoreos.devices.inverter import Wechselrichter, WechselrichterParameters from akkudoktoreos.prediction.ems import ( EnergieManagementSystem, EnergieManagementSystemParameters, SimulationResult, ) from akkudoktoreos.prediction.self_consumption_probability import ( self_consumption_probability_interpolator, ) prediction_hours = 48 optimization_hours = 24 start_hour = 1 # Example initialization of necessary components @pytest.fixture def create_ems_instance(tmp_config: AppConfig) -> EnergieManagementSystem: """Fixture to create an EnergieManagementSystem instance with given test parameters.""" # Initialize the battery and the inverter akku = PVAkku( PVAkkuParameters(kapazitaet_wh=5000, start_soc_prozent=80, min_soc_prozent=10), hours=prediction_hours, ) # 1h Load to Sub 1h Load Distribution -> SelfConsumptionRate sc = self_consumption_probability_interpolator( Path(__file__).parent.resolve() / ".." / "src" / "akkudoktoreos" / "data" / "regular_grid_interpolator.pkl" ) akku.reset() wechselrichter = Wechselrichter( WechselrichterParameters(max_leistung_wh=10000), akku, self_consumption_predictor=sc ) # Household device (currently not used, set to None) home_appliance = HomeAppliance( HomeApplianceParameters( consumption_wh=2000, duration_h=2, ), hours=prediction_hours, ) home_appliance.set_starting_time(2) # Example initialization of electric car battery eauto = PVAkku( EAutoParameters(kapazitaet_wh=26400, start_soc_prozent=10, min_soc_prozent=10), hours=prediction_hours, ) eauto.set_charge_per_hour(np.full(prediction_hours, 1)) # Parameters based on previous example data pv_prognose_wh = [ 0, 0, 0, 0, 0, 0, 0, 8.05, 352.91, 728.51, 930.28, 1043.25, 1106.74, 1161.69, 6018.82, 5519.07, 3969.88, 3017.96, 1943.07, 1007.17, 319.67, 7.88, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5.04, 335.59, 705.32, 1121.12, 1604.79, 2157.38, 1433.25, 5718.49, 4553.96, 3027.55, 2574.46, 1720.4, 963.4, 383.3, 0, 0, 0, ] strompreis_euro_pro_wh = [ 0.0003384, 0.0003318, 0.0003284, 0.0003283, 0.0003289, 0.0003334, 0.0003290, 0.0003302, 0.0003042, 0.0002430, 0.0002280, 0.0002212, 0.0002093, 0.0001879, 0.0001838, 0.0002004, 0.0002198, 0.0002270, 0.0002997, 0.0003195, 0.0003081, 0.0002969, 0.0002921, 0.0002780, 0.0003384, 0.0003318, 0.0003284, 0.0003283, 0.0003289, 0.0003334, 0.0003290, 0.0003302, 0.0003042, 0.0002430, 0.0002280, 0.0002212, 0.0002093, 0.0001879, 0.0001838, 0.0002004, 0.0002198, 0.0002270, 0.0002997, 0.0003195, 0.0003081, 0.0002969, 0.0002921, 0.0002780, ] einspeiseverguetung_euro_pro_wh = 0.00007 preis_euro_pro_wh_akku = 0.0001 gesamtlast = [ 676.71, 876.19, 527.13, 468.88, 531.38, 517.95, 483.15, 472.28, 1011.68, 995.00, 1053.07, 1063.91, 1320.56, 1132.03, 1163.67, 1176.82, 1216.22, 1103.78, 1129.12, 1178.71, 1050.98, 988.56, 912.38, 704.61, 516.37, 868.05, 694.34, 608.79, 556.31, 488.89, 506.91, 804.89, 1141.98, 1056.97, 992.46, 1155.99, 827.01, 1257.98, 1232.67, 871.26, 860.88, 1158.03, 1222.72, 1221.04, 949.99, 987.01, 733.99, 592.97, ] # Initialize the energy management system with the respective parameters ems = EnergieManagementSystem( tmp_config.eos, EnergieManagementSystemParameters( pv_prognose_wh=pv_prognose_wh, strompreis_euro_pro_wh=strompreis_euro_pro_wh, einspeiseverguetung_euro_pro_wh=einspeiseverguetung_euro_pro_wh, preis_euro_pro_wh_akku=preis_euro_pro_wh_akku, gesamtlast=gesamtlast, ), wechselrichter=wechselrichter, eauto=eauto, home_appliance=home_appliance, ) return ems def test_simulation(create_ems_instance): """Test the EnergieManagementSystem simulation method.""" ems = create_ems_instance # Simulate starting from hour 1 (this value can be adjusted) result = ems.simuliere(start_stunde=start_hour) # visualisiere_ergebnisse( # ems.gesamtlast, # ems.pv_prognose_wh, # ems.strompreis_euro_pro_wh, # result, # ems.akku.discharge_array+ems.akku.charge_array, # None, # ems.pv_prognose_wh, # start_hour, # 48, # np.full(48, 0.0), # filename="visualization_results.pdf", # extra_data=None, # ) # Assertions to validate results 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'" """ Check the result of the simulation based on expected values. """ # Example result returned from the simulation (used for assertions) assert result is not None, "Result should not be None." # Check that the result is a dictionary assert isinstance(result, dict), "Result should be a dictionary." assert SimulationResult(**result) is not None # Check the length of the main arrays assert ( len(result["Last_Wh_pro_Stunde"]) == 47 ), "The length of 'Last_Wh_pro_Stunde' should be 48." assert ( len(result["Netzeinspeisung_Wh_pro_Stunde"]) == 47 ), "The length of 'Netzeinspeisung_Wh_pro_Stunde' should be 48." assert ( len(result["Netzbezug_Wh_pro_Stunde"]) == 47 ), "The length of 'Netzbezug_Wh_pro_Stunde' should be 48." assert ( len(result["Kosten_Euro_pro_Stunde"]) == 47 ), "The length of 'Kosten_Euro_pro_Stunde' should be 48." assert ( len(result["akku_soc_pro_stunde"]) == 47 ), "The length of 'akku_soc_pro_stunde' should be 48." # Verify specific values in the 'Last_Wh_pro_Stunde' array assert ( result["Last_Wh_pro_Stunde"][1] == 1527.13 ), "The value at index 1 of 'Last_Wh_pro_Stunde' should be 1527.13." assert ( result["Last_Wh_pro_Stunde"][2] == 1468.88 ), "The value at index 2 of 'Last_Wh_pro_Stunde' should be 1468.88." assert ( result["Last_Wh_pro_Stunde"][12] == 1132.03 ), "The value at index 12 of 'Last_Wh_pro_Stunde' should be 1132.03." # Verify that the value at index 0 is 'None' # Check that 'Netzeinspeisung_Wh_pro_Stunde' and 'Netzbezug_Wh_pro_Stunde' are consistent assert ( result["Netzbezug_Wh_pro_Stunde"][1] == 0 ), "The value at index 1 of 'Netzbezug_Wh_pro_Stunde' should be 0." # Verify the total balance assert ( abs(result["Gesamtbilanz_Euro"] - 1.958185274567674) < 1e-5 ), "Total balance should be 1.958185274567674." # Check total revenue and total costs assert ( abs(result["Gesamteinnahmen_Euro"] - 1.168863124510214) < 1e-5 ), "Total revenue should be 1.168863124510214." assert ( abs(result["Gesamtkosten_Euro"] - 3.127048399077888) < 1e-5 ), "Total costs should be 3.127048399077888 ." # Check the losses assert ( abs(result["Gesamt_Verluste"] - 2871.5330639359036) < 1e-5 ), "Total losses should be 2871.5330639359036 ." # Check the values in 'akku_soc_pro_stunde' assert ( result["akku_soc_pro_stunde"][-1] == 28.675 ), "The value at index -1 of 'akku_soc_pro_stunde' should be 28.675." assert ( result["akku_soc_pro_stunde"][1] == 25.379090909090905 ), "The value at index 1 of 'akku_soc_pro_stunde' should be 25.379090909090905." # Check home appliances assert ( sum(ems.home_appliance.get_load_curve()) == 2000 ), "The sum of 'ems.home_appliance.get_load_curve()' should be 2000." assert ( np.nansum( np.where( result["Home_appliance_wh_per_hour"] is None, np.nan, np.array(result["Home_appliance_wh_per_hour"]), ) ) == 2000 ), "The sum of 'Home_appliance_wh_per_hour' should be 2000." print("All tests passed successfully.")