Debugging Postprocessing

FZJ-IEK3-VSA · Jun 25, 2024 · 92cc240 · 92cc240
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diff --git a/examples/Cell4LifeSimulationExecutorvII.py b/examples/Cell4LifeSimulationExecutorvII.py
@@ -67,16 +67,16 @@
 PV_Peak_in_W = PV_Peak_in_kW * 1000 # Umrechnung in Watt
 
 
-#FuelCellPowerW_list = [PV_Peak_in_W/(2.1),PV_Peak_in_W/(2*2.1), PV_Peak_in_W/(4*2.1), PV_Peak_in_W/(6*2.1), PV_Peak_in_W/(8*2.1), PV_Peak_in_W/(10*2.1) ]  #Electricity Power of Fuel Cell Power in Watt, depending on PV - Peak power
+FuelCellPowerW_list = [PV_Peak_in_W/(2.1),PV_Peak_in_W/(2*2.1), PV_Peak_in_W/(4*2.1), PV_Peak_in_W/(6*2.1), PV_Peak_in_W/(8*2.1), PV_Peak_in_W/(10*2.1),PV_Peak_in_W/(12*2.1),PV_Peak_in_W/(14*2.1) ]  #Electricity Power of Fuel Cell Power in Watt, depending on PV - Peak power
 
-FuelCellPowerW_list = [PV_Peak_in_W/(8*2.1), PV_Peak_in_W/(10*2.1) , PV_Peak_in_W/(12*2.1)]  #Electricity Power of Fuel Cell Power in Watt, depending on PV - Peak power
+# FuelCellPowerW_list = [PV_Peak_in_W/(8*2.1), PV_Peak_in_W/(10*2.1) , PV_Peak_in_W/(12*2.1)]  #Electricity Power of Fuel Cell Power in Watt, depending on PV - Peak power
 
 
 Inverter_Ratio_list = [3, 2.5, 2, 1.5, 1] #Means: Inverter_power_demand  = (electrolyzer_energy + h2 storage)*Inverter_Ratio_lis --> inverter is always able to deliver at least power demand of electrolyzer and h2 storage!
 
-#BatterieFaktorList = [12,10, 8, 6, 4, 2, 1] # Battery Capacity =Inverter Power * Batteriefaktorlist --> Batteriekapazität = Faktor * Inverterleistung
+BatterieFaktorList = [20, 18, 16,14, 12,10, 8, 6, 4, 2, 1] # Battery Capacity =Inverter Power * Batteriefaktorlist --> Batteriekapazität = Faktor * Inverterleistung
 
-BatterieFaktorList = [16, 14]
+#BatterieFaktorList = [16, 14]
 
 
 FuelCellPowerWUnit = "W"
@@ -94,7 +94,7 @@
 # PreResultNumber = 0
 # PreResultNumberUnit = "-"
 
-PreResultNumber = 11111
+PreResultNumber = 0
 PreResultNumberUnit = "-"
 
 for BatterieFaktor in BatterieFaktorList:
@@ -205,47 +205,48 @@
 print(finishtext)
 
 
-# # # # #*************************************************
+# # # # # #*************************************************
+# # ##Szenario 2a
 
-# ##Szenario 2a
+# szenario = "2a" 
+# szenarioUnit = "-"
+# print("Szenario ", szenario)
 
-PV_Peak_in_kW = 781  # in kW
-PV_Peak_in_W = PV_Peak_in_kW * 1000 # Umrechnung in Watt
+# PV_Peak_in_kW = 781  # in kW
+# PV_Peak_in_W = PV_Peak_in_kW * 1000 # Umrechnung in Watt
 
+# #PV_Peak_in_W/(2.1)
+# #FuelCellPowerW_list = [PV_Peak_in_W/(2.1),PV_Peak_in_W/(2*2.1), PV_Peak_in_W/(4*2.1), PV_Peak_in_W/(6*2.1), PV_Peak_in_W/(8*2.1), PV_Peak_in_W/(10*2.1), PV_Peak_in_W/(12*2.1) ]  #Electricity Power of Fuel Cell Power in Watt, depending on PV - Peak power
 
-#FuelCellPowerW_list = [PV_Peak_in_W/(2.1),PV_Peak_in_W/(2*2.1), PV_Peak_in_W/(4*2.1), PV_Peak_in_W/(6*2.1), PV_Peak_in_W/(8*2.1), PV_Peak_in_W/(10*2.1) ]  #Electricity Power of Fuel Cell Power in Watt, depending on PV - Peak power
+# FuelCellPowerW_list = [PV_Peak_in_W/(14*2.1)]  #Electricity Power of Fuel Cell Power in Watt, depending on PV - Peak power
 
-FuelCellPowerW_list = [PV_Peak_in_W/(8*2.1), PV_Peak_in_W/(10*2.1) , PV_Peak_in_W/(12*2.1)]  #Electricity Power of Fuel Cell Power in Watt, depending on PV - Peak power
+# Inverter_Ratio_list = [3, 2.5, 2, 1.5, 1] #Means: Inverter_power_demand  = (electrolyzer_energy + h2 storage)*Inverter_Ratio_lis --> inverter is always able to deliver at least power demand of electrolyzer and h2 storage!
 
+# BatterieFaktorList = [20, 18, 16,14, 12,10, 8, 6, 4, 2, 1] # Battery Capacity =Inverter Power * Batteriefaktorlist --> Batteriekapazität = Faktor * Inverterleistung
 
-Inverter_Ratio_list = [3, 2.5, 2, 1.5, 1] #Means: Inverter_power_demand  = (electrolyzer_energy + h2 storage)*Inverter_Ratio_lis --> inverter is always able to deliver at least power demand of electrolyzer and h2 storage!
+# #BatterieFaktorList = [16, 14]
 
-#BatterieFaktorList = [12,10, 8, 6, 4, 2, 1] # Battery Capacity =Inverter Power * Batteriefaktorlist --> Batteriekapazität = Faktor * Inverterleistung
 
-BatterieFaktorList = [16, 14]
+# FuelCellPowerWUnit = "W"
+# BatteryCapkWhUnit = "kWh"
+# Inverter_RatioUnit = "-"
 
-
-FuelCellPowerWUnit = "W"
-BatteryCapkWhUnit = "kWh"
-Inverter_RatioUnit = "-"
-
-# prediction_horizon = 3600*2
+# prediction_horizon = 3600*3  # Based on "Kurzfristprognosen" laut zamg Seite: https://data.hub.geosphere.at/group/wettervorhersagen --> Kurzfristprognosen gibt es für die nächsten 3 Stunden jeweils
 # prediction_horizonUnit = "seconds"
 
 
-# # PreResultNumber = 0
-# # PreResultNumberUnit = "-"
+# PreResultNumber = 385
+# PreResultNumberUnit = "-"
 
 # #BatterieFaktorList = [4,5,6,7,8]
 # #BatterieFaktorList = [6,7,8,]
 
 # for BatterieFaktor in BatterieFaktorList:
 
-#     PreResultNumber = 0
-#     PreResultNumberUnit = "-"
+
 
 #     for FuelCellPowerW in FuelCellPowerW_list:
-#     #    for BatteryCapkWh in BatteryCapkWh_list:
+#         FuelCellPowerW = int(math.ceil(FuelCellPowerW))
 #         for Inverter_Ratio in Inverter_Ratio_list:
 
 
@@ -269,18 +270,36 @@
 
 #             input_variablen = Cell4LifeSzenario2a.InputParameter()
 
+#             '''
+#                 ### aus 1b kopiert
+#                     charging_rate = input_variablen["p_el_elektrolyzer"]["value"] / (3600*40000) #umrechnung von Watt [=Joule/Sekunde, Leistung) p_el in  kg/s H2
+#                     power_demand_charging_h2storage = charging_rate * input_variablen["h_fuel"]["value"] * 3.6e3 * 1000 * input_variablen["h2storage_energy_for_charge_based_on_massflow_h_fuel"]["value"]/100 # electricity power_demand of hydrogen storage for compression of H2 in Watt;
+
+
+#                     inverte_power_demand = int(math.ceil((power_demand_charging_h2storage  + input_variablen["p_el_elektrolyzer"]["value"])*Inverter_Ratio)) # Inverterleistung hängt von
+#                     inverte_power_demandUnit = 'W'
+
+#                     BatteryCapkWh = int(math.ceil((inverte_power_demand/1000)*BatterieFaktor)) #Befehl Ceil Rundet auf; BatteryCKapazität in kWh...Batterie-Kapazität hängt von Elektrolyzer + H2 Storage Verbrauch ab!
+
+
+#                 ###
+#             '''
 
 #             charging_rate = input_variablen["p_el_elektrolyzer"]["value"] / (3600*40000) #umrechnung von Watt [=Joule/Sekunde, Leistung) p_el in  kg/s H2
 #             power_demand_charging_h2storage = charging_rate * input_variablen["h_fuel"]["value"] * 3.6e3 * 1000 * input_variablen["h2storage_energy_for_charge_based_on_massflow_h_fuel"]["value"]/100 # electricity power_demand of hydrogen storage for compression of H2 in Watt;
-#             inverte_power_demand_min = power_demand_charging_h2storage  + input_variablen["p_el_elektrolyzer"]["value"]
+#             inverte_power_demand = int(math.ceil((power_demand_charging_h2storage  + input_variablen["p_el_elektrolyzer"]["value"])*Inverter_Ratio))
+#             inverte_power_demandUnit = 'W'
 
-#             BatteryCapkWh = math.ceil(inverte_power_demand_min / 1000 * BatterieFaktor) #Befehl Ceil Rundet auf; BatteryCKapazität in kWh..INverterleistung in Watt gerechnet; Minimum Inverterleistung = 0,25 der Batteriekapazität --> folglich ist die Batteriekapazität immer 4* der Inverterleistung
+#             BatteryCapkWh = int(math.ceil(inverte_power_demand / 1000 * BatterieFaktor)) #Befehl Ceil Rundet auf; BatteryCKapazität in kWh..INverterleistung in Watt gerechnet; Minimum Inverterleistung = 0,25 der Batteriekapazität --> folglich ist die Batteriekapazität immer 4* der Inverterleistung
 
 
 #             param_df["BatteryCapkWh"][0] = BatteryCapkWh
 #             param_df["BatteryCapkWhUnit"][0] = BatteryCapkWhUnit
 #             param_df["Inverter_Ratio"][0] = Inverter_Ratio
 #             param_df["Inverter_RatioUnit"][0] = Inverter_RatioUnit
+#             param_df["inverte_power_demand"][0] = inverte_power_demand
+#             param_df["inverte_power_demandUnit"][0] = inverte_power_demandUnit
+
 
 #             param_df.to_csv("examples/params_to_loop.csv", sep=",", index= False)
 #             #del param_df
@@ -292,14 +311,14 @@
 #             #Do a copy of the economic assessment excel file        
 
 # #             if PreResultNumber == 0:
-# #                 pathbase = 'C://Users//Standard//Desktop//hisim//C4LResults//results//'
+# #                 pathbase = 'C://Users//Standard//Desktop//hisim//results//'
 # #                 name1 = '20231107_AllSimulationResults_Assessment_v5'
 # #                 filepath1 = pathbase + 'OriginalExcelFile//' + name1 + '.xlsx'
 # #                 copytopath1= pathbase
 # #                 excelfilepathallresults1, excel_filename1 = Cell4Life_Postprocessing.makeacopyofevaluationfile(copytopath1, filepath1, name1)
 
 #             #For economic assessment, create a copy of original excel file
-#             copyfrompath = 'C://Users//Standard//Desktop//hisim//C4LResults//results//'
+#             copyfrompath = 'C://Users//Standard//Desktop//hisim//results//'
 #             name2 = 'Sim_Oek_Assessment_v12'
 #             filepath2 = copyfrompath + 'OriginalExcelFile//' + name2 + '.xlsx'
 #             copytopath2 = ResultPathProviderSingleton().get_result_directory_name()
@@ -310,7 +329,7 @@
 #             del copytopath2, filepath2, name2
 
 #             #For Excel Controll File, create a copy of original excel file
-#             copyfrompath = 'C://Users//Standard//Desktop//hisim//C4LResults//results//'
+#             copyfrompath = 'C://Users//Standard//Desktop//hisim//results//'
 #             name3 = 'ControllFileData-plotting'
 #             filepath3 = copyfrompath + 'OriginalExcelFile//' + name3 + '.xlsx'
 #             copytopath3 = ResultPathProviderSingleton().get_result_directory_name()
@@ -333,6 +352,10 @@
 #             finishtext = "---Parametervariation  --vII: " + input_variablen["szenario"]["value"] + "--  abgeschlossen---"
 
 #             del input_variablen
+
+#             print('Stop')
+#             print('Stop')
+
 #             PreResultNumber += 1
 
 

diff --git a/examples/Cell4LifeSzenario2a.py b/examples/Cell4LifeSzenario2a.py
@@ -78,10 +78,10 @@ def Cell4Life(
 
 
     # Build Results Path
-    name = input_variablen["szenario"]["value"] +  "_S" + str(input_variablen["PreResultNumber"]["value"])+"_BCap._" + str(math.ceil(input_variablen["battery_capacity"]["value"])) + "kWh_Inv_" + str(math.ceil(input_variablen["battery_inverter_power"]["value"]/1000)) + "kW_FCPow_" + str(math.ceil(input_variablen["fuel_cell_power"]["value"]/1000)) +"kW"
+    name = "S" + str(input_variablen["PreResultNumber"]["value"])+"_BCap._" + str(math.ceil(input_variablen["battery_capacity"]["value"])) + "kWh_Inv_" + str(math.ceil(input_variablen["battery_inverter_power"]["value"]/1000)) + "kW_FCPow_" + str(math.ceil(input_variablen["fuel_cell_power"]["value"]/1000)) +"kW"
 
     ResultPathProviderSingleton().set_important_result_path_information(
-        module_directory = "C://Users//Standard//Desktop//hisim//C4LResults",
+        module_directory = "C://Users//Standard//Desktop//hisim//",
         model_name= name,
         #variant_name=my_sim.setup_function,
         variant_name = '',
@@ -400,6 +400,12 @@ def InputParameter():
 
     prediction_horizon = param_df["prediction_horizon"][0]
     prediction_horizonUnit = param_df["prediction_horizonUnit"][0]
+
+    inverte_power_demand = param_df["inverte_power_demand"][0]
+    inverte_power_demandUnit = param_df["inverte_power_demandUnit"][0]   
+
+
+
     #Variation Parameters:
     battery_capacity: Optional[float] = BatteryCapkWh   #Total Capacity of Battery in kWh
     battery_capacityUnit = BatteryCapkWhUnit
@@ -414,11 +420,12 @@ def InputParameter():
     p_el_percentage_standby_fuelcell = 10 #If fuel cell is running in standby, it needs so much electricity power in % of its electricitiy production power if it is running
     p_el_percentage_standby_fuelcellUnit = "%" #10 % assumption is based on [42] "Dynamics and control of a thermally self-sustaining energy storage system using integrated solid oxide cells for an islanded building" from Pegah Mottaghizadeh, Mahshid Fardadi, Faryar Jabbari, Jack Brouwer
 
-    del BatteryCapkWh, FuelCellPowerW, BatteryCapkWhUnit, FuelCellPowerWUnit 
 
     #Following parameter depends on a "variation parameter"
-    battery_inverter_power = battery_capacity*1000*Inverter_Ratio #in Watt: Batterie Inverter power is assumed to depend on Battery Capacity which is given in kWh!
-    battery_inverter_powerUnit = "W"
+    battery_inverter_power = inverte_power_demand #in Watt: Batterie Inverter power is assumed to depend on Battery Capacity which is given in kWh!
+    battery_inverter_powerUnit = inverte_power_demandUnit
+
+    del BatteryCapkWh, FuelCellPowerW, BatteryCapkWhUnit, FuelCellPowerWUnit, inverte_power_demand, inverte_power_demandUnit 
 
 
     #Static Parameters:
@@ -431,7 +438,7 @@ def InputParameter():
     init_source_weight_battery = 1
     init_source_weight_batteryUnit = "-"
 
-    electricity_threshold = 0 #Minium required power to activate fuel cell
+    electricity_threshold = '-' #Minium required power to activate fuel cell
     electricity_thresholdUnit = "W"
 
     init_source_weight_hydrogenstorage = 999 #init_source_weight_electrolyzer
@@ -449,16 +456,16 @@ def InputParameter():
     electrolyzer_source_weight = 999
     electrolyzer_source_weightUnit = "-"
 
-    min_operation_time_in_seconds_chp = 0.00000001 #
+    min_operation_time_in_seconds_chp = prediction_horizon #
     min_operation_time_in_seconds_chpUnit = "s"
 
-    minstandbytime_fuelcell = 0.00000001 # 
+    minstandbytime_fuelcell = prediction_horizon # 
     minstandbytime_fuelcellUnit = "s"
 
-    min_operation_time_in_seconds_electrolyzer = 0.00000001 #
+    min_operation_time_in_seconds_electrolyzer = prediction_horizon #
     min_operation_time_in_seconds_electrolyzerUnit = "s"
 
-    minstandbytime_electrolyzer  = 0.00000001 #
+    minstandbytime_electrolyzer  = prediction_horizon #
     minstandbytime_electrolyzerUnit = "s"
 
     h2_soc_lower_threshold_chp = 0.1 # Minimum state of charge to start operating the fuel cell in %
@@ -517,16 +524,16 @@ def InputParameter():
     Electrical_power_demand_related_to_fuelcell_percentage = 100
     Electrical_power_demand_related_to_fuelcell_percentageUnit = "%" #Faktor in % which represents the ratio  between [HouseConsumption-PV]/FuelCell (each in Watt)...--> 100 % means, that the  energy demand (houseconsumption-PV) is equivalent to fuel cell output; at this ratio, the fuel cell could be turned on if the next decisions in the decision tree are answered positively, or the Fuel Cell stays turned on if it is already running
 
-    minbatterystateofcharge_electrolyzer_turnon = 80 #minimal battery state of charge, which is necessary, to turn on electrolyzer... in % 
+    minbatterystateofcharge_electrolyzer_turnon = 50 #minimal battery state of charge, which is necessary, to turn on electrolyzer... in % 
     minbatterystateofcharge_electrolyzer_turnonUnit = "%" 
 
     minbatterystateofcharge_let_electrolyzer_staysturnedon = 0.1 #Minimal battery state of charge, which is necessary, that electrolyzer stays turned on, in %
     minbatterystateofcharge_let_electrolyzer_staysturnedonUnit = "%"
 
-    maxbatterystateofcharge_fuelcell_turnon = 80 #maximum battery state of charge; if the actual battery state of charge is above this level, then the fuel cell will not be turned on
+    maxbatterystateofcharge_fuelcell_turnon = 50 #maximum battery state of charge; if the actual battery state of charge is above this level, then the fuel cell will not be turned on
     maxbatterystateofcharge_fuelcell_turnonUnit = "%"
 
-    maxbatterystateofcharge_let_fuelcell_staysturnedon = 95 #Maximum battery state of charge; if that threshold is exceeded, then the fuel cell will be turned off
+    maxbatterystateofcharge_let_fuelcell_staysturnedon = 90 #Maximum battery state of charge; if that threshold is exceeded, then the fuel cell will be turned off
     maxbatterystateofcharge_let_fuelcell_staysturnedonUnit = "%"
     #FOLLOWING FACTORS Electrolyzer:
     #****
@@ -591,6 +598,7 @@ def InputParameter():
             "value": electricity_threshold,
             "unit": electricity_thresholdUnit,
         },
+
         "init_source_weight_hydrogenstorage": {
             "value": init_source_weight_hydrogenstorage,
             "unit":init_source_weight_hydrogenstorageUnit,

diff --git a/examples/params_to_loop.csv b/examples/params_to_loop.csv
@@ -1,2 +1,2 @@
 PreResultNumber,FuelCellPowerW,BatteryCapkWh,Inverter_Ratio,PreResultNumberUnit,FuelCellPowerWUnit,BatteryCapkWhUnit,Inverter_RatioUnit,szenario,szenarioUnit,prediction_horizon,prediction_horizonUnit,inverte_power_demand,inverte_power_demandUnit
-11113,46489.0,3437.0,2.0,-,W,kWh,-,1b,-,0,seconds,214760.0,W
+439,26565.0,62.0,1.0,-,W,kWh,-,1b,-,0,seconds,61361.0,W
diff --git a/hisim/postprocessing/4D_Plotting.py b/hisim/postprocessing/4D_Plotting.py
@@ -7,7 +7,7 @@
 
 
 # Lese die Excel-Datei und das Tabellenblatt "Bezug" ein
-df = pd.read_excel('C://Users//Standard//Desktop//hisim//results//1b20240619//Gesamtergebnis.xlsx', sheet_name='Netzbezug')
+df = pd.read_excel('C://Users//Standard//Desktop//hisim//results//2a20240624//Gesamtergebnis.xlsx', sheet_name='Netzbezug')
 print(df.head())
 # Extrahiere die relevanten Spalten
 brennstoffzellenleistung = df['FuelCellPowerkWh']  # Spalte B
@@ -38,7 +38,7 @@
 cbar.set_label('Netzbezugsmenge Strom in MWh/a')
 
 # Beschrifte die Achsen
-ax.set_xlabel('Brennstoffzellenleistung in kW')
+ax.set_xlabel('rSOC-Leistung in kW')
 ax.set_ylabel('Batteriekapazität in kWh')
 ax.set_zlabel('Inverterleistung in kW')
 
@@ -56,7 +56,7 @@
 
 # Zeige den Plot an
 #plt.show()
-plt.savefig('C://Users//Standard//Desktop//hisim//results//1b20240619//Netzbezug_scatter.png', dpi=300)  # Speichert als PNG mit 300 DPI Auflösung
+plt.savefig('C://Users//Standard//Desktop//hisim//results//2a20240624//Netzbezug_scatter.png', dpi=300)  # Speichert als PNG mit 300 DPI Auflösung
 
 
 ############################################################################# 2
@@ -83,7 +83,7 @@
 cbar.set_label('Kapitalwert nach 20 Jahren (negativ)')
 
 # Beschrifte die Achsen
-ax.set_xlabel('Brennstoffzellenleistung in kW')
+ax.set_xlabel('rSOC-Leistung in kW')
 ax.set_ylabel('Batteriekapazität in kWh')
 ax.set_zlabel('Inverterleistung in kW')
 
@@ -95,7 +95,7 @@
 
 # Zeige den Plot an
 #plt.show()
-plt.savefig('C://Users//Standard//Desktop//hisim//results//1b20240619//Kapitalwert_scatter.png', dpi=300)  # Speichert als PNG mit 300 DPI Auflösung
+plt.savefig('C://Users//Standard//Desktop//hisim//results//2a20240624//Kapitalwert_scatter.png', dpi=300)  # Speichert als PNG mit 300 DPI Auflösung
 
 
 ############################################################################# 3
@@ -130,7 +130,7 @@
 cbar.set_label('Netzbezugsmenge Strom in MWh/a')
 
 # Beschrifte die Achsen
-ax.set_xlabel('Brennstoffzellenleistung in kW')
+ax.set_xlabel('rSOC-Leistung in kW')
 ax.set_ylabel('Batteriekapazität in kWh')
 ax.set_zlabel('Inverterleistung in kW')
 
@@ -145,7 +145,7 @@
 ax.set_ylim(1500, batteriekapazität_max__small)
 ax.set_zlim(50, inverterleistung_max__small)
 #plt.show()
-plt.savefig('C://Users//Standard//Desktop//hisim//results//1b20240619//Netzbezug_20kleisnten_scatter.png', dpi=300)  # Speichert als PNG mit 300 DPI Auflösung
+plt.savefig('C://Users//Standard//Desktop//hisim//results//2a20240624//Netzbezug_20kleisnten_scatter.png', dpi=300)  # Speichert als PNG mit 300 DPI Auflösung
 
 
 
@@ -169,7 +169,7 @@
 cbar.set_label('Kapitalwert nach 20 Jahren (negativ)')
 
 # Beschrifte die Achsen
-ax.set_xlabel('Brennstoffzellenleistung in kW')
+ax.set_xlabel('rSOC-Leistung in kW')
 ax.set_ylabel('Batteriekapazität in kWh')
 ax.set_zlabel('Inverterleistung in kW')
 
@@ -187,4 +187,4 @@
 
 # Zeige den Plot an
 #plt.show()
-plt.savefig('C://Users//Standard//Desktop//hisim//results//1b20240619//Kapitalwerte_zu_Netzbezug_20kleisnten_scatter.png', dpi=300)  # Speichert als PNG mit 300 DPI Auflösung
+plt.savefig('C://Users//Standard//Desktop//hisim//results//2a20240624//Kapitalwerte_zu_Netzbezug_20kleisnten_scatter.png', dpi=300)  # Speichert als PNG mit 300 DPI Auflösung