pull request for adding vehicle data

Snakefile

@@ -7,6 +7,7 @@ rule compile_cost_assumptions:
         pypsa_costs = "inputs/costs_PyPSA.csv",
         fraunhofer_costs = "inputs/Fraunhofer_ISE_costs.csv",
         fraunhofer_energy_prices = "inputs/Fraunhofer_ISE_energy_prices.csv",
+        fraunhofer_vehicles_costs = "inputs/Fraunhofer_ISE_vehicles_costs.csv",
         EWG_costs = "inputs/EWG_costs.csv",
         dea_transport = "inputs/energy_transport_data_sheet_dec_2017.xlsx",
         dea_renewable_fuels = "inputs/data_sheets_for_renewable_fuels.xlsx",

inputs/Fraunhofer_ISE_vehicles_costs.csv

@@ -0,0 +1,38 @@
+Komponente,Gr��e,Einheit,2020,2025,2030,2035,2040,2045,2050
+LKW H2- Brennstoffzelle,Investition,EUR/LKW,151574,122291,116497,117600,120177,122939,125710
+LKW H2- Brennstoffzelle,Lebensdauer,a,15,15,15,15,15,15,15
+LKW H2- Brennstoffzelle,M/O-Kosten,% Invest,10.1,12.5,13.1,13,12.7,12.4,12.2
+LKW H2- Brennstoffzelle,Wirkungsgrad*,%,56,56,56,56,56,56,56
+LKW ICE- Fl�ssigtreibstoff,Investition,EUR/LKW,99772,102543,105315,108086,110858,113629,116401
+LKW ICE- Fl�ssigtreibstoff,Lebensdauer,a,15,15,15,15,15,15,15
+LKW ICE- Fl�ssigtreibstoff,M/O-Kosten,% Invest,18,17.5,17.1,16.6,16.2,15.8,15.5
+LKW ICE- Fl�ssigtreibstoff,Wirkungsgrad*,%,37.3,37.3,37.3,37.3,37.3,37.3,37.3
+LKW Ladeinfrastruktur Brennstoffzellen Fahrzeuge * LKW,Investition,EUR/Lades�ule,2243051,2000991,1787894,1787894,1787894,1787894,1787894
+LKW Ladeinfrastruktur Brennstoffzellen Fahrzeuge * LKW,Lebensdauer,a,30,30,30,30,30,30,30
+LKW Ladeinfrastruktur Brennstoffzellen Fahrzeuge * LKW,M/O-Kosten,% Invest,2.2,2.2,2.2,2.2,2.2,2.2,2.2
+PKW H2- Brennstoffzelle,Investition,EUR/PKW,55000,43500,33226,30720,29440,28160,26880
+PKW H2- Brennstoffzelle,Lebensdauer,a,15,15,15,15,15,15,15
+PKW H2- Brennstoffzelle,M/O-Kosten,% Invest,1.1,1.1,1.1,1.1,1.2,1.2,1.2
+PKW H2- Brennstoffzelle,Wirkungsgrad*,%,48,48,48,48,48,48,48
+PKW ICE- Fl�ssigtreibstoff,Investition,EUR/PKW,23561,24309,24999,25622,26167,26610,26880
+PKW ICE- Fl�ssigtreibstoff,Lebensdauer,a,15,15,15,15,15,15,15
+PKW ICE- Fl�ssigtreibstoff,M/O-Kosten,% Invest,1.6,1.6,1.6,1.6,1.6,1.6,1.6
+PKW ICE- Fl�ssigtreibstoff,Wirkungsgrad*,%,21.5,21.5,21.5,21.5,21.5,21.5,21.5
+PKW Ladeinfrastruktur Brennstoffzellen Fahrzeuge * PKW,Investition,EUR/Lades�ule,2243051,2000991,1787894,1788360,1788360,1788360,1788360
+PKW Ladeinfrastruktur Brennstoffzellen Fahrzeuge * PKW,Lebensdauer,a,30,30,30,30,30,30,30
+PKW Ladeinfrastruktur Brennstoffzellen Fahrzeuge * PKW,M/O-Kosten,% Invest,2.2,2.2,2.2,2.2,2.2,2.2,2.2
+PKW Ladeinfrastruktur schnell  (reine) Batteriefahrzeuge*,Investition,EUR/Lades�ule,629102,527507,448894,448894,448894,448894,448894
+PKW Ladeinfrastruktur schnell  (reine) Batteriefahrzeuge*,Lebensdauer,a,30,30,30,30,30,30,30
+PKW Ladeinfrastruktur schnell  (reine) Batteriefahrzeuge*,M/O-Kosten,% Invest,1.6,1.6,1.6,1.6,1.6,1.6,1.6
+Ladeinfrastruktur langsam (reine) Batteriefahrzeuge*,Investition,EUR/Lades�ule,1283,1126,1005,1005,1005,1005,1005
+Ladeinfrastruktur langsam (reine) Batteriefahrzeuge*,Lebensdauer,a,30,30,30,30,30,30,30
+Ladeinfrastruktur langsam (reine) Batteriefahrzeuge*,M/O-Kosten,% Invest,1.8,1.8,1.8,1.8,1.8,1.8,1.8
+NT,Wirkungsgrad el.,%,62.9,63.4,63.9,64.4,64.9,65.4,65.9
+NT,Wirkungsgrad th.,%,27.9,28.1,28.3,28.5,28.7,28.9,29.1
+PKW Batterie-Elektromotor,Investition,EUR/PKW,33000,28812,24624,24358,24092,23827,23561
+PKW Batterie-Elektromotor,Lebensdauer,a,15,15,15,15,15,15,15
+PKW Batterie-Elektromotor,M/O-Kosten,% Invest,0.9,0.9,0.9,0.9,0.9,0.9,0.9
+PKW Batterie-Elektromotor,Wirkungsgrad*,%,68,68,68,68,68,68,68
+LKW Batterie-Elektromotor,Investition,EUR/LKW,204067,165765,136400,134700,133000,131200,129400
+LKW Batterie-Elektromotor,Lebensdauer,a,15,15,15,15,15,15,15
+LKW Batterie-Elektromotor,M/O-Kosten,% Invest,14,14,15,16,16,16,16

scripts/compile_cost_assumptions.py

@@ -59,6 +59,8 @@
                 "Breede2015": "Breede et al. 2015: Overcoming challenges in the classification of deep geothermal potential, https://eprints.gla.ac.uk/169585/",
                 # Study of deep geothermal systems in the Northern Upper Rhine Graben
                 "Frey2022": "Frey et al. 2022: Techno-Economic Assessment of Geothermal Resources in the Variscan Basement of the Northern Upper Rhine Graben",
+		# vehicles 
+		"vehicles" : "PATHS TO A CLIMATE-NEUTRAL ENERGY SYSTEM The German energy transformation in its social context. https://www.ise.fraunhofer.de/en/publications/studies/paths-to-a-climate-neutral-energy-system.html"
                 }
 
 # [DEA-sheet-names]
@@ -1398,6 +1400,40 @@ def rename_ISE(costs_ISE):
 
     return costs_ISE
 
+def rename_ISE_vehicles(costs_vehicles):
+    """
+    rename ISE_vehicles costs to fit to tech data
+    """
+
+    costs_vehicles.rename(index = {"Investition": "investment",
+                          "Lebensdauer": "lifetime",
+                          "M/O-Kosten": "FOM",
+			"Wirkungsgrad*" : "Efficiency (carrier to wheel)",
+			"PKW Batterie-Elektromotor" : "Battery electric (passenger cars)",
+			"LKW Batterie-Elektromotor" : "Battery electric (trucks)",
+			"LKW H2- Brennstoffzelle": "Hydrogen fuel cell (trucks)",
+			"PKW H2- Brennstoffzelle": "Hydrogen fuel cell (passenger cars)",
+			"LKW ICE- Fl�ssigtreibstoff": "Liquid fuels ICE (trucks)",
+			"PKW ICE- Fl�ssigtreibstoff": "Liquid fuels ICE (passenger cars)",
+			"LKW Ladeinfrastruktur Brennstoffzellen Fahrzeuge * LKW": "Charging infrastructure fuel cell vehicles trucks",
+			"PKW Ladeinfrastruktur Brennstoffzellen Fahrzeuge * PKW": "Charging infrastructure fuel cell vehicles passenger cars",
+			"PKW Ladeinfrastruktur schnell  (reine) Batteriefahrzeuge*" : "Charging infrastructure fast (purely) battery electric vehicles passenger cars",
+			"Ladeinfrastruktur langsam (reine) Batteriefahrzeuge*" : "Charging infrastructure slow (purely) battery electric vehicles passenger cars"},
+                 columns = {"Einheit": "unit",
+                            "2020": 2020,
+                            "2025": 2025,
+                            "2030": 2030,
+                            "2035": 2035,
+                            "2040": 2040,
+                            "2045": 2045,
+                            "2050": 2050}, inplace=True)
+    costs_vehicles.index.names = ["technology", "parameter"]
+    costs_vehicles.unit.replace({"a": "years", "% Invest": "%"}, inplace=True)
+    costs_vehicles["source"] = source_dict["vehicles"]
+    costs_vehicles['further description'] =  costs_vehicles.reset_index()["technology"].values
+
+    return costs_vehicles
+
 def carbon_flow(costs,year):
     # NB: This requires some digits of accuracy; rounding to two digits creates carbon inbalances when scaling up
     c_in_char = 0 # Carbon ending up in char: zero avoids inbalace -> assumed to be circulated back and eventually end up in one of the other output streams
@@ -2150,7 +2186,17 @@ def geometric_series(nominator, denominator=1, number_of_terms=1, start=1):
                             index_col=[0,2]).sort_index()
     # rename some techs and convert units
     costs_pypsa = rename_pypsa_old(costs_pypsa)
-
+
+    # (b1) ------- add vehicle costs from Fraunhofer vehicle study ------------------------
+    costs_vehicles = pd.read_csv(snakemake.input.fraunhofer_vehicles_costs,
+                            engine="python",
+                            index_col=[0,1],
+                            encoding="ISO-8859-1")
+    # rename + reorder to fit to other data
+    costs_vehicles = rename_ISE_vehicles(costs_vehicles)
+    # add costs for vehicles
+    data = pd.concat([data, costs_vehicles], sort=True)
+
     # (b) ------- add costs from Fraunhofer ISE study --------------------------
     costs_ISE = pd.read_csv(snakemake.input.fraunhofer_costs,
                             engine="python",