Improve exogenous transport demand (#91)

Micha · web-flow · commit f3fc07c9c9b1 · 2025-07-21T11:27:47.000+02:00
* simplify indexing

* determine charger capacities like in prepare_sector_network; remove land_transport_electric_share

* add PHEV to number of electric cars because they provide charging capacity as well

* syntax fixes

* rename branch

* add option to specify AGEB(+KBA) as source for transport demand in 2020 and 2025

* add warning

* set transport shares to dummy values

* add changelog

* use mobility demand from uba projektionsbericht

* have separate option for the 2020 data

* renaming

* rename script and changelog

* transporte_shares matter outside of Germany!

* rename mobility_demand -&gt; mobility_data

* more renaming

* rename and refactor

* small adjustments

* explicitly define arrays as float
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,4 +1,7 @@
 # Changelog
+- Added an option to source mobility demand from UBA MWMS (Projektionsbericht 2025) for the years 2025-2035
+- Renamed functions and script for exogenous mobility demand
+- Improved the transport demand data, added an option to source 2020 and 2025 data from AGEB instead of Aladin
 - Added a helper function to change the weather_year to build_scenario
 - Longer lifetime (40 years) is only applied to existing gas CHPs, not new ones. Added a new config entry `existing_capacities:fill_value_gas_chp_lifetime`
 - Bugfix: gas CHPs are extendable again
diff --git a/Snakefile b/Snakefile
@@ -362,24 +362,29 @@ if config["enable"]["retrieve"] and config["enable"].get("retrieve_cost_data", T
     ruleorder: modify_cost_data > retrieve_cost_data
 
 
-rule build_mobility_demand:
+rule build_exogenous_mobility_data:
     params:
         reference_scenario=config_provider("iiasa_database", "reference_scenario"),
         planning_horizons=config_provider("scenario", "planning_horizons"),
         leitmodelle=config_provider("iiasa_database", "leitmodelle"),
+        ageb_for_mobility=config_provider("iiasa_database", "ageb_for_mobility"),
+        uba_for_mobility=config_provider("iiasa_database", "uba_for_mobility"),
+        shipping_oil_share=config_provider("sector", "shipping_oil_share"),
+        aviation_demand_factor=config_provider("sector", "aviation_demand_factor"),
+        energy_totals_year=config_provider("energy", "energy_totals_year"),
     input:
         ariadne="resources/ariadne_database.csv",
-        clustered_pop_layout=resources("pop_layout_base_s_{clusters}.csv"),
+        energy_totals=resources("energy_totals.csv"),
     output:
-        mobility_demand=resources(
-            "mobility_demand_aladin_{clusters}_{planning_horizons}.csv"
+        mobility_data=resources(
+            "modified_mobility_data_{clusters}_{planning_horizons}.csv"
         ),
     resources:
         mem_mb=1000,
     log:
-        logs("build_mobility_demand_{clusters}_{planning_horizons}.log"),
+        logs("build_exogenous_mobility_data_{clusters}_{planning_horizons}.log"),
     script:
-        "scripts/pypsa-de/build_mobility_demand.py"
+        "scripts/pypsa-de/build_exogenous_mobility_data.py"
 
 
 rule build_egon_data:
@@ -541,9 +546,6 @@ rule modify_prenetwork:
         must_run=config_provider("must_run"),
         clustering=config_provider("clustering", "temporal", "resolution_sector"),
         H2_plants=config_provider("electricity", "H2_plants_DE"),
-        land_transport_electric_share=config_provider(
-            "sector", "land_transport_electric_share"
-        ),
         onshore_nep_force=config_provider("onshore_nep_force"),
         offshore_nep_force=config_provider("offshore_nep_force"),
         shipping_methanol_efficiency=config_provider(
@@ -553,6 +555,9 @@ rule modify_prenetwork:
         shipping_methanol_share=config_provider("sector", "shipping_methanol_share"),
         mwh_meoh_per_tco2=config_provider("sector", "MWh_MeOH_per_tCO2"),
         scale_capacity=config_provider("scale_capacity"),
+        bev_charge_rate=config_provider("sector", "bev_charge_rate"),
+        bev_energy=config_provider("sector", "bev_energy"),
+        bev_dsm_availability=config_provider("sector", "bev_dsm_availability"),
     input:
         costs_modifications="ariadne-data/costs_{planning_horizons}-modifications.csv",
         network=resources(
@@ -564,10 +569,9 @@ rule modify_prenetwork:
             else []
         ),
         costs=resources("costs_{planning_horizons}.csv"),
-        aladin_demand=resources(
-            "mobility_demand_aladin_{clusters}_{planning_horizons}.csv"
+        modified_mobility_data=resources(
+            "modified_mobility_data_{clusters}_{planning_horizons}.csv"
         ),
-        transport_data=resources("transport_data_s_{clusters}.csv"),
         biomass_potentials=resources(
             "biomass_potentials_s_{clusters}_{planning_horizons}.csv"
         ),
diff --git a/config/config.de.yaml b/config/config.de.yaml
@@ -4,7 +4,7 @@
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#run
 run:
-  prefix: 20250721_weather_year_helper
+  prefix: 20250717_improve_transport_demand
   name:
   # - ExPol
   - KN2045_Mix
@@ -43,6 +43,8 @@ iiasa_database:
   - KN2045_NFhoch
   reference_scenario: KN2045_Mix
   region: Deutschland
+  ageb_for_mobility: true # In 2020 use AGEB data for final energy demand and KBA for vehicles
+  uba_for_mobility: false # For 2025–2035 use MWMS scenario from UBA Projektionsbericht 2025
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#foresight
 foresight: myopic
@@ -332,27 +334,28 @@ sector:
     2040: 0.29
     2045: 0.36
     2050: 0.43
+  # For Germany these settings get overwritten in build_exogenous_mobility_data
   land_transport_fuel_cell_share:
-    2020: 0.05
-    2025: 0.05
-    2030: 0.05
-    2035: 0.05
-    2040: 0.05
-    2045: 0.05
-    2050: 0.05
+    2020: 0.01
+    2025: 0.01
+    2030: 0.02
+    2035: 0.03
+    2040: 0.03
+    2045: 0.03
+    2050: 0.03
   land_transport_electric_share:
     2020: 0.05
     2025: 0.15
     2030: 0.3
     2035: 0.45
-    2040: 0.7
-    2045: 0.85
-    2050: 0.95
+    2040: 0.72
+    2045: 0.87
+    2050: 0.97
   land_transport_ice_share:
-    2020: 0.9
-    2025: 0.8
-    2030: 0.65
-    2035: 0.5
+    2020: 0.94
+    2025: 0.84
+    2030: 0.68
+    2035: 0.52
     2040: 0.25
     2045: 0.1
     2050: 0.0
diff --git a/scripts/pypsa-de/build_exogenous_mobility_data.py b/scripts/pypsa-de/build_exogenous_mobility_data.py
@@ -0,0 +1,185 @@
+import logging
+
+import pandas as pd
+
+from scripts._helpers import configure_logging, mock_snakemake
+
+logger = logging.getLogger(__name__)
+
+
+def get_mobility_data(
+    db,
+    year,
+    non_land_liquids,
+    ageb_for_mobility=True,
+    uba_for_mobility=False,
+):
+    """
+    Retrieve the German mobility demand from the transport model.
+
+    Sum over the subsectors Bus, LDV, Rail, and Truck for the fuels
+    electricity, hydrogen, and synthetic fuels.
+    """
+    subsectors = ["Bus", "LDV", "Rail", "Truck"]
+    fuels = ["Electricity", "Hydrogen", "Liquids"]
+
+    mobility_data = pd.Series(0.0, index=fuels)
+
+    if year == "2020":
+        logger.info(
+            "For 2020, using hard-coded transport data from the Ariadne2-internal database."
+        )
+
+        mobility_data = pd.Series(
+            {
+                "Electricity": 0.0 + 17.0 + 35.82 + 0.0,
+                "Hydrogen": 0.0 + 0.0 + 0.0 + 0.0,
+                "Liquids": 41.81 + 1369.34 + 11.18 + 637.23,
+            }
+        )
+
+        mobility_data = mobility_data.div(3.6e-6)  # convert PJ to MWh
+        mobility_data["million_EVs"] = 0.658407 + 0.120261  # BEV + PHEV
+
+        if ageb_for_mobility or uba_for_mobility:
+            if uba_for_mobility:
+                logger.warning(
+                    "For 2020, using historical AGEB and KBA data instead of UBA projections."
+                )
+            # AGEB 2020, https://ag-energiebilanzen.de/daten-und-fakten/bilanzen-1990-bis-2030/?_jahresbereich-bilanz=2011-2020
+            mobility_data = pd.Series(
+                {
+                    "Electricity": 39129.0 + 2394.0,  # Schiene + Straße
+                    "Hydrogen": 0.0,
+                    "Liquids": 140718.0
+                    + 1261942.0
+                    + 10782.0
+                    + 638820.0,  # Bio Strasse + Diesel Strasse + Diesel Schiene + Otto Strasse
+                }
+            )
+            mobility_data = mobility_data.div(3.6e-3)  # convert PJ to MWH
+            # https://www.kba.de/DE/Statistik/Produktkatalog/produkte/Fahrzeuge/fz27_b_uebersicht.html
+            # FZ27_202101, table FZ 27.2, 1. January 2021:
+            mobility_data["million_EVs"] = 0.358498 + 0.280149
+
+    elif year == "2025" and uba_for_mobility:
+        # https://www.umweltbundesamt.de/sites/default/files/medien/11850/publikationen/projektionsbericht_2025.pdf, Abbildung 64 & 59,
+        mobility_data = pd.Series(
+            {
+                "Electricity": 21.0,
+                "Hydrogen": 0.0,
+                "Liquids": 524.0 + 51.0,
+            }
+        )
+        mobility_data["Liquids"] -= non_land_liquids[
+            int(year)
+        ]  # remove domestic navigation and aviation from UBA data to avoid double counting
+        mobility_data = mobility_data.mul(1e6)  # convert TWh to MWh
+        mobility_data["million_EVs"] = 2.7 + 1.2  # BEV + PHEV
+
+    elif year == "2030" and uba_for_mobility:
+        mobility_data = pd.Series(
+            {
+                "Electricity": 57.0,
+                "Hydrogen": 14.0,
+                "Liquids": 418.0 + 34.0 + 1.0,
+            }
+        )
+        mobility_data["Liquids"] -= non_land_liquids[int(year)]
+        mobility_data = mobility_data.mul(1e6)
+        mobility_data["million_EVs"] = 8.7 + 1.8
+
+    elif year == "2035" and uba_for_mobility:
+        mobility_data = pd.Series(
+            {
+                "Electricity": 117.0,
+                "Hydrogen": 36.0,
+                "Liquids": 237.0 + 26.0 + 1.0,
+            }
+        )
+        mobility_data["Liquids"] -= non_land_liquids[int(year)]
+        mobility_data = mobility_data.mul(1e6)
+        mobility_data["million_EVs"] = 18.9 + 1.8
+
+    else:
+        if uba_for_mobility:
+            logger.error(
+                f"Year {year} is not supported for UBA mobility projections. Please use only 2020, 2025, 2030, 2035."
+            )
+
+        df = db[year].loc[snakemake.params.leitmodelle["transport"]]
+
+        for fuel in fuels:
+            for subsector in subsectors:
+                key = f"Final Energy|Transportation|{subsector}|{fuel}"
+                mobility_data.loc[fuel] += df.get((key, "TWh/yr"), 0.0)
+
+        mobility_data = mobility_data.mul(1e6)  # convert TWh to MWh
+        mobility_data["million_EVs"] = (
+            df.loc["Stock|Transportation|LDV|BEV", "million"]
+            + df.loc["Stock|Transportation|LDV|PHEV", "million"]
+        )
+
+    return mobility_data
+
+
+if __name__ == "__main__":
+    if "snakemake" not in globals():
+        snakemake = mock_snakemake(
+            "build_exogenous_mobility_data",
+            simpl="",
+            clusters=27,
+            opts="",
+            ll="vopt",
+            sector_opts="none",
+            planning_horizons="2020",
+            run="KN2045_Mix",
+        )
+    configure_logging(snakemake)
+
+    db = pd.read_csv(
+        snakemake.input.ariadne,
+        index_col=["model", "scenario", "region", "variable", "unit"],
+    ).loc[
+        :,
+        snakemake.params.reference_scenario,
+        "Deutschland",
+        :,
+        :,
+    ]
+
+    energy_totals = (
+        pd.read_csv(
+            snakemake.input.energy_totals,
+            index_col=[0, 1],
+        )
+        .xs(
+            snakemake.params.energy_totals_year,
+            level="year",
+        )
+        .loc["DE"]
+    )
+
+    domestic_aviation = energy_totals.loc["total domestic aviation"] * pd.Series(
+        snakemake.params.aviation_demand_factor
+    )
+
+    domestic_navigation = energy_totals.loc["total domestic navigation"] * pd.Series(
+        snakemake.params.shipping_oil_share
+    )
+
+    non_land_liquids = domestic_aviation + domestic_navigation
+
+    logger.info(
+        f"Retrieving German mobility demand from {snakemake.params.leitmodelle['transport']} transport model."
+    )
+    # get mobility_data data
+    mobility_data = get_mobility_data(
+        db,
+        snakemake.wildcards.planning_horizons,
+        non_land_liquids,
+        ageb_for_mobility=snakemake.params.ageb_for_mobility,
+        uba_for_mobility=snakemake.params.uba_for_mobility,
+    )
+
+    mobility_data.to_csv(snakemake.output.mobility_data, header=False)
diff --git a/scripts/pypsa-de/build_mobility_demand.py b/scripts/pypsa-de/build_mobility_demand.py
diff --git a/scripts/pypsa-de/modify_prenetwork.py b/scripts/pypsa-de/modify_prenetwork.py
