Biomass transport

Snakefile

@@ -180,6 +180,18 @@ rule build_biomass_potentials:
     script: 'scripts/build_biomass_potentials.py'
 
 
+rule build_biomass_transport_costs:
+    input: "data/biomass/biomass potentials in europe_web rev.pdf"
+    output:
+        supply_chain1="resources/biomass_transport_costs_supply_chain1.csv",
+        supply_chain2="resources/biomass_transport_costs_supply_chain2.csv",
+        transport_costs="resources/biomass_transport_costs.csv",
+    threads: 1
+    resources: mem_mb=1000
+    benchmark: "benchmarks/build_biomass_transport_costs"
+    script: 'scripts/build_biomass_transport_costs.py'
+
+
 rule build_ammonia_production:
     input:
         usgs="data/myb1-2017-nitro.xls"
@@ -321,9 +333,10 @@ rule prepare_sector_network:
         energy_totals_name='resources/energy_totals.csv',
         co2_totals_name='resources/co2_totals.csv',
         transport_name='resources/transport_data.csv',
-        traffic_data_KFZ = "data/emobility/KFZ__count",
-        traffic_data_Pkw = "data/emobility/Pkw__count",
+        traffic_data_KFZ="data/emobility/KFZ__count",
+        traffic_data_Pkw="data/emobility/Pkw__count",
         biomass_potentials='resources/biomass_potentials.csv',
+	    biomass_transport="resources/biomass_transport_costs.csv",
         heat_profile="data/heat_load_profile_BDEW.csv",
         costs=CDIR + "costs_{planning_horizons}.csv",
         profile_offwind_ac=pypsaeur("resources/profile_offwind-ac.nc"),

config.default.yaml

@@ -222,6 +222,7 @@ sector:
   electricity_grid_connection: true  # only applies to onshore wind and utility PV
   gas_distribution_grid: true
   gas_distribution_grid_cost_factor: 1.0  #multiplies cost in data/costs.csv
+  biomass_transport: false  # biomass potential per country + transport between countries
   conventional_generation: # generator : carrier
     OCGT: gas
 
@@ -241,7 +242,6 @@ industry:
   hotmaps_locate_missing: false
   reference_year: 2015
 
-
 costs:
   lifetime: 25 #default lifetime
   # From a Lion Hirth paper, also reflects average of Noothout et al 2016
@@ -471,3 +471,4 @@ plotting:
     today: '#D2691E'
     shipping: '#6495ED'
     electricity distribution grid: '#333333'
+    solid biomass transport: green

scripts/build_biomass_transport_costs.py

@@ -0,0 +1,70 @@
+"""
+Reads biomass transport costs for different countries of the JRC report
+
+    "The JRC-EU-TIMES model.
+    Bioenergy potentials
+    for EU and neighbouring countries."
+    (2015)
+
+converts them from units 'EUR per km/ton' -> 'EUR/ (km MWh)'
+
+assuming as an approximation energy content of wood pellets
+
+@author: bw0928
+"""
+
+import pandas as pd
+import tabula as tbl
+
+ENERGY_CONTENT = 4.8  # unit MWh/tonne (assuming wood pellets)
+
+
+def build_biomass_transport_costs():
+
+    df_list = tbl.read_pdf(
+        snakemake.input[0],
+        pages="145-147",
+        multiple_tables=True,
+    )
+
+    countries = df_list[0][0].iloc[6:].rename(index=lambda x: x + 1)
+
+    # supply chain 1
+    df = df_list[1].copy().rename(index=countries.to_dict())
+    df.rename(
+        columns=df.iloc[:6].apply(lambda col: col.str.cat(sep=" "), axis=0).to_dict(),
+        inplace=True,
+    )
+    df = df.iloc[6:]
+    df.loc[6] = df.loc[6].str.replace("€", "EUR")
+
+    # supply chain 2
+    df2 = df_list[2].copy().rename(index=countries.to_dict())
+    df2.rename(
+        columns=df2.iloc[:6].apply(lambda col: col.str.cat(sep=" "), axis=0).to_dict(),
+        inplace=True,
+    )
+    df2 = df2.iloc[6:]
+    df2.loc[6] = df2.loc[6].str.replace("€", "EUR")
+
+    df.to_csv(snakemake.output.supply_chain1)
+    df2.to_csv(snakemake.output.supply_chain1)
+
+    transport_costs = pd.concat([df["per km/ton"], df2["per km/ton"]], axis=1).drop(6)
+    transport_costs = transport_costs.astype(float, errors="ignore").mean(axis=1)
+
+    # convert unit to EUR/MWh
+    transport_costs /= ENERGY_CONTENT
+    transport_costs = pd.DataFrame(transport_costs, columns=["cost [EUR/(km MWh)]"])
+
+    # rename
+    transport_costs.rename({"UK": "GB", "XK": "KO", "EL": "GR"}, inplace=True)
+
+    # add missing Norway
+    transport_costs.loc["NO"] = transport_costs.loc["SE"]
+    transport_costs.to_csv(snakemake.output.transport_costs)
+
+
+if __name__ == "__main__":
+
+    prepare_biomass_transport_costs()