Addition of unsustainable biomass potentials

config/config.default.yaml

@@ -369,6 +369,8 @@ biomass:
     biogas:
     - Manure solid, liquid
     - Sludge
+  include_unsustainable: true
+  unsustainable_phase_out: 2035
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#solar-thermal
 solar_thermal:
@@ -1028,6 +1030,7 @@ plotting:
     services rural biomass boiler: '#c6cf98'
     services urban decentral biomass boiler: '#dde5b5'
     biomass to liquid: '#32CD32'
+    unsustainable bioliquids: '#32CD32'
     BioSNG: '#123456'
     # power transmission
     lines: '#6c9459'

rules/build_sector.smk

@@ -331,7 +331,8 @@ rule build_biomass_potentials:
             "https://zenodo.org/records/10356004/files/ENSPRESO_BIOMASS.xlsx",
             keep_local=True,
         ),
-        nuts2="data/bundle/nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson",  # https://gisco-services.ec.europa.eu/distribution/v2/nuts/download/#nuts21
+        eurostat="data/eurostat/Balances-April2023",
+        nuts2="data/bundle/nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson",
         regions_onshore=resources("regions_onshore_elec_s{simpl}_{clusters}.geojson"),
         nuts3_population=ancient("data/bundle/nama_10r_3popgdp.tsv.gz"),
         swiss_cantons=ancient("data/ch_cantons.csv"),
@@ -940,6 +941,7 @@ rule prepare_sector_network:
         countries=config_provider("countries"),
         adjustments=config_provider("adjustments", "sector"),
         emissions_scope=config_provider("energy", "emissions"),
+        biomass=config_provider("biomass"),
         RDIR=RDIR,
     input:
         unpack(input_profile_offwind),
@@ -986,15 +988,8 @@ rule prepare_sector_network:
         dsm_profile=resources("dsm_profile_s{simpl}_{clusters}.csv"),
         co2_totals_name=resources("co2_totals.csv"),
         co2="data/bundle/eea/UNFCCC_v23.csv",
-        biomass_potentials=lambda w: (
-            resources(
-                "biomass_potentials_s{simpl}_{clusters}_"
-                + "{}.csv".format(config_provider("biomass", "year")(w))
-            )
-            if config_provider("foresight")(w) == "overnight"
-            else resources(
-                "biomass_potentials_s{simpl}_{clusters}_{planning_horizons}.csv"
-            )
+        biomass_potentials=resources(
+            "biomass_potentials_s{simpl}_{clusters}_{planning_horizons}.csv"
         ),
         costs=lambda w: (
             resources("costs_{}.csv".format(config_provider("costs", "year")(w)))

scripts/build_biomass_potentials.py

@@ -211,14 +211,182 @@ def convert_nuts2_to_regions(bio_nuts2, regions):
     return bio_regions
 
 
+def build_eurostat(input_eurostat, countries, year, idees_rename):
+    """
+    Return multi-index for all countries' energy data in TWh/a.
+    """
+    df = {}
+    countries = {idees_rename.get(country, country) for country in countries} - {"CH"}
+    for country in countries:
+        filename = (
+            f"{input_eurostat}/{country}-Energy-balance-sheets-April-2023-edition.xlsb"
+        )
+        sheet = pd.read_excel(
+            filename,
+            engine="pyxlsb",
+            sheet_name=str(year),
+            skiprows=4,
+            index_col=list(range(4)),
+        )
+        df[country] = sheet
+    df = pd.concat(df, axis=0)
+
+    # drop columns with all NaNs
+    unnamed_cols = df.columns[df.columns.astype(str).str.startswith("Unnamed")]
+    df.drop(unnamed_cols, axis=1, inplace=True)
+    df.drop(year, axis=1, inplace=True)
+
+    # make numeric values where possible
+    df.replace("Z", 0, inplace=True)
+    df = df.apply(pd.to_numeric, errors="coerce")
+    df = df.select_dtypes(include=[np.number])
+
+    # write 'International aviation' to the 2nd level of the multiindex
+    int_avia = df.index.get_level_values(2) == "International aviation"
+    temp = df.loc[int_avia]
+    temp.index = pd.MultiIndex.from_frame(
+        temp.index.to_frame().fillna("International aviation")
+    )
+    df = pd.concat([temp, df.loc[~int_avia]])
+
+    # Renaming some indices
+    index_rename = {
+        "Households": "Residential",
+        "Commercial & public services": "Services",
+        "Domestic navigation": "Domestic Navigation",
+        "International maritime bunkers": "Bunkers",
+    }
+    columns_rename = {"Total": "Total all products", "UK": "GB"}
+    df.rename(index=index_rename, columns=columns_rename, inplace=True)
+    df.sort_index(inplace=True)
+    df.index.names = [None] * len(df.index.names)
+
+    # convert to MWh/a from ktoe/a
+    df *= 11.63 * 1e3
+
+    return df
+
+
+def add_unsustainable_potentials(df):
+    """
+    Add unsustainable biomass potentials to the given dataframe. The difference
+    between the data of JRC and Eurostat is assumed to be unsustainable
+    biomass.
+
+    Parameters
+    ----------
+    df : pd.DataFrame
+        The dataframe with sustainable biomass potentials.
+    unsustainable_biomass : str
+        Path to the file with unsustainable biomass potentials.
+
+    Returns
+    -------
+    pd.DataFrame
+        The dataframe with added unsustainable biomass potentials.
+    """
+    if "GB" in snakemake.config["countries"]:
+        latest_year = 2019
+    else:
+        latest_year = 2021
+    idees_rename = {"GR": "EL", "GB": "UK"}
+    df_unsustainable = (
+        build_eurostat(
+            countries=snakemake.config["countries"],
+            year=max(min(latest_year, investment_year), 1990),
+            input_eurostat=snakemake.input.eurostat,
+            idees_rename=idees_rename,
+        )
+        .xs("Primary production", level=2)
+        .droplevel([1, 2, 3])
+    )
+
+    df_unsustainable.index = df_unsustainable.index.str.strip()
+    df_unsustainable = df_unsustainable.rename(
+        {v: k for k, v in idees_rename.items()}, axis=0
+    )
+
+    bio_carriers = [
+        "Primary solid biofuels",
+        "Biogases",
+        "Renewable municipal waste",
+        "Pure biogasoline",
+        "Blended biogasoline",
+        "Pure biodiesels",
+        "Blended biodiesels",
+        "Pure bio jet kerosene",
+        "Blended bio jet kerosene",
+        "Other liquid biofuels",
+    ]
+
+    df_unsustainable = df_unsustainable[bio_carriers]
+
+    # Phase out unsustainable biomass potentials linearly from 2020 to 2035 while phasing in sustainable potentials
+    reduction_factor = max(
+        0,
+        min(
+            1,
+            1
+            - (investment_year - 2020)
+            / (snakemake.config["biomass"]["unsustainable_phase_out"] - 2020),
+        ),
+    )
+
+    df_wo_ch = df.drop(df.filter(regex="CH\d", axis=0).index)
+
+    df_wo_ch["unsustainable solid biomass"] = (
+        (
+            df_wo_ch.apply(
+                lambda c: c.sum()
+                / df_wo_ch.loc[df_wo_ch.index.str[:2] == c.name[:2]].sum().sum()
+                * df_unsustainable.loc[c.name[:2], "Primary solid biofuels"],
+                axis=1,
+            )
+        )
+        .mul(reduction_factor)
+        .clip(lower=0)
+    )
+
+    df_wo_ch["unsustainable biogas"] = (
+        (
+            df_wo_ch.apply(
+                lambda c: c.sum()
+                / df_wo_ch.loc[df_wo_ch.index.str[:2] == c.name[:2]].sum().sum()
+                * df_unsustainable.loc[c.name[:2], "Biogases"],
+                axis=1,
+            )
+        )
+        .mul(reduction_factor)
+        .clip(lower=0)
+    )
+
+    df_wo_ch["unsustainable bioliquids"] = df_wo_ch.apply(
+        lambda c: c.sum()
+        / df_wo_ch.loc[df_wo_ch.index.str[:2] == c.name[:2]].sum().sum()
+        * df_unsustainable.filter(regex="gasoline|diesel|kerosene|liquid")
+        .sum(axis=1)
+        .loc[c.name[:2]],
+        axis=1,
+    ).mul(reduction_factor)
+
+    df *= 1 - reduction_factor
+
+    df = df.join(df_wo_ch.filter(like="unsustainable")).fillna(0)
+
+    return df
+
+
 if __name__ == "__main__":
     if "snakemake" not in globals():
+        import os
+
         from _helpers import mock_snakemake
 
+        os.chdir(os.path.dirname(os.path.realpath(__file__)))
         snakemake = mock_snakemake(
             "build_biomass_potentials",
             simpl="",
-            clusters="5",
+            clusters="37",
             planning_horizons=2050,
         )
 
@@ -272,4 +440,10 @@ def convert_nuts2_to_regions(bio_nuts2, regions):
     df *= 1e6  # TWh/a to MWh/a
     df.index.name = "MWh/a"
 
+    if (
+        params["include_unsustainable"]
+        and investment_year < params["unsustainable_phase_out"]
+    ):
+        df = add_unsustainable_potentials(df)
+
     df.to_csv(snakemake.output.biomass_potentials)