Modify Industry Sector Ratios

Changelog.md

@@ -1,4 +1,5 @@
 # Changelog
+- Modify industry sector ratios for Germany to reach climate neutrality by 2045 in the industrial sector.
 - Restricting the maximum capacity of CurrentPolicies and minus scenarios to the 'uba Projektionsbericht'
 - Restricting Fischer Tropsch capacity addition with config[solving][limit_DE_FT_cap]
 - Except for Current Policies force a minimum of 5 GW of electrolysis capacity in Germany

config/config.yaml

@@ -4,7 +4,7 @@
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#run
 run:
-  prefix: 20241121-fix-missing-gas-capa
+  prefix: 20241202-modify-sector-ratios
 
   name:
   # - CurrentPolicies
@@ -62,7 +62,7 @@ scenario:
   ll:
   - vopt
   clusters:
-  - 27 #current options: 27, 49
+  - 49 #current options: 27, 49
   opts:
   - ''
   sector_opts:
@@ -206,38 +206,38 @@ clustering:
   # print(fw.div(fw.sum()).subtract(5e-5).round(4).to_dict().__repr__().replace(",","\n"))
   focus_weights:
   # 27 nodes: 8 for Germany, 3 for Italy, 2 each for Denmark, UK and Spain, 1 per each of other 10 "Stromnachbarn"
-    'DE': 0.2966
-    'AT': 0.0370
-    'BE': 0.0370
-    'CH': 0.0370
-    'CZ': 0.0370
-    'DK': 0.0741
-    'FR': 0.0370
-    'GB': 0.0741
-    'LU': 0.0370
-    'NL': 0.0370
-    'NO': 0.0370
-    'PL': 0.0370
-    'SE': 0.0370
-    'ES': 0.0741
-    'IT': 0.1111
+    # 'DE': 0.2966
+    # 'AT': 0.0370
+    # 'BE': 0.0370
+    # 'CH': 0.0370
+    # 'CZ': 0.0370
+    # 'DK': 0.0741
+    # 'FR': 0.0370
+    # 'GB': 0.0741
+    # 'LU': 0.0370
+    # 'NL': 0.0370
+    # 'NO': 0.0370
+    # 'PL': 0.0370
+    # 'SE': 0.0370
+    # 'ES': 0.0741
+    # 'IT': 0.1111
   # high spatial resolution: change clusters to 49
   # 49 nodes: 30 for Germany, 3 for Italy, 2 each for Denmark, UK and Spain, 1 per each of other 10 "Stromnachbarn"
-    # 'DE': 0.6124
-    # 'AT': 0.0204
-    # 'BE': 0.0204
-    # 'CH': 0.0204
-    # 'CZ': 0.0204
-    # 'DK': 0.0408
-    # 'FR': 0.0204
-    # 'GB': 0.0408
-    # 'LU': 0.0204
-    # 'NL': 0.0204
-    # 'NO': 0.0204
-    # 'PL': 0.0204
-    # 'SE': 0.0204
-    # 'ES': 0.0408
-    # 'IT': 0.0612
+    'DE': 0.6124
+    'AT': 0.0204
+    'BE': 0.0204
+    'CH': 0.0204
+    'CZ': 0.0204
+    'DK': 0.0408
+    'FR': 0.0204
+    'GB': 0.0408
+    'LU': 0.0204
+    'NL': 0.0204
+    'NO': 0.0204
+    'PL': 0.0204
+    'SE': 0.0204
+    'ES': 0.0408
+    'IT': 0.0612
   temporal:
     resolution_sector: 365H
 
@@ -349,6 +349,13 @@ sector:
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#industry
 industry:
+  sector_ratios_fraction_future_DE:
+    2020: 0.0
+    2025: 0.1
+    2030: 0.3
+    2035: 0.6
+    2040: 0.9
+    2045: 1.0
   ammonia: false
   St_primary_fraction:
     2020: 0.6

workflow/Snakefile

@@ -413,6 +413,45 @@ use rule build_industrial_production_per_node from pypsaeur with:
         ),
 
 
+rule modify_sector_ratios:
+    params:
+        future_DE=config_provider("industry", "sector_ratios_fraction_future_DE"),
+    input:
+        industry_sector_ratios=resources("industry_sector_ratios.csv"),
+        industrial_energy_demand_per_country_today=resources(
+            "industrial_energy_demand_per_country_today.csv"
+        ),
+        industrial_production_per_country=resources(
+            "industrial_production_per_country.csv"
+        ),
+        sector_ratios=resources("industry_sector_ratios_{planning_horizons}.csv"),
+    output:
+        sector_ratios_modified=resources(
+            "industry_sector_ratios_{planning_horizons}-modified.csv"
+        ),
+    resources:
+        mem_mb=2000,
+    log:
+        logs("modify_industry_sector_ratios_{planning_horizons}}.log"),
+    script:
+        "scripts/modify_sector_ratios.py"
+
+
+ruleorder: modify_sector_ratios > build_industry_sector_ratios_intermediate
+
+
+use rule build_industrial_energy_demand_per_node from pypsaeur with:
+    input:
+        **{
+            k: v
+            for k, v in rules.build_industrial_energy_demand_per_node.input.items()
+            if k != "industry_sector_ratios"
+        },
+        industry_sector_ratios=resources(
+            "industry_sector_ratios_{planning_horizons}-modified.csv"
+        ),
+
+
 rule build_wasserstoff_kernnetz:
     params:
         kernnetz=config_provider("wasserstoff_kernnetz"),

workflow/scripts/build_scenarios.py

@@ -178,8 +178,9 @@ def write_to_scenario_yaml(input, output, scenarios, df):
             df.loc[:, fallback_reference_scenario, :], planning_horizons
         )
 
-
-        if reference_scenario.startswith("KN2045plus"): # Still waiting for REMIND uploads
+        if reference_scenario.startswith(
+            "KN2045plus"
+        ):  # Still waiting for REMIND uploads
             fallback_reference_scenario = reference_scenario
 
         co2_budget_source = config[scenario]["co2_budget_DE_source"]

workflow/scripts/modify_sector_ratios.py

@@ -0,0 +1,119 @@
+# -*- coding: utf-8 -*-
+# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: MIT
+"""
+Overwrite the sector ratios for Germany to represent climate neutrality in 2045 already compared to 2050 for the rest of Europe.
+
+Relevant Settings
+-----------------
+
+.. code:: yaml
+
+    industry:
+        sector_ratios_fraction_future_DE:
+
+Inputs
+------
+
+- ``resources/industry_sector_ratios.csv``
+- ``resources/industrial_energy_demand_per_country_today.csv``
+- ``resources/industrial_production_per_country.csv``
+
+Outputs
+-------
+
+- ``resources/industry_sector_ratios_{planning_horizons}-modified.csv``
+
+"""
+import os
+import sys
+
+paths = ["workflow/submodules/pypsa-eur/scripts", "../submodules/pypsa-eur/scripts"]
+for path in paths:
+    sys.path.insert(0, os.path.abspath(path))
+
+import numpy as np
+import pandas as pd
+from prepare_sector_network import get
+
+
+def build_industry_sector_ratios_intermediate():
+
+    # in TWh/a
+    demand = pd.read_csv(
+        snakemake.input.industrial_energy_demand_per_country_today,
+        header=[0, 1],
+        index_col=0,
+    )
+
+    # in Mt/a
+    production = (
+        pd.read_csv(snakemake.input.industrial_production_per_country, index_col=0)
+        / 1e3
+    ).stack()
+    production.index.names = [None, None]
+
+    # in MWh/t
+    future_sector_ratios = pd.read_csv(
+        snakemake.input.industry_sector_ratios, index_col=0
+    )
+
+    today_sector_ratios = demand.div(production, axis=1).replace([np.inf, -np.inf], 0)
+
+    today_sector_ratios.dropna(how="all", axis=1, inplace=True)
+
+    rename = {
+        "waste": "biomass",
+        "electricity": "elec",
+        "solid": "coke",
+        "gas": "methane",
+        "other": "biomass",
+        "liquid": "naphtha",
+    }
+    today_sector_ratios = today_sector_ratios.rename(rename).groupby(level=0).sum()
+
+    # custom DE pathway
+    fraction_DE = get(snakemake.params.future_DE, year)
+
+    intermediate_sector_ratios_DE = {}
+
+    DE_sector_ratios = today_sector_ratios.loc[:, "DE"].reindex_like(
+        future_sector_ratios
+    )
+    missing_mask = DE_sector_ratios.isna().all()
+    DE_sector_ratios.loc[:, missing_mask] = future_sector_ratios.loc[:, missing_mask]
+    DE_sector_ratios.loc[:, ~missing_mask] = DE_sector_ratios.loc[
+        :, ~missing_mask
+    ].fillna(future_sector_ratios)
+    intermediate_sector_ratios_DE["DE"] = (
+        DE_sector_ratios * (1 - fraction_DE) + future_sector_ratios * fraction_DE
+    )
+    # make dictionary to dataframe
+    intermediate_sector_ratios_DE = pd.concat(intermediate_sector_ratios_DE, axis=1)
+
+    # read in original sector ratios
+    intermediate_sector_ratios = pd.read_csv(
+        snakemake.input.sector_ratios, header=[0, 1], index_col=0
+    )
+
+    # update DE sector ratios
+    intermediate_sector_ratios.loc[:, "DE"] = intermediate_sector_ratios_DE["DE"].values
+
+    intermediate_sector_ratios.to_csv(snakemake.output.sector_ratios_modified)
+
+
+if __name__ == "__main__":
+    if "snakemake" not in globals():
+
+        from _helpers import mock_snakemake
+
+        snakemake = mock_snakemake(
+            "modify_sector_ratios",
+            planning_horizons="2045",
+            run="KN2045_Bal_v4",
+        )
+
+    year = int(snakemake.wildcards.planning_horizons)
+
+    build_industry_sector_ratios_intermediate()