first version of st variations should work now

Author: lindnemi

Snakefile

@@ -1023,12 +1023,12 @@ rule prepare_st_low_res_network:
         + "networks/base_s_{clusters}_{opts}_{sector_opts}_{st_years}.nc",
     output:
         st_low_res_prenetwork=RESULTS
-        + "st_low_res_prenetworks/base_s_{clusters}_{opts}_{sector_opts}_{st_years}.nc",
+        + "st_low_res_prenetworks/base_s_{clusters}_{opts}_{sector_opts}_{st_years}_eeg_level_{eeg_level}.nc",
     resources:
         mem_mb=16000,
     log:
         RESULTS
-        + "logs/st_low_res_prenetwork_s_{clusters}_{opts}_{sector_opts}_{st_years}.log",
+        + "logs/st_low_res_prenetwork_s_{clusters}_{opts}_{sector_opts}_{st_years}_eeg_level_{eeg_level}.log",
     script:
         "scripts/pypsa-de/prepare_st_low_res_network.py"
 
@@ -1042,21 +1042,21 @@ rule solve_st_low_res_network:
         custom_extra_functionality=input_custom_extra_functionality,
     input:
         st_low_res_prenetwork=RESULTS
-        + "st_low_res_prenetworks/base_s_{clusters}_{opts}_{sector_opts}_{st_years}.nc",
+        + "st_low_res_prenetworks/base_s_{clusters}_{opts}_{sector_opts}_{st_years}_eeg_level_{eeg_level}.nc",
         co2_totals_name=resources("co2_totals.csv"),
         energy_totals=resources("energy_totals.csv"),
     output:
         st_low_res_network=RESULTS
-        + "st_low_res_networks/{sensitivity}/base_s_{clusters}_{opts}_{sector_opts}_{st_years}.nc",
+        + "st_low_res_networks/{sensitivity}/base_s_{clusters}_{opts}_{sector_opts}_{st_years}_eeg_level_{eeg_level}.nc",
     shadow:
         shadow_config
     log:
         solver=RESULTS
-        + "logs/st_low_res_networks/{sensitivity}/base_s_{clusters}_{opts}_{sector_opts}_{st_years}_solver.log",
+        + "logs/st_low_res_networks/{sensitivity}/base_s_{clusters}_{opts}_{sector_opts}_{st_years}_eeg_level_{eeg_level}_solver.log",
         memory=RESULTS
-        + "logs/st_low_res_networks/{sensitivity}/base_s_{clusters}_{opts}_{sector_opts}_{st_years}_memory.log",
+        + "logs/st_low_res_networks/{sensitivity}/base_s_{clusters}_{opts}_{sector_opts}_{st_years}_eeg_level_{eeg_level}_memory.log",
         python=RESULTS
-        + "logs/st_low_res_networks/{sensitivity}/base_s_{clusters}_{opts}_{sector_opts}_{st_years}_python.log",
+        + "logs/st_low_res_networks/{sensitivity}/base_s_{clusters}_{opts}_{sector_opts}_{st_years}_eeg_level_{eeg_level}_python.log",
     threads: solver_threads
     resources:
         mem_mb=config_provider("solving", "mem_mb"),
@@ -1102,25 +1102,28 @@ use rule export_ariadne_variables as export_st_variables with:
         energy_totals=resources("energy_totals.csv"),
         st_low_res_networks=expand(
             RESULTS
-            + "st_low_res_networks/{sensitivity}/base_s_{clusters}_{opts}_{sector_opts}_{st_years}.nc",
+            + "st_low_res_networks/{sensitivity}/base_s_{clusters}_{opts}_{sector_opts}_{st_years}_eeg_level_{eeg_level}.nc",
             **config["scenario"],
             st_years=config_provider("iiasa_database", "regret_run", "st_years"),
             allow_missing=True,
         ),
     output:
         exported_variables=RESULTS
-        + "st_low_res_variables/{sensitivity}/st_low_res_variables.xlsx",
+        + "st_low_res_variables/{sensitivity}/st_low_res_variables_eeg_level_{eeg_level}.xlsx",
         exported_variables_full=RESULTS
-        + "st_low_res_variables/{sensitivity}/st_low_res_variables_full.xlsx",
+        + "st_low_res_variables/{sensitivity}/st_low_res_variables_full_eeg_level_{eeg_level}.xlsx",
     log:
-        RESULTS + "logs/st_low_res_variables/{sensitivity}/st_low_res_variables.log",
+        RESULTS
+        + "logs/st_low_res_variables/{sensitivity}/st_low_res_variables_eeg_level_{eeg_level}.log",
 
 
 rule st_all:
     input:
         expand(
-            RESULTS + "st_low_res_variables/{sensitivity}/st_low_res_variables.xlsx",
+            RESULTS
+            + "st_low_res_variables/{sensitivity}/st_low_res_variables_eeg_level_{eeg_level}.xlsx",
             sensitivity=get_st_sensitivities,
+            eeg_level=config_provider("iiasa_database", "regret_run", "EEG_levels"),
             run=config_provider("run", "name"),
         ),
 

config/config.de.yaml

@@ -58,6 +58,14 @@ iiasa_database:
     #- gas_price_80
     st_years:
     - 2030
+    EEG_levels:
+    - 1.00
+    # - 0.95
+    # - 0.90
+    - 0.85
+    # - 0.80
+    # - 0.75
+    - 0.70
     unit_commitment:
       enable: false
       params: custom # options: conservative, average, optimistic, custom

scripts/pypsa-de/export_ariadne_variables.py

@@ -5542,6 +5542,10 @@ def get_data(
 
     # Load data
     _networks = [pypsa.Network(fn) for fn in snakemake.input.networks]
+    if snakemake.input.st_low_res_networks:
+        _networks_st = [pypsa.Network(fn) for fn in snakemake.input.st_low_res_networks]
+        N_st = len(_networks_st)
+        _networks[-N_st:] = _networks_st
 
     nhours = _networks[0].snapshot_weightings.generators.sum()
     nyears = nhours / 8760

scripts/pypsa-de/prepare_st_low_res_network.py

@@ -128,6 +128,7 @@ def fix_capacities(n_lt, no_flex=False):
             sector_opts="none",
             st_years="2030",
             run="HighDemand",
+            eeg_level=0.7,
         )
 
     configure_logging(snakemake)
@@ -153,7 +154,9 @@ def fix_capacities(n_lt, no_flex=False):
 
     n = fix_capacities(n_lt, snakemake.params.get("no_flex_lt_run", False))
 
-    scale_new_res_to_target(n, eeg_targets, int(st_years), ratio=1.0)
+    scale_new_res_to_target(
+        n, eeg_targets, int(st_years), ratio=float(snakemake.wildcards.eeg_level)
+    )
 
     if h2_vent:
         logger.info("H2 venting activated for short-term run.")
@@ -210,6 +213,8 @@ def fix_capacities(n_lt, no_flex=False):
         regret_run=True,
     )
 
+    logger.info("Adding negative CO2 generator and dropping co2 limits.")
+
     n.add(
         "Generator",
         "co2 atmosphere",
@@ -218,9 +223,8 @@ def fix_capacities(n_lt, no_flex=False):
         p_max_pu=0,
         p_nom_extendable=True,
         carrier="co2",
-        marginal_cost=co2_prices[int(st_years)],
+        marginal_cost=-co2_prices[int(st_years)],
     )
-    logger.info("Adding negative CO2 generator and dropping co2 limits.")
     n.global_constraints.drop("CO2Limit", inplace=True)
     n.global_constraints.drop("co2_limit-DE", inplace=True)