Merge pull request #391 from cpschau/interest_rate_sens

setup for interest rate sensitivity; fix bugs

scripts/override_respot.py

@@ -64,7 +64,7 @@ def override_values(tech, year, dr, simpl, clusters):
 
     def annuity_factor(v):
         return (
-            annuity(v["lifetime"], snakemake.wildcards["discountrate"])
+            annuity(v["lifetime"], float(snakemake.wildcards["discountrate"]))
             + v["fixedomEuroPKW"] / v["investmentEuroPKW"] / 100
         )
 

scripts/prepare_res_potentials.py

@@ -113,10 +113,7 @@ def merge_onwind(onwind, onwind_rest):
 
 
 def prepare_enertile(df, df_t):
-    tech_dict = {
-        "windonshore": "onwind",
-        "sopv": "solar",
-    }
+    tech_dict = {"windonshore": "onwind", "sopv": "solar", "pvr": "solar-rooftop"}
 
     regions = gpd.read_file(snakemake.input.regions_onshore_elec_s)
 
@@ -172,7 +169,7 @@ def prepare_enertile(df, df_t):
     )
 
     df = df.groupby(["Generator", "step", "simyear"], as_index=False).mean()
-    if technology == "solar":
+    if technology == "solar" or technology == "solar-rooftop":
         df["flh_class"] = "Q4"
     else:
         df = df.groupby(["Generator", "simyear"], as_index=False).apply(
@@ -181,6 +178,7 @@ def prepare_enertile(df, df_t):
 
     df.set_index(["Generator", "step", "simyear"], inplace=True)
     df_t.set_index(["region", "step", "simyear"], inplace=True)
+    df_t = df_t.loc[df.index]
     df_t["install_cap"] = df["p_nom_max"]
     df_t["potential"] = df["potential"]
     df_t["flh_class"] = df["flh_class"]
@@ -225,11 +223,7 @@ def prepare_enertile(df, df_t):
     # Export for every simyear and flh_class the sliced installable and res_t
     flh_class_dict = {"Q4": "", "Q3": "2", "Q2": "3", "Q1": "4"}
     for region, simyear, flh_class in installable.index:
-        ir = (
-            installable.loc[(slice(None), simyear, flh_class)]
-            .interestrate.mode()
-            .item()
-        )
+        ir = snakemake.config["costs"]["discountrate"][0]
         export_tech = technology + flh_class_dict[flh_class]
         logger.info(snakemake.output.keys())
         installable.loc[(slice(None), simyear, flh_class)].reset_index().to_csv(
@@ -272,6 +266,7 @@ def prepare_enertile(df, df_t):
     }
     renewables_enertile.remove("onwind_rest")
     for technology in renewables_enertile:
+        logger.info(f"Preparing {technology} data")
         prepare_enertile(
             df=data[technology]["potentials"], df_t=data[technology]["hourdata"]
         )

scripts/prepare_transport_data_input.py

@@ -127,6 +127,9 @@ def download_CO2_emissions():
         shutil.copy(src, dest)
     else:
         # Join the DataFrames by the 'country' column
+        CO2_emissions_csv = CO2_emissions_csv[
+            ~CO2_emissions_csv["country"].apply(lambda x: isinstance(x, list))
+        ]
         merged_df = pd.merge(vehicles_csv, CO2_emissions_csv, on="country")
         merged_df = merged_df[["country", "number cars", "average fuel efficiency"]]
 

scripts/solve_network.py

@@ -519,7 +519,7 @@ def fix_rooftopPV_utilityScale_ratio(n, target_ratio=2):
     )
 
     # Filter for rooftop and utility-scale solar generators
-    rooftop_index = n.generators.loc[n.generators.carrier == "rooftop-solar"].index
+    rooftop_index = n.generators.loc[n.generators.carrier == "solar-rooftop"].index
     utility_index = n.generators.loc[n.generators.carrier == "solar"].index
 
     # Get the generator capacity variables (p_nom) for each generator type
@@ -594,7 +594,12 @@ def extra_functionality(n, snapshots):
         "ratio_rooftop_to_utility_solar"
     ]:
         fix_rooftopPV_utilityScale_ratio(
-            n, snakemake.config["policy_config"]["ratio_rooftop_to_utility_solar"]
+            n,
+            float(
+                snakemake.config["policy_config"]["renewables"][
+                    "ratio_rooftop_to_utility_solar"
+                ]
+            ),
         )
 
     add_co2_sequestration_limit(n, snapshots)
@@ -678,8 +683,8 @@ def add_existing(n):
             ll="v1.0",
             opts="Co2L",
             planning_horizons="2035",
-            sopts="365H",
-            discountrate=0.071,
+            sopts="3H",
+            discountrate=0.06,
             demand="BI",
             h2export="0",
             h2mp="endogenous",

submit_dr.sh

@@ -0,0 +1,39 @@
+#!/bin/bash
+
+conda activate pypsa-earth
+
+# rm pypsa-earth/networks/elec.nc
+cp config.pypsa-earth_low.yaml config.pypsa-earth.yaml
+cp config.bright_ref_low.yaml config.yaml
+snakemake --profile slurm all
+cp config.bright_low.yaml config.yaml
+snakemake --profile slurm all
+
+rm pypsa-earth/networks/elec.nc
+cp config.pypsa-earth_med.yaml config.pypsa-earth.yaml
+cp config.bright_ref_med.yaml config.yaml
+snakemake --profile slurm all
+cp config.bright_med.yaml config.yaml
+snakemake --profile slurm all
+
+rm pypsa-earth/networks/elec.nc
+cp config.pypsa-earth_high.yaml config.pypsa-earth.yaml
+cp config.bright_ref_high.yaml config.yaml
+snakemake --profile slurm all
+cp config.bright_high.yaml config.yaml
+snakemake --profile slurm all
+
+rm pypsa-earth/networks/elec.nc
+cp config.pypsa-earth_vhigh.yaml config.pypsa-earth.yaml
+cp config.bright_ref_vhigh.yaml config.yaml
+snakemake --profile slurm all
+cp config.bright_vhigh.yaml config.yaml
+snakemake --profile slurm all
+
+# NEXTCLOUD_URL="https://tubcloud.tu-berlin.de/remote.php/webdav/BRIGHT/results/"
+# USERNAME="cpschau"
+# PASSWORD=$(get_nextcloud_password)
+
+# # Upload the file to Nextcloud via WebDAV
+# tar -czf results_241031.tar.gz /results/241031/
+# curl -u "$USERNAME:$PASSWORD" -T "results_241031.tar.gz" "$NEXTCLOUD_URL"