Merge pull request #389 from cpschau/capex_overriding

allow different interest rates for capex calculation of custom res

config.bright.yaml

@@ -29,8 +29,7 @@ scenario:
   - "Co2L"
   sopts:
   - "3H"
-  demand:
-  - ["BI", "DE", "GH"] # BI/DE/GH
+  demand: ["BI", "DE", "GH"] # BI/DE/GH
 
 policy_config:
   hydrogen:
@@ -66,7 +65,7 @@ fossil_reserves:
 
 export:
   h2export: "endogenous" #,20,30,40,50,60,70,80,90,100] or "endogenous" in combination with h2mp # Yearly export demand in TWh
-  h2mp: [70, 90, 100, 110, 120] # Global hydrogen market price in EUR/MWh if h2export is set to endogenous
+  h2mp: [70, 72.5, 75, 77.5, 80, 82.5, 85, 87.5, 90] # Global hydrogen market price in EUR/MWh if h2export is set to endogenous
   store: false # [True, False] # specifies wether an export store to balance demand is implemented
   store_capital_costs: "no_costs" # ["standard_costs", "no_costs"] # specifies the costs of the export store. "standard_costs" takes CAPEX of "hydrogen storage tank type 1 including compressor"
   export_profile: "constant" # use "ship" or "constant"
@@ -94,7 +93,7 @@ custom_data:
   rename_industry_carriers: {"Electricity": "electricity", "Biofuels": "solid biomass", "Heat": "low-temperature heat", "Natural Gas": "gas", "Coal": "coal", "Hydrogen": "hydrogen", "Oil": "oil"}
 
 costs: # Costs used in PyPSA-Earth-Sec. Year depends on the wildcard planning_horizon in the scenario section
-  version: v0.6.2
+  version: v0.9.2
   lifetime: 25 #default lifetime
   # From a Lion Hirth paper, also reflects average of Noothout et al 2016
   discountrate: [0.071] #, 0.086, 0.111]
@@ -112,7 +111,8 @@ costs: # Costs used in PyPSA-Earth-Sec. Year depends on the wildcard planning_ho
     H2: 0.
     battery: 0.
 
-  electrolyzer_cc: [0.7, 1.0, 1.3]
+  electrolyzer_cc: [0.5]
+
 
   emission_prices: # only used with the option Ep (emission prices)
     co2: 0.

config.pypsa-earth.yaml

@@ -338,7 +338,7 @@ renewable:
 # Costs Configuration (Do not remove, needed for Sphynx documentation).
 costs:
   year: 2030
-  version: v0.5.0
+  version: v0.9.2
   rooftop_share: 0.14  # based on the potentials, assuming  (0.1 kW/m2 and 10 m2/person)
   USD2013_to_EUR2013: 0.7532 # [EUR/USD] ECB: https://www.ecb.europa.eu/stats/exchange/eurofxref/html/eurofxref-graph-usd.en.html
   fill_values:
@@ -349,7 +349,7 @@ costs:
     investment: 0
     lifetime: 25
     CO2 intensity: 0
-    discount rate: 0.071
+    discount rate: [0.071]
   marginal_cost: # EUR/MWh
     solar: 0.01
     onwind: 0.015

scripts/override_respot.py

@@ -11,6 +11,7 @@
 import pytz
 import xarray as xr
 from helpers import mock_snakemake, override_component_attrs, sets_path_to_root
+from vresutils.costdata import annuity
 
 logger = logging.getLogger(__name__)
 
@@ -61,6 +62,19 @@ def override_values(tech, year, dr, simpl, clusters):
     else:
         existing_res = custom_res["installedcapacity"].values
 
+    def annuity_factor(v):
+        return (
+            annuity(v["lifetime"], snakemake.wildcards["discountrate"])
+            + v["fixedomEuroPKW"] / v["investmentEuroPKW"] / 100
+        )
+
+    Nyears = n.snapshot_weightings.generators.sum() / 8760
+
+    custom_res["fixed"] = [
+        annuity_factor(v) * v["investmentEuroPKW"] * Nyears
+        for i, v in custom_res.iterrows()
+    ]
+
     n.madd(
         "Generator",
         custom_res.index,
@@ -70,7 +84,7 @@ def override_values(tech, year, dr, simpl, clusters):
         p_nom_max=custom_res["p_nom_max"],
         # weight=ds["weight"].to_pandas(),
         # marginal_cost=custom_res["fixedomEuroPKW"].values * 1000,
-        capital_cost=custom_res["annualcostEuroPMW"],
+        capital_cost=custom_res["fixed"],
         efficiency=1.0,
         p_max_pu=custom_res_t,
         lifetime=custom_res["lifetime"],
@@ -86,11 +100,11 @@ def override_values(tech, year, dr, simpl, clusters):
             "override_respot",
             simpl="",
             clusters="11",
-            ll="v2.0",
+            ll="v1.0",
             opts="Co2L",
-            planning_horizons="2030",
-            sopts="144H",
-            demand="AB",
+            planning_horizons="2035",
+            sopts="3H",
+            demand="BI",
             discountrate=0.071,
         )
         sets_path_to_root("pypsa-earth-sec")

scripts/prepare_res_potentials.py

@@ -212,6 +212,7 @@ def prepare_enertile(df, df_t):
         {
             "p_nom_max": "sum",
             "annualcostEuroPMW": "mean",
+            "investmentEuroPKW": "mean",
             "fixedomEuroPKW": "mean",
             "installedcapacity": "sum",
             "lifetime": "mean",