PyPSA · fneum · Feb 13, 2026 · Feb 13, 2026 · Feb 13, 2026 · Feb 13, 2026
diff --git a/Snakefile b/Snakefile
@@ -11,7 +11,7 @@ configfile: "config.yaml"
 
 rule compile_cost_assumptions:
     input:
-        inflation_rate="inputs/Eurostat_inflation_rates.xlsx",
+        inflation_rate="inputs/prc_hicp_aind__custom_20097956_spreadsheet.xlsx",
         pypsa_costs="inputs/costs_PyPSA.csv",
         fraunhofer_costs="inputs/Fraunhofer_ISE_costs.csv",
         fraunhofer_energy_prices="inputs/Fraunhofer_ISE_energy_prices.csv",
@@ -49,7 +49,7 @@ rule compile_cost_assumptions_usa:
             year=config["nrel_atb"]["nrel_atb_input_years"],
         ),
         nrel_atb_manual_input_usa="inputs/US/manual_input_usa.csv",
-        inflation_rate="inputs/Eurostat_inflation_rates.xlsx",
+        inflation_rate="inputs/prc_hicp_aind__custom_20097956_spreadsheet.xlsx",
         nrel_atb_input_discount_rate="inputs/US/discount_rates_usa.csv",
         nrel_atb_input_fuel_costs="inputs/US/fuel_costs_usa.csv",
     output:

diff --git a/config.yaml b/config.yaml
@@ -15,7 +15,7 @@ nrel_atb:
 expectation: ""  # tech data uncertainty, possible options [None, "optimist", "pessimist"]
 
 #year for EUR outputs
-eur_year: 2020
+eur_year: 2025
 
 # add solar from different source
 solar_utility_from_vartiaien: false

diff --git a/docs/release_notes.rst b/docs/release_notes.rst
@@ -16,6 +16,8 @@ Upcoming Release
 ..   The features listed below are not released yet, but will be part of the next release! 
 ..   To use the features already you have to use the ``master`` branch.
 
+* Changed currency year from 2020 to 2025 for all cost assumptions.
+
 * Update fossil fuel (gas, oil, lignite) and nuclear fuel (nuclear, uranium) costs based on TYNDP 2024 scenarios data.
 
 * Adding `grey methanol synthesis`.

diff --git a/inputs/Eurostat_inflation_rates.xlsx b/inputs/Eurostat_inflation_rates.xlsx
diff --git a/inputs/prc_hicp_aind__custom_20097956_spreadsheet.xlsx b/inputs/prc_hicp_aind__custom_20097956_spreadsheet.xlsx
diff --git a/outputs/US/costs_2020.csv b/outputs/US/costs_2020.csv
diff --git a/outputs/US/costs_2025.csv b/outputs/US/costs_2025.csv
diff --git a/outputs/US/costs_2030.csv b/outputs/US/costs_2030.csv
diff --git a/outputs/US/costs_2035.csv b/outputs/US/costs_2035.csv
diff --git a/outputs/US/costs_2040.csv b/outputs/US/costs_2040.csv
diff --git a/outputs/US/costs_2045.csv b/outputs/US/costs_2045.csv
diff --git a/outputs/US/costs_2050.csv b/outputs/US/costs_2050.csv
diff --git a/outputs/costs_2020.csv b/outputs/costs_2020.csv
diff --git a/outputs/costs_2025.csv b/outputs/costs_2025.csv
diff --git a/outputs/costs_2030.csv b/outputs/costs_2030.csv
diff --git a/outputs/costs_2035.csv b/outputs/costs_2035.csv
diff --git a/outputs/costs_2040.csv b/outputs/costs_2040.csv
diff --git a/outputs/costs_2045.csv b/outputs/costs_2045.csv
diff --git a/outputs/costs_2050.csv b/outputs/costs_2050.csv
diff --git a/scripts/_helpers.py b/scripts/_helpers.py
@@ -217,20 +217,27 @@ def prepare_inflation_rate(fn: str, currency_to_use: str = "eur") -> pd.Series:
     if currency_to_use.casefold() == "usd":
         row_to_use = "United States"
     else:
-        row_to_use = "European Union - 27 countries (from 2020)"
-
-    inflation_rate_series = pd.read_excel(
-        fn, sheet_name="Sheet 1", index_col=0, header=[8], engine="calamine"
-    )
-    inflation_rate_series = (inflation_rate_series.loc[row_to_use].dropna()).loc[
-        "2001"::
-    ]
-    inflation_rate_series.rename(
-        index=lambda inflation_rate_val: int(inflation_rate_val), inplace=True
+        row_to_use = "European Economic Area (EEA18-1995, EEA28-2004, EEA30-2007, EEA31-2013, EEA30-2020)"
+
+    df = (
+        pd.read_excel(
+            fn,
+            sheet_name="Sheet 1",
+            index_col=0,
+            na_values=[":", "d"],
+            header=8,
+            engine="calamine",
+        )
+        .loc[row_to_use]
+        .dropna()
     )
-    inflation_rate_series = inflation_rate_series.astype(float)
-    inflation_rate_series /= 100.0
-    return inflation_rate_series
+
+    df.index = df.index.astype(int)
+    df = df.astype(float)
+
+    df /= 100.0
+
+    return df
 
 
 def adjust_for_inflation(