diff --git a/data/costs.csv b/data/costs.csv
index 15f3678..767573f 100644
--- a/data/costs.csv
+++ b/data/costs.csv
@@ -183,7 +183,8 @@ decentral solar thermal,2030,lifetime,20,years,HP;
 central solar thermal,2030,FOM,1.4,%/year,HP;
 central solar thermal,2030,investment,140000,EUR/1000m2,HP;
 central solar thermal,2030,lifetime,20,years,HP;
-HVAC overhead,2030,investment,40,EUR/MW/km,Hagspiel;
+HVAC overhead,2030,investment,400,EUR/MW/km,Hagspiel;
+MVAC overhead,2030,investment,40,EUR/MW/km,Hagspiel;
 HVAC overhead,2030,lifetime,40,years,Hagspiel;
 HVAC overhead,2030,FOM,2,%/year,Hagspiel;
 HVDC overhead,2030,investment,400,EUR/MW/km,Hagspiel;
diff --git a/scripts/add_electricity.py b/scripts/add_electricity.py
index 5888313..46ed76b 100644
--- a/scripts/add_electricity.py
+++ b/scripts/add_electricity.py
@@ -308,7 +308,7 @@ def attach_conventional_generators(
                     n.generators.loc[idx].bus.map(bus_values).dropna()
                 )
             else:
-                # Singolo valore che influenza tutti i generatori di tecnologia k indipendentemente dal paese
+                # Single value affecting all k technology generators regardless of country.
                 n.generators.loc[idx, attr] = values
 
 
@@ -357,7 +357,7 @@ def attach_load(n, load_file, tech_modelling):
 
 def update_transmission_costs(n, costs, length_factor=1.0, simple_hvdc_costs=False):
     n.lines["capital_cost"] = (
-        n.lines["length"] * length_factor * costs.at["HVAC overhead", "capital_cost"]
+        n.lines["length"] * length_factor * costs.at["MVAC overhead", "capital_cost"]
     )
 
 
diff --git a/scripts/cluster_buildings.py b/scripts/cluster_buildings.py
index 99afe31..6ae174f 100644
--- a/scripts/cluster_buildings.py
+++ b/scripts/cluster_buildings.py
@@ -79,9 +79,7 @@ def get_central_points_geojson_with_buildings(
                 "cluster": i,
             }
         )
-    central_features = gpd.GeoDataFrame(central_features, crs=microgrid_buildings.crs)
-    if microgrid_buildings.crs != "EPSG:4326":
-        central_features = central_features.to_crs("EPSG:4326")
+    central_features = gpd.GeoDataFrame(central_features, crs="EPSG:4326")
     central_features.to_file(output_filepath_centroids, driver="GeoJSON")
 
     clusters = []