diff --git a/etrago/cluster/spatial.py b/etrago/cluster/spatial.py
index 45ca52f0..57d483e7 100755
--- a/etrago/cluster/spatial.py
+++ b/etrago/cluster/spatial.py
@@ -748,6 +748,17 @@ def kmedoids_dijkstra_clustering(
 
     settings = etrago.args["network_clustering"]
 
+    if n_clusters is False:
+        busmap = pd.Series(
+            range(len(buses)), index=buses.index, name="final_assignment"
+        )
+        busmap.index.name = "bus_id"
+        busmap = busmap.apply(str)
+
+        medoid_idx = pd.Series(busmap.index, index=busmap.values, name=0)
+
+        return busmap, medoid_idx
+
     # n_jobs was deprecated for the function fit(). scikit-learn recommends
     # to use threadpool_limits:
     # https://scikit-learn.org/stable/computing/parallelism.html
diff --git a/etrago/tools/utilities.py b/etrago/tools/utilities.py
index 47c9b3a1..d7b995b3 100755
--- a/etrago/tools/utilities.py
+++ b/etrago/tools/utilities.py
@@ -3013,7 +3013,16 @@ def select_elec_network(etrago, apply_on="grid_model"):
             elec_network_buses = elec_network_buses[
                 ~elec_network_buses.isin(foreign_buses.index)
             ]
-            n_clusters = settings["n_clusters_AC"] - num_neighboring_country
+            if settings["n_clusters_AC"] is False:
+                n_clusters = False
+            else:
+                n_clusters = (
+                    settings["n_clusters_AC"] - num_neighboring_country
+                )
+                assert (
+                    n_clusters > 1
+                ), f"""'n_clusters_AC' must be greater than the number of foreign
+                countries({num_neighboring_country})"""
 
         elec_network = network_based_on_buses(
             etrago.network, elec_network_buses