diff --git a/backend/Property.py b/backend/Property.py
index a1bfe265..618dfd67 100644
--- a/backend/Property.py
+++ b/backend/Property.py
@@ -377,7 +377,9 @@ class Property:
                     x["type"] != "internal_wall_insulation"
                 ]
             else:
-                epc_transformations = [x["description_simulation"] for x in represenative_recs_to_this_phase]
+                epc_transformations = [
+                    x["description_simulation"] for x in represenative_recs_to_this_phase
+                ]
 
             # It is possible that we could have two simulations applied to the same descriptions
             # We extract these out
@@ -407,7 +409,8 @@ class Property:
                             continue
 
                         raise NotImplementedError(
-                            "Already have this key in the phase_epc_transformation - implement me")
+                            "Already have this key in the phase_epc_transformation - implement me"
+                        )
                     phase_epc_transformation[k] = v
 
             simulation_epc = self.epc_record.prepared_epc.copy()
diff --git a/recommendations/Recommendations.py b/recommendations/Recommendations.py
index 0469f501..81c26e15 100644
--- a/recommendations/Recommendations.py
+++ b/recommendations/Recommendations.py
@@ -230,6 +230,16 @@ class Recommendations:
             # When check if these recommendations have two different types, such as solid wall insulation
             # If we have multiple types, we group by type and then select the best recommendation for each type
 
+            # If we have a heating and heating control recommendation, we use JUST the heating reommendation
+            has_both_heating_types = all(
+                x in [rec["type"] for rec in recommendations_by_type] for x in ["heating", "heating_control"]
+            )
+            if has_both_heating_types:
+                # Take just heating
+                recommendations_by_type = [
+                    rec for rec in recommendations_by_type if rec["type"] == "heating"
+                ]
+
             recommendations_by_type = sorted(recommendations_by_type, key=lambda x: x["type"])
             representative_recommendations = []
             for _type, recommendations in groupby(recommendations_by_type, key=lambda x: x["type"]):