Merge pull request #745 from Hestia-Homes/bug/incorrect-secondary-heating

Handling cases where ventilation sap is zero

backend/Property.py

@@ -490,7 +490,7 @@ class Property:
         for rec_id in rec_ids:
             sim_epc = self.simulation_epcs[rec_id].copy()
             rec_impact = [x for x in impact_summary if x["recommendation_id"] == rec_id][0]
-            # We update all of the features that should have an impact on the kwh model
+            # We update all features that should have an impact on the kwh model
 
             sim_epc.update(
                 {

recommendations/Recommendations.py

@@ -499,8 +499,16 @@ class Recommendations:
         return predicted_appliances_cost_reduction, predicted_appliances_kwh_reduction
 
     @staticmethod
-    def _check_ventilation_out_of_bounds(sap_impact, ventilation_sap_limit):
+    def _check_ventilation_out_of_bounds(sap_impact: float, ventilation_sap_limit: float) -> bool:
-        return (sap_impact < ventilation_sap_limit) or (sap_impact >= 0)
+        """
+        Checks if the SAP impact of a ventilation recommendation is out of bounds, which would indicate that the
+        recommendation is not appropriate.
+        :param sap_impact: The SAP impact of the ventilation recommendation, which is typically negative or zero
+        :param ventilation_sap_limit: The SAP limit for ventilation recommendations, which is typically a negative
+        number. E.g. -4
+        :return:
+        """
+        return (sap_impact < ventilation_sap_limit) or (sap_impact > 0)
 
     @staticmethod
     def _adjust_ventilation_sap(sap_impact, ventilation_sap_limit):
@@ -691,7 +699,8 @@ class Recommendations:
         previous_phase_values: dict,
         current_phase_values: dict,
         adjustments: list,
-        property_instance,
+        property_instance: Property,
+        model_predicted_sap: float,
     ):
         # For the moment, we cap the number of SAP points that can be achieved by LEDs at 2
         if rec["type"] == "low_energy_lighting":
@@ -785,7 +794,6 @@ class Recommendations:
 
                 # Update the current phase values
                 current_phase_values["sap"] = previous_phase_values["sap"] + property_phase_impact["sap"]
-
         elif rec["type"] == "loft_insulation":
             # When we have a loft insulation recommendation, where there is an extension and the existing
             # amount of loft insulation is already good, we limit the SAP points
@@ -831,6 +839,27 @@ class Recommendations:
 
             # Update the current phase values
             current_phase_values["sap"] = previous_phase_values["sap"] + property_phase_impact["sap"]
+        elif rec["measure_type"] in ["roomstat_programmer_trvs", "time_temperature_zone_control"]:
+            # We trim the SAP point recommendations based on the minimum of the predicted and the survey SAP
+            # points
+            predicted_difference = model_predicted_sap - previous_phase_values["sap_prediction"]
+            proposed_impact = property_phase_impact["sap"]
+            numerically_the_same = np.isclose(proposed_impact, predicted_difference)
+
+            if predicted_difference > 0 and (predicted_difference < proposed_impact) and not numerically_the_same:
+                # We constrain the impact based on what the model predicts.
+                # We update the proposed impact to be the predicted difference
+                adjustments.append(
+                    {
+                        "recommendation_id": rec["recommendation_id"],
+                        "phase": rec["phase"],
+                        # If we've made an adjustment, it will be negative
+                        "sap_adjustment": property_phase_impact["sap"] - predicted_difference,
+                    }
+                )
+                property_phase_impact["sap"] = predicted_difference
+                # Update the current phase values
+                current_phase_values["sap"] = previous_phase_values["sap"] + property_phase_impact["sap"]
 
         return property_phase_impact, current_phase_values, adjustments
 
@@ -963,7 +992,8 @@ class Recommendations:
                     previous_phase_values=previous_phase_values,
                     current_phase_values=current_phase_values,
                     adjustments=adjustments,
-                    property_instance=property_instance
+                    property_instance=property_instance,
+                    model_predicted_sap=phase_energy_efficiency_metrics["sap_change"],
                 )
 
                 # Insert this information into the recommendation.

recommendations/SecondaryHeating.py

@@ -18,6 +18,9 @@ class SecondaryHeating:
     def recommend(self, phase: int):
         # Reset
         self.recommendation = []
+        if self.property.epc_record.secondheat_description in ["None", None]:
+            # No secondary heating system, so no recommendation to remove it
+            return
 
         if self.property.data['number-habitable-rooms'] > self.property.data['number-heated-rooms']:
             n_rooms = self.property.data['number-habitable-rooms'] - self.property.data['number-heated-rooms']

recommendations/optimiser/optimiser_functions.py

@@ -79,14 +79,14 @@ def prepare_input_measures(
         # if recs[0]["type"] == "solar_pv":
         #     recs = [r for r in recs if ~r["has_battery"]]
 
-        # Only include measures with non-negative cost savings
+        # Only include measures with non-negative cost savings - we allow for a minor negative impact
         if eco_measures:
             recs_to_append = [
-                rec for rec in recs if (rec["energy_cost_savings"] >= 0) or (rec["measure_type"] in eco_measures)
+                rec for rec in recs if (rec["energy_cost_savings"] >= -10) or (rec["measure_type"] in eco_measures)
             ]
         else:
             recs_to_append = [
-                rec for rec in recs if (rec["energy_cost_savings"] >= 0)
+                rec for rec in recs if (rec["energy_cost_savings"] >= -10)
             ]
         if not recs_to_append:
             continue

recommendations/tests/test_recommendations.py

@@ -373,7 +373,7 @@ def test_filter_phase_adjustment(input_data, expected):
     "sap_impact, limit, expected",
     [
         (1.0, -4, True),  # positive SAP not allowed
-        (0.0, -4, True),  # zero not allowed
+        (0.0, -4, False),  # zero is allowed
         (-1.0, -4, False),  # valid range
         (-3.9, -4, False),  # valid range
         (-4.0, -4, False),  # exact lower bound allowed
@@ -1476,7 +1476,9 @@ def test_lighting_and_loft_adjustment_combined(property_instance, heat_demand_pr
 
     assert adjustments2 == [
         {'recommendation_id': '0_phase=0', 'phase': 0, 'sap_adjustment': np.float64(1.7)},
-        {'recommendation_id': '4_phase=2', 'phase': 2, 'sap_adjustment': np.float64(4.0)}
+        {'recommendation_id': '4_phase=2', 'phase': 2, 'sap_adjustment': np.float64(4.0)},
+        {'recommendation_id': '5_phase=3', 'phase': 3, 'sap_adjustment': np.float64(1.0)},
+        {'recommendation_id': '6_phase=3', 'phase': 3, 'sap_adjustment': np.float64(1.0000000000000027)}
     ]
 
 
@@ -1499,7 +1501,8 @@ def test_mechanical_ventilation_sap_floor(property_instance):
             previous_phase_values=previous_phase_values,
             current_phase_values=current_phase_values,
             adjustments=adjustments,
-            property_instance=property_instance
+            property_instance=property_instance,
+            model_predicted_sap=0
         )
     )
 
@@ -1538,7 +1541,8 @@ def test_mechanical_ventilation_no_floor_adjustment(property_instance):
             previous_phase_values=previous_phase_values,
             current_phase_values=current_phase_values,
             adjustments=adjustments,
-            property_instance=property_instance
+            property_instance=property_instance,
+            model_predicted_sap=0
         )
     )
 
@@ -1570,7 +1574,8 @@ def test_mechanical_ventilation_exactly_one_no_adjustment(property_instance):
             previous_phase_values=previous_phase_values,
             current_phase_values=current_phase_values,
             adjustments=adjustments,
-            property_instance=property_instance
+            property_instance=property_instance,
+            model_predicted_sap=0
         )
     )
 
@@ -1578,3 +1583,182 @@ def test_mechanical_ventilation_exactly_one_no_adjustment(property_instance):
     assert updated_adjustments == []
     assert updated_current["sap"] == 1.0
     assert updated_impact["sap"] == -1.0
+
+
+def test_mechanical_ventilation_sap_zero_no_adjustment(property_instance):
+    # Test when SAP = 0
+    rec = {
+        "type": "mechanical_ventilation",
+        "recommendation_id": "mv_test",
+        "phase": 1,
+    }
+
+    previous_phase_values = {'phase': 0, 'representative': True, 'recommendation_id': '0_phase=0',
+                             'measure_type': 'flat_roof_insulation', 'sap': 68.0, 'carbon': np.float64(0.5),
+                             'heat_demand': np.float64(300.1), 'sap_prediction': np.float64(71.7)}
+    current_phase_values = {'sap': 68.0, 'carbon': np.float64(0.5), 'heat_demand': np.float64(307.0)}
+    property_phase_impact = {'sap': 0, 'carbon': 0, 'heat_demand': np.float64(-6.899999999999977)}
+    adjustments = []
+
+    updated_impact, updated_current, updated_adjustments = (
+        Recommendations._apply_measure_specific_rules(
+            rec=rec,
+            property_phase_impact=property_phase_impact,
+            previous_phase_values=previous_phase_values,
+            current_phase_values=current_phase_values,
+            adjustments=adjustments,
+            property_instance=property_instance,
+            model_predicted_sap=0
+        )
+    )
+
+    # SAP is already at 0 → no adjustment expected
+    assert updated_adjustments == []
+    assert updated_current["sap"] == 68.0
+    assert updated_impact["sap"] == 0
+
+
+def test_mv_valid_negative_no_adjustment(property_instance):
+    rec = {"type": "mechanical_ventilation", "recommendation_id": "mv", "phase": 1}
+
+    previous = {"sap": 70.0}
+    current = {"sap": 67.0}
+    impact = {"sap": -3.0, "carbon": 0, "heat_demand": 0}
+    adjustments = []
+
+    updated_impact, updated_current, updated_adjustments = (
+        Recommendations._apply_measure_specific_rules(
+            rec, impact, previous, current, adjustments, property_instance, 0
+        )
+    )
+
+    assert updated_adjustments == []
+    assert updated_current["sap"] == 67.0
+    assert updated_impact["sap"] == -3.0
+
+
+def test_mv_zero_impact_allowed(property_instance):
+    rec = {"type": "mechanical_ventilation", "recommendation_id": "mv", "phase": 1}
+
+    previous = {"sap": 68.0, "sap_prediction": 71.7}
+    current = {"sap": 68.0}
+    impact = {"sap": 0.0, "carbon": 0, "heat_demand": 0}
+    adjustments = []
+
+    updated_impact, updated_current, updated_adjustments = (
+        Recommendations._apply_measure_specific_rules(
+            rec, impact, previous, current, adjustments, property_instance, 0
+        )
+    )
+
+    assert updated_adjustments == []
+    assert updated_current["sap"] == 68.0
+    assert updated_impact["sap"] == 0.0
+
+
+def test_mv_positive_impact_corrected(property_instance):
+    rec = {"type": "mechanical_ventilation", "recommendation_id": "mv", "phase": 1}
+
+    previous = {"sap": 60.0}
+    current = {"sap": 61.0}
+    impact = {"sap": 1.0, "carbon": 0, "heat_demand": 0}
+    adjustments = []
+
+    updated_impact, updated_current, updated_adjustments = (
+        Recommendations._apply_measure_specific_rules(
+            rec, impact, previous, current, adjustments, property_instance, 0
+        )
+    )
+
+    assert len(updated_adjustments) == 1
+    assert updated_current["sap"] == previous["sap"] + updated_impact["sap"]
+    assert updated_impact["sap"] <= 0
+
+
+def test_mv_below_lower_bound_corrected(property_instance):
+    rec = {"type": "mechanical_ventilation", "recommendation_id": "mv", "phase": 1}
+
+    previous = {"sap": 70.0}
+    current = {"sap": 64.0}
+    impact = {"sap": -6.0, "carbon": 0, "heat_demand": 0}
+    adjustments = []
+
+    updated_impact, updated_current, updated_adjustments = (
+        Recommendations._apply_measure_specific_rules(
+            rec, impact, previous, current, adjustments, property_instance, 0
+        )
+    )
+
+    assert len(updated_adjustments) == 1
+    assert updated_impact["sap"] >= -4
+
+
+def test_mv_floor_triggered(property_instance):
+    rec = {"type": "mechanical_ventilation", "recommendation_id": "mv", "phase": 1}
+
+    previous = {"sap": 2.0}
+    current = {"sap": 0.5}
+    impact = {"sap": -1.5, "carbon": 0, "heat_demand": 0}
+    adjustments = []
+
+    updated_impact, updated_current, updated_adjustments = (
+        Recommendations._apply_measure_specific_rules(
+            rec, impact, previous, current, adjustments, property_instance, 0
+        )
+    )
+
+    assert updated_current["sap"] == 1.0
+    assert updated_adjustments[0]["sap_adjustment"] > 0
+
+
+def test_mv_exactly_one_no_floor(property_instance):
+    rec = {"type": "mechanical_ventilation", "recommendation_id": "mv", "phase": 1}
+
+    previous = {"sap": 2.0}
+    current = {"sap": 1.0}
+    impact = {"sap": -1.0, "carbon": 0, "heat_demand": 0}
+    adjustments = []
+
+    updated_impact, updated_current, updated_adjustments = (
+        Recommendations._apply_measure_specific_rules(
+            rec, impact, previous, current, adjustments, property_instance, 0
+        )
+    )
+
+    assert updated_adjustments == []
+    assert updated_current["sap"] == 1.0
+
+
+def test_lighting_no_cap(property_instance):
+    rec = {"type": "low_energy_lighting", "recommendation_id": "led", "phase": 1,
+           "co2_equivalent_savings": 0}
+
+    previous = {"sap": 60.0, "carbon": 2.0}
+    current = {"sap": 61.0, "carbon": 2.0}
+    impact = {"sap": 1.0, "carbon": 0, "heat_demand": 0}
+    adjustments = []
+
+    updated_impact, updated_current, updated_adjustments = (
+        Recommendations._apply_measure_specific_rules(
+            rec, impact, previous, current, adjustments, property_instance, 0
+        )
+    )
+
+    assert updated_adjustments == []
+
+
+def test_filter_phase_adjustments():
+    example_adjustments = [
+        {'recommendation_id': '0_phase=0', 'phase': 0, 'sap_adjustment': np.float64(1.7)},
+        {'recommendation_id': '4_phase=2', 'phase': 2, 'sap_adjustment': np.float64(4.0)},
+        {'recommendation_id': '5_phase=3', 'phase': 3, 'sap_adjustment': np.float64(1.0)},
+        {'recommendation_id': '6_phase=3', 'phase': 3, 'sap_adjustment': np.float64(1.0000000000000027)}
+    ]
+
+    res = Recommendations._filter_phase_adjustment(example_adjustments)
+
+    assert res == [
+        {'recommendation_id': '0_phase=0', 'phase': 0, 'sap_adjustment': np.float64(1.7)},
+        {'recommendation_id': '4_phase=2', 'phase': 2, 'sap_adjustment': np.float64(4.0)},
+        {'recommendation_id': '6_phase=3', 'phase': 3, 'sap_adjustment': np.float64(1.0000000000000027)}
+    ]