diff --git a/backend/apis/GoogleSolarApi.py b/backend/apis/GoogleSolarApi.py
index 1354bbff..905d4975 100644
--- a/backend/apis/GoogleSolarApi.py
+++ b/backend/apis/GoogleSolarApi.py
@@ -17,10 +17,6 @@ logger = setup_logger()
 class GoogleSolarApi:
     NORTH_FACING_AZIMUTH_RANGE = (-30, 30)
 
-    # Conservative estimate of the proportion of electricity that will be consumed, whereas the rest will
-    # be exported
-    SOLAR_CONSUMPTION_PROPORTION = 0.5
-
     # These are variables, described in the documentation for cost analysis for non-us locations, seen here
     # https://developers.google.com/maps/documentation/solar/calculate-costs-non-us
     # We use the default figures that the API uses for US locations
diff --git a/backend/app/assumptions.py b/backend/app/assumptions.py
index d2b7b75a..ffc186df 100644
--- a/backend/app/assumptions.py
+++ b/backend/app/assumptions.py
@@ -2,3 +2,7 @@
 # which is often quoted as a sensible efficiency range for air source heat pumps.
 PESSIMISTIC_ASHPY_EFFICIENCY = 200
 AVERAGE_ASHP_EFFICIENCY = 300
+
+# Conservative estimate of the proportion of electricity that will be consumed, whereas the rest will
+# be exported
+SOLAR_CONSUMPTION_PROPORTION = 0.5
diff --git a/backend/app/plan/router.py b/backend/app/plan/router.py
index 6f1d9935..48a78e15 100644
--- a/backend/app/plan/router.py
+++ b/backend/app/plan/router.py
@@ -655,7 +655,7 @@ async def trigger_plan(body: PlanTriggerRequest):
                     roof_area=solar_api_client.roof_area
                 )
 
-        logger.info("Getting components and epc recommendations")
+        logger.info("Identifying property recommendations")
         recommendations = {}
         recommendations_scoring_data = []
         representative_recommendations = {}
@@ -742,7 +742,7 @@ async def trigger_plan(body: PlanTriggerRequest):
         #      cylinder jacket), we should add these to the recommendations as default
 
         for p in input_properties:
-            if not recommendations[p.id]:
+            if not recommendations.get(p.id):
                 continue
             input_measures = prepare_input_measures(recommendations[p.id], body.goal)
 
diff --git a/backend/ml_models/AnnualBillSavings.py b/backend/ml_models/AnnualBillSavings.py
index d018dedb..f791599a 100644
--- a/backend/ml_models/AnnualBillSavings.py
+++ b/backend/ml_models/AnnualBillSavings.py
@@ -1,6 +1,6 @@
 import numpy as np
 import pandas as pd
-from backend.apis.GoogleSolarApi import GoogleSolarApi
+import backend.app.assumptions as assumptions
 
 QUARTERLY_ENERGY_PRICES = [
     # 2024 Q1
@@ -283,7 +283,7 @@ class AnnualBillSavings:
 
         if fuel == "Natural Gas + Solar Thermal":
             # The solar thermal covers a % of the heating kwh, so we need to adjust the cost
-            return (kwh / cop) * GoogleSolarApi.SOLAR_CONSUMPTION_PROPORTION * cls.GAS_PRICE_CAP
+            return (kwh / cop) * assumptions.SOLAR_CONSUMPTION_PROPORTION * cls.GAS_PRICE_CAP
 
         if fuel == "Oil":
             price_data = cls.FUEL_DATA[cls.FUEL_DATA["Fuel"] == "Kerosene"].squeeze()
diff --git a/recommendations/Recommendations.py b/recommendations/Recommendations.py
index d8d0ec08..af55031f 100644
--- a/recommendations/Recommendations.py
+++ b/recommendations/Recommendations.py
@@ -39,6 +39,7 @@ DESCRIPTIONS_TO_FUEL_TYPES = {
     "No system present: electric heaters assumed": {"fuel": "Electricity", "cop": 1},
     "Electric instantaneous at point of use": {"fuel": "Electricity", "cop": 1},
     "Boiler and radiators, oil": {"fuel": "Oil", "cop": 0.9},
+    "Electric storage heaters, Electric storage heaters": {"fuel": "Electricity", "cop": 1},
 }
 STARTING_DUMMY_ID_VALUE = -9999