adding fuel pricing table

backend/app/plan/router.py

@@ -343,6 +343,8 @@ def extract_propert_on_site_recommendations(config, already_installed, non_invas
         for rec in property_non_invasive_recommendations["recommendations"]:
             if isinstance(rec, str):
                 transformed.append({"type": rec, })
+            else:
+                transformed.append(rec)
 
         property_non_invasive_recommendations["recommendations"] = str(transformed)
 
@@ -720,6 +722,8 @@ async def trigger_plan(body: PlanTriggerRequest):
         )
 
         # We now insert kwh estimates and costs into the recommendations
+        # TODO: We should join the methodology which maps the heating and hot water descriptions to the fuel types in
+        #       Recommendations, but also the Property class
         for property_id in recommendations.keys():
             property_recommendations = recommendations[property_id]
             property_instance = [p for p in input_properties if p.id == property_id][0]

backend/ml_models/AnnualBillSavings.py

@@ -1,4 +1,5 @@
 import numpy as np
+import pandas as pd
 
 QUARTERLY_ENERGY_PRICES = [
     # 2024 Q1
@@ -40,6 +41,53 @@ class AnnualBillSavings:
     DAILY_STANDARD_CHARGE_GAS = 0.3143
     DAILY_STANDARD_CHARGE_ELECTRICITY = 0.601
 
+    # Based on https://www.nottenergy.com/advice-and-tools/project-energy-cost-comparison
+    # For July 2024. These quotes are based on the east midlands region, so we
+    FUEL_DATA = pd.DataFrame([
+        {"Fuel": "Electricity Standard", "Price (p)": 28.58, "Unit": "kWh", "Boiler Efficiency (%)": 100,
+         "Energy Content, Net Calorific value (kWh/unit)": 1.00, "Price per kWh (p) (inc boiler efficiency)": 28.58,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.275},
+        {"Fuel": "Mains Gas Standard", "Price (p)": 6.31, "Unit": "kWh", "Boiler Efficiency (%)": 90,
+         "Energy Content, Net Calorific value (kWh/unit)": 1.00, "Price per kWh (p) (inc boiler efficiency)": 7.01,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.213},
+        {"Fuel": "Kerosene", "Price (p)": 62.49, "Unit": "Litre", "Boiler Efficiency (%)": 90,
+         "Energy Content, Net Calorific value (kWh/unit)": 9.79, "Price per kWh (p) (inc boiler efficiency)": 7.09,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.298},
+        {"Fuel": "Gas oil", "Price (p)": 94.50, "Unit": "Litre", "Boiler Efficiency (%)": 90,
+         "Energy Content, Net Calorific value (kWh/unit)": 9.96, "Price per kWh (p) (inc boiler efficiency)": 10.54,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.316},
+        {"Fuel": "LPG", "Price (p)": 55.00, "Unit": "Litre", "Boiler Efficiency (%)": 90,
+         "Energy Content, Net Calorific value (kWh/unit)": 6.78, "Price per kWh (p) (inc boiler efficiency)": 9.01,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.240},
+        {"Fuel": "Butane", "Price (p)": 216.58, "Unit": "Litre", "Boiler Efficiency (%)": 90,
+         "Energy Content, Net Calorific value (kWh/unit)": 6.64, "Price per kWh (p) (inc boiler efficiency)": 36.24,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.248},
+        {"Fuel": "Propane", "Price (p)": 157.67, "Unit": "Litre", "Boiler Efficiency (%)": 90,
+         "Energy Content, Net Calorific value (kWh/unit)": 7.22, "Price per kWh (p) (inc boiler efficiency)": 24.25,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.239},
+        {"Fuel": "Kiln Dried (logs)", "Price (p)": 36.52, "Unit": "kg", "Boiler Efficiency (%)": 85,
+         "Energy Content, Net Calorific value (kWh/unit)": 4.09, "Price per kWh (p) (inc boiler efficiency)": 10.51,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.024},
+        {"Fuel": "Pellets (Bagged)", "Price (p)": 39.62, "Unit": "kg", "Boiler Efficiency (%)": 90,
+         "Energy Content, Net Calorific value (kWh/unit)": 4.80, "Price per kWh (p) (inc boiler efficiency)": 9.17,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.049},
+        {"Fuel": "Pellets (Blown bulk)", "Price (p)": 33.92, "Unit": "kg", "Boiler Efficiency (%)": 90,
+         "Energy Content, Net Calorific value (kWh/unit)": 4.80, "Price per kWh (p) (inc boiler efficiency)": 7.85,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.049},
+        {"Fuel": "Smokeless fuel", "Price (p)": 67.26, "Unit": "kg", "Boiler Efficiency (%)": 75,
+         "Energy Content, Net Calorific value (kWh/unit)": 6.70, "Price per kWh (p) (inc boiler efficiency)": 13.38,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.404},
+        {"Fuel": "Coal", "Price (p)": 48.50, "Unit": "kg", "Boiler Efficiency (%)": 75,
+         "Energy Content, Net Calorific value (kWh/unit)": 7.95, "Price per kWh (p) (inc boiler efficiency)": 8.13,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.404},
+        {"Fuel": "GSHP", "Price (p)": 28.58, "Unit": "kWh", "Boiler Efficiency (%)": 350,
+         "Energy Content, Net Calorific value (kWh/unit)": 1.00, "Price per kWh (p) (inc boiler efficiency)": 8.17,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.079},
+        {"Fuel": "ASHP", "Price (p)": 28.58, "Unit": "kWh", "Boiler Efficiency (%)": 294,
+         "Energy Content, Net Calorific value (kWh/unit)": 1.00, "Price per kWh (p) (inc boiler efficiency)": 9.72,
+         "CO2eq emission factor kgCO2eq/kWh (Gross CV)": 0.094}
+    ])
+
     EPC_BANDS = ["G", "F", "E", "D", "C", "B", "A"]
 
     @classmethod
@@ -200,6 +248,15 @@ class AnnualBillSavings:
 
         return cls.EPC_BANDS[expected_index - 1]
 
+    @staticmethod
+    def cost_per_kwh(price_per_unit, energy_content_per_unit):
+        """
+        Calculate the cost of fuel per kWh given the price per unit in GBP and the energy content per unit in kWh.
+        """
+        cost_per_kwh = price_per_unit / energy_content_per_unit
+        # Tgis data is returned in pennies so we convert to pounds
+        return cost_per_kwh / 100
+
     @classmethod
     def calculate_recommendation_fuel_cost(cls, kwh, fuel, cop):
         if fuel == "Electricity":
@@ -207,3 +264,22 @@ class AnnualBillSavings:
 
         if fuel == "Natural Gas":
             return (kwh / cop) * cls.GAS_PRICE_CAP
+
+        if fuel == "LPG":
+            # Get the cost per kwh
+            price_data = cls.FUEL_DATA[cls.FUEL_DATA["Fuel"] == "LPG"].squeeze()
+            cost_per_kwh = cls.cost_per_kwh(
+                price_data["Price (p)"], price_data["Energy Content, Net Calorific value (kWh/unit)"]
+            )
+
+            return (kwh / cop) * cost_per_kwh
+
+        if fuel == "Wood":
+            price_data = cls.FUEL_DATA[cls.FUEL_DATA["Fuel"] == "Pellets (Bagged)"].squeeze()
+            cost_per_kwh = cls.cost_per_kwh(
+                price_data["Price (p)"], price_data["Energy Content, Net Calorific value (kWh/unit)"]
+            )
+
+            return (kwh / cop) * cost_per_kwh
+
+        raise Exception("Fuel not recognised")

recommendations/Recommendations.py

@@ -27,6 +27,8 @@ DESCRIPTIONS_TO_FUEL_TYPES = {
     "Room heaters, electric": {"fuel": 'Electricity', "cop": 1},
     "Electric immersion, standard tariff": {"fuel": 'Electricity', "cop": 1},
     "Portable electric heaters assumed for most rooms": {"fuel": 'Electricity', "cop": 1},
+    "Boiler and radiators, LPG": {"fuel": 'LPG', "cop": 0.9},
+    "Room heaters, dual fuel (mineral and wood)": {"fuel": 'Wood', "cop": 1},
 }
 STARTING_DUMMY_ID_VALUE = -9999
 
@@ -516,7 +518,7 @@ class Recommendations:
         mapped = DESCRIPTIONS_TO_FUEL_TYPES[heating_description]
         heating_fuel = mapped["fuel"]
 
-        if hotwater_description == "From main system":
+        if hotwater_description in ["From main system", "From main system, no cylinder thermostat"]:
             return {
                 "heating_fuel_type": heating_fuel, "hotwater_fuel_type": heating_fuel,
                 "heating_cop": mapped["cop"], "hotwater_cop": mapped["cop"]