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adjusting costs so they are based on 2024 figures
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Khalim Conn-Kowlessar
parent
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commit
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1 changed files with 76 additions and 39 deletions
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@ -643,6 +643,15 @@ class Property:
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https://www.sciencedirect.com/science/article/pii/S0378778823002542
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:return:
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"""
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# We should adjust the costs first and then calculate the energy consumption
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# These are the costs at the time that the EPC was created - we need a cost based on today's prices so
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# we do the following:
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# 1) Score the models to get kwh for heating and hot water
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# 2) Adjust the kwh values with the UCL paper
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# 3) Convert the kwh values to costs today using current prices
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#
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# For the moment, we'll just use the same cost for lighting, since the value is quite low
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scoring_df = pd.DataFrame([self.epc_record.prepared_epc])
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# Change columns from underscores to hyphens
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scoring_df.columns = [
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@ -651,30 +660,6 @@ class Property:
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for col in ["heating_kwh", "hot_water_kwh"]:
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scoring_df[col] = None
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# We should adjust the costs first and then calculate the energy consumption
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lighting_cost = float(self.data["lighting-cost-current"])
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heating_cost = float(self.data["heating-cost-current"])
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hot_water_cost = float(self.data["hot-water-cost-current"])
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adjusted_heating_cost = AnnualBillSavings.adjust_energy_cost_to_metered(
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epc_energy_cost=heating_cost,
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current_epc_rating=self.data["current-energy-rating"],
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)
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adjusted_hot_water_cost = AnnualBillSavings.adjust_energy_cost_to_metered(
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epc_energy_cost=hot_water_cost,
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current_epc_rating=self.data["current-energy-rating"],
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)
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adjusted_lighting_cost = AnnualBillSavings.adjust_energy_cost_to_metered(
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epc_energy_cost=lighting_cost,
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current_epc_rating=self.data["current-energy-rating"],
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)
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scoring_df["heating-cost-current"] = [adjusted_heating_cost]
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scoring_df["hot-water-cost-current"] = [adjusted_hot_water_cost]
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scoring_df["lighting-cost-current"] = [adjusted_lighting_cost]
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energy_consumption_client.data = None
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heating_prediction = energy_consumption_client.score_new_data(
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new_data=scoring_df, target="heating_kwh"
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@ -685,30 +670,82 @@ class Property:
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)[0]
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# We convert the lighting cost into kwh, just using the price cap
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lighting_kwh = float(adjusted_lighting_cost) / AnnualBillSavings.ELECTRICITY_PRICE_CAP
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lighting_kwh = float(self.data["lighting-cost-current"]) / AnnualBillSavings.ELECTRICITY_PRICE_CAP
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appliances_energy_use = AnnualBillSavings.estimate_appliances_energy_use(total_floor_area=self.floor_area)
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appliances_energy_cost = appliances_energy_use * AnnualBillSavings.ELECTRICITY_PRICE_CAP
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appliances_kwh = AnnualBillSavings.estimate_appliances_energy_use(total_floor_area=self.floor_area)
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total_energy_consumption = heating_prediction + hot_water_prediction + lighting_kwh + appliances_energy_use
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self.current_adjusted_energy = AnnualBillSavings.adjust_energy_to_metered(
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epc_energy_consumption=total_energy_consumption,
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adjusted_heating_kwh = AnnualBillSavings.adjust_energy_cost_to_metered(
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epc_energy_cost=heating_prediction,
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current_epc_rating=self.data["current-energy-rating"],
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)
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adjusted_hot_water_kwh = AnnualBillSavings.adjust_energy_cost_to_metered(
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epc_energy_cost=hot_water_prediction,
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current_epc_rating=self.data["current-energy-rating"],
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)
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adjusted_lighting_kwh = AnnualBillSavings.adjust_energy_cost_to_metered(
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epc_energy_cost=lighting_kwh,
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current_epc_rating=self.data["current-energy-rating"],
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)
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adjusted_applicances_kwh = AnnualBillSavings.adjust_energy_cost_to_metered(
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epc_energy_cost=appliances_kwh,
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current_epc_rating=self.data["current-energy-rating"],
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)
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# Convert to cost
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if self.heating_energy_source == "Electricity":
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adjusted_heating_cost = adjusted_heating_kwh * AnnualBillSavings.ELECTRICITY_PRICE_CAP
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elif self.heating_energy_source == "Natural Gas":
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adjusted_heating_cost = adjusted_heating_kwh * AnnualBillSavings.GAS_PRICE_CAP
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else:
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raise NotImplementedError("Not implemented cost for this fuel type")
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if self.hot_water_energy_source == "Electricity":
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adjusted_hot_water_cost = adjusted_hot_water_kwh * AnnualBillSavings.ELECTRICITY_PRICE_CAP
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elif self.hot_water_energy_source == "Natural Gas":
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adjusted_hot_water_cost = adjusted_hot_water_kwh * AnnualBillSavings.GAS_PRICE_CAP
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else:
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raise NotImplementedError("Not implemented cost for this fuel type")
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adjusted_lighting_cost = adjusted_lighting_kwh * AnnualBillSavings.ELECTRICITY_PRICE_CAP
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adjusted_appliances_cost = adjusted_applicances_kwh * AnnualBillSavings.ELECTRICITY_PRICE_CAP
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# Sum up the adjusted kwh figures
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self.current_adjusted_energy = (
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adjusted_heating_kwh + adjusted_hot_water_kwh + adjusted_lighting_kwh + adjusted_applicances_kwh
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)
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self.energy_cost_estimates = {
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"heating": adjusted_heating_cost,
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"hot_water": adjusted_hot_water_cost,
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"lighting": adjusted_lighting_cost,
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"appliances": appliances_energy_cost
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"adjusted": {
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"heating": adjusted_heating_cost,
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"hot_water": adjusted_hot_water_cost,
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"lighting": adjusted_lighting_cost,
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"appliances": adjusted_appliances_cost
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},
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"original": {
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"heating": float(self.data["heating-cost-current"]),
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"hot_water": float(self.data["hot-water-cost-current"]),
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"lighting": float(self.data["lighting-cost-current"]),
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"appliances": appliances_kwh
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}
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}
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self.energy_consumption_estimates = {
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"heating": heating_prediction,
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"hot_water": hot_water_prediction,
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"lighting": lighting_kwh,
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"appliances": appliances_energy_use
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"adjusted": {
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"heating": adjusted_heating_kwh,
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"hot_water": adjusted_hot_water_kwh,
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"lighting": adjusted_lighting_kwh,
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"appliances": adjusted_applicances_kwh
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},
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"original": {
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"heating": heating_prediction,
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"hot_water": hot_water_prediction,
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"lighting": lighting_kwh,
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"appliances": appliances_kwh
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}
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}
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self.expected_energy_bill = (
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