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estimate_new_consumption debugging

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Khalim Conn-Kowlessar 2024-08-19 19:06:45 +01:00
parent 6bd66d83f5
commit f13ce39bed
3 changed files with 9 additions and 9 deletions
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2
backend/Property.py
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@ -1287,7 +1287,7 @@ class Property:
# If the property currently has an electric boiler, it will still benefit from the ASHP efficiency gain
remap_fuel_sources = [
"Natural Gas", "LPG", "Wood Logs", "Oil", "Electricity", "Coal", "Smokeless Fuel",
"Natural Gas + Solar Thermal", "Anthracite", "Wood Pellets",
"Natural Gas + Solar Thermal", "Anthracite", "Wood Pellets", "LPG + Solar Thermal"
]
heating_energy_source = self.heating_energy_source

8
backend/app/plan/router.py
View file

@ -518,14 +518,6 @@ async def trigger_plan(body: PlanTriggerRequest):
# TODO: For simple properties, we should do a comparison/check between the solar API's roof area and the
# basic estimate of roof area
# TODO: Debug this
for p in input_properties:
if p.uprn in [10002634631, 100031601798, 10009574286, 10007366417]:
continue
p.estimate_electrical_consumption(
assumed_ashp_efficiency=assumptions.AVERAGE_ASHP_EFFICIENCY, exclusions=body.exclusions
)
building_ids = [
{
"building_id": p.building_id,

8
backend/ml_models/AnnualBillSavings.py
View file

@ -289,6 +289,14 @@ class AnnualBillSavings:
# The solar thermal covers a % of the heating kwh, so we need to adjust the cost
return (kwh / cop) * assumptions.SOLAR_CONSUMPTION_PROPORTION * cls.ELECTRICITY_PRICE_CAP
if fuel == "LPG + Solar Thermal":
# The solar thermal covers a % of the heating kwh, so we need to adjust the cost
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 * assumptions.SOLAR_CONSUMPTION_PROPORTION
if fuel == "Oil":
price_data = cls.FUEL_DATA[cls.FUEL_DATA["Fuel"] == "Kerosene"].squeeze()
cost_per_kwh = cls.cost_per_kwh(