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handling more fuel types

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Khalim Conn-Kowlessar 2025-11-14 23:43:07 +00:00
parent 1458cff95c
commit 4d6a73fd7b
3 changed files with 7 additions and 2 deletions
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3
backend/app/assumptions.py
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@ -82,6 +82,9 @@ DESCRIPTIONS_TO_FUEL_TYPES = {
"Ground source heat pump, warm air, electric": {"fuel": "Electricity", "cop": AVERAGE_ASHP_EFFICIENCY / 100}, "Ground source heat pump, warm air, electric": {"fuel": "Electricity", "cop": AVERAGE_ASHP_EFFICIENCY / 100},
"Room heaters, mains gas, Electric storage heaters": {"fuel": "Natural Gas", "cop": 0.85}, "Room heaters, mains gas, Electric storage heaters": {"fuel": "Natural Gas", "cop": 0.85},
"Water source heat pump, radiators, electric": {"fuel": "Electricity", "cop": AVERAGE_ASHP_EFFICIENCY / 100}, "Water source heat pump, radiators, electric": {"fuel": "Electricity", "cop": AVERAGE_ASHP_EFFICIENCY / 100},
"Air source heat pump, Systems with radiators, electric": {"fuel": "Electricity",
"cop": AVERAGE_ASHP_EFFICIENCY / 100},
"Ground source heat pump, underfloor, electric": {"fuel": "Electricity", "cop": AVERAGE_ASHP_EFFICIENCY / 100},
} }
# These are the measure types where if there is a ventilation recommendation, we force the inclusion of it # These are the measure types where if there is a ventilation recommendation, we force the inclusion of it

2
backend/ml_models/AnnualBillSavings.py
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@ -286,7 +286,7 @@ class AnnualBillSavings:
# The solar thermal covers a % of the heating kwh, so we need to adjust the cost # The solar thermal covers a % of the heating kwh, so we need to adjust the cost
return (kwh / cop) * assumptions.SOLAR_CONSUMPTION_PROPORTION * cls.GAS_PRICE_CAP return (kwh / cop) * assumptions.SOLAR_CONSUMPTION_PROPORTION * cls.GAS_PRICE_CAP
if fuel == "Electricity + Solar Thermal": if fuel in ["Electricity + Solar Thermal", 'Unmapped + Solar Thermal']:
# The solar thermal covers a % of the heating kwh, so we need to adjust the cost # 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 return (kwh / cop) * assumptions.SOLAR_CONSUMPTION_PROPORTION * cls.ELECTRICITY_PRICE_CAP

4
backend/tests/test_integration.py
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@ -90,8 +90,10 @@ costs_by_floor_area = costs_by_floor_area.groupby("current-energy-efficiency")[
["lighting-cost-current_scaled", "heating-cost-current_scaled", "hot-water-cost-current_scaled"] ["lighting-cost-current_scaled", "heating-cost-current_scaled", "hot-water-cost-current_scaled"]
].mean().reset_index() ].mean().reset_index()
epc_data = epc_data[~pd.isnull(epc_data["UPRN"])]
sample_epc_data = epc_data[pd.to_datetime(epc_data["LODGEMENT_DATE"]) >= "2015-01-01"].drop_duplicates("UPRN").sample( sample_epc_data = epc_data[pd.to_datetime(epc_data["LODGEMENT_DATE"]) >= "2015-01-01"].drop_duplicates("UPRN").sample(
3000).reset_index(drop=True) 5000).reset_index(drop=True)
# TODO: In Property find_energy_sources, sort out biomass community heating - what fuel type # TODO: In Property find_energy_sources, sort out biomass community heating - what fuel type
# TODO: We might be able to remove find_energy_sources entirely and remove estimate_electrical_consumption. It's used # TODO: We might be able to remove find_energy_sources entirely and remove estimate_electrical_consumption. It's used