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Khalim Conn-Kowlessar 2024-04-16 03:05:26 +01:00
parent cc6277c191
commit 83d472a710
3 changed files with 30 additions and 6 deletions
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15
backend/app/db/models/portfolio.py
View file

@ -45,6 +45,21 @@ class Portfolio(Base):
labour_days = Column(Float) labour_days = Column(Float)
created_at = Column(DateTime, nullable=False, default=datetime.datetime.now(pytz.utc)) created_at = Column(DateTime, nullable=False, default=datetime.datetime.now(pytz.utc))
updated_at = Column(DateTime, nullable=False, default=datetime.datetime.now(pytz.utc)) updated_at = Column(DateTime, nullable=False, default=datetime.datetime.now(pytz.utc))
# Aggregations for summary
epc_breakdown_pre_retrofit = Column(Text)
epc_breakdown_post_retrofit = Column(Text)
n_units_to_retrofit = Column(Integer)
co2_per_unit_pre_retrofit = Column(Text)
co2_per_unit_post_retrofit = Column(Text)
energy_bill_per_unit_pre_retrofit = Column(Text)
energy_bill_per_unit_post_retrofit = Column(Text)
energy_consumption_per_unit_pre_retrofit = Column(Text)
energy_consumption_per_unit_post_retrofit = Column(Text)
valuation_improvement_per_unit = Column(Text)
cost_per_unit = Column(Text)
cost_per_co2_saved = Column(Text)
cost_per_sap_point = Column(Text)
valuation_return_on_investment = Column(Text)
class PropertyCreationStatus(enum.Enum): class PropertyCreationStatus(enum.Enum):

18
backend/app/plan/router.py
View file

@ -99,10 +99,9 @@ def extract_portfolio_aggregation_data(
agg_data = [] agg_data = []
for p in input_properties: for p in input_properties:
# Get the recommendations for the property # Get the recommendations for the property - we include all properties, even ones without recommendations
property_recommendations = recommendations.get(p.id, []) property_recommendations = recommendations.get(p.id, [])
if not property_recommendations:
continue
# Get just the default recommendations # Get just the default recommendations
default_recommendations = [r for r in property_recommendations if r["default"]] default_recommendations = [r for r in property_recommendations if r["default"]]
@ -113,11 +112,16 @@ def extract_portfolio_aggregation_data(
post_retrofit_co2 = pre_retrofit_co2 - carbon_savings post_retrofit_co2 = pre_retrofit_co2 - carbon_savings
pre_retrofit_energy_bill = p.current_energy_bill pre_retrofit_energy_bill = p.current_energy_bill
post_retrofit_energy_bill = p.expected_energy_bill post_retrofit_energy_bill = p.current_energy_bill - sum(
[r["energy_cost_savings"] for r in default_recommendations]
)
pre_retrofit_energy_consumption = p.current_adjusted_energy pre_retrofit_energy_consumption = p.current_adjusted_energy
post_retrofit_energy_consumption = p.expected_adjusted_energy post_retrofit_energy_consumption = p.current_adjusted_energy - sum(
[r["adjusted_heat_demand"] for r in default_recommendations]
)
# Add up energy savings
cost = sum([r["total"] for r in default_recommendations]) cost = sum([r["total"] for r in default_recommendations])
sap_point_improvement = sum([r["sap_points"] for r in default_recommendations]) sap_point_improvement = sum([r["sap_points"] for r in default_recommendations])
@ -166,7 +170,9 @@ def extract_portfolio_aggregation_data(
"valuation_improvement_per_unit": format_money(valuation_improvment_per_unit), "valuation_improvement_per_unit": format_money(valuation_improvment_per_unit),
"cost_per_unit": format_money(agg_data["cost"].mean()), "cost_per_unit": format_money(agg_data["cost"].mean()),
"cost_per_co2_saved": format_money(agg_data["cost"].sum() / total_carbon_saved), "cost_per_co2_saved": format_money(agg_data["cost"].sum() / total_carbon_saved),
"cost_per_sap_point": format_money(agg_data["cost"].sum() / total_sap_points) "cost_per_sap_point": format_money(agg_data["cost"].sum() / total_sap_points),
"valuation_return_on_investment": str(round(total_valuation_increase / agg_data["cost"].sum(), 2))
# TODO: Could we add 10yr carbon credits value?
} }
return aggregation_data return aggregation_data

3
recommendations/Recommendations.py
View file

@ -272,6 +272,8 @@ class Recommendations:
current_epc_rating=property_instance.data["current-energy-rating"], current_epc_rating=property_instance.data["current-energy-rating"],
) )
# TODO: This isn't quite right as this is based on EVERY possible measure, not just the ones that are
# actually implemented
expected_adjusted_energy = AnnualBillSavings.adjust_energy_to_metered( expected_adjusted_energy = AnnualBillSavings.adjust_energy_to_metered(
epc_energy_consumption=expected_heat_demand, epc_energy_consumption=expected_heat_demand,
current_epc_rating=property_instance.data["current-energy-rating"], current_epc_rating=property_instance.data["current-energy-rating"],
@ -281,6 +283,7 @@ class Recommendations:
current_adjusted_energy - expected_adjusted_energy current_adjusted_energy - expected_adjusted_energy
) )
# TODO: We should determine if the home is gas & electricity or just electricity
current_energy_bill = AnnualBillSavings.calculate_annual_bill(current_adjusted_energy) current_energy_bill = AnnualBillSavings.calculate_annual_bill(current_adjusted_energy)
expected_energy_bill = AnnualBillSavings.calculate_annual_bill(expected_adjusted_energy) expected_energy_bill = AnnualBillSavings.calculate_annual_bill(expected_adjusted_energy)