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updating costing methodology for new installer costs

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This commit is contained in:
Khalim Conn-Kowlessar 2024-09-23 15:55:07 +01:00
parent 503a19291d
commit 767d0d3132
3 changed files with 32 additions and 78 deletions
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18
backend/apis/GoogleSolarApi.py
View file

@ -42,6 +42,9 @@ class GoogleSolarApi:
# your area
installation_life_span = 20
MIN_UNIT_PANELS = 4 # Minimum number of panels we allow for a domestic building
MIN_BUILDING_PANELS = 10 # Minimum number of panels we allow for a block of flats
def __init__(self, api_key, max_retries=5):
"""
Initialize the GoogleSolarApi class with the provided API key and maximum retries.
@ -250,6 +253,9 @@ class GoogleSolarApi:
Optimise the solar panel configuration for the building.
:return:
"""
# If we look at the building level, we don't include any projects fewer than 10 panels, otherwise the
# minimum is 4
min_panels = self.MIN_BUILDING_PANELS if is_building else self.MIN_UNIT_PANELS
cost_instance = Costs(property_instance=property_instance) if property_instance is not None else None
@ -264,6 +270,10 @@ class GoogleSolarApi:
roi_summary = []
for segment in roof_segment_summaries:
if segment["panelsCount"] < min_panels:
continue
wattage = segment["panelsCount"] * self.insights_data["solarPotential"]["panelCapacityWatts"]
generated_dc_energy = segment["yearlyEnergyDcKwh"]
ratio = generated_dc_energy / wattage
@ -272,7 +282,9 @@ class GoogleSolarApi:
cost = MCS_SOLAR_PV_COST_DATA["average_cost_per_kwh"] * (wattage / 1000)
else:
cost = cost_instance.solar_pv(
wattage=wattage, has_battery=False
n_panels=segment["panelsCount"],
has_battery=False,
n_floors=property_instance.number_of_floors,
)["total"]
roi_summary.append(
@ -330,10 +342,6 @@ class GoogleSolarApi:
# We can have duplicate configurations
panel_performance = panel_performance.drop_duplicates()
# If we look at the building level, we don't include any projects fewer than 10 panels, otherwise the
# minimum is 4
min_panels = 10 if is_building else 4
panel_performance = panel_performance[panel_performance["n_panels"] >= min_panels]
if panel_performance.empty:
self.panel_performance = pd.DataFrame(

77
recommendations/Costs.py
View file

@ -54,6 +54,8 @@ INSTALLER_SOLAR_COSTS = [
{'n_panels': 17, 'array_kwp': 7.0, 'cost': 5500.00, 'installer': 'CEG'},
{'n_panels': 18, 'array_kwp': 7.4, 'cost': 6021.00, 'installer': 'CEG'}
]
# This is the maximum number of panels that we have a cost from the installers for
INSTALLER_MAX_PANELS = 18
# CEG uses use Solshare as an inverter to provide solar PV to multiple flats. This costs £7500 for the inverter alone
# https://midsummerwholesale.co.uk/buy/solshare
@ -362,7 +364,7 @@ class Costs:
"labour_days": labour_days
}
def internal_wall_insulation(self, wall_area, material, non_insulation_materials):
def internal_wall_insulation(self, wall_area, material):
"""
Broadly speaking, the high level steps to an internal wall insulation job are the following:
@ -401,74 +403,25 @@ class Costs:
"labour_days": labour_days,
}
# Extract and check the different types of data we'll need
demolition_data = [x for x in non_insulation_materials if x["type"] == "iwi_wall_demolition"]
vapour_barrier_data = [x for x in non_insulation_materials if x["type"] == "iwi_vapour_barrier"]
redecoration_data = [x for x in non_insulation_materials if x["type"] == "iwi_redecoration"]
if not demolition_data:
raise ValueError("No data found for iwi_wall_demolition")
if (len(vapour_barrier_data) != 1) or (len(redecoration_data) != 3):
raise ValueError("Incorrect number of data entries for non-insulation materials")
# Break out the individual material costs
# Since we don't know the exact wall construction, we take an average for demolition costs, since
# the cost will depend on the type of wall construction
demolition_material_costs = np.mean([x["material_cost"] * wall_area for x in demolition_data])
insulation_material_costs = material["material_cost"] * wall_area
vapour_barrier_material_costs = vapour_barrier_data[0]["material_cost"] * wall_area
redecoration_material_costs = sum([x["material_cost"] * wall_area for x in redecoration_data])
demolition_plant_costs = np.mean([x["plant_cost"] * wall_area for x in demolition_data])
# Again for demolition, we average since we aren't sure which demolition process will be used
demolition_labour_costs = np.mean([x["labour_cost"] * wall_area for x in demolition_data])
insulation_labour_costs = material["labour_cost"] * wall_area
vapour_barrier_labour_costs = vapour_barrier_data[0]["labour_cost"] * wall_area
redecoration_labour_costs = sum([x["labour_cost"] * wall_area for x in redecoration_data])
labour_costs = (demolition_labour_costs + insulation_labour_costs + vapour_barrier_labour_costs +
redecoration_labour_costs)
labour_costs = labour_costs * self.labour_adjustment_factor
materials_costs = (demolition_material_costs + insulation_material_costs + vapour_barrier_material_costs +
redecoration_material_costs)
subtotal_before_profit = labour_costs + materials_costs + demolition_plant_costs
contingency_cost = subtotal_before_profit * self.IWI_CONTINGENCY
preliminaries_cost = subtotal_before_profit * self.PRELIMINARIES
profit_cost = subtotal_before_profit * self.PROFIT_MARGIN
subtotal_before_vat = subtotal_before_profit + contingency_cost + preliminaries_cost + profit_cost
vat_cost = subtotal_before_vat * self.VAT_RATE
total_cost = subtotal_before_vat + vat_cost
demolition_labour_hours = np.mean([x["labour_hours_per_unit"] * wall_area for x in demolition_data])
insulation_labour_hours = material["labour_hours_per_unit"] * wall_area
vapour_barrier_labour_hours = vapour_barrier_data[0]["labour_hours_per_unit"] * wall_area
redecoration_labour_hours = sum([x["labour_hours_per_unit"] * wall_area for x in redecoration_data])
labour_hours = (demolition_labour_hours + insulation_labour_hours + vapour_barrier_labour_hours +
redecoration_labour_hours)
total_including_vat = material["total_cost"] * wall_area
total_excluding_vat = total_including_vat / (1 + self.VAT_RATE)
vat_cost = total_including_vat - total_excluding_vat
# We estimate 1 weeks worth of work
labour_hours = 160
# To install internal wall insulation, a small to medium size project might be conducted by a team of 3-5 people
labour_days = (labour_hours / 8) / 4
return {
"total": total_cost,
"subtotal": subtotal_before_vat,
"total": total_including_vat,
"subtotal": total_excluding_vat,
"vat": vat_cost,
"contingency": contingency_cost,
"preliminaries": preliminaries_cost,
"material": materials_costs,
"profit": profit_cost,
"labour_hours": labour_hours,
"labour_days": labour_days,
"labour_cost": labour_costs
}
def suspended_floor_insulation(self, insulation_floor_area, material, non_insulation_materials):
@ -1088,7 +1041,15 @@ class Costs:
units
"""
system_cost = [c for c in INSTALLER_SOLAR_COSTS if c["n_panels"] == n_panels][0]["cost"]
if n_panels > INSTALLER_MAX_PANELS:
base_cost = [c for c in INSTALLER_SOLAR_COSTS if c["n_panels"] == INSTALLER_MAX_PANELS][0]["cost"]
cost_per_panel = [
c for c in INSTALLER_SOLAR_COSTS if c["n_panels"] == (INSTALLER_MAX_PANELS - 1)
][0]["cost"]
cost_per_panel = base_cost - cost_per_panel
system_cost = base_cost + (n_panels - INSTALLER_MAX_PANELS) * cost_per_panel
else:
system_cost = [c for c in INSTALLER_SOLAR_COSTS if c["n_panels"] == n_panels][0]["cost"]
total_cost = array_cost if array_cost is not None else system_cost

15
recommendations/WallRecommendations.py
View file

@ -106,23 +106,10 @@ class WallRecommendations(Definitions):
part for part in materials if part["type"] == "internal_wall_insulation"
]
self.internal_wall_non_insulation_materials = [
part
for part in materials
if part["type"]
in ["iwi_wall_demolition", "iwi_vapour_barrier", "iwi_redecoration"]
]
self.external_wall_insulation_materials = [
part for part in materials if part["type"] == "external_wall_insulation"
]
self.external_wall_non_insulation_materials = [
part
for part in materials
if part["type"] in ["ewi_wall_demolition", "ewi_wall_preparation", "ewi_wall_redecoration"]
]
def ewi_valid(self):
"""
This method check available data, to determine if a property is suitable for external wall insulation
@ -508,7 +495,6 @@ class WallRecommendations(Definitions):
cost_result = self.costs.internal_wall_insulation(
wall_area=self.property.insulation_wall_area,
material=material.to_dict(),
non_insulation_materials=non_insulation_materials,
)
already_installed = (
"internal_wall_insulation"
@ -617,7 +603,6 @@ class WallRecommendations(Definitions):
iwi_recommendations = self._find_insulation(
u_value=u_value,
insulation_materials=pd.DataFrame(self.internal_wall_insulation_materials),
non_insulation_materials=self.internal_wall_non_insulation_materials,
phase=phase,
)