junte/Model
1
0
Fork 0
mirror of https://github.com/Hestia-Homes/Model.git synced 2026-06-08 11:17:27 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions
Model/recommendations/Costs.py
Khalim Conn-Kowlessar 4ae439ddd3 fixed costs tests
2026-01-22 09:45:32 +00:00

922 lines
36 KiB
Python
Raw Blame History

import numpy as np
from recommendations.county_to_region import county_to_region_map
from utils.logger import setup_logger
from backend.ml_models.AnnualBillSavings import AnnualBillSavings
logger = setup_logger()
# This data comes from SPONs 2023
regional_labour_variations = [
{"Region": "Outer London", "Adjustment_Factor": 1.00},
{"Region": "Inner London", "Adjustment_Factor": 1.05},
{"Region": "South East England", "Adjustment_Factor": 0.96},
{"Region": "South West England", "Adjustment_Factor": 0.90},
{"Region": "East of England", "Adjustment_Factor": 0.93},
{"Region": "East Midlands", "Adjustment_Factor": 0.88},
{"Region": "West Midlands", "Adjustment_Factor": 0.87},
{"Region": "North East England", "Adjustment_Factor": 0.83},
{"Region": "North West England", "Adjustment_Factor": 0.88},
{"Region": "Yorkshire and the Humber", "Adjustment_Factor": 0.86},
{"Region": "Wales", "Adjustment_Factor": 0.88},
{"Region": "Scotland", "Adjustment_Factor": 0.88},
{"Region": "Northern Ireland", "Adjustment_Factor": 0.76}
]
# Installers are now working with 435 watt panels
PANEL_SIZE = 0.435
INSTALLER_SOLAR_COSTS = [
{'n_panels': 4, 'array_kwp': 4 * PANEL_SIZE, 'cost': 4089.25, 'installer': 'CEG'},
{'n_panels': 5, 'array_kwp': 5 * PANEL_SIZE, 'cost': 4242.48, 'installer': 'CEG'},
{'n_panels': 6, 'array_kwp': 6 * PANEL_SIZE, 'cost': 4395.71, 'installer': 'CEG'},
{'n_panels': 7, 'array_kwp': 7 * PANEL_SIZE, 'cost': 4548.94, 'installer': 'CEG'},
{'n_panels': 8, 'array_kwp': 8 * PANEL_SIZE, 'cost': 4702.17, 'installer': 'CEG'},
{'n_panels': 9, 'array_kwp': 9 * PANEL_SIZE, 'cost': 4855.41, 'installer': 'CEG'},
{'n_panels': 10, 'array_kwp': 10 * PANEL_SIZE, 'cost': 5010.95, 'installer': 'CEG'},
{'n_panels': 11, 'array_kwp': 11 * PANEL_SIZE, 'cost': 5166.49, 'installer': 'CEG'},
{'n_panels': 12, 'array_kwp': 12 * PANEL_SIZE, 'cost': 5322.04, 'installer': 'CEG'},
{'n_panels': 13, 'array_kwp': 13 * PANEL_SIZE, 'cost': 5657.6, 'installer': 'CEG'},
{'n_panels': 14, 'array_kwp': 14 * PANEL_SIZE, 'cost': 5993.16, 'installer': 'CEG'},
{'n_panels': 15, 'array_kwp': 15 * PANEL_SIZE, 'cost': 6328.71, 'installer': 'CEG'},
{'n_panels': 16, 'array_kwp': 16 * PANEL_SIZE, 'cost': 6483.33, 'installer': 'CEG'},
{'n_panels': 17, 'array_kwp': 17 * PANEL_SIZE, 'cost': 6637.95, 'installer': 'CEG'},
{'n_panels': 18, 'array_kwp': 18 * PANEL_SIZE, 'cost': 6792.57, 'installer': 'CEG'}
]
# These are costs we received from CRG, for pricing up air source heat pumps
# These are costs that we have been provided from CRG specifically for air source heat pumps
ASHP_SMALL_SYSTEM_COST = 8812.92 # 4.8 to 8.5, based on their pricing
ASHP_LARGE_SYSTEM_COST = 11053.25
ASHP_SECURITY = 455.00
ASHP_WALL_BRACKET = 574.17
ASHP_DISTRIBUTION_SYSTEM_COSTS = [
{"n_radiators": 4, "cost": 3380.00},
{"n_radiators": 5, "cost": 3607.50},
{"n_radiators": 6, "cost": 4116.67},
{"n_radiators": 7, "cost": 4647.50},
{"n_radiators": 8, "cost": 5200.00},
{"n_radiators": 9, "cost": 5730.83},
{"n_radiators": 10, "cost": 6283.33},
{"n_radiators": 11, "cost": 6857.50},
{"n_radiators": 12, "cost": 7431.67},
{"n_radiators": 13, "cost": 8016.67},
{"n_radiators": 14, "cost": 8612.50},
{"n_radiators": 15, "cost": 9219.17},
{"n_radiators": 16, "cost": 9804.17},
{"n_radiators": 17, "cost": 10389.17},
]
ASHP_CYLINDER_COSTS = [
{"capacity_l": 120, "cost": 3318.25},
{"capacity_l": 180, "cost": 3480.75},
{"capacity_l": 200, "cost": 3853.42},
{"capacity_l": 250, "cost": 3961.75},
]
# 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
INSTALLER_SOLAR_PV_INVERTER_COST = 7500
INSTALLER_SOLAR_PV_INVERTER_LABOUR_COST = 500 # Just a rough guess to labour costs
INSTALLER_SOLAR_BATTERY_COSTS = [
{'capacity_kwh': 5, 'description': 'Battery Add on', 'cost': 3769.89, 'installer': 'JJC'},
# {'capacity_kwh': 10, 'description': 'Battery Add on', 'cost': 4300.00, 'installer': 'CEG'},
# {'capacity_kwh': 5, 'description': 'Battery Retrofit existing system', 'cost': 4250.00, 'installer': 'CEG'},
# {'capacity_kwh': 10, 'description': 'Battery Retrofit Existing system', 'cost': 5950.00, 'installer': 'CEG'}
]
# This is based on https://www.checkatrade.com/blog/cost-guides/cost-smart-thermostat/
SMART_APPLIANCE_THERMOSTAT_COST = 400
PROGRAMMER_COST = 120
ROOM_THERMOSTAT_COST = 150
TRVS_COST = 35
BYPASS_COST = 350 # Based on desktop research for a complex installation
# https://www.checkatrade.com/blog/cost-guides/cost-install-water-shut-off-valve/
# Cost for TTZC
# Smart thermostat based on checkatrade https://www.checkatrade.com/blog/cost-guides/cost-smart-thermostat/
# Based on the Nest system
TTZC_SMART_THERMOSTAT_COST = 205
TTZC_SMART_THERMOSTAT_LABOUR_HOURS = 2
TTZC_ELECTRICIAN_HOURLY_RATE = 45
# Based on cost of a Nest temperature sensor
TTZC_ROOM_TEMPERATURE_SENSOR_COST = 50
TTZC_ROOM_TEMPERATURE_SENSOR_LABOUR_HOURS = 0.17 # (Assume ~ 10 mins install per sensor)
# Basedon an average cost of smart radiator values
TTZC_SMART_RADIATOR_VALUES = 50
TTZC_SMART_RADIATOR_VALUES_LABOUR_HOURS = 0.37 # (Assume ~ 15-30 mins install per valve)
# boiler prices based on
# This is the cost of a firs time central heating install from The Warm Front rate card
# These are exclusive of installation costs
CONDENSING_BOILER_COST = 2600
# Electric boiler prices base on
# https://www.greenmatch.co.uk/boilers/combi-boilers/electric-combi-boilers
# https://www.tlc-direct.co.uk/Products/ERMAC15.html
# The unit is a 15kw boiler, capable of outputting between 3kw and 15kw. Costs seem to be around £1800
ELECTRIC_BOILER_COSTS = 1800
# Assumes 1 hours to remove each heater (including re-decorating)
ROOM_HEATER_REMOVAL_COST = 25
ROOM_HEATER_REMOVAL_LABOUR_HOURS = 3
DOUBLE_RADIATOR_COST = 300
FLUE_COST = 600
PIPEWORK_COST = 750 # Min cost is £500
# Based on SCIS figures
# TODO: Add this to databse
CAVITY_EXTRACTION_COST = 25
class Costs:
"""
A class to calculate the costs associated with construction works,
specifically focusing on cavity wall insulation.
It includes contingency, preliminaries, profit margin, and VAT calculations.
As a sense check, there is a useful article from checkatrade on retrofitting and expected costs:
https://www.checkatrade.com/blog/cost-guides/retrofit-insulation-cost/
Another useful article for benchmarking the cost of floor insulation:
https://www.checkatrade.com/blog/cost-guides/floor-insulation-cost/
"""
# Contingency is a percentage of the total cost of the work and covers unforseen expenses
# We assume a conservative 10% contingency for all works which is a rate defined by SPONs
CONTINGENCY = 0.1
# Measure level contingency
CONTINGENCIES = {
"cavity_wall_insulation": 0.1,
"internal_wall_insulation": 0.26,
"external_wall_insulation": 0.26,
"loft_insulation": 0.1,
"solar_pv": 0.15,
"air_source_heat_pump": 0.25,
"flat_roof_insulation": 0.26,
"suspended_floor_insulation": 0.2,
"solid_floor_insulation": 0.26,
"low_energy_lighting": 0.26,
"high_heat_retention_storage_heaters": 0.1,
"windows_glazing": 0.15,
}
# Preliminaries are a percentage of the total cost of the work and covers the cost of site-specific costs
# such as site preparation, safety measures and project management. This rate can vary but we'll assume a 10%
# rate, on the total cost before VAT, as recommended by SPONs
PRELIMINARIES = 0.1
VAT_RATE = 0.2
PROFIT_MARGIN = 0.2
# Based on this greenmatch article, on average, a Sash window is around 50% more expensive than a casement window.
# Therefore, for a conservative cost estimate, and allowance for a more premium window type, we inflate the material
# cost of the windows to allow for a sash window type
# https://www.greenmatch.co.uk/windows/double-glazing/cost
SASH_WINDOW_INFLATION_FACTOR = 1.5
# Based on relative costs from SCIS
SECONDARY_GLAZING_SCALING_FACTOR = 0.85
def __init__(self, property_instance):
"""
Initializes the Costs class with a property instance.
:param property_instance: Instance of a Property class containing relevant details like wall area.
"""
if not hasattr(property_instance, 'insulation_wall_area'):
raise ValueError("Property instance must have an 'insulation_wall_area' attribute")
self.property = property_instance
self.regional_labour_variations = regional_labour_variations
self.region = county_to_region_map.get(self.property.data["county"], None)
if self.region is None:
# Try and grab using the local-authority-label
self.region = county_to_region_map.get(self.property.data["local-authority-label"], None)
if self.region is None:
# Try and get the region after converting the keys to lower
self.region = {
k.lower(): v for k, v in county_to_region_map.items()
}.get(self.property.data["local-authority-label"].lower(), None)
if self.region is None:
logger.warning("No region found for county %s, defaulting to South East England",
self.property.data["county"])
self.region = "South East England"
self.labour_adjustment_factor = [
x["Adjustment_Factor"] for x in self.regional_labour_variations if
x["Region"] == self.region
][0]
if not self.labour_adjustment_factor:
raise ValueError("Labour adjustment factor not found")
def cavity_wall_insulation(self, wall_area, material, is_extraction_and_refill=False):
"""
Calculates the total cost for cavity wall insulation based on material and labor costs,
including contingency, preliminaries, profit, and VAT.
Because of some limitations in the SPONs data, there are no materials that can be blown through a wall,
therefore we have adapted similar materials, basing our estimates on 75mm cavity slabs, and have halved the
labour time required. That is why we still price based on wall area despite volume actually being the correct
metric.
:return: A dictionary containing detailed cost breakdown.
"""
# CWI usually takes 1 day
labour_hours = 8
labour_days = 1
total_cost = material["total_cost"] * wall_area
return {
"total": total_cost,
"contingency": self.CONTINGENCIES["cavity_wall_insulation"] * total_cost,
"contingency_rate": self.CONTINGENCIES["cavity_wall_insulation"],
"labour_hours": labour_hours,
"labour_days": labour_days,
}
def loft_and_flat_insulation(self, floor_area, material):
"""
Calculates the total cost for loft/flat roof insulation based on material and labor costs,
including contingency, preliminaries, profit, and VAT.
:return: A dictionary containing detailed cost breakdown.
"""
total_cost = material["total_cost"] * floor_area
if material["type"] == "loft_insulation":
contingency_rate = self.CONTINGENCIES["loft_insulation"]
contingency = contingency_rate * total_cost
else:
contingency_rate = self.CONTINGENCIES["flat_roof_insulation"]
contingency = contingency_rate * total_cost
return {
"total": total_cost,
"contingency": contingency,
"contingency_rate": contingency_rate,
"labour_hours": 8,
"labour_days": 1,
}
def solid_wall_insulation(self, wall_area, material):
"""
Implements costing methodology now that we have direct quotes from installers.
:return:
"""
# if the material is based on an installer cost, we return the flat price
total_cost = material["total_cost"] * wall_area
if material["type"] == "internal_wall_insulation":
contingency_rate = self.CONTINGENCIES["internal_wall_insulation"]
else:
contingency_rate = self.CONTINGENCIES["external_wall_insulation"]
labour_hours = material["labour_hours_per_unit"] * wall_area
# 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,
"contingency": contingency_rate * total_cost,
"contingency_rate": contingency_rate,
"labour_hours": labour_hours,
"labour_days": labour_days,
}
def suspended_floor_insulation(self, insulation_floor_area, material):
"""
Given an installer cost for the works, produces an estimate for the cost of works.
Includes contingency
"""
# if the material is based on an installer cost, we return the flat price
total_cost = material["total_cost"] * insulation_floor_area
labour_hours = material["labour_hours_per_unit"] * insulation_floor_area
# To install suspended floor insulation, a small to medium size project might be conducted by a team of 3
# people
labour_days = (labour_hours / 8) / 3
return {
"total": total_cost,
"contingency": self.CONTINGENCIES["suspended_floor_insulation"] * total_cost,
"contingency_rate": self.CONTINGENCIES["suspended_floor_insulation"],
"labour_hours": labour_hours,
"labour_days": labour_days,
}
@staticmethod
def _estimate_number_of_days_for_solid_floor(insulation_floor_area: float) -> float:
"""
Estimate the number of labour days required to install solid floor insulation,
based on the floor area being treated.
This is a heuristic (rule-of-thumb) estimate designed for early-stage planning
and costing. It deliberately avoids strict linear scaling because real-world
construction work includes fixed overheads and efficiency gains.
Core assumptions:
- A typical solid floor insulation job covering ~45 m2 takes around 7 working days.
This is based on market guidance (e.g. Checkatrade).
- Very small jobs still require multiple days due to setup, preparation,
curing/drying time, and inspections — even if the area is small.
- Larger jobs take longer, but each additional square metre adds slightly less
time than the previous one, because crews become more efficient once work
is underway.
The estimate therefore:
- Scales with floor area
- Applies a minimum realistic duration
- Uses non-linear scaling to reflect economies of scale
:param insulation_floor_area: float - total floor area to be insulated
"""
# Reference case:
# A "typical" job (about half of a 90 m² house) takes ~7 days to complete
base_days = 7
base_area = 45 # m2 of solid floor insulated in the reference case
# Exponent < 1 means sub-linear scaling:
# doubling the area does NOT double the time, because setup costs
# and learning effects reduce the marginal effort per extra m²
labour_exponent = 0.85
# Minimum number of days for any solid floor job.
# Even small areas require mobilisation, preparation, installation,
# and finishing time, so jobs realistically won't complete faster than this.
min_days = 3
# Calculate estimated labour days:
# - Scale relative to the reference job
# - Apply sub-linear scaling for realism
# - Enforce a minimum duration so estimates are not unrealistically low
labour_days = max(
min_days,
base_days * (insulation_floor_area / base_area) ** labour_exponent
)
return labour_days
def solid_floor_insulation(self, insulation_floor_area, material):
"""
based on costing data from installers, produces an estimate for the cost of works. Returns contingency
:param insulation_floor_area: Area of the floor to be insulated
:param material: Selected insulation material
:return:
"""
total_cost = material["total_cost"] * insulation_floor_area
daily_labour_rate = 300 # Based on checkatrade
labour_days = self._estimate_number_of_days_for_solid_floor(insulation_floor_area)
labour_cost = labour_days * daily_labour_rate
total_cost = total_cost + labour_cost
total_cost = round(total_cost)
return {
"total": total_cost,
"contingency": self.CONTINGENCIES["solid_floor_insulation"] * total_cost,
"contingency_rate": self.CONTINGENCIES["solid_floor_insulation"],
"labour_hours": labour_days * 8,
"labour_days": labour_days,
}
def low_energy_lighting(self, number_of_lights, material):
"""
Calculates the total cost for low energy lighting based on material and labor costs,
including contingency, preliminaries, profit, and VAT.
:param number_of_lights: Int, number of light
:material: Dict, material data containing costs of fittings
"""
# If there are no lights fitted in the property, we increase the contingency in case there are potential wiring
# blockers
total_cost = material["total_cost"] * number_of_lights
labour_hours = 1
labour_days = (labour_hours / 8)
return {
"total": total_cost,
"contingency": self.CONTINGENCIES["low_energy_lighting"] * total_cost,
"contingency_rate": self.CONTINGENCIES["low_energy_lighting"],
"labour_hours": labour_hours,
"labour_days": labour_days,
}
def window_glazing(self, number_of_windows, material, is_secondary_glazing=False):
"""
Given an isntaller quote, produces an estimate for the cost of works.
"""
total_cost = material["total_cost"] * number_of_windows
labour_hours = material["labour_hours_per_unit"] * number_of_windows
# To install windows, a small to medium size project might be conducted by a team of 2-3 people
labour_days = (labour_hours / 8) / 2
return {
"total": total_cost,
"contingency": self.CONTINGENCIES["windows_glazing"] * total_cost,
"contingency_rate": self.CONTINGENCIES["windows_glazing"],
"labour_hours": labour_hours,
"labour_days": labour_days,
}
@classmethod
def solar_pv(
cls,
solar_product,
scaffolding_options,
n_floors
):
"""
"""
system_cost = solar_product["total_cost"]
if not solar_product["includes_scaffolding"]:
# We base this on the number of floors
scaffolding = [x["total_cost"] for x in scaffolding_options if x["size"] == n_floors]
if not scaffolding:
# If we have no options, handle this
if n_floors <= 3:
raise ValueError("No scaffolding options available for 3 or fewer floors")
# We take the largest scaffolding option available
scaffolding_cost = max([x["total_cost"] for x in scaffolding_options])
else:
scaffolding_cost = min(scaffolding)
system_cost += scaffolding_cost
# Labour hours are based on estimates from online research but an average team seems to consist of 3 people
# and most jobs take around 2 days. Assuming an 8 hour day for 3 people across 2 days, gives us 48 hours of
# labour
return {
"total": system_cost,
"subtotal": system_cost,
"contingency": system_cost * cls.CONTINGENCIES["solar_pv"],
"contingency_rate": cls.CONTINGENCIES["solar_pv"],
"vat": 0,
"labour_hours": 48,
"labour_days": 2,
}
def programmer_and_appliance_thermostat(self, has_programmer):
"""
Calculate the total cost of installing a programmer and appliance thermostat
If the property already has a programmer, then the only thing we need to calculate the cost for is the
appliance thermostat
"""
if has_programmer:
labour_hours = 2
total_cost = SMART_APPLIANCE_THERMOSTAT_COST
else:
labour_hours = 4
total_cost = SMART_APPLIANCE_THERMOSTAT_COST + PROGRAMMER_COST
subtotal_before_vat = total_cost / (1 + self.VAT_RATE)
vat = total_cost - subtotal_before_vat
# We estimate the cost of an appliance thermostat at £400, which is the upper end of the range
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCY,
"contingency_rate": self.CONTINGENCY,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": labour_hours,
"labour_days": 1,
}
def electric_room_heaters(self, number_heated_rooms):
"""
We base the estimates for the cost of electric room heaters on the cost per room as estimated by the
following article:
https://www.bestelectricradiators.co.uk/blog/cost-to-install-a-new-heating-system-uk/
:param number_heated_rooms: int, number of rooms to be heated
:return:
"""
total_cost = 500 * number_heated_rooms
subtotal_before_vat = total_cost / (1 + self.VAT_RATE)
vat = total_cost - subtotal_before_vat
# TODO: Rough estimate to be reviewed
labour_hours = 1 * number_heated_rooms
labour_days = np.ceil(labour_hours / 8)
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCY,
"contingency_rate": self.CONTINGENCY,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": labour_hours,
"labour_days": labour_days,
}
def high_heat_electric_storage_heaters(
self, number_heated_rooms: int,
needs_cylinder: bool,
product: dict | None = None
):
"""
We base the estimates for the cost of electric storage heaters on the cost per room as estimated by the
energy saving trust
https://energysavingtrust.org.uk/advice/electric-heating/
The cost is based on the number of heated rooms
:param number_heated_rooms: int, number of rooms to be heated
:param needs_cylinder: bool, whether the property needs a hot water cylinder
:param product: dict, product data containing costs of heaters
"""
if needs_cylinder:
# 1500 is the cost of a new hot water cylinder
total_cost = product["total_cost"] * number_heated_rooms + 1500
else:
# 500 is the cost of a dual immersion heater - a rough estimate
total_cost = product["total_cost"] * number_heated_rooms + 500
subtotal_before_vat = total_cost / (1 + self.VAT_RATE)
vat = total_cost - subtotal_before_vat
labour_hours = 3 * number_heated_rooms
labour_days = np.ceil(labour_hours / 8)
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCIES["high_heat_retention_storage_heaters"],
"contingency_rate": self.CONTINGENCIES["high_heat_retention_storage_heaters"],
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": labour_hours,
"labour_days": labour_days,
}
def celect_type_controls(self):
"""
Calculate the cost of installing Celect type controls
"""
# The £50 cost is a rough estimate based on internet research
total_cost = 50
subtotal_before_vat = total_cost / (1 + self.VAT_RATE)
vat = total_cost - subtotal_before_vat
# We estimate the labour hours to be 4
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCY,
"contingency_rate": self.CONTINGENCY,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": 4,
"labour_days": 1,
}
def cylinder_thermostat(self):
"""
Calculate the cost of installing a cylinder thermostat
"""
# The £200 cost is a rough estimate based on internet research
total_cost = 200
subtotal_before_vat = total_cost / (1 + self.VAT_RATE)
vat = total_cost - subtotal_before_vat
# We estimate the labour hours to be 2
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCY,
"contingency_rate": self.CONTINGENCY,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": 2,
"labour_days": 1,
}
def hot_water_tank_insulation(self):
"""
Calculate the cost of installing hot water tank insulation
"""
# The £50 cost is a rough estimate based on internet research
total_cost = 50
subtotal_before_vat = total_cost / (1 + self.VAT_RATE)
vat = total_cost - subtotal_before_vat
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCY,
"contingency_rate": self.CONTINGENCY,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": 0,
"labour_days": 0,
}
def roomstat_programmer_trvs(
self, number_heated_rooms, has_programmer, has_trvs, has_room_thermostat
):
"""
:return:
"""
total_cost = 0
labour_hours = 0
if not has_programmer:
total_cost += PROGRAMMER_COST
labour_hours += 1
if not has_trvs:
total_cost += TRVS_COST * number_heated_rooms
labour_hours += 0.25 * number_heated_rooms
if not has_room_thermostat:
total_cost += ROOM_THERMOSTAT_COST
labour_hours += 0.5
subtotal_before_vat = total_cost / (1 + self.VAT_RATE)
vat = total_cost - subtotal_before_vat
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCY,
"contingency_rate": self.CONTINGENCY,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": labour_hours,
"labour_days": 1,
}
def time_and_temperature_zone_control(self, number_heated_rooms):
# The product costs are inclusive of VAT
product_costs = (
TTZC_SMART_THERMOSTAT_COST +
TTZC_ROOM_TEMPERATURE_SENSOR_COST * number_heated_rooms +
TTZC_SMART_RADIATOR_VALUES * number_heated_rooms
)
labour_hours = (
TTZC_SMART_THERMOSTAT_LABOUR_HOURS +
TTZC_ROOM_TEMPERATURE_SENSOR_LABOUR_HOURS * number_heated_rooms +
TTZC_SMART_RADIATOR_VALUES_LABOUR_HOURS * number_heated_rooms
)
labour_costs = TTZC_ELECTRICIAN_HOURLY_RATE * labour_hours
# Add continency and preliminaries to the labour to account for the complexity of the job
labour_costs = labour_costs * (1 + self.CONTINGENCY + self.PRELIMINARIES)
vat = labour_costs * self.VAT_RATE
subtotal_before_vat = product_costs + labour_costs
total_cost = subtotal_before_vat + vat
labour_days = np.ceil(labour_hours / 8)
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCY,
"contingency_rate": self.CONTINGENCY,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": labour_hours,
"labour_days": labour_days,
}
def programmer_trvs_bypass(self, number_heated_rooms, has_programmer, has_trvs, has_bypass):
total_cost = 0
labour_hours = 0
if not has_programmer:
total_cost += PROGRAMMER_COST
labour_hours += 1
if not has_trvs:
total_cost += TRVS_COST * number_heated_rooms
labour_hours += 0.25 * number_heated_rooms
if not has_bypass:
total_cost += BYPASS_COST
labour_hours += 0.5
subtotal_before_vat = total_cost / (1 + self.VAT_RATE)
vat = total_cost - subtotal_before_vat
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCY,
"contingency_rate": self.CONTINGENCY,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": labour_hours,
"labour_days": 1,
}
def heater_removal(self, n_rooms):
"""
Estimates the costs of removal of heaters, including the redecoration costs of the space behind the heater
:return:
"""
removal_cost = ROOM_HEATER_REMOVAL_COST * n_rooms
removal_labour_hours = ROOM_HEATER_REMOVAL_LABOUR_HOURS * n_rooms
vat = removal_cost * self.VAT_RATE
subtotal_before_vat = removal_cost
total_cost = subtotal_before_vat + vat
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCY,
"contingency_rate": self.CONTINGENCY,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": removal_labour_hours,
"labour_days": np.ceil(removal_labour_hours / 8),
}
@staticmethod
def _estimate_n_radiators(number_habitable_rooms, total_floor_area, property_type, built_form):
# Base number of radiators: one per habitable room
base_radiators = number_habitable_rooms
# Additional radiators for non-habitable essential areas (e.g., kitchens, hallways)
additional_radiators = 3 # Initial assumption
# Adjust additional radiators based on property type
if property_type == 'Flat':
additional_radiators -= 1 # Flats may need fewer radiators due to less exposure
elif property_type in ['House', 'Bungalow', 'Maisonette']:
# Multiple floors in Maisonette may require additional heating points
additional_radiators += 2 # Houses and bungalows might need more due to greater exposure
else:
raise Exception("Invalid property type")
# Adjust total radiator needs based on built form
form_factor = {
'Enclosed Mid-Terrace': 0.9,
'Mid-Terrace': 0.95,
'Enclosed End-Terrace': 0.95,
'Semi-Detached': 1.05,
'Detached': 1.25,
'End-Terrace': 1.05
}
# Calculate total heating power needed and number of radiators based on standard output
total_heating_power_required = total_floor_area * 80 # Watts per square meter
radiator_output = 1000 # Average wattage per radiator
total_radiators_based_on_power = (total_heating_power_required / radiator_output) * form_factor[built_form]
# Final estimation taking the higher of calculated needs or base room count
estimated_radiators = max(total_radiators_based_on_power, base_radiators + additional_radiators)
return round(estimated_radiators)
def boiler(self, exising_room_heaters, system_change, n_heated_rooms, n_rooms, is_electric=False):
"""
Based on a basic estimate of median value £2600 to install a low carbon combi boiler
First time central heating vosts can als be found here:
https://www.checkatrade.com/blog/cost-guides/central-heating-installation-cost/
:return:
"""
if not is_electric:
unit_cost = CONDENSING_BOILER_COST
else:
unit_cost = ELECTRIC_BOILER_COSTS
# The unit cost is the cost without VAT
# We now need to estimate the cost of the works
labour_days = 2
labour_hours = labour_days * 8
labour_rate = 300
# Average cost of installation is 1 (maybe 2days) at £300 per day
# https://www.checkatrade.com/blog/cost-guides/new-boiler-cost/
# To be pessimistic, assume 2 days work
labour_cost = labour_rate * self.labour_adjustment_factor * labour_days
# Add contingency and preliminaries
vat = labour_cost * self.VAT_RATE
subtotal_before_vat = unit_cost + labour_cost
total_cost = subtotal_before_vat + vat
# if there are existing room heaters, we need to add the cost of removing them
if exising_room_heaters:
removal_costing = self.heater_removal(n_rooms=n_heated_rooms)
# Add the totals to the existing totals
total_cost += removal_costing["total"]
subtotal_before_vat += removal_costing["subtotal"]
labour_hours += removal_costing["labour_hours"]
labour_days += removal_costing["labour_days"]
vat += removal_costing["vat"]
if system_change:
# We need the cost of radiators
n_radiators = self._estimate_n_radiators(
number_habitable_rooms=n_rooms,
total_floor_area=self.property.floor_area,
property_type=self.property.data["property-type"],
built_form=self.property.data["built-form"]
)
additionals_labour_cost = labour_rate * self.labour_adjustment_factor
radiator_cost = DOUBLE_RADIATOR_COST * n_radiators
system_change_cost = radiator_cost + FLUE_COST + PIPEWORK_COST + additionals_labour_cost
system_change_cost_before_vat = system_change_cost / (1 + self.VAT_RATE)
system_change_vat = system_change_cost - system_change_cost_before_vat
# We add an extra labour day for the system change
labour_days += 1
labour_hours += 8
total_cost += system_change_cost
subtotal_before_vat += system_change_cost_before_vat
vat += system_change_vat
return {
"total": total_cost,
"contingency": total_cost * self.CONTINGENCY,
"contingency_rate": self.CONTINGENCY,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": labour_hours,
"labour_days": labour_days,
}
@staticmethod
def _select_cylinder_capacity(occupants: float):
if occupants <= 2:
return 120
elif occupants <= 3:
return 180
elif occupants <= 4:
return 200
else:
return 250
def air_source_heat_pump(self, ashp_size: float, number_heated_rooms: int, total_floor_area: float) -> dict:
"""
We produce a cost estimation for an air source heat pump, based on costs we have received from installers.
"""
system_cost = (
(ASHP_SMALL_SYSTEM_COST if ashp_size <= 8.5 else ASHP_LARGE_SYSTEM_COST) + ASHP_SECURITY + ASHP_WALL_BRACKET
)
available_n_rads = [x["n_radiators"] for x in ASHP_DISTRIBUTION_SYSTEM_COSTS]
if number_heated_rooms < min(available_n_rads):
# We use the smallest value
rads_to_use = min(available_n_rads)
elif number_heated_rooms > max(available_n_rads):
# We use the largest value
rads_to_use = max(available_n_rads)
else:
rads_to_use = int(number_heated_rooms)
distribution_system_cost = [
x for x in ASHP_DISTRIBUTION_SYSTEM_COSTS if x["n_radiators"] == rads_to_use
][0]["cost"]
# Cylinder cost
est_n_occupants = AnnualBillSavings.calculate_occupants(total_floor_area)
cylinder_capacity = self._select_cylinder_capacity(est_n_occupants)
cylinder_cost = [
x for x in ASHP_CYLINDER_COSTS if x["capacity_l"] == cylinder_capacity
][0]["cost"]
total = system_cost + distribution_system_cost + cylinder_cost
return {
"total": total,
"contingency": total * self.CONTINGENCIES["air_source_heat_pump"],
"contingency_rate": self.CONTINGENCIES["air_source_heat_pump"],
"vat": 0,
"labour_hours": 80,
"labour_days": 10,
}
Reference in a new issue View git blame Copy permalink