Model/recommendations/Costs.py
2024-01-16 11:45:19 +00:00

872 lines
45 KiB
Python

import numpy as np
from recommendations.county_to_region import county_to_region_map
# 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}
]
# This data is based on the MCS database
MCS_SOLAR_PV_COST_DATA = {
"last_updated": "2024-01-04",
"average_cost_per_kwh": 2013.94,
"average_cost_per_kwh-Outer London": 2618.75,
"average_cost_per_kwh-Inner London": 2618.75,
"average_cost_per_kwh-South East England": 2083.33,
"average_cost_per_kwh-South West England": 2113,
"average_cost_per_kwh-East of England": 1973.86,
"average_cost_per_kwh-East Midlands": 1981.86,
"average_cost_per_kwh-West Midlands": 1926.55,
"average_cost_per_kwh-North East England": 2028.49,
"average_cost_per_kwh-North West England": 1620.42,
"average_cost_per_kwh-Yorkshire and the Humber": 2060.9,
"average_cost_per_kwh-Wales": 1898.83,
"average_cost_per_kwh-Scotland": 1967.97,
"average_cost_per_kwh-Northern Ireland": 2126.09,
}
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
# For flat roof, we assume it's a high risk project as it's very weather dependent and also is heavily
# dependent on the quality of the existing roof
FLAT_ROOF_CONTINGENCY = 0.15
# We use a higher contingency rate for internal wall insulation because of the potential for issues with moving
# fittings and trimming doors, as well as scope for damage to the existing wall during preparation.
IWI_CONTINGENCY = 0.2
# Where there is more uncertainty, a higher contingency rate is used
HIGH_RISK_CONTINGENCY = 0.2
# When there is less uncertainty, a lower contingency rate is used
LOW_RISK_CONTINGENCY = 0.05
# 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
# For higher risk projects, a higher preliminaries rate is used. SPONs indicates that a higher risk project might
# have a preliminaries of 12-14% so we use 12% as the median for the preliminaries rate.
# For External wall insulation (EWI), we use 15% as the preliminaries rate if we think the property might
# need scaffolding, otherwise we use 12%. This is to account for any site preparation that might be required
EWI_NO_SCAFFOLDING_PRELIMINARIES = 0.2
EWI_SCAFFOLDING_PRELIMINARIES = 0.25
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
# Typically, secondary glazing can be installed for 25% of the cost of double glazed windows - to be conservative,
# we scale the cost by half
SECONDARY_GLAZING_SCALING_FACTOR = 0.5
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:
raise ValueError("Region not found in county map")
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):
"""
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.
"""
material_cost_per_m2 = material["material_cost"]
base_material_cost = material_cost_per_m2 * wall_area
labour_cost = material["labour_cost"] * wall_area * self.labour_adjustment_factor
subtotal_before_profit = base_material_cost + labour_cost
contingency_cost = subtotal_before_profit * self.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
labour_hours = material["labour_hours_per_unit"] * wall_area
# Assume a team of 2
labour_days = (labour_hours / 8) / 2
return {
"total": total_cost,
"subtotal": subtotal_before_vat,
"vat": vat_cost,
"contingency": contingency_cost,
"preliminaries": preliminaries_cost,
"material": base_material_cost,
"profit": profit_cost,
"labour_hours": labour_hours,
"labour_cost": labour_cost,
"labour_days": labour_days
}
def loft_insulation(self, floor_area, material):
"""
Calculates the total cost for cavity wall insulation based on material and labor costs,
including contingency, preliminaries, profit, and VAT.
:return: A dictionary containing detailed cost breakdown.
"""
material_cost_per_m2 = material["material_cost"]
# We inflate material costs due to recent price increases
material_cost_per_m2 = material_cost_per_m2 * 1.5
base_material_cost = material_cost_per_m2 * floor_area
labour_cost = material["labour_cost"] * floor_area * self.labour_adjustment_factor
subtotal_before_profit = base_material_cost + labour_cost
# We use high risk contingency because of the possibility of access issues and clearing existing insulation
contingency_cost = subtotal_before_profit * self.HIGH_RISK_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
labour_hours = material["labour_hours_per_unit"] * floor_area
# Assume a team of 1 person
labour_days = labour_hours / 8
return {
"total": total_cost,
"subtotal": subtotal_before_vat,
"vat": vat_cost,
"contingency": contingency_cost,
"preliminaries": preliminaries_cost,
"material": base_material_cost,
"profit": profit_cost,
"labour_hours": labour_hours,
"labour_cost": labour_cost,
"labour_days": labour_days
}
def internal_wall_insulation(self, wall_area, material, non_insulation_materials):
"""
Broadly speaking, the high level steps to an internal wall insulation job are the following:
1) Demolition: This involves removing existing wall linings, fittings, and any other obstacles.
It's important to factor in the disposal of debris and the potential need for additional protective
measures to ensure the safety of the work area.
2) Insulation Installation: This is the core part of the process where the chosen insulation material is
applied. The choice of insulation material will depend on several factors including thermal performance,
wall construction, and space constraints.
3) Vapour Barrier Installation: This is crucial for preventing moisture from penetrating the insulation,
which can compromise its effectiveness and lead to mold growth.
4) Re-decoration: This involves applying plaster to the wall and then painting.
The quality of finish here is important for both aesthetic and functional reasons.
5) Trim and Finishing Work: Post-insulation, tasks such as re-installing skirting boards, door frames,
or window sills might be necessary.
:return:
"""
# 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)
# 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,
"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):
"""
We characterise the steps for suspended floor insulation as the following tasks:
1) Removal of Carpet and Underfelt: Where necessary, remove existing floor coverings to access the floorboards.
2) Removal of Floor Boarding: Carefully remove floorboards to access the space beneath for insulation.
3) Installation of Vapour Barrier: Install a vapour barrier to prevent moisture from affecting
the insulation and floor structure.
4) Installation of Insulation: Fit the chosen insulation material between the joists in the floor void.
5) Refixing Floorboards: Replace and secure the floorboards after insulation installation.
6) Re-carpeting: Lay down the carpet or other floor coverings once the insulation and floorboards are in place.
:return:
"""
demolition_data = [x for x in non_insulation_materials if x["type"] == "suspended_floor_demolition"]
vapour_barrier_data = [x for x in non_insulation_materials if x["type"] == "suspended_floor_vapour_barrier"]
redecoration_data = [x for x in non_insulation_materials if x["type"] == "suspended_floor_redecoration"]
if (len(demolition_data) != 2) or (len(vapour_barrier_data) != 1) or (len(redecoration_data) != 2):
raise ValueError("Incorrect number of data entries for non-insulation materials")
# Break out the individual material costs
demolition_material_costs = sum([x["material_cost"] * insulation_floor_area for x in demolition_data])
insulation_material_costs = material["material_cost"] * insulation_floor_area
vapour_barrier_material_costs = vapour_barrier_data[0]["material_cost"] * insulation_floor_area
redecoration_material_costs = sum([x["material_cost"] * insulation_floor_area for x in redecoration_data])
demolition_labour_costs = sum([x["labour_cost"] * insulation_floor_area for x in demolition_data])
insulation_labour_costs = material["labour_cost"] * insulation_floor_area
vapour_barrier_labour_costs = vapour_barrier_data[0]["labour_cost"] * insulation_floor_area
redecoration_labour_costs = sum([x["labour_cost"] * insulation_floor_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
# Because of the possiblity of damage to the existing floor, or difficulties associated to moving fittings,
# we use a higher contingency rate
contingency_cost = subtotal_before_profit * self.HIGH_RISK_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 = sum([x["labour_hours_per_unit"] * insulation_floor_area for x in demolition_data])
insulation_labour_hours = material["labour_hours_per_unit"] * insulation_floor_area
vapour_barrier_labour_hours = vapour_barrier_data[0]["labour_hours_per_unit"] * insulation_floor_area
redecoration_labour_hours = sum([x["labour_hours_per_unit"] * insulation_floor_area for x in redecoration_data])
labour_hours = (demolition_labour_hours + insulation_labour_hours + vapour_barrier_labour_hours +
redecoration_labour_hours)
# Assume a team of 3 people for a small to medium size project
labour_days = (labour_hours / 8) / 3
return {
"total": total_cost,
"subtotal": subtotal_before_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 solid_floor_insulation(self, insulation_floor_area, material, non_insulation_materials):
"""
We characterise the steps for solid floor insulation as the following tasks:
1) Removal of Carpet and Underfelt: This is the initial stage where any existing floor coverings, like carpets,
tiles, or linoleum, are carefully removed. This exposes the solid floor beneath, which is typically concrete.
2) Preparation of Flooring: This step is critical. It involves:
- Cleaning the existing floor surface thoroughly to remove debris and ensure a flat surface.
- Assessing and repairing any damage to the concrete floor. This might include filling cracks or leveling
uneven areas.
3) Installation of a Damp Proof Membrane (DPM): Before installing insulation, a DPM is often laid down to
prevent moisture from rising into the insulation and the interior space. This step is crucial in areas prone to
dampness.
4) Install Insulation: The insulation, often in the form of rigid foam boards, is laid over the DPM.
The choice of insulation material will depend on the desired thermal properties and the available floor height.
Care is taken to minimize thermal bridges and ensure a snug fit between insulation boards.
5) Laying a New Subfloor: Over the insulation, a new subfloor is often installed. This could be a layer of
screed (a type of concrete) or wooden boarding, depending on the specific requirements and preferences.
6) Re-decoration and Finishing Touches: Once the subfloor is in place and has set or dried (if necessary),
the final floor finish can be applied. This might involve:
- Laying new tiles, wooden flooring, or other chosen materials.
- If you're planning to re-carpet, this would be the stage to do it.
- Skirting boards may need to be refitted or replaced.
7) Considerations for Doors and Fixtures: It's important to note that raising the floor level can affect door
thresholds and other fixtures. Doors may need to be trimmed, and fixtures might need adjustments.
:param insulation_floor_area: Area of the floor to be insulated
:param material: Selected insulation material
:param non_insulation_materials: Non-insulation materials required for the job
:return:
"""
demolition_data = [x for x in non_insulation_materials if x["type"] == "solid_floor_demolition"]
preparation_data = [x for x in non_insulation_materials if x["type"] == "solid_floor_preparation"]
vapour_barrier_data = [x for x in non_insulation_materials if x["type"] == "solid_floor_vapour_barrier"]
redecoration_data = [x for x in non_insulation_materials if x["type"] == "solid_floor_redecoration"]
if ((len(demolition_data) != 1) or (len(preparation_data) != 2) or (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
preparation_material_costs = sum([x["material_cost"] * insulation_floor_area for x in preparation_data])
insulation_material_costs = material["material_cost"] * insulation_floor_area
vapour_barrier_material_costs = vapour_barrier_data[0]["material_cost"] * insulation_floor_area
redecoration_material_costs = sum([x["material_cost"] * insulation_floor_area for x in redecoration_data])
demolition_labour_costs = sum([x["labour_cost"] * insulation_floor_area for x in demolition_data])
preparation_labour_costs = sum([x["labour_cost"] * insulation_floor_area for x in preparation_data])
insulation_labour_costs = material["labour_cost"] * insulation_floor_area
vapour_barrier_labour_costs = vapour_barrier_data[0]["labour_cost"] * insulation_floor_area
redecoration_labour_costs = sum([x["labour_cost"] * insulation_floor_area for x in redecoration_data])
preparation_plant_costs = sum([x["plant_cost"] * insulation_floor_area for x in preparation_data])
labour_costs = (demolition_labour_costs + insulation_labour_costs + vapour_barrier_labour_costs +
redecoration_labour_costs + preparation_labour_costs)
labour_costs = labour_costs * self.labour_adjustment_factor
materials_cost = (preparation_material_costs + insulation_material_costs + vapour_barrier_material_costs +
redecoration_material_costs)
subtotal_before_profit = labour_costs + materials_cost + preparation_plant_costs
# We use HIGH_RISH_CONTINGENCY because of the potential for issues with moving fittings and trimming doors,
# as well as scope for damage to the existing floor during preparation.
contingency_cost = subtotal_before_profit * self.HIGH_RISK_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 = sum([x["labour_hours_per_unit"] * insulation_floor_area for x in demolition_data])
preparation_labour_hours = sum([x["labour_hours_per_unit"] * insulation_floor_area for x in preparation_data])
insulation_labour_hours = material["labour_hours_per_unit"] * insulation_floor_area
vapour_barrier_labour_hours = vapour_barrier_data[0]["labour_hours_per_unit"] * insulation_floor_area
redecoration_labour_hours = sum([x["labour_hours_per_unit"] * insulation_floor_area for x in redecoration_data])
labour_hours = (demolition_labour_hours + insulation_labour_hours + vapour_barrier_labour_hours +
redecoration_labour_hours + preparation_labour_hours)
# Assume a team of 3 people for a small to medium size project
labour_days = (labour_hours / 8) / 3
return {
"total": total_cost,
"subtotal": subtotal_before_vat,
"vat": vat_cost,
"contingency": contingency_cost,
"preliminaries": preliminaries_cost,
"material": materials_cost,
"profit": profit_cost,
"labour_hours": labour_hours,
"labour_days": labour_days,
"labour_cost": labour_costs
}
def external_wall_insulation(self, wall_area, material, non_insulation_materials):
"""
We characterise external wall insulation as the following steps:
1) Preparation of the Area: Tidying up the surroundings, trimming back foliage, and laying down protective
sheets to protect the flooring and landscaping around the work area.
2) Scaffolding Setup (if needed): Erecting scaffolding for safe access to the walls of semi-detached or
detached houses. For terraced houses or lower-level work, scaffolding might not be necessary.
3) Wall Surface Preparation: Cleaning the wall surface, removing any loose or flaking material,
and possibly applying a primer. If the existing wall is weak or damaged, partial or full replacement
of the top surface may be necessary.
4) Applying Primer: If the existing wall is suitable, applying a primer to improve adhesion of the insulation
boards and stabilize the wall surface, especially if it's old or weathered.
5) Insulation Application: Attaching insulation boards to the primed wall using adhesive, mechanical fixings,
or a combination of both.
6) Basecoat and Mesh Application: Applying a basecoat embedded with a reinforcing mesh over the insulation.
This layer provides strength and helps prevent cracking.
7) Decorative Finish: Applying a decorative finish, such as render or cladding, which protects the insulation
and provides an aesthetic look.
8) Reinstalling Fixtures: Reattaching any fixtures like downpipes, satellite dishes, or lighting fixtures that
were removed during preparation. Extensions or adjustments may be required due to the increased wall thickness.
9) Inspection and Cleanup: Conducting a thorough inspection to ensure quality and integrity of the EWI system,
followed by cleaning up the site to remove all debris and materials.
In the actual materials data, at this point, we have costing for:
- wall preparation, hacking off existing wall finishes, linings, etc (ewi_wall_demolition)
- wall surface cleaning and priming (ewi_wall_preparation)
- insulation (external_wall_insulation)
- basecoat and mesh with decorative render topcoat finish (ewi_basecoat_and_mesh)
All of this data comes from SPONS, however there are some clear features missing. Because we could not find
suitable cost records in SPONS for steps like cleaning the area, setting up small scale scaffolding,
re-attaching any fitings and cleaning up the area afterwards, instead we have accounted for these steps by
increasing the preliminaries rate. It is acknowldeged though, that this is not ideal and that the cost of these
steps should be included in the materials data. We will look to improve this in the future, with data from
installers
:param wall_area:
:param material:
:param non_insulation_materials:
:return:
"""
# For semi detatched and detatched houses, as well as maisonettes, we price for scaffolding
if self.property.data["property-type"] == "House":
if self.property.data["built-form"] in ['Semi-Detached', 'Detached', "End-Terrace"]:
preliminaries_rate = self.EWI_SCAFFOLDING_PRELIMINARIES
else:
preliminaries_rate = self.EWI_NO_SCAFFOLDING_PRELIMINARIES
elif self.property.data["property-type"] == "Maisonette":
preliminaries_rate = self.EWI_SCAFFOLDING_PRELIMINARIES
elif self.property.data["property-type"] == "Bungalow":
preliminaries_rate = self.EWI_NO_SCAFFOLDING_PRELIMINARIES
else:
raise ValueError("Unsupported property type - haven't handled flats")
demolition_data = [x for x in non_insulation_materials if x["type"] == "ewi_wall_demolition"]
preparation_data = [x for x in non_insulation_materials if x["type"] == "ewi_wall_preparation"]
redecoration_data = [x for x in non_insulation_materials if x["type"] == "ewi_wall_redecoration"]
if (len(demolition_data) != 3) or (len(preparation_data) != 1) or (len(redecoration_data) != 1):
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
preparation_material_costs = preparation_data[0]["material_cost"] * wall_area
redecoration_material_costs = redecoration_data[0]["material_cost"] * wall_area
demolition_plant_costs = np.mean([x["plant_cost"] * wall_area for x in demolition_data])
demolition_labour_costs = np.mean([x["labour_cost"] * wall_area for x in demolition_data])
insulation_labour_costs = material["labour_cost"] * wall_area
preparation_labour_costs = preparation_data[0]["labour_cost"] * wall_area
redecoration_labour_costs = redecoration_data[0]["labour_cost"] * wall_area
labour_costs = (demolition_labour_costs + insulation_labour_costs + redecoration_labour_costs +
preparation_labour_costs)
labour_costs = labour_costs * self.labour_adjustment_factor
materials_costs = (demolition_material_costs + insulation_material_costs + preparation_material_costs +
redecoration_material_costs)
subtotal_before_profit = labour_costs + materials_costs + demolition_plant_costs
contingency_cost = subtotal_before_profit * self.CONTINGENCY
preliminaries_cost = subtotal_before_profit * preliminaries_rate
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
preparation_labour_hours = preparation_data[0]["labour_hours_per_unit"] * wall_area
redecoration_labour_hours = redecoration_data[0]["labour_hours_per_unit"] * wall_area
labour_hours = (demolition_labour_hours + insulation_labour_hours + redecoration_labour_hours +
preparation_labour_hours)
# Assume a team of 3-5 people for a small to medium size project
labour_days = (labour_hours / 8) / 4
return {
"total": total_cost,
"subtotal": subtotal_before_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 low_energy_lighting(self, number_of_lights, number_current_lel_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
:param number_current_lel_lights: Int, number of low energy lights currently installed in the home
: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
if number_current_lel_lights == 0:
contingency = self.HIGH_RISK_CONTINGENCY
else:
contingency = self.CONTINGENCY
material_cost = material["material_cost"] * number_of_lights
labour_cost = material["labour_cost"] * number_of_lights * self.labour_adjustment_factor
subtotal_before_profit = material_cost + labour_cost
contingency_cost = subtotal_before_profit * 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
labour_hours = material["labour_hours_per_unit"] * number_of_lights
# Assume a single electrician installing
labour_days = (labour_hours / 8)
return {
"total": total_cost,
"subtotal": subtotal_before_vat,
"vat": vat_cost,
"contingency": contingency_cost,
"preliminaries": preliminaries_cost,
"material": material_cost,
"profit": profit_cost,
"labour_hours": labour_hours,
"labour_days": labour_days,
"labour_cost": labour_cost
}
def flat_roof_insulation(self, floor_area, material, non_insulation_materials):
"""
A model of a warm, flat roof construction can be seen in this video:
https://www.youtube.com/watch?v=WZ6Ng6YI9OA
Warm, flat roof insulation will normally be 100-125mm in depth
We break this measure down into the following jobs to be done
1) Preparation of the room. This involves cleaning the existing roof surface, removing any debris and repairing
any damage. Additionally, an edge barrier will likely need to be installed, to protect the sides of the
roof from water ingress.
2) Primer Application. A layer of primer is applied to the clean roof surface to enhance the adhestia of
subsequent layers, and seal the existing roof surface.
3) Vapour Proof Layer Installation. Lay a vapour control layer to prevent moisture ingress from inside the
building, which is essential in warm roof construction.
4) Insulation Layer Application. Place and securely fix insulation boards over the roof. These could be rigid
boards like PIR (Polyisocyanurate).
5) Waterproofing Membrane Installation: Cover the insulation (and timber layer, if used) with a
waterproofing membrane, like EPDM, PVC, or bituminous felt. Carefully seal all joints, edges, and around any
roof penetrations to ensure water tightness
:param floor_area: Area of the flat roof to be insulated, based on the area of the floor
:param material: Selected insulation material
:param non_insulation_materials: Non-insulation materials required for the job
:return:
"""
preparation_data_m2 = [
x for x in non_insulation_materials if
(x["type"] == "flat_roof_preparation") and (x["cost_unit"] == "gbp_per_m2")
]
vapour_barrier_data = [x for x in non_insulation_materials if x["type"] == "flat_roof_vapour_barrier"]
waterproofing_data = [x for x in non_insulation_materials if x["type"] == "flat_roof_waterproofing"]
if (len(preparation_data_m2) != 2) or (len(vapour_barrier_data) != 1) or (
len(waterproofing_data) != 1):
raise ValueError("Incorrect number of data entries for non-insulation materials")
# Break out the individual material costs
preparation_m2_material_costs = sum([x["material_cost"] * floor_area for x in preparation_data_m2])
vapour_barrier_material_costs = vapour_barrier_data[0]["material_cost"] * floor_area
insulation_material_costs = material["material_cost"] * floor_area
preparation_m2_labour_costs = sum([x["labour_cost"] * floor_area for x in preparation_data_m2])
vapour_barrier_labour_costs = vapour_barrier_data[0]["labour_cost"] * floor_area
# For waterproofing and upstand, we only have a total cost
waterproofing_total_costs = waterproofing_data[0]["total_cost"] * floor_area
labour_costs = preparation_m2_labour_costs + vapour_barrier_labour_costs
labour_costs = labour_costs * self.labour_adjustment_factor
materials_costs = preparation_m2_material_costs + vapour_barrier_material_costs + insulation_material_costs
subtotal_before_profit = labour_costs + materials_costs + waterproofing_total_costs
contingency_cost = subtotal_before_profit * self.FLAT_ROOF_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
preparation_m2_labour_hours = sum([x["labour_hours_per_unit"] * floor_area for x in preparation_data_m2])
vapour_barrier_labour_hours = vapour_barrier_data[0]["labour_hours_per_unit"] * floor_area
waterproofing_labour_hours = waterproofing_data[0]["labour_hours_per_unit"] * floor_area
labour_hours = preparation_m2_labour_hours + vapour_barrier_labour_hours + waterproofing_labour_hours
# To install flat roof insulation, assume a small/medium project might be conducted by a team of 2-4.
# We'll assume a team of 2 since a lot of the roofs will be on the smaller side and will review this later
labour_days = (labour_hours / 8) / 2
return {
"total": total_cost,
"subtotal": subtotal_before_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 window_glazing(self, number_of_windows, material, is_secondary_glazing=False):
"""
We characterise the jobs to be done for window glazing as the following:
1) Initial Assessment and Measurements: Before removing the existing window, it's essential to assess the
condition of the window frame and opening. Precise measurements are taken to ensure the new double glazed
windows fit perfectly.
2) Remove the Existing Window: This involves carefully dismantling and removing the old single glazed window. It
requires skill to avoid damaging the surrounding wall and the window frame (if it's to be reused).
3) Dispose of the Existing Window: The old window, especially if it's a single glazed unit, needs to be
disposed of responsibly. Glass and other materials should be recycled where possible.
4) Surface Preparation: The window opening might need some preparation, especially if there's damage or if
adjustments are needed to accommodate the new window. This can include repairing or replacing parts of the
window frame, sealing gaps, and ensuring the opening is level and square.
5) Install the Window Frame (if new frames are used): In many cases, double glazed windows come with their
frames. These need to be installed securely into the window opening. This process involves aligning, leveling,
and fixing the frame in place.
6) Install the Window Sill: If a new window sill is required, it is installed at this stage. It needs to be
correctly aligned with the frame and securely attached.
7) Install the Double Glazed Glass Units: The glass units are carefully inserted into the frame. This step
requires precision to ensure a snug fit without causing stress on the glass, which could lead to cracking or
breaking.
8) Sealing and Weatherproofing: After the glass units are in place, it's crucial to seal around the frame and
between the glass and frame to ensure there are no drafts and that the installation is weather-tight. This
typically involves applying silicone sealant or other appropriate sealing materials.
9) Finishing Touches: This includes any cosmetic work, such as trimming, painting, or staining the frame and
sill to match the rest of the property. It might also involve cleaning up any mess created during the
installation.
10) Inspection and Testing: Finally, the new windows should be inspected to ensure they open, close, and lock
correctly. This is also a good time to check for any gaps or issues with the sealing.
For this cost estimation process, we factor in initial assement into the preliminaries
"""
material_cost = material["material_cost"] * number_of_windows
labour_cost = (
material["labour_cost"] * number_of_windows * self.labour_adjustment_factor
)
multiplier = self.SECONDARY_GLAZING_SCALING_FACTOR if is_secondary_glazing else (
self.SASH_WINDOW_INFLATION_FACTOR)
subtotal = (material_cost + labour_cost) * multiplier
contingency_cost = subtotal * self.CONTINGENCY
preliminaries_cost = subtotal * self.PRELIMINARIES
profit_cost = subtotal * self.PROFIT_MARGIN
subtotal_before_vat = subtotal + contingency_cost + preliminaries_cost + profit_cost
vat_cost = subtotal_before_vat * self.VAT_RATE
total_cost = subtotal_before_vat + vat_cost
labour_hours = material["labour_hours_per_unit"] * number_of_windows
labour_hours = labour_hours * self.SECONDARY_GLAZING_SCALING_FACTOR if is_secondary_glazing else labour_hours
# Assume a team of 2
labour_days = (labour_hours / 8) / 2
return {
"total": total_cost,
"subtotal": subtotal_before_vat,
"vat": vat_cost,
"contingency": contingency_cost,
"preliminaries": preliminaries_cost,
"material": material_cost,
"profit": profit_cost,
"labour_hours": labour_hours,
"labour_cost": labour_cost,
"labour_days": labour_days
}
def solar_pv(self, wattage: float):
"""
Calculates the total cost for solar PV based data provided by the MCS dashboard, which contains
costing data for installations of renewable and clean energy measures.
The data in the dashboard is filtered on domestic building installations and then the data across the
various regions is manually collected. There is currently no automated way to get the data from the MCS
dashboard
Price can also be benchmarked against this checkatrade article:
https://www.checkatrade.com/blog/cost-guides/cost-of-solar-panel-installation/
:param wattage: Peak wattage of the solar PV system
:return:
"""
# Get the cost data relevant to the region
regional_cost = MCS_SOLAR_PV_COST_DATA["-".join(["average_cost_per_kwh", self.region])]
kw = wattage / 1000
total_cost = kw * regional_cost
subtotal_before_vat = total_cost / (1 + self.VAT_RATE)
vat = total_cost - subtotal_before_vat
# 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 72 hours of
# labour
return {
"total": total_cost,
"subtotal": subtotal_before_vat,
"vat": vat,
"labour_hours": 72,
"labour_days": 2,
}