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 - taken the figures for June 2024 MCS_SOLAR_PV_COST_DATA = { "last_updated": "2024-07-10", "average_cost_per_kwh": 1825, "average_cost_per_kwh-Outer London": 1950, "average_cost_per_kwh-Inner London": 1950, "average_cost_per_kwh-South East England": 1966, "average_cost_per_kwh-South West England": 1864, "average_cost_per_kwh-East of England": 1719, "average_cost_per_kwh-East Midlands": 1730, "average_cost_per_kwh-West Midlands": 1789, "average_cost_per_kwh-North East England": 1872, "average_cost_per_kwh-North West England": 1860, "average_cost_per_kwh-Yorkshire and the Humber": 1789, "average_cost_per_kwh-Wales": 1676, "average_cost_per_kwh-Scotland": 1781, "average_cost_per_kwh-Northern Ireland": 1347, } INSTALLER_SOLAR_COSTS = [ {'n_panels': 4, 'array_kwp': 1.6, 'cost': 3040.00, 'installer': 'CEG'}, {'n_panels': 5, 'array_kwp': 2.1, 'cost': 3201.00, 'installer': 'CEG'}, {'n_panels': 6, 'array_kwp': 2.5, 'cost': 3363.00, 'installer': 'CEG'}, {'n_panels': 7, 'array_kwp': 2.9, 'cost': 3524.00, 'installer': 'CEG'}, {'n_panels': 8, 'array_kwp': 3.3, 'cost': 3686.00, 'installer': 'CEG'}, {'n_panels': 9, 'array_kwp': 3.7, 'cost': 3847.00, 'installer': 'CEG'}, {'n_panels': 10, 'array_kwp': 4.1, 'cost': 4009.00, 'installer': 'CEG'}, {'n_panels': 11, 'array_kwp': 4.5, 'cost': 4170.00, 'installer': 'CEG'}, {'n_panels': 12, 'array_kwp': 4.9, 'cost': 4332.00, 'installer': 'CEG'}, {'n_panels': 13, 'array_kwp': 5.3, 'cost': 4835.00, 'installer': 'CEG'}, {'n_panels': 14, 'array_kwp': 5.7, 'cost': 5015.00, 'installer': 'CEG'}, {'n_panels': 15, 'array_kwp': 6.2, 'cost': 5176.00, 'installer': 'CEG'}, {'n_panels': 16, 'array_kwp': 6.6, 'cost': 5338.00, 'installer': 'CEG'}, {'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 INSTALLER_SOLAR_PV_INVERTER_COST = 7500 INSTALLER_SOLAR_PV_INVERTER_LABOUR_COST = 500 # Just a rough guess to labour costs INSTALLER_SCAFFOLDING_COSTS = [ {'stories': 1, 'description': '1 Story Scaffold', 'cost': 531.00, 'installer': 'CEG'}, {'stories': 2, 'description': '2 Story Scaffold', 'cost': 841.00, 'installer': 'CEG'}, {'stories': 3, 'description': '3 Story Scaffold', 'cost': 1077.00, 'installer': 'CEG'} ] # This data is based on the MCS database, We use the larger figure between the 2023 and 2024 average, # to be conservative MCS_AIR_SOURCE_HEAT_PUMP_COST_DATA = { "Outer London": 13220, "Inner London": 13220, "South East England": 13547, "South West England": 12776, "East of England": 12585, "East Midlands": 12239, "West Midlands": 13182, "North East England": 11829, "North West England": 11714, "Yorkshire and the Humber": 11919, "Wales": 13701, "Scotland": 12586, "Northern Ireland": 12000, # There are hardly any air source heat pump installs going on in Northern Ireland } INSTALLER_ASHP_COSTS = [ {'capacity_kw': 5.0, 'brand': 'Mitsubishi', 'tank_size_liters': 150, 'cost': 10149.53, 'installer': 'CEG'}, {'capacity_kw': 6.0, 'brand': 'Mitsubishi', 'tank_size_liters': 170, 'cost': 10823.48, 'installer': 'CEG'}, {'capacity_kw': 8.5, 'brand': 'Mitsubishi', 'tank_size_liters': 200, 'cost': 11312.43, 'installer': 'CEG'}, {'capacity_kw': 11.2, 'brand': 'Mitsubishi', 'tank_size_liters': 250, 'cost': 12156.75, 'installer': 'CEG'}, {'capacity_kw': 14.0, 'brand': 'Mitsubishi', 'tank_size_liters': 300, 'cost': 14405.54, 'installer': 'CEG'}, {'capacity_kw': 14.0, 'brand': 'Mitsubishi', 'tank_size_liters': 300, 'cost': 14405.54, 'installer': 'CEG'}, {'capacity_kw': 17.0, 'brand': 'Grant', 'tank_size_liters': 300, 'cost': 14445.00, 'installer': 'CEG'}, {'capacity_kw': 20.0, 'brand': 'Ecoforest', 'tank_size_liters': 400, 'cost': 21189.41, 'installer': 'CEG'}, {'capacity_kw': None, 'brand': '2 x cascaded ASHPs', 'tank_size_liters': 500, 'cost': 22950.00, 'installer': 'CEG'} ] BOILER_UPGRADE_SCHEME_ASHP_VALUE = 7500 INSTALLER_SOLAR_BATTERY_COSTS = [ {'capacity_kwh': 5, 'description': 'Battery Add on', 'cost': 2700.00, 'installer': 'CEG'}, {'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) # Low carbon combi boiler - median value based on £2200 - £3000 range LOW_CARBON_COMBI_BOILER = 2200 # boiler prices based on # https://www.greenmatch.co.uk/boilers/30kw-boiler # https://www.greenmatch.co.uk/boilers/35kw-boiler # https://www.greenmatch.co.uk/boilers/40kw-boiler # These are exclusive of installation costs CONDENSING_BOILER_COSTS = { "30kw": 1550, "35kw": 1610, "40kw": 1625 } # 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 = 50 ROOM_HEATER_REMOVAL_LABOUR_HOURS = 3 # This is a cost quoted by Jim for a system flush - existig system will run more efficiently SYSTEM_FLUSH_COST = 250 SINGLE_RADIATOR_COST = 150 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 # 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 # 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: 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, 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 # if the material is based on an installer cost, we return the flat price if material["is_installer_quote"]: total_cost = material["total_cost"] * wall_area return { "total": total_cost, "labour_hours": labour_hours, "labour_days": labour_days, } total_including_vat = material["total_cost"] * wall_area if is_extraction_and_refill: total_including_vat = CAVITY_EXTRACTION_COST * wall_area # Additional 2 days work labour_hours += + (2 * 8) labour_days += + 2 total_excluding_vat = total_including_vat / (1 + self.VAT_RATE) vat_cost = total_including_vat - total_excluding_vat return { "total": total_including_vat, "subtotal": total_excluding_vat, "vat": vat_cost, "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. """ if material["is_installer_quote"]: total_cost = material["total_cost"] * floor_area return { "total": total_cost, "labour_hours": 8, "labour_days": 1, } total_including_vat = material["total_cost"] * floor_area total_excluding_vat = total_including_vat / (1 + self.VAT_RATE) vat_cost = total_including_vat - total_excluding_vat return { "total": total_including_vat, "subtotal": total_excluding_vat, "vat": vat_cost, "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 if material["is_installer_quote"]: total_cost = material["total_cost"] * wall_area 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, "labour_hours": labour_hours, "labour_days": labour_days, } # 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 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_including_vat, "subtotal": total_excluding_vat, "vat": vat_cost, "labour_hours": labour_hours, "labour_days": labour_days, } 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: """ # if the material is based on an installer cost, we return the flat price if material["is_installer_quote"]: 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, "labour_hours": labour_hours, "labour_days": labour_days, } 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: """ # if the material is based on an installer cost, we return the flat price if material["is_installer_quote"]: 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, "labour_hours": labour_hours, "labour_days": labour_days, } 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 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 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 """ if material["is_installer_quote"]: 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, "labour_hours": labour_hours, "labour_days": labour_days, } 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 } @classmethod def solar_pv( cls, n_panels: int | float, has_battery: bool = False, array_cost=None, n_floors: int = 1, battery_kwh: int = 5, needs_inverter=False ): """ 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 n_panels: Number of solar panels :param has_battery: Bool, whether the system includes a battery :param array_cost: float, containing the cost of the solar PV array :param n_floors: int, number of floors in the property, used to estimate the cost of scaffolding :param battery_kwh: int, capacity of the battery in kWh. Defaulted to 5 :param needs_inverter: Bool, whether the system needs an inverter, where the solar panels are feeding multiple units """ 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"] subtotal = array_cost if array_cost is not None else system_cost if has_battery: battery_cost = [c for c in INSTALLER_SOLAR_BATTERY_COSTS if c["capacity_kwh"] == battery_kwh][0]["cost"] subtotal += battery_cost scaffolding_cost = [c for c in INSTALLER_SCAFFOLDING_COSTS if c["stories"] == n_floors][0]["cost"] subtotal += scaffolding_cost if needs_inverter: subtotal += INSTALLER_SOLAR_PV_INVERTER_COST # We also add an additional labour cost subtotal += INSTALLER_SOLAR_PV_INVERTER_LABOUR_COST # We add an additional cost for scaffolding # The costs from installers exclude VAT vat = subtotal * cls.VAT_RATE total_cost = subtotal + 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 48 hours of # labour return { "total": total_cost, "subtotal": subtotal, "vat": vat, "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, "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, "subtotal": subtotal_before_vat, "vat": vat, "labour_hours": labour_hours, "labour_days": labour_days, } def high_heat_electric_storage_heaters(self, number_heated_rooms, needs_cylinder): """ 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 """ if needs_cylinder: # 1000 is the cost of a new hot water cylinder total_cost = 1200 * number_heated_rooms + 1000 else: # 500 is the cost of a dual immersion heater - a rough estimate total_cost = 1200 * number_heated_rooms + 500 subtotal_before_vat = total_cost / (1 + self.VAT_RATE) vat = total_cost - subtotal_before_vat # TODO: Rough estimate to be reviewed labour_hours = 3 * number_heated_rooms labour_days = np.ceil(labour_hours / 8) return { "total": total_cost, "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, "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, "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, "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, "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, "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, "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, "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 = { 'Mid-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, size, 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_COSTS[size] 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 labour_cost = labour_cost * (1 + self.CONTINGENCY + self.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, "subtotal": subtotal_before_vat, "vat": vat, "labour_hours": labour_hours, "labour_days": labour_days, } def air_source_heat_pump(self, ashp_size): """ Based on the region and type of property, this function will produce a cost estimation for an air source heat pump. This cost will include the boiler upgrade scheme grant """ # This is the average cost of a project, we'll add some additional contingency if ashp_size is None: cost = [x for x in INSTALLER_ASHP_COSTS if x["capacity_kw"] is None][0]["cost"] else: cost = [x for x in INSTALLER_ASHP_COSTS if x][0]["cost"] # We add some contingency since there are additional costs such as resizing radiators, that could be required subtotal = cost * (1 + self.CONTINGENCY) # The costs from installers exclude VAT vat = subtotal * self.VAT_RATE total_cost = subtotal + vat # We assume 5 days installation labour_days = 5 labour_hours = labour_days * 8 return { "total": subtotal, "subtotal": subtotal, "vat": vat, "labour_hours": labour_hours, "labour_days": labour_days, }