Characterisation of dwellings in the UK determining the potential for enhanced energy efficiency Part of the BRE Trust

Transcription

1 John Riley & Jack Hulme BRE 29 th February 2012 TABULA European Building Typologies Characterisation of dwellings in the UK determining the potential for enhanced energy efficiency Part of the BRE Trust

2 Structure of presentation Objectives Stock typology Progress to-date What s achievable? The scale of the task Challenges

3 UK Carbon Emissions Domestic, 27% (UK wide) Lighting, appliances and cooking 27% Agriculture etc. 1% Public 4% Business ~39% Emissions from the use of electricity and heating fuels by households account for 27% of the UK s total, making MtCO 2 Space and water heating 73% 73% of household emissions arise from space and water heating, and 27% from lighting, appliances and cooking Source: Transport 29%

4 To consider the stock we need to simplify Whole stock 26,000,000 dwellings Each is different National survey 25,000 sample survey Nationally representative Archetypes 40 archetypes Average charactertistics of each type

5 Developing typologies All dwellings House Flat Detached Attached Converted Purpose built Semidetached Terrace High rise Low rise

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7 Stock typology - Stock characteristics Part of the BRE Trust

8 Developing typologies BRE use two mechanisms for describing the stock ahead of improvement (or any other) modelling 1) Archetype approach 2) Housing Survey data approach

9 The archetype method Method 1: Archetype method Development of typical dwelling plans and descriptions for limited number of types. Layout and built form Description of key metrics Dimensions Energy efficiency characteristics This is followed by simulation of improvements onto these specific types

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11 Archetype approach Using archetypes in this way is simplification of reality Beneath each type is variability Size Condition Energy efficiency etc. Concentrating on a single stereotype can be an oversimplification Where this variability is important (typically stock level modelling) use another technique

12 Housing Survey data approach Method 2: Use Housing Survey data directly Run models using 25,000+ records to allow more resolution and acknowledgement of the underlying variability Distribution of dimensions Distribution of dwelling condition Distribution of insulation Allows us to split the results of data by numerous factors (household type, tenure, income of household) As well as by classical typology variables of dwelling type and age. BUT data more complex to work with, to interpret is a conceptual leap for those more used to archetype approach. Still a simplification (essentially 20,000+ archetypes)

13 For any particular property type Number of occupants Insula'on levels Wall area Variation in input parameters from underlying data. We represent this variation by running thousands of cases for each type. Calculation of energy use y = y(x 1, x 2, x 3...x n ) Final distribu'on of energy use Variation in output produced mirrors underlying variability in the stock

14 Measuring improvements to energy efficiency Part of the BRE Trust

15 The scale of the task for England Mean SAP rating Average SAP rating

16 Progress to-date % as a proportion of dwellings with cavity walls owner occupied private rented local authority RSL all tenures

17 SAP by Dwelling Age Mean SAP Pre Post 1980

18 SAP by Dwelling Type Mean SAP End terrace Mid terrace Semi detached Detached Bungalow Converted flat Purpose built flat

19 Predicting change The potential Part of the BRE Trust

20 Market penetration of home energy-efficiency related measures 100% 90% Hot water tank insulation ETP Scenario 1 80% Draught proofing Scenario 2 70% Central heating Percentage of potential 60% 50% 40% Double glazing Condensing boilers (scenarios developed under the Market Transformation programme) 30% 20% 10% Loft insulation (any) Cavity wall insulation Ref 0% Year

21 Example of an Energy Performance Certificate

22 Understanding the scale of the task EPC recommended energy efficiency measures (2009) size of applicable group (000s) number of dwellings that would benefit from the measure (000s) percentage of applicable group (%) low cost measures (less than 500) loft insulation 19,737 8, cavity wall insulation 15,441 6, hot water cylinder insulation 12,522 3, higher cost measures (more than 500) heating controls 19,627 6, boiler upgrade 19,431 13, storage heater upgrade 2,358 1, hot water cylinder thermostat 12,522 1,134 9 replacement warm air system install biomass system

23 Potential improvements in energy efficiency (SAP) ratings, CO2 emissions and fuel costs by dwelling age, 2009 SAP (rating) current perfomance CO2 (tones/ year) cost ( / year) post-improvement SAP (rating) CO2 (tones/ year) cost ( / year) SAP inc. (rating) difference CO2 saving (tones/ year) cost saving ( / year) pre post all ages

24 The scale of the task for England Mean SAP rating Average SAP rating

25 Reaching the 80% target by 2050 Need to include: Stock condition Decarbonisation of the power supply Low carbon heat Advances in technology Changes in occupant behaviour

26 Stock Characteristics & the reality for improving energy efficiency The Challenges for Retrofitting Part of the BRE Trust

27 Retrofitting Challenges Stock Condition

28 Hard to Treat stock Category of HTT Dwellings Included Dwellings not included Solid wall Off gas network No loft High rise flats Traditional 9 masonry Single leaf masonry > 9 walls Concrete walls Metal panelled walls Timber panelled walls Dwellings with no mains gas system present Dwellings surveyed as having no loft Dwellings with mansard, chalet or flat roofs built pre-1990 Dwellings with pre-1990 loft conversions Flats at least 6 storeys high Cavity walls that cannot be filled for technical reasons Dwellings with communal heating systems Dwellings with mansard, chalet or flat roofs built post-1990 Dwellings with post-1990 loft conversions

29 Hard to Treat stock Number of dwellings (000s) % of all dwellings % of Hard to Treat stock Hard To Treat? Yes 9, No 13, Total 22, Solid wall 6, Off gas network 3, No loft space 1, High rise flat

30 Summary - Typologies help us by: - Splitting the stock into manageable groups - Allow us to consider the stock as a whole - Energy efficiency progress can be tracked against these typologies - Good progress made but much to achieve - Important to always recognise the simplifications of your typologies - Real nature (and difficulties) in the stock can be hidden by simplistic methods - Recommend multiple approaches are developed to avoid this

31 John Riley & Jack Hulme BRE 29 th February 2012 TABULA European Building Typologies Characterisation of dwellings in the UK determining the potential for enhanced energy efficiency Part of the BRE Trust