Modelling residential retrofit:

Transcription

1 Modelling residential retrofit: Insights on the effect of regional characteristics for the Cardiff and Manchester City Regions Presented by Dr Aliki Georgakaki Acknowledgements: Kruti Gandhi, Prof. Malcolm Eames Low Carbon Research Institute Welsh School of Architecture, Cardiff University Niall Kerr and Prof. Andy Gouldson, Centre for Climate Change Economics and Policy, Sustainability Research Institute, School of Earth and Environment, University of Leeds

2 Background rationale for the work Residential sector: a critical area of intervention to achieve energy efficiency and emission reduction targets models provide projections at the national level many decisions are taken at the local level City Region Population Households Cardiff 1.6 M.5 M Manchester 2.6 M 1.8 M application in the context of the Local Authorities based on assumptions and data substitution from other regions here a top down methodology is used to model the domestic sector in combination with data specific to the Local Authorities

3 Adapting the Modelling Methodology BREDEM-12 Model Energy Saving Trust NERA Economic consulting CCC model HEED Database UK Household Projections Renewable Heat model Information on Capital Costs, the Economics and Cost Effectiveness of each Measure Domestic LCR model HEED Data for CCR and MCR City Region Domestic Model Household Projections

4 Input from the Home Energy Efficiency Database UK Region LAs Area summary report : housing stock data for each local authority Installation summary report: information about the number and type of sustainable energy measures installed in an area Property Type Tenure Property age Loft Insulation External wall type Glazing type Main heating fuel Main heating system Appliances Heating Insulation Lighting Micro generation Other External wall types by property age: information about the type of external wall insulation installed in each LA by property age Unknowns excluded: the statistical distribution within the sample of known properties is considered representative Cavity Wall Unfilled Cavity Wall Filled Solid Wall - Uninsulated Solid Wall - Externally Insulated Solid Wall Internally Insulated Solid Wall - Built Insulated

5 Share of homes in LA Representation of the City Regions in the HEED Chart (a) Data series overlapped, Chart (a) & (b) Data source: HEED (EST) Number of records Thousands Cardiff Total number of homes Total in HEED Main heating fuel External wall type Manchester 6 Property age Loft insulation 1 3 Glazing type Main heating system 5 7% (a) 7% 6% 5% 6% 5% 4% 3% 1% % average range 4% 3% 1% % (b)

6 Wall insulation for the City Regions in the HEED Data source: HEED (EST) 1% 8% 6% 4% % Solid Wall - Built Insulated Solid Wall - Internally Insulated Solid Wall - Externally Insulated Solid Wall - Uninsulated Cavity Wall Filled Cavity Wall Unfilled 1% 8% 6% 4% % Cardiff larger share of uninsulated walls larger share of solid walls increased solid wall insulation in certain areas Manchester

7 Number of installations per 1 Homes All measures for the City Regions in the HEED Data source: HEED (EST) Renewables Fuel Switching Systems Fabric Cardiff measure of activity Manchester Cardiff worse than Welsh average but slightly better than UK average Manchester much better than the UK average

8 Fuel Share - Residential Sector The effect of differences in the domestic fuel mix Data source: Chart (a) HEED (EST), Charts (b) DECC Space Heating Weighted Average Emission Factor [kg CO 2 /kwh] (a) Translate the energy savings to fuel and cost savings that account for the fuel mix Use emission factors that reflect the decarbonisation trajectory of the fuel cost scenario chosen.18 1% 1% 8% 8% 6% 4% % Solid fuels Petroleum Electricity Gas 6% 4% % (b)

9 Domestic fuel mix estimates & projections Data source: DECC Available at UK level Electricity Solid fuel Oil Gas Share of energy consumed by the domestic sector for each use Fuel mix within each end use Projections on the future fuel mix Space heating Water heating Cooking/catering Lighting / appliances 11 Electricity : UK domestic consumption Fuel Mix Gas Oil Solid fuel Electricity End Use UK Average 65% 7% 4% 25% Space heating 6% 8% 9% 6% 5% Water heating 18% 84% 7% 1% 8% Cooking / catering 3% 53% 47% Lighting / appliances 19% 1% units [ktoe]

10 Oil share in total energy use Oil share in domestic energy use (DECC) Oil share in water heating Fuel use correlations based on statistical data Data sources: HEED (EST), DECC 5% 4% Each point is a Welsh local authority % 7% Each point is a year UK average 3% 6% 1% R² =.9633 % % 1% 3% 4% Oil share in main heating fuel (HEED excl. unknown) 5% R² = % 7.5% 8.% 8.5% 9.% 9.5% 1.% Oil share in space heating 8.% 7.5% Each point is a year UK average 5% 4% Combination of charts on the left 7.% 3% 6.5% 6.% 5.5% R² = % 7.5% 8.% 8.5% 9.% 9.5% 1.% Oil share in space heating 1% % % 5% 1% 15% 25% 3% 35% 4%

11 Scenario options & Selected Results The scenario presented refers to high energy prices with a 7% discount rate and taxation included. Results presented will focus on building fabric measures which are included in the compositional downscale and can demonstrate the effect of regional stock Many of the measures, not analysed here, can be downscaled but not adjusted to regional conditions because the data and methodology are not available Because of the original modelling not accounting for all interactions between certain measures, they can be ranked but not added up in terms of effect All results refer to the time period from present to 222

12 Selected measures that have been modelled Fabric measures Wall Insulation Pre76 cavity wall insulation Loft Insulation Glazing Other cavity wall insulation Post '83 cavity wall insulation Solid wall insulation Paper type solid wall insulation Loft insulation - 27mm Loft insulation 25-27mm Loft insulation 5-27mm Loft insulation 75-27mm Loft insulation 1-27mm Glazing - single to new Glazing - old double to new double Glazing (to Best Practice) Improve airtightness DIY floor insulation (susp. timber floors) Systems &: Appliances Heating Room thermostat to control heating Behavioural Lights and appliances Thermostatic radiator valves Hot water cylinder 'stat Uninsulated cylinder to high performance Modestly insulated cyl to high performance Insulate primary pipework A++ rated cold appliances A+ rated wet appliances Efficient lighting Integrated digital TVs Reduced standby consumption Information and Communication Technology products Electronic products Reduce household heating by 1 C Turn unnecessary lighting off Reduce heating for washing machines /ton CO kt CO 2 /year Sample Marginal Abatement Cost Curve to 222

13 Thousands of households Thousands of households Thousands of households Thousands of households Scale of cost effective fabric measures high high Cavity Wall Insulation Solid Wall Insulation Loft insulation Glazing Other Cavity Wall Insulation Solid Wall insulation Loft insulation Glazing Other 2 low Cardiff 2 low Manchester Cavity Wall Insulation Solid Wall Insulation Loft insulation Glazing Other Cavity Wall Insulation Solid Wall insulation Loft insulation Glazing Other

14 Potential annual CO 2 savings (normalised) [kg/household/year] Normalised annual CO 2 saving potential DIY floor insulation Improve airtightness Glazing (to Best Practice) Glazing - old double to new Glazing - single to new Loft insulation 1-27mm Loft insulation 75-27mm Loft insulation 5-27mm Loft insulation 25-27mm Loft insulation - 27mm 1 5 Cardiff Post '83 cavity wall insulation cavity wall insulation Pre76 cavity wall insulation Solid wall insulation Manchester

15 Influence of space heating fuel mix and cost 7. Cardiff 7. Manchester % % 6.4 1% 6.4 1% % % 5.8 % 5.8 % Cost of space heating ( /kwh) Non-gas space heating Electric space heating at the moment the share of electricity in space heating seems to be the deciding factor

16 Manchester Cardiff Results: Scale vs Investment vs Effect High Fuel Price Scenario scale investment emissions 19% 17% 6% 9% 1% 12% 19% 17% Glazing Loft insulation Wall insulation 29% 35% 66% 61% Other wall insulation the most 18% costly but also the most effective 16% 4% 6% 2% 12% 2% 37% 9% 12% Pre76 cavity wall insulation cavity wall insulation 14% cavity wall insulation for pre-76 29% built properties 33% the most cost effective option 8% 78% 2% 4% 65% 57% Post '83 cavity wall insulation Solid wall insulation

17 Glazing - single to new Glazing - old double to new Glazing (to Best Practice) Loft insulation - 27mm Loft insulation 25-27mm Loft insulation 5-27mm Loft insulation 75-27mm Loft insulation 1-27mm Pre76 cavity wall insulation cavity wall insulation Post '83 cavity wall insulation Solid wall insulation DIY floor insulation Improve airtightness Insulate primary pipework Insulate cylinder to high performance Investment needed per household - Cardiff Blaenau Gwent Bridgend Caerphilly Cardiff Merthyr Tydfil Monmouthshire Neath Port Talbot Newport Rhondda, Cynon, Taff Swansea The Vale of Glamorgan Torfaen Table A.9 : Normalised figures of the investment needed per household in each local authority. High fuel cost scenario, EMR grid decarbonisation profile, 7% interest rate, taxation included. Highlight where the greatest potential lies per measure Identify areas that are in need of investment for multiple measures Provide an overview of cost-effectiveness Compare scenarios Legend : Maximum Minimum Five colour scale from maximum (red) to minimum (green) values Colour coded per column i.e. where is the greatest need for investment per household.

18 Glazing - single to new Glazing - old double to new Glazing (to Best Practice) Loft insulation - 27mm Loft insulation 25-27mm Loft insulation 5-27mm Loft insulation 75-27mm Loft insulation 1-27mm Pre76 cavity wall insulation cavity wall insulation Post '83 cavity wall insulation Solid wall insulation DIY floor insulation Improve airtightness Insulate primary pipework Insulate cylinder to high performance Investment needed per household - Manchester Bolton Bury Manchester Oldham Rochdale Salford Stockport Tameside Trafford Wigan Table A.9 : Normalised figures of the investment needed per household in each local authority. High fuel cost scenario, EMR grid decarbonisation profile, 7% interest rate, taxation included. Highlight where the greatest potential lies per measure Identify areas that are in need of investment for multiple measures Provide an overview of cost-effectiveness Compare scenarios Legend : Maximum Minimum Five colour scale from maximum (red) to minimum (green) values Colour coded per column i.e. where is the greatest need for investment per household.

19 Discussion points to take away a compositional downscale based on statistical information can provide useful insights about the retrofit needs and potential at the local authority level there is a need for a mid-level approach and stakeholder involvement The study has only considered a number of measures; limitations and assumptions are inherent in the modelling process; periodic review of the cost and technology data in necessary; a representative statistical sample of the stock is crucial.

20 Thank you for your attention Prof Malcolm Eames ' +44 () * EamesM@cardiff.ac.uk