Modelling retrofit changes to the housing stock:

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Presentation to: East Midlands CAN 14 th March 2012 Presentation to: East Midlands CAN 14 th March

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Presentation transcript:

Modelling retrofit changes to the housing stock: simulating decision making and capturing geographic variation Dr Timothy Lee @MyBCU www.facebook.com/birminghamcityuniversity

Introduction Challenging 2050 target 80% reduction in CO2 emissions Housing accounts for c.28% of current emissions Therefore changes needed to existing housing if target is to be met Stock models projecting uptake of energy saving measures can aid planning towards the 2050 target @MyBCU www.facebook.com/birminghamcityuniversity

Shortcomings of current modelling No geographic variation in model stocks Eg: City centre flats have different retrofit options to off-gas rural properties Uptake rates of retrofit measures are imposed No consideration of the decision making of the dwelling owners who will actually drive the uptake of measures and therefore the energy and CO2 savings @MyBCU www.facebook.com/birminghamcityuniversity

Geographically based housing stock model Develop a test model for the North East of England (1.1 million homes) Model dwelling stock variation across the region Output area (OA) (c.150 homes) -> Lower level super output area (LSOA) (c.700) -> Medium level super output area (MSOA) (c. 3500) -> Local authority (LA) (c. 80,000) @MyBCU www.facebook.com/birminghamcityuniversity

Housing data English Housing Survey data on 935 dwellings in the North East Provides sufficient data for calculation of energy demand Decile IMD rating and 4 level ruralness scale Census Data - Output Area (OA) Built form/detachment IMD Decile Ruralness Heating fuel type @MyBCU www.facebook.com/birminghamcityuniversity

Geographic energy data DECC: Experimental data for gas and electricity use at LSOA level Data for gas and electricity use at MSOA level and LA level 1657 LSOAs in North East in 2011 Census 341 MSOAs in North East in 2011 Census 12 LAs in North East @MyBCU www.facebook.com/birminghamcityuniversity

Geographic model results @MyBCU www.facebook.com/birminghamcityuniversity

Understanding and Modelling Decision Making Retrofit measures only installed when owners decide to install Owner-occupiers Energy Saving Trust (2009) Element Energy (2008) Discrete choice survey data Multiple Criteria Decision Making Model Agent based model @MyBCU www.facebook.com/birminghamcityuniversity

Understanding and Modelling Decision Making Simple additive weighting Available technologies: Fabric Improvements, Heating System Upgrades, Renewable Energy Technologies Considers: Price, Saving, Maintenance, Disruption, Subsidy, Taxation, Recommendation @MyBCU www.facebook.com/birminghamcityuniversity

Adoption curves @MyBCU www.facebook.com/birminghamcityuniversity

Next steps Improve behavioural understanding Expand to all tenure types Integrate agents with geographic model @MyBCU www.facebook.com/birminghamcityuniversity

Thank you Any questions? timothy.lee@bcu.ac.uk @MyBCU www.facebook.com/birminghamcityuniversity