CarbonBuzz and other data sets: what is energy data

CarbonBuzz and other datasets: what is the data telling us? Paul Ruyssevelt Professor of Energy and Building Performance UCL Energy InsAtute [email protected] Contents • 
Energy Data and Energy Epidemiology Embed data for Retrofit for the Future CarbonBuzz data Sharing data and informaAon -­‐ CBx ‘In theory,
theory and practice are the same,
but in practice,
Santa Fe Institute in Factor Four
they’re not’
But why? 1.  Physics applied incorrectly? 2.  Not built/refurbished as modelled/theory 3.  Do not understand changes in occupant behaviour The UCL Energy InsAtute launched in June 2009 •  70 staff and 130 MRes/MSc/PhD students •  PorXolio of over £32m of funding, 10% from industry •  Vibrant Doctoral Training Programme •  Made important findings which it has presented to government, other academics and stakeholders •  Focused on the analysis and interpretaAon of actual energy use data from buildings The performance gap in housing Mean Dwelling Gas Demand per Bedroom (kWh/yr) 12,000 10,000 8,000 6,000 4,000 2,000 0 pre 1900 1900-­‐29 1930-­‐49 1950-­‐66 1967-­‐75 1976-­‐82 1983-­‐90 1991-­‐95 Dwelling Age Predicted¥ Actual* Adj. Predicted* Note: *Actual demand is drawn from randomly selected 10% representaAve sample from HEED linked to gas consumpAon (N=374,616); ¥Predicted demand is drawn from EHS 2008 SAP; †Predicted demand is adjusted using predicted/actual fuel vs fuel expenditure/income intensity curve algorithm. Solid wall U-­‐values Solid walls are 27% of stock Measured mean U-­‐value 1.3 Wm-­‐2K-­‐1 NormaAve U-­‐value 2.1 Wm-­‐2K-­‐1 Analysis of field trial data revealed under-­‐
performance of post-­‐insulated solid wall properAes Stamford Brook – thermal
envelope defects –
convective bypasses
(Lowe et al 2007)
Energy Epidemiology Energy epidemiology draws on the established methodological and analy>cal framework of epidemiology developed in the health sciences Energy epidemiology for buildings adopts and adapts the epidemiological approach in order to: •  Describe and measure the distribu>on of energy demand at the populaAon level; •  idenAfy the rela>onship between factors and their influence on the distribuAon of energy demand; •  provide an over-­‐arching approach for all the disciplines involved. UCL has established the RCUK Centre for Energy Epidemiology (CEE) to: •  undertake primary data collecAon; •  advise on data collecAon; •  provide secure and ethical curaAon of a wealth of administraAve, commercial and research data; •  link, develop and use innovaAve research methods; •  support a structured research programme on energy demand intended to achieve a major reducAon in UK carbon emissions •  provide the secretariat for a new internaAonal network DATASETS embed dataset embed dataset Target: 80% CO2 reducAons rarely achieved equivalent reducAon 50% 80% Performance related to air-­‐Aghtness? Performance related technologies? Strongest correlaAon with good energy performance: • 
Good planning to anAcipate challenges Detailed design with use of PHPP Good communicaAons throughout Good liaison with residents Good site management and reporAng CarbonBuzz – idenAfying and resolving the performance gap Launched 6th June 2013: 800 buildings, 200 organisa;ons, 60 case studies The performance gap according to CarbonBuzz CarbonBuzz projects registered with energy data Projects 160 140 120 100 80 60 40 20 0 CarbonBuzz performance gap for all buildings in the dataset Mean energy use kWh/m2 (all buildings in CB dataset) 100 14% 90 80 70 60 50 40 52% 130% 62% 30 20 10 0 General Office General Office Schools (design) Schools (actual) University University General Retail General Retail (design) (actual) campus (design) campus (actual) (design) (actual) Electrcity Fossil Fuel Fossil Fuel performance gap for matched buildings (with design and actual data) Fossil Fuel kWh/m2 Design vs Actual for matched buildings 120 100 80 -­‐34% 25% 8% 60 40 20 0 General Office Schools Design Fossil Fuel Use Median University campus Actual Fossil Fuel Use Median Electricity performance gap for matched buildings (with design and actual data) Electricity kWh/m2 Design vs Actual for matched buildings 180 160 140 120 100 232% 80 116% 90% 60 40 20 0 General Office Schools Design Electric Use Median University campus Actual Electric Use Median How do we close this performance gap Share data Develop insights IdenAfy specific issues Discuss and develop soluAons Involve all parAes – designers, clients, academics, government, etc. and more than once a year at Ecobuild…. • 
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