What can DECC’s NEED data tell us about what drives domestic electricity consumption and how could data linkage help? (ADRN 2016)

What can DECC’s NEED data tell us about what drives domestic electricity consumption and how could data linkage help? (ADRN 2016)

Paper presented at ADRN Research Conference, London, 3rd June 2016

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Ben Anderson

June 03, 2016
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  1. What can DECC’s NEED data tell us about what drives

    domestic electricity consumption and how could data linkage help? Ben Anderson - b.anderson@soton.ac.uk (@dataknut) Engineering & Environment (Energy & Climate Change) Gabi Durrant, Vivian So School of Social Sciences
  2. The menu § The problem § The current approach(es) §

    What do we want? § When do we want it? 2
  3. Andrewglaser at English Wikipedia Energy demand Infrastructures & institutions Need,

    entitlement and norms Social practices The problem… Variation
  4. • Differences in • socio-demographics • appliances & infrastructures •

    habits Between household: • Changes in • socio-demographics • appliances & infrastructures • habits Within household: Two types of variation: 4
  5. •Suppliers •NEED 2005 - 2012 Administrative: •English Housing Survey •Living

    Costs & Food Survey •Understanding Society Survey: Two types of data: 5 Public Use anonymised sample: 49,815 Licensed Use anonymised sample: 4,086,448
  6. •Suppliers •NEED 2005 - 2012 Administrative: •English Housing Survey •Living

    Costs & Food Survey •Understanding Society Survey: Two types of data: 6
  7. •Suppliers •NEED 2005 - 2012 Administrative: •English Housing Survey •Living

    Costs & Food Survey •Understanding Society Survey: Current approach (I) 7 Licensed Use anonymised sample: 4,086,448
  8. 1 10 100 1000 10000 100000 2005 2006 2007 2008

    2009 2010 2011 2012 2013 Econs kWh Electricity Max Electricity Mean Electricity Median Electricity Min ECUK 2014 Non-corrected 'average' electricity NEED: Levels & Trends 8 Source: DECC (2014) NEED End User License Data, error bar = +/- 1 s.d; DECC (2014) Energy Consumption in the UK (2014)
  9. 0.00% 1.00% 2.00% 3.00% 4.00% 5.00% 6.00% 2005 2006 2007

    2008 2009 2010 2011 2012 % of households M(issing) G (> 25,000) L (< 200) NEED: Exclusions 9 Source: DECC (2014) NEED End User License Data, includes ‘L’ and ‘G’ ‘Cleansing’: Some were ‘missing’ ‘Too high’ > 25,000 kWh -> ‘G’ ‘Too low’ < 200 kWh -> ‘L’
  10. 97% 98% 98% 99% 99% 100% 100% 1 to 50

    51-100 101-150 Over 151 Gas Other A or B C D E F G Floor area m2 Main fuel EE Band Valid Econs Excluded > 25,000 Exclusion analysis I 10 Source: DECC (2014) NEED End User License Data
  11. NEED 2012: Electricity consumption 11 Source: DECC (2014) NEED End

    User License Data, log Electricity consumption for 2012 only, multivariate OLS regression using STATA Variables: region, economy 7, fuel, property age, type, floor area, EE band, loft insulation, wall type, 10% sample (n = 408,644) -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 North East (contrast) North West Yorkshire & The Humber East Midlands West Midlands East of England London South East South West Wales Economy 7 (No) Economy 7 (Yes) Main heat fuel (Gas) Main heat fuel (Other) before 1930 (contrast) 1930-1949 1950-1966 1967-1982 1983-1995 1996 onwards Detached house (contrast) Semi-detached house End terrace house Mid terrace house Bungalow Flat (inc. maisonette) 1 to 50 m2 (contrast) 51-100 m2 101-150 m2 Over 151 m2 Band A or B (contrast) Band C Band D Band E Band F Band G Loft: Less than 150mm Loft: Greater than or equal to… Cavity wall Other wall b (coefficient)
  12. NEED 2012: Electricity consumption 12 -0.05 0 0.05 0.1 0.15

    0.2 0.25 North East (contrast) North West Yorkshire & The Humber East Midlands West Midlands East of England London South East South West Wales b (coefficient) -0.1 0 0.1 0.2 Band A or B (contrast) Band C Band D Band E Band F Band G Loft: Less than 150mm Loft: Greater than or equal to 150mm Cavity wall Other wall b (coefficient) Source: DECC (2014) NEED End User License Data, log Electricity consumption for 2012 only, multivariate OLS regression using STATA Variables: region, economy 7, fuel, property age, type, floor area, EE band, loft insulation, wall type, 10% sample (n = 408,644)
  13. NEED 2012: Electricity consumption 13 0 0.2 0.4 0.6 Economy

    7 (No) Economy 7 (Yes) Main heat fuel (Gas) Main heat fuel (Other) b (coefficient) 0 0.2 0.4 0.6 0.8 1 1 to 50 m2 (contrast) 51-100 m2 101-150 m2 Over 151 m2 b (coefficient) -0.3 -0.2 -0.1 0 0.1 0.2 before 1930 (contrast) 1930-1949 1950-1966 1967-1982 1983-1995 1996 onwards Detached house (contrast) Semi-detached house End terrace house Mid terrace house Bungalow Flat (inc. maisonette) b (coefficient) Source: DECC (2014) NEED End User License Data, log Electricity consumption for 2012 only, multivariate OLS regression using STATA Variables: region, economy 7, fuel, property age, type, floor area, EE band, loft insulation, wall type, 10% sample (n = 408,644)
  14. Adjusted r sq = 0.15 => 85% of the variance

    is unexplained What’s missing? But 14 Source: DECC (2014) NEED End User License Data, log Electricity consumption for 2012 only, multivariate OLS regression using STATA Variables: region, economy 7, fuel, property age, type, floor area, EE band, loft insulation, wall type, 10% sample (n = 408,644)
  15. People! 15 Source: DECC (2014) NEED End User License Data,

    Electricity consumption for 2012 only
  16. •Suppliers •NEED 2005 - 2012 Administrative: •English Housing Survey •Living

    Costs & Food Survey •Understanding Society Survey: How can we add people? 16
  17. Reported electricity £/month 17 Source: Living Costs and Food Survey

    2002-2012, multivariate OLS regression on reported electricity bill (n = 74, 309) -2 -1.5 -1 -0.5 0 0.5 1 1.5 Semi (Detached) Terrace Flat/maisonette Other 2 rooms (1 room) 3 rooms 4 rooms 5+ rooms Rent from council (Own) Social rent Private rent/other -2 -1.5 -1 -0.5 0 0.5 1 1.5 HRP NS-SEC 2 (NS-SEC 1) HRP NS-SEC 3 HRP Inactive HRP Retired HRP single person HRP other N Children < 14 N Children 14-16 HRP 25-34 (16-24) 35-44 45-54 55-64 65-74 75+
  18. -2 -1.5 -1 -0.5 0 0.5 1 1.5 Total raindays

    3 year anomaly low (previous quarter) Mean rainfall 3 year anomaly high (previous quarter) Mean sunshine 3 year anomaly high (previous quarter) And we can add ‘climate’ context 18 Source: Living Costs and Food Survey 2002-2012, multivariate OLS regression on reported electricity bill (n = 74, 309) Metoffice regional weather data Drier than usual Sunnier than usual
  19. This is reported expenditure Unknown error We need linked survey

    & admin data But 19 Source: Living Costs and Food Survey 2002-2012 Source: SPRG/ARCC-Water Survey, 2011 www.sprg.ac.uk
  20. Electricity consumption: to summarise • But we only have ‘dwelling’

    data NEED: we can’t explain much variance • Check for reported consumption errors • Consumption ‘context’ and dwelling • Cross-sectional: Differences between households LCFS <-> NEED linkage • Check for reported consumption errors • Consumption ‘context’ and dwelling • Longitudinal: Difference within and between over time Understanding Society <-> NEED linkage 20
  21. Questions? § @dataknut § Original 2014 'End User License' version

    of the data: – available from: UK DATA ARCHIVE: Study Number 7518 - National Energy Efficiency Data-Framework, 2014 http://discover.ukdataservice.ac.uk/catalogue/?sn=7518 – Detailed documentation: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/332169/need_anony mised_dataset_accompanying_documentation.pdf – Full coding details of variables at: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/315189/need_datase t_look_ups.xlsx § Code: github.com/dataknut/DECC-data/tree/master/NEED 21