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Developing insight from commercial 
data to support #Census2022 
BSPS Conference – September 2014 
Andy Newing a.newing@so...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Overview 
2
Census2022: Extracting value from near real time …….. RGS Aug 2014 
What we are trying to do: Census2022 
 UK Census 2011...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Smart metering 
• Universal mandate 
• Quasi-real time...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Smart metering 
5 
Smart 
Gas 
Meter 
Smart 
Electrici...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Electricity Load profiles 
• Household composition & c...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Generating area based household 
statistics and indica...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Smart meter-like dataset
Census2022: Extracting value from near real time …….. RGS Aug 2014 
UoS Energy Monitoring Study (UoS-E) 
9 
 Smart meter-...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
10 
Descriptive Analysis 
1-2 persons vs 3+ Midweek: N...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Analytically: Load profile indicators 
11
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Evening consumption factor (ECF) 
Midweek (Tuesday – T...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Predicting household 
characteristics
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Inferring household characteristics 
Presumption of av...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Inferring household characteristics 
using classificat...
Census2022: Extracting value from near real time …….. RGS Aug 2014
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Generating area based 
statistics
Census2022: Extracting value from near real time …….. RGS Aug 2014 
In an ideal world… 
18 
This project
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Realising the ‘added value’ from 
domestic smart meter...
Census2022: Extracting value from near real time …….. RGS Aug 2014 
Thank you 
 http://www.energy.soton.ac.uk/tag/census2...
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Developing insight from commercial data to support #Census2022

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Paper presented at British Society for Population Studies Conference, 8th September 2014, University of Winchester

Published in: Data & Analytics
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Developing insight from commercial data to support #Census2022

  1. 1. Developing insight from commercial data to support #Census2022 BSPS Conference – September 2014 Andy Newing a.newing@soton.ac.uk Ben Anderson b.anderson@soton.ac.uk (@dataknut) Sustainable Energy Research Group
  2. 2. Census2022: Extracting value from near real time …….. RGS Aug 2014 Overview 2
  3. 3. Census2022: Extracting value from near real time …….. RGS Aug 2014 What we are trying to do: Census2022  UK Census 2011/2021 evolution  Timeliness & cost  Challenges  Finding new ways to deliver the Census – ‘Census-like’  Opportunities  New kinds of data  New kinds of social indicators - ‘Census-plus’  More frequently 3
  4. 4. Census2022: Extracting value from near real time …….. RGS Aug 2014 Smart metering • Universal mandate • Quasi-real time • High temporal resolution • Geo-coded • Reveals actual behaviors • Near 100% coverage 4
  5. 5. Census2022: Extracting value from near real time …….. RGS Aug 2014 Smart metering 5 Smart Gas Meter Smart Electricity Meter WAN DCC Utilities and Authorised Third Parties 3 In Home Display(s) Utility World managed by the utility Consumer World managed by the consumer 2 1 Bills etc. SMHAN Smart Meter Home Area Network Comms Hub Consumer Gateway(s) •Appliances •Consumer HAN •Internet •Services •Future See also http://www.gov.uk/government/policies/helping-households-to-cut-their-energy-bills/supporting-pages/smart-meters
  6. 6. Census2022: Extracting value from near real time …….. RGS Aug 2014 Electricity Load profiles • Household composition & characteristics • Ownership and use of appliances • Habits and routines 6
  7. 7. Census2022: Extracting value from near real time …….. RGS Aug 2014 Generating area based household statistics and indicators Household Load Profiles Infer household characteristics Aggregate to small area geographies
  8. 8. Census2022: Extracting value from near real time …….. RGS Aug 2014 Smart meter-like dataset
  9. 9. Census2022: Extracting value from near real time …….. RGS Aug 2014 UoS Energy Monitoring Study (UoS-E) 9  Smart meter-like household dataset  n=180  Repeated surveys:  characteristics, behaviors and attitudes  1 second level power import  Sample: October 2011  ~ 500m records (1 second)  Cleaned & checked  Aggregated (mean power)  ~ 250,000 records (half hourly)
  10. 10. Census2022: Extracting value from near real time …….. RGS Aug 2014 10 Descriptive Analysis 1-2 persons vs 3+ Midweek: No children vs 1-2 vs 3+ Midweek: Respondent in employment vs not
  11. 11. Census2022: Extracting value from near real time …….. RGS Aug 2014 Analytically: Load profile indicators 11
  12. 12. Census2022: Extracting value from near real time …….. RGS Aug 2014 Evening consumption factor (ECF) Midweek (Tuesday – Thursday) Ratio of mean 30 minute evening peak power import (4pm – 8pm) to off peak power import Ψ note: n= 5 12 ECF All households Employed Not in active employment All households 2.13 1.64 No Children 2.21 2.54 2.09 With Children 2.31 2.29 1.30Ψ
  13. 13. Census2022: Extracting value from near real time …….. RGS Aug 2014 Predicting household characteristics
  14. 14. Census2022: Extracting value from near real time …….. RGS Aug 2014 Inferring household characteristics Presumption of availability via administrative sources • Exploratory analysis suggests clear links but poor explanatory/predictive power • However … improvements in model fit are encouraging given limitations of the dataset
  15. 15. Census2022: Extracting value from near real time …….. RGS Aug 2014 Inferring household characteristics using classification • Classification / cluster Profile analysis Indicators • Applied within electricity sector to cluster households based on their consumption • Our interest is in underlying characteristics • Partitional clustering technique (k-means) Consumption driven clusters Link to characteristics of interest
  16. 16. Census2022: Extracting value from near real time …….. RGS Aug 2014
  17. 17. Census2022: Extracting value from near real time …….. RGS Aug 2014 Generating area based statistics
  18. 18. Census2022: Extracting value from near real time …….. RGS Aug 2014 In an ideal world… 18 This project
  19. 19. Census2022: Extracting value from near real time …….. RGS Aug 2014 Realising the ‘added value’ from domestic smart metering 19 Smart Gas Meter Smart Electricity Meter WAN DCC Utilities and Authorised Third Parties 3 In Home Display(s) Utility World managed by the utility Consumer World managed by the consumer 2 1 Bills etc. SMHAN Smart Meter Home Area Network Comms Hub Consumer Gateway(s) •Appliances •Consumer HAN •Internet •Services •Future See also http://www.gov.uk/government/policies/helping-households-to-cut-their-energy-bills/supporting-pages/smart-meters
  20. 20. Census2022: Extracting value from near real time …….. RGS Aug 2014 Thank you  http://www.energy.soton.ac.uk/tag/census2022/  Ben Anderson b.anderson@soton.ac.uk (@dataknut)  Andy Newing a.newing@soton.ac.uk 20

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