Abstract
This paper assesses the feasibility of determining key household characteristics based on temporal load profiles of household electricity demand. It is known that household characteristics, behaviours and routines drive a number of features of household electricity loads in ways which are currently not fully understood. The roll out of domestic smart meters in the UK and elsewhere could enable better understanding through the collection of high temporal resolution electricity monitoring data at the household level. Such data affords tremendous potential to invert the established relationship between household characteristics and temporal load profiles. Rather than use household characteristics as a predictor of loads, observed electricity load profiles, or indicators based on them, could instead be used to impute household characteristics. These micro level imputed characteristics could then be aggregated at the small area level to produce ‘census-like’ small area indicators. This work briefly reviews the nature of current and future census taking in the UK before outlining the household characteristics that are to be found in the UK census and which are also known to influence electricity load profiles. It then presents descriptive analysis of a large scale smart meter-like dataset of half-hourly domestic electricity consumption before reviewing the correlation between household attributes and electricity load profiles. The paper then reports the results of multilevel model-based analysis of these relationships. The work concludes that a number of household characteristics of the kind to be found in UK census-derived small area statistics may be predicted from particular load profile indicators. A discussion of the steps required to test and validate this approach and the wider implications for census taking is also provided.
Highlights
This paper assesses the feasibility of determining key household characteristics based on temporal load profiles of household electricity demand
This work briefly reviews the nature of current and future census taking in the United Kingdom (UK) before outlining the household characteristics that are to be found in the UK census and which are known to influence electricity load profiles
The work concludes that a number of household characteristics of the kind to be found in UK census-derived small area statistics may be predicted from particular load profile indicators
Summary
Area based population statistics in the United Kingdom (UK) have historically been derived from the decadal census of housing and population. As a number of recent authors have noted large-scale geo-coded transactional datasets, such as those collected in the retail, telecommunications, finance and utilities sectors could offer opportunities to supplement census based small area statistics by supporting the delivery of area-based population statistics, and generating novel indicators at a neighbourhood level (Deville et al, 2014; Dugmore et al, 2011b; Struijs, Braaksma, & Daas, 2014). The planned universal rollout of electricity smart meters collecting at least half-hourly consumption data (DECC, 2013) means that consideration of the value of suitably anonymised and aggregated smart meter data in the production of official statistics is timely. It considers the extent to which digital trace data from the commercial sector could represent a novel tool to generate census type small-area statistics, before focusing on the use high resolution electricity consumption monitoring data collected via smart metering. Based on preliminary analyses of a ‘smart meter-like’ dataset the research highlights the potential value of the approach and discusses significant challenges and concludes by setting out a research programme which could systematically test the value of the approach
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
