Anderson, B, Lin, S, Newing, A orcid.org/0000-0002-3222-6640 et al. (2 more authors) (2017) Electricity consumption and household characteristics: Implications for census-taking in a smart metered future. Computers, Environment and Urban Systems, 63. pp. 58-67. ISSN 0198-9715
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 two smart meter-like datasets of half-hourly domestic electricity consumption before reporting on the results from a multilevel modelling-based analysis of the same data. 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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | census; smart meter; transactional data; big data; households |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Jun 2016 09:40 |
Last Modified: | 23 Jun 2023 22:07 |
Published Version: | https://dx.doi.org/10.1016/j.compenvurbsys.2016.06... |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.compenvurbsys.2016.06.003 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:100949 |