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Explaining daily energy demand in British housing using linked smart meter and socio-technical data in a bottom-up statistical model

McKenna, E; Few, J; Webborn, E; Anderson, B; Elam, S; Shipworth, D; Cooper, A; ... Oreszczyn, T; + view all (2022) Explaining daily energy demand in British housing using linked smart meter and socio-technical data in a bottom-up statistical model. Energy and Buildings , Article 111845. 10.1016/j.enbuild.2022.111845. (In press).

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Abstract

This paper investigates factors associated with variation in daily total (electricity and gas) energy consumption in domestic buildings using linked pre-COVID-19 smart meter, weather, building thermal characteristics, and socio-technical survey data covering appliance ownership, demographics, behaviours, and attitudes for two nested sub-samples of 1418 and 682 British households selected from the Smart Energy Research Laboratory (SERL) Observatory panel. Linear mixed effects modelling resulted in adjusted R2 between 63% and 80% depending on sample size and combinations of contextual data used. Increased daily energy consumption was significantly associated (p-value<0.05, VIF<5) with: households living in buildings with more rooms and bedrooms, that are older, more detached, have air-conditioning, and experience colder (more heating degree days) or less sunny weather; households with more adult occupants, more children, older adult occupants, higher heating temperature setpoints, and that do not try to save energy. The results demonstrate the value of smart meter data linked with contextual data for improving understanding of energy demand in British housing. Accredited UK researchers are invited to apply to access the data, which has recently been updated to include over 13,000 households from across Great Britain. This paper provides guidance on appropriate methods to use when analysing the data.

Type: Article
Title: Explaining daily energy demand in British housing using linked smart meter and socio-technical data in a bottom-up statistical model
DOI: 10.1016/j.enbuild.2022.111845
Publisher version: https://doi.org/10.1016/j.enbuild.2022.111845
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: building; energy; heating; gas; electricity; demand; consumption; household; residential; domestic; smart meter; daily; longitudinal; regression; mixed effects; random effects; survey; energy performance certificate; weather; temperature; solar radiation; building physics; sociodemographic; occupant; behaviour; attitudes.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/10141909
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