Explaining daily total energy demand in British housing using linked smart meter and socio-technical data in a bottom-up statistical model
Explaining daily total energy demand in British housing using linked smart meter and socio-technical data in a bottom-up statistical model
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 R
2 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.
Attitudes, Behaviour, Building, Building physics, Consumption, Daily, Demand, Domestic, Electricity, Energy, Energy performance certificate, Gas, Heating, Household, Longitudinal, Mixed effects, Occupant, Random effects, Regression, Residential, Smart meter, Sociodemographic, Solar radiation, Survey, Temperature, Weather
McKenna, Eoghan
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Few, Jessica
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Webborn, Ellen
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Anderson, Ben
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Elam, Simon
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Shipworth, David
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Cooper, Adam
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Pullinger, Martin
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Oreszczyn, Tadj
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1 March 2022
McKenna, Eoghan
6b4322f5-c975-4a03-a332-3d199df865c3
Few, Jessica
a69af079-c278-45f5-a218-223cb8899122
Webborn, Ellen
f210ccbe-36c5-4b88-9651-43246eba8157
Anderson, Ben
01e98bbd-b402-48b0-b83e-142341a39b2d
Elam, Simon
de1073f3-0d77-4379-a77b-484239aaf73e
Shipworth, David
5be0ad54-c260-4ec7-9ad1-5f9a70db31e2
Cooper, Adam
bc52a8bc-eb6d-410c-990b-a705fee6322d
Pullinger, Martin
2214983c-8b79-4a98-85f9-16f2fd04ba8f
Oreszczyn, Tadj
cd7ee772-c397-41af-877b-74d2f2e795d9
McKenna, Eoghan, Few, Jessica, Webborn, Ellen, Anderson, Ben, Elam, Simon, Shipworth, David, Cooper, Adam, Pullinger, Martin and Oreszczyn, Tadj
(2022)
Explaining daily total energy demand in British housing using linked smart meter and socio-technical data in a bottom-up statistical model.
Energy and Buildings, 258, [111845].
(doi:10.1016/j.enbuild.2022.111845).
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 R
2 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.
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Submitted date: 15 September 2021
Published date: 1 March 2022
Additional Information:
Funding Information:
This work has been funded by EPSRC through grant EP/P032761/1. There are over 30 individuals across 8 organisations in the SERL Consortium (University College London, the University of Essex (UK Data Archive), University of Edinburgh, Cardiff University, Loughborough University, Leeds Beckett University, the University of Southampton and the Energy Saving Trust) who have contributed to the development of SERL and thus the content of this paper. Particular thanks go to the SERL technical team at the UK Data Archive: Darren Bell, Deirdre Lungley, Martin Randall and Jacob Joy and to SERL Consortium Manager James O'Toole at UCL. We acknowledge support from the SERL Independent Advisory Board, Data Governance Board and Research Programme Board which played critical role in the establishment and ethical operation of SERL. The SERL Observatory includes European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 data. Neither the European Commission nor the European Centre for Medium-Range Weather Forecasts is responsible for any use that may be made of the Copernicus information or data it contains.
Funding Information:
This work has been funded by EPSRC through grant EP/P032761/1. There are over 30 individuals across 8 organisations in the SERL Consortium ( University College London , the University of Essex (UK Data Archive), University of Edinburgh, Cardiff University, Loughborough University, Leeds Beckett University, the University of Southampton and the Energy Saving Trust) who have contributed to the development of SERL and thus the content of this paper. Particular thanks go to the SERL technical team at the UK Data Archive: Darren Bell, Deirdre Lungley, Martin Randall and Jacob Joy and to SERL Consortium Manager James O’Toole at UCL.
Funding Information:
We acknowledge support from the SERL Independent Advisory Board, Data Governance Board and Research Programme Board which played critical role in the establishment and ethical operation of SERL.
Publisher Copyright:
© 2022 Elsevier B.V.
Keywords:
Attitudes, Behaviour, Building, Building physics, Consumption, Daily, Demand, Domestic, Electricity, Energy, Energy performance certificate, Gas, Heating, Household, Longitudinal, Mixed effects, Occupant, Random effects, Regression, Residential, Smart meter, Sociodemographic, Solar radiation, Survey, Temperature, Weather
Identifiers
Local EPrints ID: 451751
URI: http://eprints.soton.ac.uk/id/eprint/451751
ISSN: 0378-7788
PURE UUID: 17d0cce8-a946-4119-95e7-76c2852ff65b
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Date deposited: 25 Oct 2021 16:31
Last modified: 17 Mar 2024 06:51
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Contributors
Author:
Eoghan McKenna
Author:
Jessica Few
Author:
Ellen Webborn
Author:
Simon Elam
Author:
David Shipworth
Author:
Adam Cooper
Author:
Martin Pullinger
Author:
Tadj Oreszczyn
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