Improving the prediction of UK domestic energy-demand using annual consumption-data

Baker, Keith; Rylatt, R. M.

doi:10.1016/j.apenergy.2007.09.004

Cited by 149 publications

(75 citation statements)

References 1 publication

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“…Solutions for reducing CO 2 emissions from the housing stock must account for the variety in age, size, quality, composition, function, and social value of the physical buildings, as well as the different needs, expectations, and budgets of home owners and occupiers (Dowson et al, 2012). Domestic fuel consumption is strongly related to the size and composition of the household, as well as the type and structure of the property itself (Baker and Rylatt, 2008;Gough, 2013). Whilst the UK appears to be performing strongly in meeting its carbon reduction and GHG targets overall, trends in domestic energy consumption and GHG emissions have been erratic since 2009.…”

Section: Energy Efficiency In the English Housing Stockmentioning

confidence: 99%

Delivering energy efficiency and carbon reduction schemes in England: Lessons from Green Deal Pioneer Places

2015

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Section: Energy Efficiency In the English Housing Stockmentioning

confidence: 99%

Delivering energy efficiency and carbon reduction schemes in England: Lessons from Green Deal Pioneer Places

2015

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“…Baker and Rylatt's (2007) study of 148 houses across Leicester and Sheffield showed that the number of bedrooms accounted for almost 35 % in the variation in household gas and electricity consumption. A similar study of 36 low energy houses in Milton Keynes revealed that the top 30 % of households by income used more energy than the remaining 70 % of households combined (Summerfield et al 2010a).…”

Section: Identifying Energy (In)efficiencymentioning

confidence: 99%

“…Data on the physical size of houses, even at LSOA level, were not readily available and so, in keeping with other studies (see Baker andRylatt 2007, DECC 2013c), the average number of rooms per house from the 2001 Census was used to approximate house size. Although house type and tenure have been shown to be strongly correlated with the size of house (DECC 2013c), tenure and house types were included from the 2001 Census to confirm this.…”

Section: Explanatory Variablesmentioning

confidence: 99%

Benchmarking and tracking domestic gas and electricity consumption at the local authority level

et al. 2015

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Government, local authority and industry initiatives to improve the energy efficiency of housing stocks are central to national and international commitments to reduce carbon dioxide emissions. To be effective, initiatives need to target homes which, given their location, size, fuel type and occupancy, use more energy than expected. This paper illustrates how energy efficiency benchmarks can be developed that account for these factors and highlights the shortcomings of relying on simple energy consumption statistics. The study uses existing data (with national coverage) and the measured electricity and gas consumption of groups consisting of, on average, 500-700 households to benchmark and track domestic gas and electricity consumption across England. Multiple regression models, which account for 65 % of the variation in domestic gas consumption and 73 % of domestic electricity variation, are used to derive the benchmarks. The actual gas and electricity consumption of each group of homes is compared against the derived benchmark and an energy efficiency index presented. The approach enables changes in energy efficiency to be tracked temporally, for example to assess the effectiveness of government, local authority or industry initiatives. National and city-scale patterns of energy efficiency are also discussed.

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“…The type of dwelling, tenure, household composition, location and socio-economic characteristics of the residents are also extremely important. Baker and Rylatt (2008) analysed gas and electricity consumption and identified the most statistically significant indicators to be the number of bedrooms and regular home working.…”

Section: Energy Use and Appliance Ownership In Ireland 1 Introductionmentioning

confidence: 99%

Energy use and appliance ownership in Ireland

2010

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This paper examines domestic energy use and appliance ownership in Ireland. Regression analyses on a large micro-dataset reveal how household characteristics can help explain the ownership of energy using appliances. The location of the household, the number of rooms and household income are important factors, as are certain characteristics of the highest earner in the household such as education level and age. We also find evidence that household income, number of persons, accommodation characteristics, region, and age of the highest earner can help explain domestic electricity use, even after taking account of the household's endowment of appliances. The level of demand for domestic heating is also associated with housing tenure and the employment status of the highest earner.Corresponding Author: Sean.Lyons@esri.ie

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Improving the prediction of UK domestic energy-demand using annual consumption-data

Cited by 149 publications

References 1 publication

Delivering energy efficiency and carbon reduction schemes in England: Lessons from Green Deal Pioneer Places

Delivering energy efficiency and carbon reduction schemes in England: Lessons from Green Deal Pioneer Places

Benchmarking and tracking domestic gas and electricity consumption at the local authority level

Energy use and appliance ownership in Ireland

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