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

McKenna, Eoghan; Few, Jessica; Webborn, Ellen; Anderson, Ben; Elam, Simon; Shipworth, David; Cooper, Adam; Pullinger, Martin; Oreszczyn, Tadj

doi:10.1016/j.enbuild.2022.111845

Cited by 34 publications

(14 citation statements)

References 47 publications

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“…Data collection is ongoing and future editions will provide updated smart meter data. compare the SERL data to other domestic energy datasets in the UK, finding a much wider array of energy demand co-variates and more detailed energy use data than had previously been reported in the literature, while McKenna et al (2022) find that the covariates within the SERL Observatory provide good explanatory power for the variation in daily energy demand.…”

Section: Investigating the 'Energy Performance Gap'mentioning

confidence: 77%

The over-prediction of energy use by EPCs in Great Britain: A comparison of EPC-modelled and metered primary energy use intensity

Few¹,

MANOUSELI²,

McKenna³

et al. 2023

Preprint

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This analysis compares the difference between the Energy Performance Certificate (EPC)-modelled and smart meter measured annual energy use on a like-for-like basis in 1,374 gas-heated British households selected from the Smart Energy Research Lab (SERL) Observatory. EPCs and metered energy use were converted to primary energy use intensity to provide a comparison of the same quantity for the first time.We show that EPCs predict substantially and significantly more energy use than metered in homes in Great Britain. EPC bands A and B show no statistically significant difference, but all other bands show a statistically significant and increasing gap as EPC rating decreases. Average energy use in low efficiency bands is very similar, despite large differences in EPC-modelled energy use. This difference persists after removing homes matching the EPC model assumptions regarding occupancy, thermostat set-point and whole-home heating; suggesting that differences in modelled and actual behaviour are unlikely to fully explain the discrepancy. EPCs are a core tool in the residential energy sector, and the gap between EPC-modelled and metered energy use could have a significant impact on policy, research and industry. Future research should investigate this discrepancy and its implications, and action should be taken to improve EPCs.

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Section: Investigating the 'Energy Performance Gap'mentioning

confidence: 77%

The over-prediction of energy use by EPCs in Great Britain: A comparison of EPC-modelled and metered primary energy use intensity

Few¹,

MANOUSELI²,

McKenna³

et al. 2023

Preprint

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“…31 This data is available for research purposes, and has been used to explore how domestic energy relates to variables from EPCs and household questionnaires. 32 Alongside NEED, there are several other longrunning documents on UK housing characteristics. Most notably EHS (the English Housing Survey) and EFUS (the Energy Follow Up Survey).…”

Section: Domestic Energy Use In the Ukmentioning

confidence: 99%

Producing domestic energy benchmarks using a large disaggregate stock model

Godoy-Shimizu,

Liddiard,

Evans

et al. 2024

Building Services Engineering Research and Technology

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Within the UK, domestic buildings account for 16% of total national emissions. Considerable improvements to the performance of the existing building stock will be necessary in the context of the UK’s commitment to emissions reductions, and for this to be achieved successfully and efficiently will require an improved understanding of the current performance of the stock. This paper presents an analysis of metered gas and electricity use from 808,559 dwellings with detailed building characteristic data in London, showing how energy use can be examined using a highly detailed, fully disaggregate building stock model. New gas and electricity benchmarks have been produced for houses (split by the level of attachment) and flats, for both gas- and electrically-heated properties. The paper shows how energy use varies with form, and how the choice of units influences the relative performance of different types. Comparing gas use across the types, for example, when calculated as kWh/m2, consumption follows building compactness, but when calculated as kWh/household, the trends follow building size. Finally, the paper examines how energy use varies with building thermal performance, using the Heat Loss Parameter (HLP), a standardised measure which accounts for thermal transfer through building envelopes as well as via air flow. Practical Application: This paper presents domestic energy consumption benchmarks based on measured not modelled data, produced from a large sample of London houses and flats. Results are shown for different dwelling types and heating fuels. Additionally, the relationship between gas use and envelope thermal performance is explored. The results will hopefully be beneficial for researchers, policy-makers and designers interested in better understanding current domestic energy use, and informing decisions about future improvements to energy efficiency within the stock. This paper also provides details for anyone interested in the production of the domestic benchmarks for the CIBSE benchmarking tool.

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“…Studies on the impact of the first lockdown applied simple methods which, while able to deliver results quickly, were unable to account for different weather conditions during lockdown 1 compared with the preceding weeks or the same period in the previous year. Weather is known to be a significant driver of domestic electricity and gas demand [27], and the weather conditions were unusual during lockdown 1 [21]. The most robust UK study of this period [5] was limited to a sample of 280 social housing properties in Cornwall, mostly with a retired or non-working household member.…”

Section: Aims and Paper Outlinementioning

confidence: 99%

“…Linear interpolation was used to generate half-hourly datapoints from the hourly weather data in the SERL Observatory (see 5.2.1. in the Appendix). Temperature, solar irradiance, and rainfall were selected to be the predictor weather variables, as these were deemed most relevant to energy consumption [27]. Following interpolation, means were calculated for each period of the day and each day.…”

Section: Weather Datamentioning

confidence: 99%

The impact of COVID-19 on household energy consumption in England and Wales from April 2020 – March 2022

Zapata-Webborn¹,

Pullinger²,

McKenna³

et al. 2023

Preprint

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The COVID-19 pandemic changed the way many people lived, worked, and studied around the world, both during and after the lockdowns. Changes to daily routines affected domestic electricity and gas use. While early studies estimated the impact of the first national lockdown, the long-term effects remain under-researched. In this paper we analyse how domestic electricity and gas consumption changed in the two years since the first UK lockdown in terms of both total demand and timing of demand. We develop counterfactual (predictive) models using elastic net regression, neural networks, and extreme gradient boosting and compare observed energy use with predicted use given weather and calendar variables for each household (508 for electricity, 326 for gas). We apply cluster analysis to identify common daily energy demand profiles and observe the changes in the proportions of households in each cluster for 3540 (electricity) and 2850 (gas) households between January 2020 and March 2022. We compare the results for different subsamples, such as those with and without children or working adults, households with different levels of financial wellbeing, and households in different Energy Performance Certificate (EPC) bands. We find that the pandemic increased electricity consumption throughout the two-year period, and increased gas consumption during the winter lockdowns. Demand profiles for weekdays became more similar to those on weekends for households with children or with adults in work. On average electricity consumption was still around 5% higher than predicted at the start of 2022, largely due to increased use in households with children. On average, gas consumption was lower than predicted during winter 2021/22, which may be attributable to rising gas prices.

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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

Cited by 34 publications

References 47 publications

The over-prediction of energy use by EPCs in Great Britain: A comparison of EPC-modelled and metered primary energy use intensity

The over-prediction of energy use by EPCs in Great Britain: A comparison of EPC-modelled and metered primary energy use intensity

Producing domestic energy benchmarks using a large disaggregate stock model

The impact of COVID-19 on household energy consumption in England and Wales from April 2020 – March 2022

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