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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.

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.

To contain the spread of COVID-19, governments across the world imposed partial or complete lockdowns. National energy demand decreased in periods of lockdowns; however, as people spent more time at home, residential energy use likely increased. This paper reports results of a survey study with N = 1016 participants in the UK about their energy use practices during the first lockdown in March 2020. Results indicated that self-reported heating behaviours did not substantially change during lockdown. Regarding appliance use, in particular the duration of usage for TVs and computing equipment has increased and has spread out more over the day. Being less able to manage financially was correlated with greater usage of the smart-meter in-home-display and greater attempt to save energy was positively correlated with greater usage of the in-home display though correlations were small. In summary, the results indicate that home energy use behaviours, in particular around heating, did not change as much as might have been expected, which might at least partly be explained by the comparatively warm weather during the first lockdown. Corroborating the survey findings with actual energy data is the next essential step to understand findings in more detail.