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

Abstract

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

“…We would expect to see a stronger trend in the gas analysis, as heating requirements should be more strongly related to EPC rating. That said, recent analysis has shown that the energy use in EPC bands C, D, F and G typically do not reflect the energy use predicted by EPCs, and the average energy use between these bands is very similar [33]. Figure 7 reveals that dwellings in bands D-G increased gas use by more than those in bands B and C during October 2020 -March 2021 (including the winter lockdowns).…”

“…For both fuels, around half had an Energy Performance Certificate (EPC), among which the most and least efficient dwellings are overrepresented in our samples. Recent evidence suggests that the EPC provides a good indication of actual energy use for the most efficient bands (A and B), but not for all other bands [33]. Thus, the overrepresentation of the most efficient bands is likely to mean that there are more efficient homes in the sample than expected, but the over-representation of homes in less efficient EPC bands does not necessarily mean that these homes are particularly inefficient.…”

“…We also trialled different time resolutions: half-hourly, by period of the day (see Table 2), and daily. The eight time periods were constructed by identifying times of the day when average energy use is approximately constant [34]. Due to the night-time period starting at 11pm, all days were redefined to start at 11pm rather than midnight in all the counterfactual modelling analysis presented here.…”

Winter Demand Falls as Fuel Bills Rise: Understanding the Energy Impacts of the Cost-of-Living Crisis on British Households

“…The most and least efficient dwellings are over-represented in our sample, at the expense of dwellings in EPC band C, while band B dwellings are represented fairly (and the most common category). It is unclear how this may affect the results, particularly as recent analysis has shown that EPC band is a poor predictor of energy use for bands C-G [77]. In general the SERL dataset struggled to be representative by dwelling and tenure type due to the uneven rollout of smart metering [50], and thus our sample is biased towards detached dwellings and owner-occupiers and under-represents flats/ apartments and renters.…”

“…We use the 6th edition Smart Energy Research Lab (SERL) [48][49][50][51][52] datasets comprising electricity, gas (where available), survey and weather data for around 13,000 homes in Great Britain. Initially households were removed from the sample who indicated having installed/replaced a heat pump or acquired an electric vehicle (EV) in the previous 12 months in the 2023 SERL Energy Survey (described below) as the predictive models are trained on the previous winter (before the heat pump installation or EV charging began/increased).…”