Covid-19 lockdown: impacts on GB electricity demand and CO₂ emissions

Abstract

In early 2020 a wide range of social and economic restrictions were implemented in most countries in response to the global coronavirus pandemic (Covid-19). This paper uses national electricity generation data to examine the extent to which overall British electricity consumption deviated from 'normal' consumption patterns during the UK's spring lockdown period, and how the combination of consumption reduction and variation in carbon intensity affected greenhouse gas emissions (GHG) associated with electricity consumption. The paper shows that ongoing trends in the reduction of electricity demand and generation carbon intensity mean that lower year-on-year demand and lower emissions would have been expected even in the absence of Covid-19. Controlling for this, the paper estimates lockdowndriven below-trend electricity reductions of up to 20% in the morning peak period, 11% in the daytime and 9% in the evening peak period in April, declining to 6%, 4% and 4%, respectively, by June. These correspond to marked reductions in morning (06:00-08:00 hours) and daytime demand during all restriction periods studied, but relatively smaller reductions in evening demand, and some evidence of a relative increase on Friday and Saturday evenings. PRACTICE RELEVANCE The observed changes in demand are likely to be repeated in future national or local restriction periods and provide insights of value for grid and local distribution network management. This is especially true if such restrictions are required in spring 2021, as looks increasingly likely, but are also relevant to the winter 2020-21 heating season, which is likely to exacerbate the demand for electric heating, although gas remains the dominant heating fuel source in homes. However, unlike fossil fuel-based transport, the changes observed do not translate to direct emissions reductions due to the mixture of fuels used to generate electricity in Britain. Electricity generation emissions were either close to or above the trend during this period, and the effect is especially noticeable for the traditionally carbon-intensive evening peak period.

Survey study on energy use in UK homes during Covid-19

“…For example, electricity demand in China dropped by 13% in February 2020, in Italy by about 28% in March-April 2020 and in the UK by 12-13% during the same period. Focusing on the UK and controlling for general trends in the consumption of electricity, an overall reduction in electricity was estimated, with reductions of up to 20% in the morning peak period, 11% in the daytime and 9% in the evening peak period in April (Anderson & James 2021).…”

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

“…[6], [12]). Historical trends from 2017 -2020 were compared by [13], [20]. These approaches removed the initial (pre-lockdown) effects of the pandemic from the control group but ignored weather fluctuations between years.…”

“…They reported a fall in both national electricity and gas demand during lockdown 1 (15.6% +/-1.8% electricity reduction and 12.0 +/-0.8% gas reduction) and to a much lesser extent during lockdown 2 (6.3% +/-2.3% electricity reduction and 4.1 +/-1.1% gas reduction). [13] analysed the change in national electricity demand by time of day, with reductions of up to 20% during the morning peak, 11% during the daytime, and 9% in the evening peak during April 2020. These changes had reduced to decreases of only 6% (morning peak), 4% (daytime), and 4% (evening peak) by June 2020 when lockdown restrictions were easing.…”

“…During lockdowns we might expect the greatest changes in energy demand to be on weekdays due to the closure of schools and workplaces, but our results paint a somewhat different, and unclear, picture. Figure 3 compares how energy demand is estimated to have changed 13 on weekends and weekdays. We analyse by quarter as there are fewer data points when splitting by weekends/weekdays which reduces monthly model accuracy.…”

“…The reasons for this are again, unclear. 13 Average change is calculated by taking, for each household, the mean difference between daily observed and counterfactual energy demand for each household (which form a distribution), and then take the median. and as a percentage.…”