Residential Electricity and Gas Demand in Great Britain: Archetypal Demand Profiles and Household Explanatory Factors

Abstract

Understanding household energy demand patterns is essential for effective energy system planning and policy design. Building on previous cluster analysis of common daily demand profiles, this study identifies household electricity and gas ‘demand archetypes’ which capture the typical summer and winter weekday demand profiles for each home using modal daily demand profiles. We apply logistic regression with household survey data to identify potential explanatory factors. Our study uses half-hourly smart meter data from the Smart Energy Research Lab Observatory in Great Britain between November 2021 and August 2022; 9844 households with electricity data and 7251 with gas data after filtering. We find that household gas demand archetypes show much greater variability between seasons than electricity archetypes, consistent with seasonal variations in gas heating needs. Household demand archetypes with a morning and/or evening peak are the most prevalent in both seasons for electricity and gas. However, a substantial share of households exhibits highly variable demand profiles in both seasons, indicating inconsistent and possibly flexible routines. Logistic regression analysis reveals strong correlations between microgeneration and a midday trough in electricity demand, while electric vehicle ownership increases the likelihood of a variable demand profile. Financial wellbeing and family structure also show correlations with demand archetypes, with lower-income households more likely to exhibit variable and peak-time gas archetypes; perhaps indicating efforts to reduce costs. Our findings highlight the value of analysing household electricity and gas demand archetypes for different seasons and offer important insights for demand-side energy management, forecasting and policy.