Excess? Exploring social, structural and behavioural drivers of energy demand in areas of high combined energy consumption or “how much energy is more than enough?”

Panel: 6. Transport and mobility

Authors:
Tim Chatterton, United Kingdom
Jillian Anable, University of Leeds, United Kingdom
Milena Buchs, University of Leeds, United Kingdom
Robin Lovelace, University of Leeds, United Kingdom
Karen Lucas, University of Leeds, United Kingdom
Caroline Mullen, University of Leeds, United Kingdom
Malcolm Morgan, University of Leeds, United Kingdom
Muhammed Adeel, University of Leeds, United Kingdom

Abstract

Previous work within the MOT (Motoring and vehicle Ownership and Trends) project identified correlations at a spatial level between energy consumption through the use of private vehicles and through domestic gas and electricity. High vehicle energy areas also tend to be high domestic consumption areas, with the top 5% highest consumption areas using around 2.5 times as much direct energy per capita as the lowest.

Due to growing electrification, energy demand from private vehicles is becoming increasingly linked to domestic consumption. There are approximately 200,000 electric vehicles in the UK fleet (including plug-in hybrids) – this is around 0.5% of the light duty fleet. Around 75% of these are in private ownership. Both for assessing energy footprints and to deal with strategic issues such as local grid capacity, there is a need to look at energy consumption in a holistic manner, investigating relations between energy use in the home and from transport. With the rapid rise of options for virtual mobility, personal transport has become less necessary for participating in a range of activities, yet this does not necessarily reduce overall energy use. Linked analyses are essential to assess where and how consumption in one domain may become displaced to another e.g. technologies that permit home working may reduce transport use but increase energy consumption in homes.

The ‘Excess?’ project, is being undertaken within the Centre for Research into Energy Demand Solutions (CREDS). It is using a mixed-methods approach to better understand the causes of disproportionately high consumption, i.e. can it be explained by structural and systemic factors (e.g. poor public transport, inefficient or precarious housing), social factors (e.g. demographic characteristics) or behavioural factors (e.g. social expectations and norms, or lifestyle choices). The aim is both to highlight risks to distribution networks from clustering of new electric technologies, and to examine justice issues around unequal patterns of energy demand. Whilst much work on energy demand has focussed on meeting basic needs (e.g. fuel poverty and transport vulnerability), Excess? has its sights on examining high consumption in order help identify where energy consumption can be reduced ‘furthest and fastest’.

The presentation will cover the initial identification and characterisation of high consumption areas, and a review of high consumption households from national surveys.

Spatial Data Analysis

Aggregated data based on readings from over 70m domestic energy meters and vehicle odometers will be used to map patterns of energy consumption across England. These will be analysed in terms of socio-demographic and geographic data at the LSOA level (av. size 672 households), exploring relationships with housing type, household composition, levels of accessibility and public transport provision. The data will also be used to model down to an Output Area (OA size = 129 households) level using Geographically Weighted Regression.

National Survey Data Analysis

Data from a range of national surveys (incl. National Transport Survey, Living Costs and Food Survey, Understanding Society) will be used to explore the relationships at a household level between transport and domestic consumption that lie behind aggregated spatial data, and the structural, socio-demographic and behavioural factors driving high consumption.

Local Area Household Analysis

Then, using a framework derived from the above analyses, alongside an exploration of theoretical framings of excess, a number of areas will be identified for face-to-face methods to provide a qualitative exploration of reasons for high energy consumption.

The authors gratefully acknowledge support from UK Research and Innovation through the Centre for Research into Energy Demand Solutions, grant reference number EP/R 035288/1.