The effect of age on residential energy demand

Panel: 8. Dynamics of consumption

This is a peer-reviewed paper.

Authors:
Matthias Deutsch, Prognos AG, Germany
Philip Timpe, Dortmund University of Technology
Faculty of Spatial Planning
Department of Utility Systems, Germany

Abstract

Residential energy demand is influenced by several factors. For example, building characteristics, the willingness to invest in energy efficiency measures, the way individuals inhabit their dwellings, as well as households’ socio-economic and demographic attributes – including age. All else being equal, do households with older members demand more or less energy than those consisting of younger members? Answering this question is particularly relevant for long-term, capital-intensive infrastructure planning for grid-connected energy supply systems, such as gas or district heating, given that over- or underestimating future demand may involve considerable cost. With an ageing population, Germany will need to plan its infrastructure accordingly. Yet, determining the effect of age is challenging because energy consumption statistics are usually not available at the level of individual households; and even if they are, it is difficult to match them with adequate socio-demographic data.

Overcoming those difficulties is at the core of an ongoing research project in Germany that brings together micro data on energy consumption, socio-demographic household characteristics as well as building data, to measure the effect of age on residential energy demand for heating and electricity. Whereas the energy consumption data stems from municipal public utilities and housing companies, the remaining data is provided by a German statistical office. They have been collected during the German Census in 2011 in the context of the EU-wide Population and Housing Census. This pilot project will use the advanced methods of the statistical office to complement existing census data with additional data on households’ energy consumption for three cities of different size. The paper will describe the method used and will discuss its limitations and potential for replication, to improve our understanding of the effect of age on residential energy demand.