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Exploring socioeconomic and temporal characteristics of British and German residential energy demand

McKenna, R., Kleinebrahm, M., Yunusov, T., Lorincz, M. J. and Torriti, J. (2018) Exploring socioeconomic and temporal characteristics of British and German residential energy demand. In: British Institute of Energy Economics 2018, 18-19 September 2018, Oxford, UK.

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The British and German residential sectors account for similar fractions of national energy demand and carbon emissions. They also exhibit underlying differences in the building stock, fuel split, tenure and household load profiles. The temporal habits in British and German households are also quite different, which is challenging to measure due to the paucity of German smart meter data. This contribution takes this background as a starting point to explore some of the temporal and socioeconomic characteristics of residential energy demand in Britain and Germany. The Centre for Renewable Energy Systems Technology (CREST) residential load profile generator is updated for the UK and extended to the German context and validated with standard load profiles, providing high levels of accuracy according standard normalized root-mean-squared error (NRMSE) measures. The paper then analyzes the energy-related activities of different socioeconomic household groups based on with National Time Use Survey data from both countries. The analysis showed some clear differences between groups and countries, which are a reminder of the importance of non-energy policy (e.g. school hours) in determining peaks. As well as encountering useful insights into international differences in energy related behaviour, the results showed some key differences within specific socioeconomic groups, such as single persons, families with children, and pensioners. Further work will focus on extending the German CREST model to include a German appliance stock, as well as allocating these appliances according to households’ socioeconomic characteristics. The definition of the groups themselves needs to be refined, perhaps to include multiple variables and based on clustering or similar techniques, and validation with smart meter data.

Item Type:Conference or Workshop Item (Paper)
Divisions:Science > School of the Built Environment > Energy and Environmental Engineering group
ID Code:79760
Uncontrolled Keywords:Time use data, residential sector, load profiles, energy demand


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