Accessibility navigation


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.

[img] Text - Accepted Version
· Restricted to Repository staff only until 19 September 2019.

452kB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Official URL: http://www.biee.org/downloads/

Abstract/Summary

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)
Refereed:No
Divisions:Faculty of Science > School of the Built Environment > Construction Management and Engineering > Innovative and Sustainable Technologies
ID Code:79760
Uncontrolled Keywords:Time use data, residential sector, load profiles, energy demand

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation