Paper Conference

Proceedings of Building Simulation 2017: 15th Conference of IBPSA


The Socio-Economics and Energy Demand – United Kingdom Model (SEED-UK) Understanding the Dynamics, Diversity and Socio-Economics of the UK Domestic Stock

Trevor Sweetnam1, Catalina Spataru1, Mark Barrett1
1UCL Energy Institute, University College London, 14 Upper Woburn Place, London, WC1H ONN, UK

Abstract: Domestic energy demand is driven by the patterns of energy services required in the home as people go about their daily lives. Understanding these patterns, both how they combine with the physical determinants of energy demand, such as the building stock, and how they vary amongst our society is important when designing time of use tariffs and demand response programs. This paper presents the Socio-Economics and Energy Demand – United Kingdom (SEED-UK) model, a dynamic model of the UK domestic stock. The model is built using a bottom-up framework combining both statistical and physics based techniques to create daily and seasonal electricity and heat demand profiles at a 10 minute time step as well as estimates of total consumption for a series of household types and sizes. The model synthesis a number of previously developed models and approaches and capitalises on a number of large datasets describing the UK population and energy demand in the UK which have been summarised and linked in order to create probabilistic relationships for example between socio-economic groups, appliance sets and dwelling type, the ‘technical environment’. The dynamics of energy services demand within this ‘technical environment’ are driven by a simulation of household activity which allows electricity, hot water and heating demand patterns to be simulated. Model performance is evaluated using a dataset which contains the gas and electricity demand profiles of 15,000 UK domestic customers. This paper presents the resulting electricity and heat demand profiles which highlight subtle differences between the consumption patterns of socio-economic groups. Understanding and quantifying these differences and the diversity of demand between and within groups provides important data for the design of time of use tariffs and demand response programs.
Pages: 309 - 318