Clustering of household occupancy profiles for archetype building models
|Title:||Clustering of household occupancy profiles for archetype building models||Authors:||Buttitta, Giuseppina
Turner, William J. N.
|Permanent link:||http://hdl.handle.net/10197/8291||Date:||Mar-2016||Abstract:||The continued penetration of renewable energy sources in electricity generation and the de-carbonization of the domestic space heating and hot water sectors is increasing the importance of demand side management (DSM). The development of end-use energy consumption models that can be easily integrated with electricity dispatch models is crucial for the assessment of the integration of supply and demand. The energy consumption of the domestic building stock is highly correlated with occupant behaviour, however the inclusion of occupant behaviour in energy models is challenging due to its highly variable nature. Nevertheless, in order to obtain reliable models of domestic energy consumption at high time resolution, the analysis of occupant behaviour patterns is fundamental. This paper aims to develop a new methodology to generate realistic occupancy patterns that can be representative of large numbers of households. This method is based on the clustering of household occupancy profiles using the UK 2000 Time Use Survey data as a case study. The occupancy profiles that result from this method can be used as input to residential building energy end-use models, thereby giving improved overall model performance.||Funding Details:||European Commission Horizon 2020||Type of material:||Conference Publication||Publisher:||Elsevier||Copyright (published version):||2016 the Authors||Keywords:||Building model;Occupancy profile;K-mode clustering||DOI:||10.1016/j.egypro.2017.03.018||Language:||en||Status of Item:||Peer reviewed||Conference Details:||8th International Conference on Sustainability in Energy and Buildings (SEB-16), Turin, Italy, 11-13 September 2016|
|Appears in Collections:||Mechanical & Materials Engineering Research Collection|
ERC Research Collection
Energy Institute Research Collection
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