The diversity of residential electricity demand – a comparative analysis of metered and simulated data

Ramirez-Mendiola, J. L. ORCID: https://orcid.org/0000-0001-7666-7440, Grünewald, P. and Eyre, N. (2017) The diversity of residential electricity demand – a comparative analysis of metered and simulated data. Energy and Buildings, 151. pp. 121-131. ISSN 0378-7788 doi: 10.1016/j.enbuild.2017.06.006

Abstract/Summary

A comparative study between simulated residential electricity demand data and metered data from theUK Household Electricity Survey is presented. For this study, a high-resolution probabilistic model wasused to test whether this increasingly widely used modelling approach provides an adequate represen-tation of the statistical characteristics the most comprehensive dataset of metered electricity demandavailable in the UK. Both the empirical and simulated electricity consumption data have been analysedon an aggregated level, paying special attention to the mean daily load profiles, the distribution of house-holds with respect to the total annual demands, and the distributions of the annual demands of particularappliances. A thorough comparison making use of both qualitative and quantitative methods was madebetween simulated datasets and it’s metered counterparts. Significant discrepancies were found in thedistribution of households with respect to both overall electricity consumption and consumption ofindividual appliances. Parametric estimates of the distributions of metered data were obtained, and theanalytic expressions for both the density function and cumulative distribution are given. These can beincorporated into new and existent modelling frameworks, as well as used as tools for further analysis.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/90544
Item Type	Article
Refereed	Yes
Divisions	Science > School of the Built Environment No Reading authors. Back catalogue items Science > School of the Built Environment > Energy and Environmental Engineering group
Publisher	Elsevier
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