Accessibility navigation


Graph-based algorithms for comparison and prediction of household-level energy use profiles

Charlton, N., Vukadinovic Greetham, D. and Singleton, C. (2013) Graph-based algorithms for comparison and prediction of household-level energy use profiles. In: IEEE International Workshop on Intelligent Energy Systems, 14 Nov 2013, Wienna, pp. 119-124.

[img] Text - Accepted Version
· Restricted to Repository staff only
· The Copyright of this document has not been checked yet. This may affect its availability.

645kB

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://dx.doi.org/10.1109/IWIES.2013.6698572

Abstract/Summary

We present an efficient graph-based algorithm for quantifying the similarity of household-level energy use profiles, using a notion of similarity that allows for small time–shifts when comparing profiles. Experimental results on a real smart meter data set demonstrate that in cases of practical interest our technique is far faster than the existing method for computing the same similarity measure. Having a fast algorithm for measuring profile similarity improves the efficiency of tasks such as clustering of customers and cross-validation of forecasting methods using historical data. Furthermore, we apply a generalisation of our algorithm to produce substantially better household-level energy use forecasts from historical smart meter data.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Centre for the Mathematics of Human Behaviour (CMOHB)
ID Code:33465

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

Page navigation