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.
![]() |
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: | 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