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Energy disaggregation for SMEs using recurrence quantification analysis

Hattam, L. and Vukadinovic Greetham, D. (2018) Energy disaggregation for SMEs using recurrence quantification analysis. In: ACM e-Energy 2018, 12 Jun 2018, Karlsruhe, Germany, pp. 610-617.

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Official URL: http://doi.org/10.1145/3208903.3210280

Abstract/Summary

Energy disaggregation determines the energy consumption of individual appliances from the total demand signal, which is recorded using a single monitoring device. There are varied approaches to this problem, which are applied to different settings. Here, we focus on small and medium enterprises (SMEs) and explore useful applications for energy disaggregation from the perspective of SMEs. More precisely, we use recurrence quantification analysis (RQA) of the aggregate and the individual device signals to create a two-dimensional map, which is an outlined region in a reduced information space that corresponds to ‘normal’ energy demand. Then, this map is used to monitor and control future energy consumption within the example business so to improve their energy efficiency practices. In particular, our proposed method is shown to detect when an appliance may be faulty and if an unexpected, additional device is in use.

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
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:76848

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