Energy disaggregation for SMEs using recurrence quantification analysisHattam, 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.
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://doi.org/10.1145/3208903.3210280 Abstract/SummaryEnergy 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.
Download Statistics DownloadsDownloads per month over past year Deposit Details University Staff: Request a correction | Centaur Editors: Update this record |