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Energy Disaggregation for SMEs using Recurrence Quantification Analysis

Hattam, Laura and Vukadinović Greetham, Danica (2018). Energy Disaggregation for SMEs using Recurrence Quantification Analysis. In: Proceedings of the Ninth International Conference on Future Energy Systems - e-Energy '18, ACM, pp. 610–617.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1145/3208903.3210280
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Abstract

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
Copyright Holders: 2018 ACM, 2018 Danica Vukadinovic Greetham, 2018 Laura Hattam
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 55703
Depositing User: Danica Vukadinovic Greetham
Date Deposited: 07 Nov 2018 16:38
Last Modified: 27 May 2019 21:21
URI: http://oro.open.ac.uk/id/eprint/55703
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