Domestic smart metering infrastructure and a method for home appliances identification using low‐rate power consumption data

Paraskevas, I ORCID: https://orcid.org/0000-0002-9547-6444, Barbarosou, M, Fitton, R ORCID: https://orcid.org/0000-0002-7514-6819 and Swan, W ORCID: https://orcid.org/0000-0001-8780-6557 2021, 'Domestic smart metering infrastructure and a method for home appliances identification using low‐rate power consumption data' , IET Smart Cities, 3 (2) , pp. 91-106.

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Abstract

The deployment of domestic smart metering infrastructure in Great Britain provides the opportunity for identification of home appliances utilising non-intrusive load monitoring methods. Identifying the energy consumption of certain home appliances generates useful insights for the energy suppliers and for other bodies with a vested interest in energy consumption. Consequently, the domestic smart metering system, which is an integral part of the smart cities' infrastructure, can also be used for home appliance identification purposes taking into account the limitations of the system. In this article, a step-by-step description on accessing data directly from the domestic Smart Meter via an external Consumer Access Device is described, as well as an easy-to-implement method for identifying commonly used home appliances through their power consumption signals sampled at a rate similar to the rate available by the domestic smart metering system. The experimental results indicate that the combination of time domain with frequency domain features extracted either from the 1D/2D Discrete Fourier Transform or the Discrete Cosine Transform provides improved recognition performance compared to the case where the time domain or the frequency domain features are used separately.

Item Type:	Article
Schools:	Schools > School of Computing, Science and Engineering
Journal or Publication Title:	IET Smart Cities
Publisher:	Wiley
ISSN:	2631-7680
Related URLs:	Publication
Depositing User:	USIR Admin
Date Deposited:	26 May 2021 09:09
Last Modified:	16 Feb 2022 07:12
URI:	https://usir.salford.ac.uk/id/eprint/60405

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