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.

Highlights

  • The aims of the domestic smart metering rollout in Great Britain were to enable consumers to monitor and control their energy usage and to assist in the transition of the country towards a low‐carbon economy [1]

  • To develop an end‐to‐end solution for home appliance identification which would be beneficial for both the consumer and the energy supply company harnessing the benefits of the data generated from the domestic smart metering system

  • Taking into consideration on one hand the limitations of the domestic smart metering data in terms of granularity and on the other hand the opportunity for the consumer to engage with their data, this work aims to: (i) provide a description on how the consumers can access their data from the domestic smart metering system via the MQ Telemetry Transport (MQTT) Application Programming Interface (API) through the external Consumer Access Devices (CADs) and (ii) present and test an easy‐to‐implement method for home appliance identification by utilising power consumption data with granularity similar to the granularity available by the domestic smart metering system which is 10 s

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Summary

Introduction

The aims of the domestic smart metering rollout in Great Britain were to enable consumers to monitor and control their energy usage and to assist in the transition of the country towards a low‐carbon economy [1]. The initial target of the UK government was to install smart metering systems in all houses and small businesses in Great Britain by the end of 2020 [2]. This deadline has been extended to 2024 [3, 4]. Data from approximately 21 million smart metering systems, installed in Great Britain [3], are gathered by the energy supply companies for both SMETS1 and SMETS2. To develop an end‐to‐end solution for home appliance identification which would be beneficial for both the consumer and the energy supply company harnessing the benefits of the data generated from the domestic smart metering system

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