Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach

Non-intrusive load monitoring (NILM) is a set of techniques that aims to decompose the aggregate energy consumptions of a household into the energy consumed by the respective individual appliances. When some of the home appliances have power consumptions levels that overlap with each other, it becom...

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Main Authors: Aiad, Misbah, Lee, Peng Hin
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/137056
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1370562020-02-17T08:46:27Z Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach Aiad, Misbah Lee, Peng Hin School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Non-intrusive Load Monitoring Energy Disaggregation Non-intrusive load monitoring (NILM) is a set of techniques that aims to decompose the aggregate energy consumptions of a household into the energy consumed by the respective individual appliances. When some of the home appliances have power consumptions levels that overlap with each other, it becomes a challenging problem to disaggregate the energy consumed by each of these appliances. In this work, we present an approach that split the clusters of the overlapping energy consumptions into the respective energy consumed by the individual appliances. The proposed approach involves firstly to analyze the cohesion of devices clusters to determine if a cluster should be split into two clusters. The proposed cluster splitting approach was tested on cases of overlapping devices clusters from six real houses available from the REDD public data sets. The results showed that the performance of the proposed approach depends on the degree of overlapping of the devices clusters, on whether the clusters are tight or loose and on the sizes of the clusters. The proposed approach can be applied to a clustering-based load disaggregation method as a subsequent step to deal with situations of overlapping appliances consumptions, so as to improve the overall energy disaggregation accuracy. Accepted version 2020-02-17T08:46:27Z 2020-02-17T08:46:27Z 2018 Journal Article Aiad, M., & Lee, P. H. (2018). Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach. Sustainable Cities and Society, 43, 487-494. doi:10.1016/j.scs.2018.08.020 2210-6707 https://hdl.handle.net/10356/137056 10.1016/j.scs.2018.08.020 2-s2.0-85054030961 43 487 494 en Sustainable Cities and Society © 2018 Elsevier Ltd. All rights reserved. This paper was published in Sustainable Cities and Society and is made available with permission of Elsevier Ltd. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Non-intrusive Load Monitoring
Energy Disaggregation
spellingShingle Engineering::Electrical and electronic engineering
Non-intrusive Load Monitoring
Energy Disaggregation
Aiad, Misbah
Lee, Peng Hin
Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach
description Non-intrusive load monitoring (NILM) is a set of techniques that aims to decompose the aggregate energy consumptions of a household into the energy consumed by the respective individual appliances. When some of the home appliances have power consumptions levels that overlap with each other, it becomes a challenging problem to disaggregate the energy consumed by each of these appliances. In this work, we present an approach that split the clusters of the overlapping energy consumptions into the respective energy consumed by the individual appliances. The proposed approach involves firstly to analyze the cohesion of devices clusters to determine if a cluster should be split into two clusters. The proposed cluster splitting approach was tested on cases of overlapping devices clusters from six real houses available from the REDD public data sets. The results showed that the performance of the proposed approach depends on the degree of overlapping of the devices clusters, on whether the clusters are tight or loose and on the sizes of the clusters. The proposed approach can be applied to a clustering-based load disaggregation method as a subsequent step to deal with situations of overlapping appliances consumptions, so as to improve the overall energy disaggregation accuracy.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Aiad, Misbah
Lee, Peng Hin
format Article
author Aiad, Misbah
Lee, Peng Hin
author_sort Aiad, Misbah
title Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach
title_short Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach
title_full Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach
title_fullStr Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach
title_full_unstemmed Energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach
title_sort energy disaggregation of overlapping home appliances consumptions using a cluster splitting approach
publishDate 2020
url https://hdl.handle.net/10356/137056
_version_ 1681047489076002816