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2017 | OriginalPaper | Chapter

Unsupervised Energy Disaggregation of Home Appliances

Authors : Kondwani M. Kamoto, Qi Liu, Xiaodong Liu

Published in: Cloud Computing and Security

Publisher: Springer International Publishing

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Abstract

Energy management is a growing concern especially with the increasing growth of smart appliances within the home. Energy disaggregation is an ongoing challenge to discover the appliance usage by examining the energy output of a household or building. Unsupervised NILM presents the additional challenge of energy disaggregation without any reliance on training data. A key issue to address in Unsupervised NILM is the discovery of appliances without a priori information. In this paper we present a new approach based on Competitive Agglomeration (CA) which incorporates the good qualities of both hierarchical and partitional clustering. Our proposed energy disaggregation algorithm makes use of CA in order to discover appliances without prior information about the number of appliances. Validation with experimental data from the Reference Energy Disaggregation Dataset (REDD), and comparison with recent state of the art Unsupervised NILM indicates that our proposed algorithm is effective.

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Metadata
Title
Unsupervised Energy Disaggregation of Home Appliances
Authors
Kondwani M. Kamoto
Qi Liu
Xiaodong Liu
Copyright Year
2017
Book
Cloud Computing and Security

Print ISBN: 978-3-319-68504-5

Electronic ISBN: 978-3-319-68505-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-68505-2_34

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