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Permanent link (DOI): https://doi.org/10.7939/R3Z60C95M

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Decomposition Techniques for Non-intrusive Home Appliance Load Monitoring Open Access

Descriptions

Other title
Subject/Keyword
Multi-label Classification
Sequence Matching
Non-intrusive load monitoirng
Delay Coordinate embedding
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Tabatabaei, Seyed Mostafa
Supervisor and department
Scott Dick (Electrical and Computer Engineering)
Wilsun Xu (Electrical and Computer Engineering)
Examining committee member and department
Biao Huang (Chemical and Material Engineering)
Di Niu (Electrical and Computer Engineering)
Department
Department of Electrical and Computer Engineering
Specialization
Energy Systems
Date accepted
2014-01-28T13:43:20Z
Graduation date
2014-06
Degree
Master of Science
Degree level
Master's
Abstract
Energy-saving is a key element of Smart Grid. By encouraging consumers to moderate their energy demands, utilities can make more efficient use of their generation assets, and reduce total fuel consumption. For this purpose, we must provide homeowners with appliance energy consumption data, without requiring sensors on each appliance. This means that energy consumption from the house main feeder must be disaggregated into individual appliances. In this thesis, two novel methodologies for disaggregating household power consumption are evaluated. The first method is multi-label classification, which is used to predict appliance participation in the power signal. The second method is a new signature-based sequence matching algorithm. Two sets of features have been used. In the time domain, a delay embedding of the observed power signal is constructed. The second feature set is a wavelet decomposition of the power signal, using Haar wavelet. We evaluate our techniques and features on two synthetic datasets, and two households from REDD.
Language
English
DOI
doi:10.7939/R3Z60C95M
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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