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An unsupervised training method for non-intrusive appliance load monitoring

Abstract:

Non-intrusive appliance load monitoring is the process of disaggregating a household's total electricity consumption into its contributing appliances. In this paper we propose an unsupervised training method for non-intrusive monitoring which, unlike existing supervised approaches, does not require training data to be collected by sub-metering individual appliances, nor does it require appliances to be manually labelled for the households in which disaggregation is performed. Instead, we prop...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.artint.2014.07.010

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Institution:
University of Oxford
Oxford college:
St Anne's College
Role:
Author
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Grant:
EP/I011587/1/
Publisher:
Elsevier Publisher's website
Journal:
Artificial Intelligence Journal website
Publication date:
2014-07-30
Acceptance date:
2014-07-23
DOI:
EISSN:
1872-7921
ISSN:
0004-3702
Source identifiers:
690274
Keywords:
Pubs id:
pubs:690274
UUID:
uuid:6e52938f-522c-4eb5-9c33-be39998370ed
Local pid:
pubs:690274
Deposit date:
2017-04-20

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