Journal article
An unsupervised training method for non-intrusive appliance load monitoring
- Abstract:
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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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- Files:
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(Accepted manuscript, pdf, 565.4KB)
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- Publisher copy:
- 10.1016/j.artint.2014.07.010
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Authors
Funding
Bibliographic Details
- Publisher:
- Elsevier Publisher's website
- Journal:
- Artificial Intelligence Journal website
- Publication date:
- 2014-07-30
- Acceptance date:
- 2014-07-23
- DOI:
- EISSN:
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1872-7921
- ISSN:
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0004-3702
- Source identifiers:
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690274
Item Description
- Keywords:
- Pubs id:
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pubs:690274
- UUID:
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uuid:6e52938f-522c-4eb5-9c33-be39998370ed
- Local pid:
- pubs:690274
- Deposit date:
- 2017-04-20
Terms of use
- Copyright holder:
- Elsevier
- Copyright date:
- 2014
- Notes:
- © 2014 Elsevier B.V. All rights reserved. This is the Accepted Manuscript version of the article. The final version is available online from Elsevier at: https://doi.org/10.1016/j.artint.2014.07.010
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