Journal article
Clustering disaggregated load profiles using a Dirichlet process mixture model
- Abstract:
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The increasing availability of substantial quantities of power-use data in both the residential and commercial sectors raises the possibility of mining the data to the advantage of both consumers and network operations. We present a Bayesian non-parametric model to cluster load profiles from households and business premises. Evaluators show that our model performs as well as other popular clustering methods, but unlike most other methods it does not require the number of clusters to be predet...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Version of record, pdf, 1.2MB)
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- Publisher copy:
- 10.1016/j.enconman.2014.12.080
Authors
Bibliographic Details
- Publisher:
- Elsevier Publisher's website
- Journal:
- Energy Conversion and Management Journal website
- Volume:
- 92
- Pages:
- 507-516
- Publication date:
- 2015-01-16
- Acceptance date:
- 2014-12-24
- DOI:
- ISSN:
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0196-8904
Item Description
- Keywords:
- Pubs id:
-
pubs:505984
- UUID:
-
uuid:38fea267-d554-433b-9f36-2cee47870a04
- Local pid:
- pubs:505984
- Source identifiers:
-
505984
- Deposit date:
- 2016-06-06
Terms of use
- Copyright holder:
- Ramon Granell et al
- Copyright date:
- 2015
- Notes:
-
This is an open access article under the CC BY license (http://
creativecommons.org/licenses/by/4.0/).
- Licence:
- CC Attribution (CC BY)
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