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Cluster analysis and prediction of residential peak demand profiles using occupant activity data

Abstract:

Researching the dynamics of residential electricity consumption at finely-resolved timescales is increasingly practical with the growing availability of high-resolution data and analytical methods to characterize them. One methodological approach that is popular for exploring consumption dynamics is load profile clustering. Despite an abundance of available algorithmic techniques, clustering load profiles is challenging because clustering methods do not always capture the temporal aspects of ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.apenergy.2019.114246

Authors


More by this author
Institution:
University of Oxford
Division:
SSD
Department:
SOGE
Role:
Author
ORCID:
0000-0002-3224-4574
More by this author
Institution:
University of Oxford
Division:
Social Sciences Division
Department:
SOGE
Sub department:
Environmental Change Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Social Sciences Division
Department:
SOGE
Sub department:
Environmental Change Institute
Role:
Author
Publisher:
Elsevier Publisher's website
Journal:
Applied Energy Journal website
Volume:
260
Article number:
114246
Publication date:
2019-12-11
Acceptance date:
2019-11-23
DOI:
ISSN:
0306-2619
Source identifiers:
1078041
Language:
English
Keywords:
Pubs id:
pubs:1078041
UUID:
uuid:e33ce0f7-b6d1-427c-8300-5fd959a50b6b
Local pid:
pubs:1078041
Deposit date:
2019-12-16

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