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Impacts of raw data temporal resolution using selected clustering methods on residential electricity load profiles

Abstract:

There is growing interest in discerning behaviors of electricity users in both the residential and commercial sectors. With the advent of high-resolution time-series power demand data through advanced metering, mining this data could be costly from the computational viewpoint. One of the popular techniques is clustering, but depending on the algorithm the resolution of the data can have an important influence on the resulting clusters. This paper shows how temporal resolution of power demand ...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1109/TPWRS.2014.2377213

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Institution:
University of Oxford
Department:
Oxford, MPLS, Oxford e-Research Centre
Role:
Author
More by this author
Institution:
University of Oxford
Department:
Oxford, MPLS, Oxford e-Research Centre
Role:
Author
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
IEEE Transactions on Power Systems Journal website
Volume:
30
Issue:
6
Pages:
3217-3224
Publication date:
2014-12-19
Acceptance date:
2014-11-22
DOI:
EISSN:
1558-0679
ISSN:
0885-8950
URN:
uuid:fe57b392-8f13-4396-84e5-8f81d80ecdcd
Source identifiers:
502555
Local pid:
pubs:502555
Paper number:
6

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