Slope-based shape cluster method for smart metering load profiles

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dc.contributor.authorXiang, Yue
dc.contributor.authorHong, Juhua
dc.contributor.authorYang, Zhiyu
dc.contributor.authorWang, Yang
dc.contributor.authorHuang, Yuan
dc.contributor.authorZhang, Xin
dc.contributor.authorChai, Yanxin
dc.contributor.authorYao, Haotian
dc.date.accessioned2020-01-17T11:45:47Z
dc.date.available2020-01-17T11:45:47Z
dc.date.issued2020-01-10
dc.description.abstractCluster analysis is used to study the group of load profiles from smart meters to improve the operability in distribution network. The traditional K-means clustering analysis method employs Euclidean distance as similarity measurement, which is insufficient in reflecting the shape similarities of load profiles. In this work, we propose a novel shape cluster method based on the segmented slope of load profiles. Compared with traditional K-means and two improved algorithms, the proposed method can improve the clustering accuracy and efficiency by capturing the shape features of smart metering load profiles.en_UK
dc.identifier.citationXiang Y, Hong J, Yang Z, et al., (2020) Slope-based shape cluster method for smart metering load profiles. IEEE Transactions on Smart Grid, Volume 11, Issue 2, March 2020, pp.1809-1811en_UK
dc.identifier.issn1949-3053
dc.identifier.urihttps:doi.org/10.1109/TSG.2020.2965801
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/14940
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectCluster analysisen_UK
dc.subjectload profileen_UK
dc.subjectK-meansen_UK
dc.subjectsimilarityen_UK
dc.titleSlope-based shape cluster method for smart metering load profilesen_UK
dc.typeArticleen_UK

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