Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/16612
Title: [AAM REQ publisher permission LKR 28/06/2018] Application of cluster analysis for enhancing power consumption awareness in smart grids
Authors: Coletta, G
Vaccaro, A
Villacci, D
Zobaa, AF
Issue Date: 2018
Publisher: Academic Press
Citation: Application of Smart Grid Technologies Case Studies in Saving Electricity in Different Parts of the World, 2018, pp. 397 - 414
Abstract: The conceptualization of computing paradigms aimed at converting the power demand data into actionable information, allowing the prosumer to have a full understanding of the available information, represents a timely and relevant issue to address in the context of the future smart grids. In the light of this need, this Chapter outlines the potential role of self-organizing models based on clustering analysis for classifying the load profiles, correlating them with the endogenous measured variables, and identifying irregularities in energy consumptions. The benefits deriving by the application of the proposed framework on complex load patterns have been assessed by detailed experimental results obtained on a real case study. Keywords: load monitoring, situational awareness, smart grids computing, data clustering, data driven techniques.
URI: http://bura.brunel.ac.uk/handle/2438/16612
DOI: http://dx.doi.org/10.1016/B978-0-12-803128-5.00012-X
ISBN: 0128031433
ISSN: 12
12
12
12
http://dx.doi.org/10.1016/B978-0-12-803128-5.00012-X
http://dx.doi.org/10.1016/B978-0-12-803128-5.00012-X
Other Identifiers: 12
12
Appears in Collections:Dept of Electronic and Computer Engineering Embargoed Research Papers

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