Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/44591
Type of publication: Konferencijų tezės nerecenzuojamuose leidiniuose / Conference theses in non-peer-reviewed publications (T2)
Field of Science: Matematika / Mathematics (N001)
Author(s): Krilavičius, Tomas;Užupytė, Rūta
Title: Application of clustering for electricity usage patterns detection
Is part of: Data analysis methods for software systems : 6th international workshop, Druskininkai, Lithuania, December 4-6, 2014 : [abstracts book]. Vilnius : Vilnius University
Extent: p. 31-31
Date: 2014
ISBN: 9789986680505
Abstract: Electricity usage patterns are important for suppliers in order to ensure efficient electricity distribution and pricing, and for users to save costs. Smart meters provide high granularity electricity usage data (e.g., hourly), which can be used to extract patterns of daily/weekly/monthly/ yearly electricity usage. In this research we propose a method for grouping electricity users based on hourly electricity usage data, based on the k-means clustering and periodicity analysis, with semi-automatic parameters selection based on adequacy measure. We illustrate the method with 1500 electricity users 3 years’ data, discuss pros and cons of the methods, and future plans. Acknowledgements We thank Binar Solutions for cooperation and European Social Fund and the Republic of Lithuania (grant number VP1-3.2-ŠMM-01-K-02-002) for funding
Internet: https://hdl.handle.net/20.500.12259/44591
Affiliation(s): Baltijos pažangių technologijų institutas, Vilnius
Informatikos fakultetas
Taikomosios informatikos katedra
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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