Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/57411
Type of publication: research article
Type of publication (PDB): Straipsnis kitose duomenų bazėse / Article in other databases (S4)
Field of Science: Informatika / Informatics (N009)
Author(s): Užupytė, Rūta;Krilavičius, Tomas;Babarskis, Tomas
Title: Identification of electricity consumption profiles based on smart meters data
Is part of: International journal of design, analysis and tools for integrated circuits and systems (IJDATICS). Hong Kong : Solari Co, 2017, vol. 6, no. 1
Extent: p. 44-47
Date: 2017
Note: eISSN 2071-2987
Keywords: Electricity patterns;Load profiling;Time–series clustering;Clustering technique
Abstract: The changes and evolution of the electricity distribution has provided new possibilities to the electricity providers for developing a better marketing and trading strategies. A key aspect for designing specific tariff structures is the identification of customers groups exhibiting similar consumption patterns. This paper presents a new methodology for the classification of electricity customers on the basis of their electrical behaviour. Approach is based on the periodicity analysis and well known clustering technique – k–means. The paper presents the classification results obtained on a set of 3753 industrial users, whose consumption has been monitored for 3 years
Internet: http://ijdatics.datics.net/current_issues/IJDATICS_06_01/IJDATICS_06_01_11.pdf
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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