DocumentCode
2616834
Title
Clustering bus load curves
Author
Salgado, Ricardo Menezes ; Ohishi, Takaaki ; Ballini, Rosangela
Author_Institution
UNICAMP, Campinas, Brazil
fYear
2004
fDate
10-13 Oct. 2004
Firstpage
1251
Abstract
This paper proposes the clustering of a set of busses through a fuzzy c-means clustering approach. The utilization of fuzzy techniques in a clustering problem aims the attainment of a partition fuzzy in the data set, allowing degrees of relationship between different elements of the set, this way, an element can belong to more than one group with different membership value. In this paper the clustering algorithm aims at exploring data characteristics and determining groups composed by busses with similar bus daily load. Results show the efficiency of the clustering method, where the data was classified into distinct groups such as: commercial, residential and industrial consumption profiles.
Keywords
busbars; fuzzy reasoning; bus load curves; data set; fuzzy c-means clustering; industrial consumption profiles; Autoregressive processes; Clustering algorithms; Clustering methods; Data analysis; Data mining; Databases; Fuzzy sets; Neural networks; Partitioning algorithms; Signal processing algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Systems Conference and Exposition, 2004. IEEE PES
Print_ISBN
0-7803-8718-X
Type
conf
DOI
10.1109/PSCE.2004.1397652
Filename
1397652
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