Title :
Clustering bus load curves
Author :
Salgado, Ricardo Menezes ; Ohishi, Takaaki ; Ballini, Rosangela
Author_Institution :
UNICAMP, Campinas, Brazil
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;
Conference_Titel :
Power Systems Conference and Exposition, 2004. IEEE PES
Print_ISBN :
0-7803-8718-X
DOI :
10.1109/PSCE.2004.1397652