DocumentCode
3105105
Title
Electricity load profile classification using Fuzzy C-Means method
Author
Prahastono, Iswan ; King, David J. ; Ozveren, C.S. ; Bradley, D.
Author_Institution
PT. PLN Indonesia, Univ. of Abertay, Dundee
fYear
2008
fDate
1-4 Sept. 2008
Firstpage
1
Lastpage
5
Abstract
This paper presents the Fuzzy C-Means (FCM) clustering method. The FCM technique assigns a degree of membership for each data set to several clusters, thus offering the opportunity to deal with load profiles that could belong to more than one group at the same time. The FCM algorithm is based on minimising a c-means objective function to determine an optimal classification. The simulation of FCM was carried out using actual sample data from Indonesia and the results are presented. Some validity index measurements was carried out to estimate the compactness of the resulting clusters or to find the optimal number of clusters for a data set.
Keywords
fuzzy set theory; load forecasting; pattern clustering; Indonesia; data set clusters; electricity load profile classification; fuzzy c-means clustering method; Business; Clustering algorithms; Clustering methods; Databases; Euclidean distance; Flowcharts; Government;
fLanguage
English
Publisher
ieee
Conference_Titel
Universities Power Engineering Conference, 2008. UPEC 2008. 43rd International
Conference_Location
Padova
Print_ISBN
978-1-4244-3294-3
Electronic_ISBN
978-88-89884-09-6
Type
conf
DOI
10.1109/UPEC.2008.4651527
Filename
4651527
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