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
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;
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
DOI :
10.1109/UPEC.2008.4651527
