DocumentCode :
635337
Title :
Deriving the optimal number of clusters in the electricity consumer segmentation procedure
Author :
Panapakidis, Ioannis P. ; Alexiadis, Minas C. ; Papagiannis, Grigoris K.
Author_Institution :
Dept. of Electr. & Comput. Eng., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece
fYear :
2013
fDate :
27-31 May 2013
Firstpage :
1
Lastpage :
8
Abstract :
This study examines a set of methods that determine the optimal number of clusters in the electricity consumer segmentation procedure. For the purpose of clustering the load curves of the consumers, we involve two algorithms of different concept and complexity, namely the Minimum Variance Method (MVM) hierarchical agglomerative algorithm and the Fuzzy C-Means (FCM). A parametric analysis takes place in order to optimize the FCM` s parameters. Apart from the two clustering algorithms, we introduce in the load profiling studies two other methods that provide indications of the number of clusters within a data sample, namely the Max-Min and the Chain-map methods. For the sake of assessing the algorithm effectiveness, we utilize the ratio of Within Cluster sum of squares to Between Cluster variation (WCBCR) adequacy measure and the Bayesian Information Criterion (BIC). We also propose an improved version of the WCBCR.
Keywords :
fuzzy set theory; load management; minimax techniques; power markets; Bayesian information criterion; MVM; WCBCR; between cluster variation; chain-map method; different concept; electricity consumer segmentation procedure; fuzzy C-mean algorithm; hierarchical agglomerative algorithm; load curve clustering; load profiling study; max-min method; minimum variance method; optimal cluster number; parametric analysis; within cluster sum of squares; Consumer classification; cluster analysis; fuzzy clustering; hierarchical clustering; load profiling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
European Energy Market (EEM), 2013 10th International Conference on the
Conference_Location :
Stockholm
Type :
conf
DOI :
10.1109/EEM.2013.6607329
Filename :
6607329
Link To Document :
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