Title :
Analysing the segmentation of energy consumers using mixed fuzzy clustering
Author :
Hanna Schäfer;Joaquim L. Viegas;Marta C. Ferreira;Susana M. Vieira;J. M. C. Sousa
Author_Institution :
IDMEC, LAETA, Instituto Superior Té
Abstract :
The current demands on the energy market, such as efficiency, sustainability and affordability increase the need for customer understanding and data analysis. This paper presents an analysis of the segmentation of electricity consumers based on the fuzzy clustering of time variant electricity consumption data and invariant features like the demographic customer information. The algorithm used is mixed fuzzy clustering (MFC), which allows integrating both variant and invariant features into one clustering. The clustering is evaluated both in its stability over the two years of data, using a entropy measurement and in its general quality given by the three clustering validity indices, Calinski-Harabasz, Davies-Bouldin and Silhouette index.
Keywords :
"Prototypes","Clustering algorithms","Mathematical model","Algorithm design and analysis","Energy consumption","Entropy","Stability analysis"
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on
DOI :
10.1109/FUZZ-IEEE.2015.7338120