%0 Journal Article 
%A Valero Verdú, Sergio
%A Ortiz García, Mario
%A García Franco, Francisco J.
%A Encinas Redondo, Nuria
%A Gabaldón Marín, Antonio
%A Molina García, Ángel
%A Gómez Lázaro, Emilio
%T Characterization and identification of electrical customers through the use of self-organizing maps and daily load parameters
%D 2004
%U http://hdl.handle.net/10317/1143
%X This paper shows the capacity of modern
computational techniques such as the self-organizing map (SOM)
as a methodology to achieve the classification of the electrical
customers in a commercial or geographical area. This approach
allows to extract the pattern of customer behavior from historic
load demand series. Several ways of data analysis from load
curves can be used to get different input data to “feed” the neural
network. In this work, we propose two methods to improve
customer clustering: the use of frequency-based indices and the
use of the hourly load curve. Results of a case study developed on
a set of different spanish customers and a comparison between
the two approachs proposed here are presented.
%K Ingeniería Eléctrica
%K Redes neuronales artificiales
%K Segmentación de clientes eléctricos
%K Mercado eléctrico
%K Análisis tiempo-frecuencia
%K Agregación de cliente
%K Artificial neural networks
%K Electrical customer segmentation
%K Electricity market
%K Time-Frequency analysis
%~ GOEDOC, SUB GOETTINGEN