TY - JOUR 
A1 - Valero Verdú, Sergio
AU - Ortiz García, Mario
AU - García Franco, Francisco J.
AU - Encinas Redondo, Nuria
AU - Gabaldón Marín, Antonio
AU - Molina García, Ángel
AU - Gómez Lázaro, Emilio
T1 - Characterization and identification of electrical customers through the use of self-organizing maps and daily load parameters
Y1 - 2004
UR - http://hdl.handle.net/10317/1143
AB - 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.
KW - Ingeniería Eléctrica
KW - Redes neuronales artificiales
KW - Segmentación de clientes eléctricos
KW - Mercado eléctrico
KW - Análisis tiempo-frecuencia
KW - Agregación de cliente
KW - Artificial neural networks
KW - Electrical customer segmentation
KW - Electricity market
KW - Time-Frequency analysis
LA - eng
PB - IEEE Power & Energy Society (PES)
ER -