Characterization and identification of electrical customers through the use of self-organizing maps and daily load parameters
Título de la tesis:
Characterization and identification of electrical customers through the use of self-organizing maps and daily load parameters
Autor/es:
Valero Verdú, Sergio - Ortiz García, Mario - García Franco, Francisco J. - Encinas, Nuria - Gabaldón Marín, Antonio - Molina García, Ángel - Gómez Lázaro, Emilio
Tipo de documento:
Ponencia
Universidad:
Universidad Politécnica de Cartagena
Departamento:
Idioma:
Castellano
Palabras clave:
Redes neuronales artificiales, Segmentación de clientes eléctricos, Mercados electricos, Análisis tiempo-frecuencia, Agregación de cliente, Artificial Neuronal Networks, Electrical Customer Segmentation, Electricity Markets, Time-Frequency analysis
Fecha de la defensa:
Oct-2004
Notas:
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...
Valoración:
Clasificación por
