RT info:eu-repo/semantics/article
T1 Classification and clustering of electricity demand patterns in industrial parks
A1 Hernández Callejo, Luis
A1 Baladrón García, Carlos
A1 Aguiar Pérez, Javier Manuel
A1 Carro Martínez, Belén
A1 Sánchez Esguevillas, Antonio Javier
K1 Industrial park
K1 Pattern recognition
K1 Self-organizing map
K1 k-means
K1 Clustering
K1 Energy demand
K1 33 Ciencias Tecnológicas
AB Understanding of energy consumption patterns is extremely important foroptimization of resources and application of green trends. Traditionally, analyses wereperformed for large environments like regions and nations. However, with the advent ofSmart Grids, the study of the behavior of smaller environments has become a necessity toallow a deeper micromanagement of the energy grid. This paper presents a data processingsystem to analyze energy consumption patterns in industrial parks, based on the cascadeapplication of a Self-Organizing Map (SOM) and the clustering k-means algorithm. Thesystem is validated with real load data from an industrial park in Spain. The validationresults show that the system adequately finds different behavior patterns which aremeaningful, and is capable of doing so without supervision, and without any priorknowledge about the data.
PB MDPI
SN 1996-1073
YR 2012
FD 2012
LK https://uvadoc.uva.es/handle/10324/57644
UL https://uvadoc.uva.es/handle/10324/57644
LA eng
NO Energies, 2012, vol. 5, n. 12, p. 5215-5228
NO Producción Científica
DS UVaDOC
RD 30-jun-2024