Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/20510
Title: Long term predictions of electricity demand: a challenge for computer engineering
Authors: Winter, Gabriel 
Pulido Alonso, Antonio 
González Landín, Begoña 
Maarouf, Mustapha
González-Guerra, Jonay 
Cruz Pérez, José Juan
Galván González, Blas José 
UNESCO Clasification: 3306 Ingeniería y tecnología eléctricas
332201 Distribución de la energía
531205 Energía
1206 Análisis numérico
Keywords: Electricity demand
Long-Term prediction
Genetic algorithms
Artificial neural network
Isolated power system
Issue Date: 2015
Journal: Dyna (Bilbao) 
Abstract: Long terms predictions of electrical energy demand (EED) are important for both electric utilities and enterprise of resource management and land planning. The repercussion and need to have adequate EED predictions is highlighted. New scenes imply greater efforts, both considering new variables, and using efficient methods of computational engineering.
URI: http://hdl.handle.net/10553/20510
ISSN: 0012-7361
DOI: 10.6036/7834
Source: Dyna (Spain)[ISSN 0012-7361],v. 90, p. 582-584
Rights: by
Appears in Collections:Artículos
Thumbnail
Adobe PDF (498,83 kB)
Show full item record

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.