Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/20510
Title: Predicción de la demanda de la energía eléctrica a largo plazo : un reto en ingeniería computacional
Other Titles: Long-terms 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.
Both private companies and public administrations require long-term forecasts of electrical energy demand (EED). Among electric utilities are the carrier and manager of the electrical system, the generation and distribution utilities, and the trading companies; also the fuel supply companies to the generation power plants, and the public administrations responsible for the resource management and land planning, which are in charge of reserving land for placing infrastructures that ensure energy supply to the different activities developed in it. The authors have participated in the Special Territorial Plans of Energy Infrastructure Planning of various islands in the Canary Islands [1-3]. It should be noted that, if the predictions are very low, deficiencies could occur in the power supply, causing inconveniences to different economic sectors, but if they are very high, it could carry a high and unproductive economic investment.
URI: http://hdl.handle.net/10553/20510
ISSN: 0012-7361
DOI: 10.6036/7834
Source: Dyna (Bilbao)[ISSN 0012-7361], v. 90 (6), p. 582-584
Rights: by
URL: http://dialnet.unirioja.es/servlet/articulo?codigo=5273940
Appears in Collections:Artículos
Thumbnail
Adobe PDF (498,83 kB)
Show full item record

SCOPUSTM   
Citations

1
checked on May 16, 2021

Page view(s)

34
checked on May 17, 2021

Download(s)

39
checked on May 17, 2021

Google ScholarTM

Check

Altmetric


Share



Export metadata



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