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LONG TERMS PREDICTIONS OF ELECTRICITY DEMAND: A CHALLENGE FOR COMPUTER ENGINEERING

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NOVEMBER 2015   -  Volume: 90 -  Pages: 582-584

DOI:

https://doi.org/10.6036/7834

Authors:

GABRIEL WINTER ALTHAUS -
BEGOÑA GONZALEZ LANDIN
- ANTONIO PULIDO ALONSO - BLAS GALVAN GONZALEZ - MUSTAPHA MAAROUF - JONAY GONZALEZ GUERRA - MANUEL CRUZ PEREZ

Disciplines:

  • Electrical technology and engineering (OTRAS (ESPECIFICAR) )
  • Computer Sciences (ARTIFICIAL INTELLIGENCE / INTELIGENCIA ARTIFICIAL )

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Key words:
Demanda de la energía eléctrica, Predicción a Largo Plazo, Regresión Lineal Múltiple, Regresión Logarítmica, Algoritmos Genéticos, Redes Neuronales Artificiales, Sistemas eléctricos insulares, lectricity Demand, Long-Term Prediction, Multiple Linear Regression, Multiple Logarithmic Regression, Support Vector Machine, Genetic Algorithms, Artificial Neural Networks, Insular Electric System
Article type:
NOTA TECNICA / TECHNICAL NOTE
Section:
COLLABORATIONS

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. The results of EED predictions with different methods and the inclusion of consumer price index (CPI) variable for the electrical system of the Canary Islands, of special interest for being an isolated power system, are evaluated.

Keywords: Electricity Demand, Long-Term Prediction, Genetic Algorithms, Artificial Neural Networks, Isolated Power System.

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