Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/55588
Título: Daily global solar radiation estimation for Gran Canaria Island using artificial neural networks
Autores/as: Mazorra Aguiar, Luis 
Lauret, P.
Díaz Reyes, Felipe 
Ortegón, A.
Pérez-Suárez, R.
Clasificación UNESCO: 33 Ciencias tecnológicas
Palabras clave: Artificial Neural Networks
Forecasting
Perceptron
Solar radiation
Fecha de publicación: 2016
Publicación seriada: Renewable energy and power quality journal 
Resumen: Forecasting of global solar radiation is an important tool for power systems planning and operation, especially in island grids. The aim of this paper is the analysis of an artificial neural network as a reliable method to obtain a daily forecast for solar radiation. Some different tests are proposed to obtain the optimal ANN that will capture the underlying physical process that generates the data. In the present study, the available data come from seven measuring stations throughout the Gran Canaria Island along six years. ANN was trained and tested only with past ground measurement solar radiation and other meteorological data available at measurement stations as inputs.
URI: http://hdl.handle.net/10553/55588
ISSN: 2172-038X
DOI: 10.24084/repqj14.546
Fuente: Renewable energy and power quality journal [ISSN 2172-038X], v. 1 (14), p. 992-996
Colección:Artículos
miniatura
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