Daily Global Solar Radiation estimation for Gran Canaria Island using Artificial Neural Networks

Authors

  • L. Mazorra Aguiar Author
  • P. Lauret Author
  • F. Díaz Author
  • A. Ortegón Author
  • R. Pérez-Suárez Author

DOI:

https://doi.org/10.24084/repqj14.546

Keywords:

Artificial Neural Networks, Forecasting, Perceptron, Solar radiation

Abstract

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.

Author Biographies

  • L. Mazorra Aguiar

    Department of Electrical Engineering. University of Las Palmas de Gran Canaria 
    Campus Tafira, 35017 Las Palmas de Gran Canaria (Spain) 

  • P. Lauret

    Laboratoire PIMENT from the University of La Réunion, France

  • F. Díaz

    Department of Electrical Engineering. University of Las Palmas de Gran Canaria 
    Campus Tafira, 35017 Las Palmas de Gran Canaria (Spain) 

  • A. Ortegón

    Instituto Tecnológico de Canarias (ITC), Canary Islands, Spain

Published

2024-01-16

Issue

Section

Articles