Solar radiation modelling for the estimation of the solar energy generation

Author

Hernandez-Travieso, Jose G. ; Travieso, Carlos M. ; Alonso, Jesus B. ; Dutta, Malay Kishore

Author_Institution

Signal & Commun. Dept., Univ. of Las Palmas deGran Canaria, Las Palmas de Gran Canaria, Spain

fYear

2014

fDate

7-9 Aug. 2014

Firstpage

536

Lastpage

541

Abstract

To know in advance the value of solar radiation is an advantage in order to obtain solar energy. This paper proposes the design and implementation of solar radiation modelling for the estimation of the solar energy generation, based on different series of data collected from meteorological stations in Gran Canaria and Tenerife (Canary Islands, Spain), helping to generate green energy from sun by the estimation of solar radiation. Artificial Neural Network multilayer perceptron, were the classification method used to obtain the forecast. The study of solar radiation prediction achieves a mean average error of 0.04 kilowatts hour per square meter.

Keywords

multilayer perceptrons; power engineering computing; solar power; solar power stations; solar radiation; Gran Canaria; Tenerife; artificial neural network multilayer perceptron; green energy generation; meteorological station data collection; solar energy generation estimation; solar radiation prediction modelling; Artificial neural networks; Estimation; Mean square error methods; Solar energy; Solar radiation; Standards; Wind speed; Solar radiation prediction; artificial neural networks; green energy;

fLanguage

English

Publisher

ieee

Conference_Titel

Contemporary Computing (IC3), 2014 Seventh International Conference on

Conference_Location

Noida

Print_ISBN

978-1-4799-5172-7

Type

conf

DOI

10.1109/IC3.2014.6897230

Filename

6897230