Fully Complex Valued Wavelet Network for Forecasting the Global Solar Irradiation

Forecasting solar irradiation is very important to plane and size PV systems. In this paper, the fully complex valued wavelet network (FCWN) for forecasting the global solar irradiation is proposed. The complex valued gradient descent-learning algorithm is used to find the optimal complex-valued par...

Full description

Saved in:
Bibliographic Details
Published in:Neural processing letters 2017-04, Vol.45 (2), p.475-505
Main Authors: Saad Saoud, L., Rahmoune, F., Tourtchine, V., Baddari, K.
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Complex Systems
Computational Intelligence
Computer Science
Forecasting
Fourier transforms
Irradiation
Machine learning
Neural networks
Solar radiation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Forecasting solar irradiation is very important to plane and size PV systems. In this paper, the fully complex valued wavelet network (FCWN) for forecasting the global solar irradiation is proposed. The complex valued gradient descent-learning algorithm is used to find the optimal complex-valued parameters of the network. An improved fully wavelet function is proposed and used as an activation function of the hidden neurons of the FCWN. The meteorological measured data of Tamanrasset city, Algeria (latitude: 22 ∘ 48 N; longitude: 05 ∘ 26 E) is used to validate the developed model. The hourly and the daily solar irradiations are forecasted using the multi input single output and the multi input multi output strategies. Several results are presented to test the feasibility and the performance of the FCWN for forecasting either daily or hourly solar irradiation. Results obtained throughout this paper show that the FCWN is a promising technique for forecasting daily and hourly solar irradiation.
ISSN:1370-4621
1573-773X
DOI:10.1007/s11063-016-9537-7