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Neural Processing Letters

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18-07-2016

Fully Complex Valued Wavelet Network for Forecasting the Global Solar Irradiation

Authors: L. Saad Saoud, F. Rahmoune, V. Tourtchine, K. Baddari

Published in: Neural Processing Letters | Issue 2/2017

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Abstract

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: \(22^{\circ }48\)N; longitude: \(05^{\circ }26\)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.

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Title: Fully Complex Valued Wavelet Network for Forecasting the Global Solar Irradiation
Authors: L. Saad Saoud
F. Rahmoune
V. Tourtchine
K. Baddari
Publication date: 18-07-2016
Publisher: Springer US
Published in: Neural Processing Letters / Issue 2/2017
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI: https://doi.org/10.1007/s11063-016-9537-7

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