Prediction of the solar radiation evolution using computational intelligence techniques and cloudiness indices

Ruano, Antonio; Crispim, E. M.; Ferreira, P. M.

http://hdl.handle.net/10400.1/2224

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Authors

Ruano, Antonio

Crispim, E. M.

Ferreira, P. M.

Abstract(s)

In this paper, Artificial Neural Networks are applied for multi-step long term solar radiation prediction. The input-output structure of the neural network models is selected using evolutionary computation methods. The networks are trained as onestep- ahead predictors and iterated over time to obtain multi-step longer term predictions. Auto-regressive and auto-regressive with exogenous inputs models are compared, considering cloudiness indices as inputs in the latter case. These indices are obtained through pixel classification of ground-to-sky images, captured by a CCD camera.

Keywords

Cloudiness indices Solar radiation Neural networks Multi-objective genetic algorithms

URI

http://hdl.handle.net/10400.1/2224

Citation

Ruano, Antonio Eduardo de Barros; Crispim, E. M.; Ferreira, P. M. Prediction of the solar radiation evolution using computational intelligence techniques and cloudiness indices, International Journal of Innovative Computing Information and Control, 4, 5, 1121-1133, 2008.