Title: Artificial intelligence techniques for prediction of solar radiation data: a review

Authors: Mohamed Benghanem

Addresses: Department of Physics, Faculty of Sciences, Taibah University, P.O. Box 30002, Madinah, Saudi Arabia; International Centre of Theoretical Physics (ICTP), Strada Costiera 11-34014, Trieste, Italy

Abstract: Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques. They have been used to solve complicated practical problems in various areas and are able to deal with non-linear problems. AI techniques have been applied for modelling, identification, optimisation, prediction, forecasting, and control of complex systems. Artificial neural networks have been used by the author in the field of solar energy for the estimation of solar radiation data. The main objective of this paper is to present an overview of the AI-techniques for prediction of solar radiation data. Published literature presented in this paper show the potential of AI as a design tool for the simulation of solar radiation data and also forecasting and modelling others meteorological data. The advantage of using an AI-based prediction of solar radiation is that it provides good estimation of data, especially in isolated areas, where the weather data are not available.

Keywords: artificial intelligence; AI; artificial neural networks; ANNs; fuzzy logic; genetic algorithms; GAs; wavelet transforms; solar radiation data; modelling; solar energy; solar power; radiation prediction; simulation; forecasting.

DOI: 10.1504/IJRET.2012.045626

International Journal of Renewable Energy Technology, 2012 Vol.3 No.2, pp.189 - 220

Received: 28 Aug 2010
Accepted: 17 Jun 2011

Published online: 15 Feb 2012 *

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