Artificial neural networks applications in wind energy systems: a review

Rasit Ata

Renewable and Sustainable Energy Reviews, 2015, vol. 49, issue C, 534-562

Abstract: Neural networks approaches are becoming useful as an alternate way to classical methods. As a computation and learning paradigm, they are presented as a different modeling approach to solve complicated problems. They have been used to solve complicated practical problems in various areas, such as engineering, medicine, business, manufacturing, military etc. They have also been applied for modeling, identification, optimization, prediction, forecasting, evaluation, classification, and control of complex systems. During the last three decades, artificial neural network have been extensively employed in numerous fields of science and technology. They are not programmed in the conventional procedure but they are trained using data exemplifying the behaviour of a system. This study presents various applications of neural networks used in wind energy systems. The applications of neural networks in wind energy systems could be grouped in three major categories: forecasting and prediction, prediction and control, identification and evaluation. The main purpose of this paper is to present an overview of the neural network applications in wind energy systems. Published literature presented in this study indicate the potential of ANN as a useful tool for wind energy systems. Author strongly believes that this survey will be very much useful to the researchers, scientific engineers working in this area to find out the relevant references and current state of the field.

Keywords: Artificial neural networks; Wind energy sytems; System modeling; System performance prediction (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

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DOI: 10.1016/j.rser.2015.04.166

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