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Analytic neural network model of a wind turbine

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Abstract

In this paper, an analytic neural network model is introduced for the modeling of the wind turbine behavior. The proposed hybrid method is the combination of the analytic and neural network models. The neural network model is used as a compensator to improve the approximation of the analytic model. It is guaranteed that the error of the analytic neural network model is smaller than the error of the analytic model. Two experiments show the effectiveness of the proposed technique.

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Acknowledgments

The author is grateful with the editor and with the reviewers for their valuable comments and insightful suggestions, which can help to improve this research significantly. The author thanks the Secretaría de Investigación y Posgrado, Comisión de Operación y Fomento de Actividades Académicas del IPN, and Consejo Nacional de Ciencia y Tecnología for their help in this research.

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Authors and Affiliations

  1. Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional, Av. de las Granjas no. 682, Col. Santa Catarina, Mexico, D.F., 02250, Mexico

    José de Jesús Rubio

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  1. José de Jesús Rubio
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Correspondence to José de Jesús Rubio.

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Communicated by E. Lughofer.

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de Jesús Rubio, J. Analytic neural network model of a wind turbine. Soft Comput 19, 3455–3463 (2015). https://doi.org/10.1007/s00500-014-1290-0

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