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Evolutionary product unit neural networks for short-term wind speed forecasting in wind farms

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Abstract

Combinations of physical and statistical wind speed forecasting models are frequently used in wind speed prediction problems arising in wind farms management. Artificial neural networks can be used in these models as a final step to obtain accurate wind speed predictions. The aim of this work is to determine the potential of evolutionary product unit neural networks (EPUNNs) for improving the accuracy and interpretation of these systems. Traditional neural network and EPUNN approaches have been used to develop different wind speed prediction models. The results obtained using different EPUNN models show that the functional model and the hybrid algorithms proposed provide very accurate prediction compared with standard neural networks used to solve this regression problem. One of the main advantages of the application of these EPUNNs has been the possibility of obtaining some interpretation of the non-linear relation predicted by the model, as will be shown in real data of a wind farm in Spain.

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Notes

  1. For this comparison, we have considered the WEKA machine learning workbench with the corresponding RBFNetwork algorithm (http://www.cs.waikato.ac.nz/ml/weka/).

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Acknowledgments

This work has been partially supported by Spanish Ministry of Industry, Tourism and Trading, under an Avanza 2 project, number TSI-020100-2010-663, by the TIN 2008-06681-C06-03 project of the Spanish Inter-Ministerial Commission of Science and Technology (MICYT), FEDER funds and by the P08-TIC-3745 project of the “Junta de Andalucía” (Spain).

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Authors and Affiliations

  1. Department of Computer Science and Numerical Analysis, Universidad de Córdoba, Córdoba, Spain

    C. Hervás-Martínez & P. A. Gutiérrez

  2. Department of Signal Theory and Communications, Universidad de Alcalá, Alcalá de Henares, Spain

    S. Salcedo-Sanz & E. G. Ortiz-García

  3. Energy Resources Department, Iberdrola Renovables, Madrid, Spain

    L. Prieto

Authors
  1. C. Hervás-Martínez
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  2. S. Salcedo-Sanz
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  3. P. A. Gutiérrez
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  4. E. G. Ortiz-García
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  5. L. Prieto
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Correspondence to S. Salcedo-Sanz.

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Hervás-Martínez, C., Salcedo-Sanz, S., Gutiérrez, P.A. et al. Evolutionary product unit neural networks for short-term wind speed forecasting in wind farms. Neural Comput & Applic 21, 993–1005 (2012). https://doi.org/10.1007/s00521-011-0582-x

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  • DOI: https://doi.org/10.1007/s00521-011-0582-x

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