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Wave prediction based on a modified grey model MGM(1,1) for real-time control of wave energy converters in irregular waves

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  • Truong, D.Q.
  • Ahn, K.K.

Abstract

Recently, wave energy research has been more and more paid attention as a potentially sustainable energy resource. With the knowledge of wave characteristics in advance is one effective manner to investigate this wealthy resource as well as to apply to design stages of wave energy plants. The aim of this study is to design a simple and precise wave prediction method for applications to real-time control of wave energy converters (WECs). The proposed prediction method is based on a so-called modified grey model with first order – one variable – MGM(1,1). This model was developed from the conventional grey model – GM(1,1) in which the background series used to establish grey differential equation was designed to be obtained by an exact solution, consequently, improving the model accuracy. The model can predict well online any wave parameter at any future time-series point while only requiring a few of its historical data. In order to validate the applicability of the proposed approach, ocean wave data during several years at different offshore areas in South Korea was observed for the investigation. A comparison between prediction results of using the suggested grey model, the traditional grey model and a typical autoregressive (AR) model has been also carried out to evaluate the prediction performances.

Suggested Citation

  • Truong, D.Q. & Ahn, K.K., 2012. "Wave prediction based on a modified grey model MGM(1,1) for real-time control of wave energy converters in irregular waves," Renewable Energy, Elsevier, vol. 43(C), pages 242-255.
    • Handle: RePEc:eee:renene:v:43:y:2012:i:c:p:242-255
    DOI: 10.1016/j.renene.2011.11.047
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    References listed on IDEAS

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    1. Rusu, Eugen & Guedes Soares, C., 2009. "Numerical modelling to estimate the spatial distribution of the wave energy in the Portuguese nearshore," Renewable Energy, Elsevier, vol. 34(6), pages 1501-1516.
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