• DocumentCode
    67057
  • Title

    Up-Wave and Autoregressive Methods for Short-Term Wave Forecasting for an Oscillating Water Column

  • Author

    Paparella, Francesco ; Monk, Kieran ; Winands, Victor ; Lopes, M.F.P. ; Conley, Daniel ; Ringwood, John V.

  • Author_Institution
    Center for Ocean Energy Res. (COER), Nat. Univ. of Ireland, Maynooth, Ireland
  • Volume
    6
  • Issue
    1
  • fYear
    2015
  • fDate
    Jan. 2015
  • Firstpage
    171
  • Lastpage
    178
  • Abstract
    The real-time control of wave energy converters (WECs) requires the prediction of the wave elevation at the location of the device in order to maximize the power extracted from the waves. One possibility is to predict the future wave elevation by combining its past history with the spatial information coming from a sensor which measures the free surface elevation up-wave of the WEC. As an application example, this paper focuses on the prediction of the wave elevation inside the chamber of the oscillating water column (OWC) for the Pico OWC plant in the Azores, and two different sensors for the measurement of the free surface elevation up-wave of the OWC were tested. The study showed that the use of the additional information coming from the up-wave sensor does not significantly improve the linear prediction of the chamber wave elevation given by a forecasting model based only on the past values of the chamber wave elevation.
  • Keywords
    autoregressive processes; hydrological techniques; sensors; wave power plants; Azores; Pico OWC plant; WEC; autoregressive methods; chamber wave elevation; forecasting model; free surface elevation up-wave; oscillating water column; short-term wave forecasting; up-wave sensor; wave energy converters; Artificial neural networks; Finite impulse response filters; Forecasting; Predictive models; Sea measurements; Sea surface; Surface waves; Time series; wave energy; wave forecasting;
  • fLanguage
    English
  • Journal_Title
    Sustainable Energy, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1949-3029
  • Type

    jour

  • DOI
    10.1109/TSTE.2014.2360751
  • Filename
    6971235