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    Short-Term Forecasting of Sea Surface Elevation for Wave Energy Applications: The Autoregressive Model Revisited

    Peña-Sanchez, Yerai and Mérigaud, Alexis and Ringwood, John (2018) Short-Term Forecasting of Sea Surface Elevation for Wave Energy Applications: The Autoregressive Model Revisited. IEEE Journal of Oceanic Engineering. ISSN 0364-9059

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    For wave energy converter control applications, autoregressive (AR) models have been proposed as a simple wave forecasting method, solely based on measured or estimated values of the past wave elevation (or excitation force) signal. Using offline-filtered wave time series, AR models can achieve accurate forecasts several wave periods into the future. In this paper, the AR method is examined from the broader perspective of linear, Gaussian processes. In particular, assuming Gaussian waves and perfect knowledge of the wave spectrum, it is possible to derive a theoretically-optimal wave elevation predictor. It is shown that, in realistic situations, AR models can achieve a performance comparable to the theoretically optimal, spectrum-based predictor, both in simulated wave time series and using actual wave elevation records.

    Item Type: Article
    Additional Information: This is the postprint version of the article, which has been accepted for inclusion in a future issue of the journal. Content is final as presented, with the exception of pagination.
    Keywords: Autoregressive model (AR); filtering; forecasting; Gaussian process; time series; wave energy;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research
    Item ID: 12394
    Identification Number:
    Depositing User: Professor John Ringwood
    Date Deposited: 07 Feb 2020 14:42
    Journal or Publication Title: IEEE Journal of Oceanic Engineering
    Publisher: IEEE
    Refereed: Yes
    Funders: Science Foundation Ireland (SFI), Marine Renewable Ireland Centre
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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