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    Short-Term Wave Forecasting with AR models in Real-Time Optimal Control of Wave Energy Converters

    Fusco, Francesco and Ringwood, John (2010) Short-Term Wave Forecasting with AR models in Real-Time Optimal Control of Wave Energy Converters. In: IEEE International Symposium on Industrial Electronics, 4-7 July, 2010, Bari, Italy.

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    Time domain control of wave energy converters requires knowledge of future incident wave elevation in order to approach conditions for optimal energy extraction. Autoregressive models revealed to be a promising approach to the prediction of future values of the wave elevation only from its past history. Results on real wave observations from different ocean locations show that AR models allow to achieve very good predictions for more than one wave period in the future if the focus is put on low frequency components, which are the most interesting from a wave energy point of view. For real-time implementation, however, the lowpass filtering introduces an error in the wave time series, as well as a delay, and AR models need to be designed so to be as robust as possible to these errors.

    Item Type: Conference or Workshop Item (Paper)
    Keywords: Short-Term Wave Forecasting; AR models; Real-Time Optimal Control; 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: 3614
    Depositing User: Professor John Ringwood
    Date Deposited: 01 May 2012 10:00
    Refereed: Yes
    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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