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    Excitation force estimation and forecasting for wave energy applications


    Garcia-Abril, Marina, Paparella, Francesco and Ringwood, John (2017) Excitation force estimation and forecasting for wave energy applications. IFAC-PapersOnLine, 50 (1). pp. 14692-14697. ISSN 2405-8963

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    Abstract

    The implementation of the majority of energy maximising control strategies requires the knowledge of the wave excitation force experienced by the wave energy converter (WEC). In addition, many optimal numerical control strategies also require future knowledge, or a forecast, of future values of the excitation force. This paper examines both the excitation force estimation and forecasting problem for a heaving buoy wave energy device. In particular, a Kalman filter is used to estimate excitation force, where the wave force model is comprised of a set of oscillators at discrete frequencies. The forecasting algorithm consists of an autoregressive model, where the value of prefiltering, in terms of forecasting performance, is evaluated. The paper provides a level of sensitivity analysis of the estimation and forecasting performance to variations in sampling period, sea spectral shape factor and prediction horizon. Results demonstrate that the achievable performance of the estimator/forecaster is consistent with the broad requirements of numerical optimal WEC control strategies (Fusco and Ringwood (2012)), which depends on the characteristics of the radiation impulse response.
    Item Type: Article
    Keywords: Excitation force; prediction; estimation; Kalman filter; energy maximization;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research
    Item ID: 11770
    Identification Number: 10.1016/j.ifacol.2017.08.2499
    Depositing User: Professor John Ringwood
    Date Deposited: 20 Nov 2019 17:17
    Journal or Publication Title: IFAC-PapersOnLine
    Publisher: Elsevier
    Refereed: Yes
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/11770
    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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