MURAL - Maynooth University Research Archive Library



    Linearisation-based nonlinearity measures for wave-to-wire models in wave energy


    Penalba, Markel and Ringwood, John (2019) Linearisation-based nonlinearity measures for wave-to-wire models in wave energy. Ocean Engineering, 171. pp. 496-504. ISSN 0029-8018

    [img]
    Preview
    Download (2MB) | Preview


    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...



    Add this article to your Mendeley library


    Abstract

    It is important to consider nonlinear effects when designing controllers to maximise generated energy in wave energy converters (WECs). Due to the substantial extra computation and complexity added when considering nonlinearities in the controller calculations, quantifying the extent of nonlinearity in WECs’ behaviour is crucial to avoid designing overcomplicated control strategies. This paper suggests two nonlinearity measures to quantify the nonlinearity degree of wave-to-wire (W2W) models in steady-state, using the best linear approximation identified through a minimisation problem as a benchmark. The first measure, referred to as the original nonlinearity measure, evaluates the nonlinear effects of the wave-absorber hydrodynamic interaction. The second measure, referred to as the power nonlinearity measure, quantifies the nonlinear effects in power take-off (PTO) systems, considering the quadratic response of the power signal. The degree of nonlinearity of two WEC models, a partially-nonlinear hydrodynamic model with an ideal PTO model and a complete nonlinear W2W model, is evaluated using monochromatic and polychromatic waves over a wide range of wave periods and heights, covering the whole operational space of a WEC.

    Item Type: Article
    Keywords: Wave energy; Nonlinearity measures; Best linear approximation; Wave-to-wire models; Power take-off dynamics; Energy maximising control;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research
    Faculty of Science and Engineering > Electronic Engineering
    Item ID: 14267
    Identification Number: https://doi.org/10.1016/j.oceaneng.2018.11.033
    Depositing User: Professor John Ringwood
    Date Deposited: 29 Mar 2021 14:01
    Journal or Publication Title: Ocean Engineering
    Publisher: Elsevier
    Refereed: Yes
    URI:

      Repository Staff Only(login required)

      View Item Item control page

      Downloads

      Downloads per month over past year