MURAL - Maynooth University Research Archive Library



    Fast optimal control performance evaluation for wave energy control co-design


    Lin, Zechuan, Huang, Xuanrui, Xiao, Xi and Ringwood, John (2025) Fast optimal control performance evaluation for wave energy control co-design. Renewable Energy, 239. p. 121974. ISSN 09601481

    [thumbnail of JR_fast.pdf]
    Preview
    Text
    JR_fast.pdf

    Download (4MB) | Preview

    Abstract

    With the application of energy-maximizing control for wave energy converters (WECs), the WEC design problem becomes a control co-design problem. One of the fundamental requirements of co-design is to evaluate the optimal control performance, i.e., average power generation. Previous control techniques include model predictive control (MPC) and pseudo-spectral (PS) control, but both require iterative optimization, with computational requirements the main limiting factor in co-design. In this study, a fast optimal control performance evaluation method is proposed based on a ‘wave-by-wave’ (WbW) representation. The idea is to split the wave excitation force (WEF) signals into individual waves, process them separately, and then combine the results with the distribution of WEF amplitude and period, yielding a straightforward average power calculation. The method is fully developed and studied, considering the cases of position-only, and general, constraints, as well as different choices to obtain the WEF parameter distribution. It is shown that the WbW method can achieve a very high control evaluation fidelity (within a 5% error) and give almost the same co-design result as MPC and PS (implemented using WecOptTool), but with a significantly reduced computation time (e.g., hundreds of times faster), therefore being a game changer for control co-design of WECs.
    Item Type: Article
    Keywords: Wave energy converter; Control co-design; Model predictive control; Pseudo-spectral control;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Item ID: 19543
    Identification Number: 10.1016/j.renene.2024.121974
    Depositing User: Professor John Ringwood
    Date Deposited: 04 Mar 2025 12:31
    Journal or Publication Title: Renewable Energy
    Publisher: Elsevier
    Refereed: Yes
    Related URLs:
    URI: https://mural.maynoothuniversity.ie/id/eprint/19543
    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

    Repository Staff Only (login required)

    Item control page
    Item control page

    Downloads

    Downloads per month over past year

    Origin of downloads