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    Energy‐maximising moment‐based constrained optimal control of ocean wave energy farms


    Faedo, Nicolás, Scarciotti, Giordano, Astolfi, Alessandro and Ringwood, John (2021) Energy‐maximising moment‐based constrained optimal control of ocean wave energy farms. IET Renewable Power Generation, 15 (14). pp. 3395-3408. ISSN 1752-1416

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    Abstract

    Successful commercialisation of wave energy technology inherently incorporates the concept of an array of wave energy converters (WECs). These devices, which constantly interact via hydrodynamic effects, require optimised control that can guarantee maximum energy extraction from incoming ocean waves while ensuring, at the same time, that any physical limitations associated with device and actuator systems are being consistently respected. This paper presents a moment-based energy-maximising optimal control framework for WECs arrays subject to state and input constraints. The authors develop a framework under which the objective function (and system variables) can be mapped to a finite-dimensional tractable quadratic program (QP), which can be efficiently solved using state-of-the-art solvers. Moreover, the authors show that this QP is always concave, i.e. existence and uniqueness of a globally optimal solution is guaranteed under this moment based framework. The performance of the proposed strategy is demonstrated through a case study, where (state and input constrained) energy-maximisation for a WEC farm composed of CorPower-like WEC devices is considered
    Item Type: Article
    Keywords: Energy-maximising; moment-based; optimal control; ocean 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: 16119
    Identification Number: 10.1049/rpg2.12284
    Depositing User: Professor John Ringwood
    Date Deposited: 16 Jun 2022 13:43
    Journal or Publication Title: IET Renewable Power Generation
    Refereed: Yes
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/16119
    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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