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    A high-fidelity wave-to-wire model for wave energy converters


    Penalba, Markel and Ringwood, John (2019) A high-fidelity wave-to-wire model for wave energy converters. Renewable Energy, 134. pp. 367-378. ISSN 0960-1481

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    Abstract

    Mathematical models incorporating all the necessary components of wave energy converters (WECs) from ocean waves to the electricity grid, known as wave-to-wire (W2W) models, are vital in the development of wave energy technologies. Ideally, precise W2W models should include all the relevant nonlinear dynamics, constraints and energy losses. This paper presents a balanced W2W model that incorporates high-fidelity models for each conversion system, and can accommodate different types of WECs, hydraulic power take-off (PTO) topologies, electric generators and grid connections. The models of the different conversion stages presented herein are efficiently implemented in the W2W model using a multi-rate integration scheme that reduces the computational requirements by a factor of 10. Two W2W models, i.e. one with the constant-pressure hydraulic PTO configuration and one with the variablepressure configuration, are compared in this paper. Results show that a higher PTO efficiency (30% higher for the constant-pressure configuration) does not necessarily imply a higher electricity generation (2% higher for the variable-pressure configuration), which reinforces the need for high-fidelity W2W models for the design of successful WECs.
    Item Type: Article
    Keywords: Wave energy; Wave-to-wire modelling; High-fidelity; Hydraulic power take-off; Multi-rate solver;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research
    Faculty of Science and Engineering > Electronic Engineering
    Item ID: 14268
    Identification Number: 10.1016/j.renene.2018.11.040
    Depositing User: Professor John Ringwood
    Date Deposited: 29 Mar 2021 14:05
    Journal or Publication Title: Renewable Energy
    Publisher: Elsevier
    Refereed: Yes
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/14268
    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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