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    Ocean forecasting for wave energy production


    Mérigaud, Alexis, Ramos, Victor, Paparella, Francesco and Ringwood, John (2017) Ocean forecasting for wave energy production. The Sea: The Science of Ocean Prediction. Supplement to Journal of Marine Research, 75 (17). pp. 459-505. ISSN 0022-2402

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    Abstract

    There are a variety of requirements for future forecasts in relation to optimizing the production of wave energy. Daily forecasts are required to plan maintenance activities and allow power producers to accurately bid on wholesale energy markets, hourly forecasts are needed to warn of impending inclement conditions, possibly placing devices in survival mode, while wave-by-wave forecasts are required to optimize the real-time loading of the device so that maximum power is extracted from the waves over all sea conditions. In addition, related hindcasts over a long time scale may be performed to assess the power production capability of a specific wave site. This paper addresses the full spectrum of the aforementioned wave modeling activities, covering the variety of time scales and detailing modeling methods appropriate to the various time scales, and the causal inputs, where appropriate, which drive these models. Some models are based on a physical description of the system, including bathymetry, for example (e.g., in assessing power production capability), while others simply use measured data to form time series models (e.g., in wave-to-wave forecasting). The paper describes each of the wave forecasting problem domains, details appropriate model structures and how those models are parameterized, and also offers a number of case studies to illustrate each modeling methodology.
    Item Type: Article
    Keywords: real-time energy markets; time series models, up-wave forecasting, wave forecasting; wave energy resource; wave hindcasting; wave power production assessment; wave spectra;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research
    Faculty of Science and Engineering > Electronic Engineering
    Item ID: 12468
    Depositing User: Professor John Ringwood
    Date Deposited: 20 Feb 2020 16:56
    Journal or Publication Title: The Sea: The Science of Ocean Prediction. Supplement to Journal of Marine Research
    Publisher: Journal of Marine Research, Yale University
    Refereed: Yes
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/12468
    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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