Availability growth and state-of-knowledge uncertainty simulation for offshore wind farms

Zitrou, Athena and Bedford, Tim and Walls, Lesley and Wilson, Kevin and Bell, Keith (2013) Availability growth and state-of-knowledge uncertainty simulation for offshore wind farms. In: 22nd ESREL conference 2013, 2013-09-29 - 2013-10-02.

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    Abstract

    The UK offshore wind sector has developed rapidly, but needs to develop even further to meet the low carbon targets set by the government. In order to increase capacity and reduce costs, new offshore wind farms will use larger and more complex technology that goes beyond current understanding and experience. As a result, predicting the technical performance of offshore wind farms involves a considerable amount of uncertainty, especially during early life when teething problems may arise. We present a model that allows us to distinguish between natural variability and state-of-knowledge uncertainty when assessing the growth in technical performance of offshore wind farms over early operational life. As such, the model can be used to inform decisions to reduce uncertainties and to support effective risk management. To describe wind farm performance, we use an indicator we call availability-informed capability measures the capacity of the farm to generate electricity. We use an example based on a two-phase Monte Carlo simulation to illustrate the use of the model.

    Creators(s): Zitrou, Athena, Bedford, Tim ORCID logoORCID: https://orcid.org/0000-0002-3545-2088, Walls, Lesley ORCID logoORCID: https://orcid.org/0000-0001-7016-9141, Wilson, Kevin and Bell, Keith ORCID logoORCID: https://orcid.org/0000-0001-9612-7345;
    Item type:Conference or Workshop Item(Paper)
    ID code:45377
    Keywords:availability growth, state-of-knowledge , offshore wind farms, uncertainty simulation, Management. Industrial Management, Electrical engineering. Electronics Nuclear engineering, Strategy and Management, Electrical and Electronic Engineering
    Subjects:Social Sciences > Industries. Land use. Labor > Management. Industrial Management
    Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Strathclyde Business School > Management Science
    Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:24 Oct 2013 13:15
    Last modified:01 Jan 2021 03:18
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/45377
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