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    A state-of-the-art review on wind power converter fault diagnosis

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    1-s2.0-S2352484722007338-main.pdf (2.894Mb)
    Date
    2022
    Author
    Liang, Jinping
    Zhang, Ke
    Al-Durra, Ahmed
    Muyeen, S.M.
    Zhou, Daming
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    Abstract
    The rapid expansion of installed wind energy capacity and the continuous development of wind turbine technology has drawn attention to operation and maintenance issues. In order to keep wind power a competitive energy source, the development of high-reliability and low-maintenance wind turbine systems is imminent, the rise of fault diagnosis provides a guarantee for their satisfactory operation and maintenance. A large number of statistical studies have pointed out that converter fault is the main cause of wind turbine system failure shutdown. Up to now, wind power converters' fault diagnosis has obtained fruitful results, and those are constantly reported in power system literature. This paper presents a state-of-the-art review on wind power converters' fault diagnosis for both short-circuit faults and open-circuit faults of power switch, including model-based, signal-based and data-driven methods. It provides a wide range, involving component fault modes, the robustness and reliability issues, algorithm investigation of fault diagnosis, quantitative analysis and qualitative analysis metrics for assessing the advantages of the developed techniques, and challenges in fault diagnosis design. Main purposes of this paper are: (1) Investigating the current research status of fault diagnosis on wind power converters to update the relevant research literature; (2) Discussing the robustness and reliability issues that must be considered in real engineering and safety critical systems; (3) Providing effective performance indices involves both quantitative and qualitative analysis, so that readers can understand the novelty of the proposed method. 2022 The Authors
    DOI/handle
    http://dx.doi.org/10.1016/j.egyr.2022.03.178
    http://hdl.handle.net/10576/40385
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    • Electrical Engineering [‎2822‎ items ]

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