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    Speed control of grid-connected switched reluctance generator driven by variable speed wind turbine using adaptive neural network controller

    245845.pdf (1.197Mb)
    Access Status
    Open access
    Authors
    Hasanien, H.
    Muyeen, S.M.
    Date
    2012
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Hasanien, H. and Muyeen, S.M. 2012. Speed control of grid-connected switched reluctance generator driven by variable speed wind turbine using adaptive neural network controller. Electric Power Systems Research. 84 (1): pp. 206-213.
    Source Title
    Electric Power Systems Research
    DOI
    10.1016/j.epsr.2011.11.019
    ISSN
    0378-7796
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/7540
    Collection
    • Curtin Research Publications
    Abstract

    In wind energy conversion system, variable speed operation is becoming popular nowadays, where conventional synchronous generators, permanent magnet synchronous generators, and doubly fed induction generators are commercially used as wind generators. Along with the existing and classical solutions of the aforementioned machines used in wind power applications, the switched reluctance generator (SRG) can also be considered as a wind generator due to its inherent characteristics such as simple construction, robustness, low manufacturing cost, etc. This paper presents a novel speed control of switched reluctance generator by using adaptive neural network (ANN) controller. The SRG is driven by variable speed wind turbine and it is connected to the grid through an asymmetric half bridge converter, DC-link, and DC-AC inverter system. Speed control is very important for variable speed operation of SRG to ensure maximum power delivery to the grid for any particular wind speed. Detailed modeling and control strategies of SRG as well as other individual components including wind turbine, converter, and inverter systems are presented. The effectiveness of the proposed system is verified with simulation results using the real wind speed data measured at Hokkaido Island, Japan. The dynamic simulation study is carried out using PSCAD/EMTDC.

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