Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Power and velocity control of wind turbines by adaptive fuzzy controller during full load operation

    Access Status
    Fulltext not available
    Authors
    Habibi, Hamed
    Yousefi Koma, A.
    Sharifian, A.
    Date
    2016
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Habibi, H. and Yousefi Koma, A. and Sharifian, A. 2016. Power and velocity control of wind turbines by adaptive fuzzy controller during full load operation. Iranian Journal of Fuzzy Systems. 13 (3): pp. 35-48.
    Source Title
    Iranian Journal of Fuzzy Systems
    ISSN
    1735-0654
    School
    WASM: Minerals, Energy and Chemical Engineering (WASM-MECE)
    URI
    http://hdl.handle.net/20.500.11937/70986
    Collection
    • Curtin Research Publications
    Abstract

    © 2016, University of Sistan and Baluchestan. All rights reserved. Research on wind turbine technologies have focused primarily on power cost reduction. Generally, this aim has been achieved by increasing power output while maintaining the structural load at a reasonable level. However, disturbances, such as wind speed, affect the performance of wind turbines, and as a result, the use of various types of controller becomes crucial. This paper deals with two adaptive fuzzy controllers at full load operation. The first controller uses the generated power, and the second one uses the angular velocity as feedback signals. These feedback signals act to control the load torque on the generator and blade pitch angle. Adaptive rules, derived from the fuzzy controller, are defined based on the differences between state variables of the power and angular velocity of the generator and their nominal values. The results, which are compared with verified results of reference controller, show that the proposed adaptive fuzzy controller in full load operation has a higher efficiency than that of reference ones, insensitive to fast wind speed variation that is considered as disturbance.

    Related items

    Showing items related by title, author, creator and subject.

    • Application of SMES Unit to improve the performance of doubly fed induction generator based WECS
      Yunus, A. M. Shiddiq (2012)
      Due to the rising demand of energy over several decades, conventional energy resources have been continuously and drastically explored all around the world. As a result, global warming is inevitable due to the massive ...
    • Reduction of frequency fluctuation for wind farm connected power systems by an adaptive artificial neural network controlled energy capacitor system
      Muyeen, S.M.; Hasanien, H.; Jamura, J. (2012)
      Frequency fluctuations are a major concern for transmission system operators and power grid companies from the beginning of power system operation due to their adverse effects on modern computer-controlled industrial ...
    • Power improvement of non-linear wind turbines during partial load operation using fuzzy inference control
      Habibi, H.; Koma, A.; Howard, Ian (2017)
      Power generation in modern and industrial wind turbines can be improved by careful choice and analysis of operational control strategies. In this paper a new controller scheme is proposed in partial load operation of the ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.