• Title of article

    Reliability Modeling of Various Type of Wind Turbines

  • Author/Authors

    Ghaedi ، Amir Department of Electrical Engineering - Islamic Azad University, Dariun Branch , Sedaghati ، Reza Department of Electrical Engineering - Islamic Azad University, Beyza Branch , Mahmoudian ، Mehrdad Department of Electrical and Electronic Engineering - Shiraz University of Technology

  • From page
    227
  • To page
    244
  • Abstract
    Various wind turbines have been manufactured for converting wind power into electric energy. They are fixed speed concepts with squirrel cage induction generators, limited variable speed concepts with wound rotor induction generators, variable speed concepts with double fed induction generators, direct-drive concepts with electrically excited synchronous generators and gearbox-free concepts with permanent magnet induction technologies. The composed components and the power curve of these technologies are different and to select an appropriate wind turbine for a wind site, in addition to the economic parameter, reliability criterion must be considered. To address this, a reliability model is developed in this paper that considers both component failure and the unpredictable nature of wind speed for different types of wind turbines. The optimal state number of reliability presentations is determined using XB index calculation and fuzzy c-means clustering method to create multi-state presentations for wind turbines. The proposed approach can be used to determine the most reliable wind turbine for a given wind site by assessing the adequacy of the electric network containing various types of wind turbines. The approach’s effectiveness is demonstrated through adequacy assessments of the RBTS and IEEE-RTS, which contain various types of wind turbines.
  • Keywords
    Wind turbine , Adequacy , Reliability , Induction Generator , Fuzzy C , Means Clustering
  • Journal title
    AUT Journal of Electrical Engineering
  • Journal title
    AUT Journal of Electrical Engineering
  • Record number

    2773955