• DocumentCode
    1603972
  • Title

    Optimization maintenance of wind turbines using Markov decision processes

  • Author

    Wu, Yan-ru ; Zhao, Hong-shan

  • Author_Institution
    Dept. of Electr. Eng., North China Electr. Power Univ., Baoding, China
  • fYear
    2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    As the wind power industry is getting more mature, and wind farms are taking their place as one of the mainstream options for new power generation, the demands for ensuring the wind turbines of reliable and economical operation are getting higher. Maintenance is indispensable to the core business objectives of the wind industry. Maintenance optimization is a means to determine the most cost-effective maintenance strategy. After studied the exiting maintenance method of wind turbines, this brief paper presents a method which incorporates modeling of equipment deterioration, inspection and minor & preventive maintenance for optimal maintenance decision. Using Markov decision processes, we provide an optimal cost-effective maintenance policy including maintenance actions based on the condition revealed at the time of inspection and inspection interval. Furthermore, an example is presented to illustrate the implementation of proposed method.
  • Keywords
    Markov processes; maintenance engineering; optimisation; power generation economics; wind turbines; Markov decision processes; economical operation; inspection interval; optimal cost-effective maintenance policy; optimal maintenance decision; optimization maintenance method; preventive maintenance; wind farms; wind power industry; wind turbines; Inspection; Markov processes; Optimization; Preventive maintenance; Wind power generation; Wind turbines; Condition-based maintenance; Cost-effective solution; Gearbox; Optimization maintenance; Semi-Markov Decision Processes; Wind turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology (POWERCON), 2010 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-5938-4
  • Type

    conf

  • DOI
    10.1109/POWERCON.2010.5666092
  • Filename
    5666092