• DocumentCode
    3125931
  • Title

    MRAS-based sensorless wind energy control for wind generation system using RFNN

  • Author

    Lin, Whei-Min ; Hong, Chih-Ming ; Ou, Ting-Chia ; Cheng, Fu-Sheng

  • Author_Institution
    Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
  • fYear
    2010
  • fDate
    15-17 June 2010
  • Firstpage
    2270
  • Lastpage
    2275
  • Abstract
    This paper presents an analysis of a high-performance model reference adaptive system (MRAS) observer for the sensorless control of a induction generator (IG). The sensorless control is based on a model reference adaptive system observer for estimating the rotational speed. The proposed output maximization control is achieved without mechanical sensors such as wind speed or position sensor, and the new control system will deliver maximum electric power with light weight, high efficiency, and high reliability. The concept has been developed and analyzed using a turbine directly driven IG. The estimation of the rotor speed is on the basis of the MRAS control theory. A sensorless vector-control strategy for an IG operating in a grid-connected variable speed wind energy conversion system is presented.
  • Keywords
    asynchronous generators; fuzzy neural nets; machine vector control; model reference adaptive control systems; recurrent neural nets; sensorless machine control; wind power; RFNN; electric power; grid-connected variable speed wind energy conversion system; induction generator; model reference adaptive system; recurrent fuzzy neural network; rotational speed; sensorless wind energy control; vector-control; wind generation system; Adaptive control; Adaptive systems; Control systems; Induction generators; Lighting control; Mechanical sensors; Programmable control; Sensorless control; Wind energy; Wind energy generation; induction generator (IG); model reference adaptive system (MRAS); recurrent fuzzy neural network (RFNN); sensorless control; wind turbine (WT);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on
  • Conference_Location
    Taichung
  • Print_ISBN
    978-1-4244-5045-9
  • Electronic_ISBN
    978-1-4244-5046-6
  • Type

    conf

  • DOI
    10.1109/ICIEA.2010.5516672
  • Filename
    5516672