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
Link To Document