Speed-sensorless vector control of an wind turbine induction generator using artificial neural network

Author

Dumnic, Boris ; Popadic, Bane ; Milicevic, Dragan ; Katic, Vladimir ; Oros, Djura

Author_Institution

Dept. of Power, Electron. & Commun. Eng., Univ. of Novi Sad, Novi Sad, Serbia

fYear

2014

fDate

21-24 Sept. 2014

Firstpage

371

Lastpage

376

Abstract

This paper present speed-sensorless vector control strategy for a squirrel cage induction generator (SCIG) used in variable speed wind energy conversion systems (WECS). In order to perform maximum power point tracking control (MPPT) of WECS, it is necessary to drive wind turbine at an optimal rotor speed. In this paper, rotational speed of the SCIG is estimated using improved model reference adaptive system (MRAS observer), with adaptive model based on artificial neural network (ANN). Extensive experimentation is conducted in order to verify efficiency and reliability of proposed control technique.

Keywords

angular velocity control; asynchronous generators; maximum power point trackers; model reference adaptive control systems; neurocontrollers; sensorless machine control; wind turbines; ANN; MPPT; MRAS observer; SCIG; WECS; adaptive model; artificial neural network; maximum power point tracking control; model reference adaptive system; speed-sensorless vector control; squirrel cage induction generator; variable speed wind energy conversion systems; wind turbine induction generator; Adaptation models; Artificial neural networks; Mathematical model; Observers; Rotors; Wind turbines; MRAS observer; artificial neural network; induction generator; speed estimation; wind energy;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Electronics and Motion Control Conference and Exposition (PEMC), 2014 16th International

Conference_Location

Antalya

Type

conf

DOI

10.1109/EPEPEMC.2014.6980521

Filename

6980521