DocumentCode
24822
Title
Induction machines sensors-less wind generator with integrated intelligent maximum power point tracking and electric losses minimisation technique
Author
Pucci, Marcello
Author_Institution
Inst. of Intell. Syst. for the Autom. (ISSIA), Palermo, Italy
Volume
9
Issue
12
fYear
2015
fDate
8 6 2015
Firstpage
1831
Lastpage
1838
Abstract
This study presents a high-performance wind generation system with induction machine (IM), specifically devised with the target of maximising the efficiency of the electromechanical conversion, and contemporary minimising the number of the system sensors and their cost. To this aim, the control system has been integrated, from one side, with an intelligent maximum power point tracking (MPPT) technique, so to make the generator track the power available in the wind, from the other side with techniques for the minimisation of the electrical losses (ELMT). Particularly, the power converters´ switching losses have been reduced adopting a discontinuous pulsewidth modulation, while the IM overall losses have been reduced by a suitable electric losses minimisation technique. Contemporary, to reduce costs and increase the reliability of the system, the system has been devised as a fully sensors-less generation unit, meaning that both the wind speed and the machine speed sensors are not present. The anemometer has been substituted by the wind speed estimator integrated in the MPPT, based on the growing neural gas (GNG) network. The encoder has been substituted with an intelligent IM speed estimator, the so called MCA EXIN + reduced order observer (ROO). The performance of the adopted technique has been verified experimentally on a suitably devised test set-up.
Keywords
PWM power convertors; anemometers; asynchronous generators; cost reduction; maximum power point trackers; neurocontrollers; observers; power generation control; power generation reliability; reduced order systems; sensorless machine control; wind power; IM; MCA EXIN; MPPT technique; anemometer; cost reduction; discontinuous pulsewidth modulation; electric loss minimisation technique; electromechanical conversion; growing neural gas network; high-performance wind generation system; induction machine sensorsless wind generator; integrated intelligent maximum power point tracking; intelligent IM speed estimator; power converter switching loss; reduced order observer; sensors-less generation unit; wind speed estimator;
fLanguage
English
Journal_Title
Control Theory & Applications, IET
Publisher
iet
ISSN
1751-8644
Type
jour
DOI
10.1049/iet-cta.2014.1049
Filename
7166447
Link To Document