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.
CITATION STYLE
Pucci, M. (2015). Induction machines sensors-less wind generator with integrated intelligent maximum power point tracking and electric losses minimisation technique. IET Control Theory and Applications, 9(12), 1831–1838. https://doi.org/10.1049/iet-cta.2014.1049
Mendeley helps you to discover research relevant for your work.