Induction-Machines-Based Wind Generators With Neural Maximum Power Point Tracking and Minimum Losses Techniques

This paper presents an induction machine (IM)-based wind generation unit with integrated maximum power point tracking (MPPT), electric losses minimization technique (ELMT), and discontinuous pulsewidth modulation (D-PWM) features. The target is the development of a highly efficient wind generation unit with high dynamic performance, which is able not only to rapidly track the maximum generable power according to any wind speed variation but also to minimize, at the same time, the converter's and the machine's losses. The proposed wind generator (WG) is based on a back-to-back power converter topology with two voltage source inverters and contains previously developed neural-based MPPT, as well as an original version of an ELMT. The proposed wind generation unit has been experimentally tested on a suitably developed test set-up. Results clearly show that the integration of ELMT+D-PWM into the MPPT-based WG control permits the active power injected into the power grid to be increased up to 37.5% at high wind speeds and up to 240% at low wind speeds.