Implementation of neural network-based maximum power tracking control for wind turbine generators

Abstract

In this study, the maximum power point tracking (MPPT) of a permanent magnet synchronous generator used in a wind generator system is realized by a prototype installed in a laboratory environment. The installed prototype is modeled in a MATLAB/Simulink environment. The MPPT is realized by an artificial neural network (ANN). The obtained simulation and experimental results are compared. The maximum power estimation at various windmill speeds (rpm) of the trained ANN in determined reference speeds is analyzed. The zero crossing points of the phases are determined by a digital signal peripheral interface controller and the system is operated according to the triggering angles obtained from the ANN-based control algorithm at the maximum power points.