Dynamic Performance Enhancement of a Self-Excited Induction Generator Connected to the Grid Using an Effective Control Algorithm

Abstract

The current study aims to present a comprehensive analysis of a control technique used for improving the dynamic performance of a grid connected self-excited induction generator (SEIG). All components in the control system are modelled and explained in details. The management of SEIG operation is achieved through controlling the machine side converter using a new formulated predictive voltage control scheme (PVC). The proposed (PVC) is compared to field oriented control (FOC), model predictive current control (MPCC) and model predictive direct torque control (MPDTC) systems. MPDTC and MPCC have several drawbacks like high ripple, high load commutation, and using a weighting factor in their cost function, While FOC systems depend on machine parameters for variable estimation factors, need to use PI regulators and co-ordinate transformations, which complicate the system and slow down the dynamic response. The results obtained indicate that the proposed PVC is effective, as the ripples are reduced by 43% when compared to the MPDTC-used one and by 30% when compared to MPCC. Additionally, PVC's time response is less than that of the FOC by 15%, MPCC by 9%, and MPDTC by 4%. Furthermore, PVC produces 38% fewer commutations than MPCC and 40% fewer commutations than MPDTC. Consequently, the generator's efficiency and dependability both increased as a result of its better performance.