Dynamic Modeling Analysis of a Doubly-Fed Induction Generator-Based Wind Energy System

Abstract

The increasing integration of wind energy into modern power systems introduces significant challenges in maintaining frequency stability and power quality due to the stochastic nature of wind speed, particularly in microgrid environments. This study focuses on the modeling and control of a wind energy conversion system based on a Doubly Fed Induction Generator (DFIG) operating in conjunction with an external power supply system. A comprehensive simulation model of the wind energy system was developed in MATLAB (R2023b), incorporating both the wind turbine and power converter subsystems. The control strategy is based on stator flux-oriented vector control, which enables independent regulation of active and reactive power, combined with space vector pulse-width modulation (SVPWM) to improve the performance of the power electronic converters. The system employs a dual-converter structure, where the rotor-side converter ensures bidirectional power flow and the grid-side converter maintains the DC-link voltage. The simulation results demonstrate that the proposed control system ensures fast dynamic response and stable operation under variable wind conditions. In particular, the stator current reaches a steady state within 0.01 s, satisfying the specified technical requirement for transient performance. Additionally, the DC-link voltage is effectively stabilized at approximately 700 V, ensuring reliable operation of the converter system. The use of SVPWM contributes to improved switching performance and efficient synthesis of voltage vectors, enhancing overall system stability. The developed model also confirms the stable operation of the wind energy system within a microgrid, ensuring coordinated interaction between system components under fluctuating wind conditions. Compared to conventional approaches, the applied vector control strategy provides effective decoupling of power components and improved dynamic characteristics for the system. The results obtained validate the effectiveness of the proposed modeling and control approach for small-scale wind energy systems and demonstrate its applicability for improving the stability and performance of renewable energy integration in modern power systems.