LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Optimization Control of Sub-Synchronous Oscillations in Doubly Fed Generators with Wind Turbines Using the Genetic Algorithm

The sub-synchronous oscillation accident of large-scale doubly fed wind turbines connected to a grid through series compensation has caused a serious impact on the power system. By optimizing the parameters… Click to show full abstract

The sub-synchronous oscillation accident of large-scale doubly fed wind turbines connected to a grid through series compensation has caused a serious impact on the power system. By optimizing the parameters of the doubly fed wind turbines control system, the system impedance can be effectively improved to solve the problem of sub-synchronous oscillation. However, owing to the complexity of a grid-connected system of doubly fed generators connected to wind turbines and the influence of the time-varying oscillation characteristics of the system, it is often difficult to achieve a successful suppression. To solve this problem, this paper proposes an optimized additional damping method for the rotor- and grid-side controllers, which can achieve efficient suppression of the sub-synchronous oscillation. The parameters of the proposed additional damping method are optimized for all variable operation conditions using a genetic algorithm under the established frequency–domain impedance model. The detailed time–domain simulation model was constructed with the RTLAB platform to verify the proposed method. The experimental results show that the optimized control strategy can effectively and quickly suppress the sub-synchronous oscillation under different operating conditions, and the amplitude suppression rate reached 85.99%, which effectively improved the grid-connected stability of the wind turbines.

Keywords: system; oscillation; control; wind turbines; sub synchronous; doubly fed

Journal Title: Applied Sciences
Year Published: 2025

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.