GA-optimized cascade control strategy of DFIG-Based twin-rotor wind turbines

Direct Power Control (DPC) is widely employed in wind power systems (WPSs) due to its simplicity, effectiveness, and ability to manage the power of WPSs. However, conventional DPC suffers from power quality issues, including harmonic distortion, current ripple, uncertainty, and reduced efficiency when the system parameters vary significantly. To address these issues, this work presents a new, straightforward, and more reliable control approach based on a proportional-integral regulator, known as cascade control (CC). The gains of this CC were optimized via a genetic algorithm (GA). This CC-GA approach is applied to doubly fed induction generators (DFIGs) with rotor-side converter (RSC) management, which are commonly used generators in WPSs. This is accomplished by regulating the RSC pulse-width modulation. Moreover, effective control of the output power of twin-rotor large wind turbines is essential to ensure maximum energy extraction under varying wind conditions. The proposed CC-GA outperforms some DPC techniques in terms of power quality under both normal and abnormal operating conditions. The effectiveness of the presented CC-GA approach is confirmed in terms of robustness, dynamic rapid response, current fitness, and ripple ratio.