Enhanced Control of 1.5 MW DFIG Generators in MRWT Systems Using GA‐Based PI‐ST‐SMC: Comparative Assessment With ST‐SMC

ABSTRACT This paper proposes a novel genetic algorithm‐based proportional–integral super‐twisting sliding mode control (GA‐PI‐ST‐SMC) strategy for the rotor‐side converter of a 1.5 MW doubly‐fed induction generator (DFIG) operating in marine renewable wind turbine (MRWT) systems. The proposed approach integrates the strong robustness and finite‐time convergence characteristics of super‐twisting sliding mode control with the global optimization capability of genetic algorithms to achieve optimal controller tuning and enhanced system performance under varying operating conditions. The effectiveness of the proposed controller is systematically evaluated under both nominal and perturbed conditions and benchmarked against the conventional super‐twisting sliding mode controller (ST‐SMC). Comparative results reveal substantial improvements in power quality and dynamic response. Under nominal operating conditions, the proposed GA‐PI‐ST‐SMC reduces active power ripple by 46.35% and current total harmonic distortion (THD) by 34.60%. Moreover, under robustness tests involving parameter variations and system uncertainties, the controller maintains superior performance, achieving reductions of 95.06% in reactive power ripple and 39.14% in current THD compared with the conventional ST‐SMC scheme. These results demonstrate that the proposed optimization‐based control framework significantly enhances disturbance rejection capability, suppresses power oscillations, and improves current waveform quality while preserving system stability and robustness. Consequently, the GA‐PI‐ST‐SMC emerges as an effective and reliable control solution for high‐power DFIG‐based MRWT applications, contributing to the advancement of robust and high‐efficiency renewable energy conversion systems.