Enhancing power quality with optimized PI controller in three-phase four-wire wind energy system

This work represents a renewable wind turbine-based energy system using a self-excited induction generator (SEIG) for electromechanical energy conversion. The system employs a robust variable step-size fractional least mean square (RVSS-FLMS) control technique to control the amplitude of the frequency and voltage at the common coupling point (PCC) and improve power quality, while a battery energy storage system (BESS) maintains power balance during wind fluctuations. The RVSS-FLMS approach outperforms the conventional least mean square (LMS) algorithm, showcasing a superior combination of reduced overshoot percentage and faster settling time. Additionally, the proposed control scheme demonstrates exceptional performance in both steady-state and dynamics when compared to existing methods. The proportional–integral (PI) gains have been optimized by the system using the whale optimization algorithm (WOA), which allows for adaptation to changing system parameters. The performance of WOA is compared with particle swarm optimization algorithm (PSO). The recommended work is evaluated with statistical tools like rise time, settling time, and percentage overshoot under dynamics. The simulation framework of the entire structure is developed in MATLAB software, and observations from simulation indicate the efficiency of the suggested control method for compensating the reactive power, neutral current, and harmonic current within the IEEE 519-2014 standard.