Enhancing Wind Turbine Efficiency: An Experimental Investigation of a Sensorless Three-Vector Finite Set Predictive Torque Control Approach for PMSG-Based Systems

Wind energy is a fast-growing renewable energy source that helps reduce greenhouse gas emissions and supports sustainable power solutions. However, managing wind turbines efficiently and reliably is challenging, especially when wind conditions are unpredictable. Traditional control methods often rely on mechanical sensors such as anemometers, which increase complexity, maintenance costs, and reduce reliability. They can also suffer from problems like torque fluctuations, high computational demands, and reduced power quality. To make wind turbines work efficiently and reliably, especially under changing wind conditions, advanced control strategies are needed. This paper addresses these challenges by proposing an innovative control method designed to improve system performance and simplify turbine management. This paper presents a new control strategy that combines two intelligent estimation techniques—the Extended Kalman Filter (EKF) and Particle Swarm Optimization (PSO)—with Three-Vector Finite Set Predictive Torque Control (3V FS-PTC). This method is designed specifically for wind turbines that use Permanent Magnet Synchronous Generators (PMSGs) connected directly to the power grid (Variable Speed Wind Turbine (VSWT)). This approach does not require an anemometer, mechanical parameters, or rotor position sensors, making the system simpler, more reliable, and cost-effective. The 3V FS-PTC algorithm enhances control performance by selecting the three most optimal voltage vectors, two active voltage vectors and one zero voltage vector. Experimental results demonstrate a 19.75% reduction in computational time during wind speed profile, and the method significantly reduces torque and flux ripples compared to Conventional Model Predictive Torque Control (CMPTC), which uses just one voltage vector per control period and often leads to significant torque fluctuations. Additionally, the Tip Speed Ratio Maximum Power Point Tracking (TSR-MPPT) approach is used to maximize efficiency, achieving the power coefficient value at 0.48. Then the energy produced has been successfully integrated into the grid with low THD value of 3.5% and high power factor value of 0.99. The proposed FS-PTC strategy was implemented experimentally, and its performance was evaluated under varying wind speeds using MATLAB/SIMULINK, ControlDesk, dSPACE DS1104, and the DSP LAUNCHXL-F28379D real-time platform.