A novel sorting-based multi-objective model predictive control for PMSG wind turbines

A novel multi-objective model predictive control strategy which is based on sorting and ranking approach for controlling converters of wind power system is proposed in this paper. In order to avoid the nontrivial process of weighting factors tuning that is typical in traditional multi-objective model predictive control, multi-objective optimization based on sorting is developed where quick sort is incorporated to sort the control variables to obtain the candidate which has the smallest objective function value. In addition, predictive direct power and direct torque control are adopted separately for the grid-side and the generator-side converters where one-step delay in digital implementation and switching losses are compensated without deterioration of control system stability. Simulations are conducted in MATLAB/Simulink to show that the proposed method can get excellent performance under both steady and dynamic states with lowered fluctuations and switching frequencies while avoid the cumbersome process of weighting factors tuning.