Simulation And Experimental Research Of Model Predictive Control With Constant Switching Frequency For Grid-connected Converter

In recent years,the energy consumption by human is increasing day by day with the rapid development of human society.The traditional fossil energy is not only not renewable,but also proved to be one of the main causes of environmental pollution.The use of renewable energy such as wind energy and solar energy can promote energy saving and reduce environmental pollution.As an important power electronic conversion device,grid-connected converter is an interface between renewable energy power generation system and large power grid.Its control strategy research is of great significance.Model predictive control(MPC)is widely used in the field of power electronics with the advantage of solving the multi-constraint and multi-objective optimization problem.In order to reduce power tracking error,keep constant switching frequenty,and reduce the harmonic content for three-phase converter,finite state model predictive control(FCS-MPC)is studied and some improved strategies are presented in this paper.Firstly,the mathematical model of three-phase converter is established,and the principle of FCS-MPC strategy is introduced in detail.The shortcomings of FCS-MPC are pointed out,such as high sampling frequency,unfixed switching frequency,large power control error and large amount of computation.In view of the large computational of FCS-MPC,some scholars proposed the low-complexity model prediction(LC-MPC)based on single vector and double vector successively.These metheds take negative conjugate of complex power in synchronous frame as the control variable.By judging the position of the error vector,the number of calculation of the cost function is reduced,which effectively reduces the computational complexity.However,the steady-state tracking accuracy is still poor,and the charged system has large power errors.Secondly,in view of the research of single-vector-based LC-MPC(1V-LC-MPC)method,a double-vector-based MPC(2V-MPC)method based on the calculatin of switching state function is proposed which takes advantage of the low complexity model.The method has analyzed the characteristics of the switching state signals of the three-phase converter and calculated the switching state function directly.The virtual vector is constructed with two adjacent effective vectors in each sector with the help of PWM modulation.Then,based on 2V-MPC,a three-vector model predictive control(3V-MPC)method is proposed.The zero vector is inserted to optimize the switching state function,and the power control is more precise by allocating the vector action time accurately.Theoretically,the steady-state error-free is achieved.Finally,based on the 3V-MPC modulation,a constant switching frequency model predictive control(CSF-MPC)method is obtained.Finally,the traditional 1V-LC-MPC method,the proposed 2V-MPC,3V-MPC and CSF-MPC are simulated and experimentally tested on three-phase rectifier simulation model and experimental platform.Simulation and experimental results obtained have shown that the scheme generate smaller(near zero)power control error per switching period,and has faster dynamic response and a constant switching frequency.These features have been attained without demanding for an excessively high sampling frequency.