Computationally efficient model predictive power control with self-balancing capacitor voltages for grid-tied nested neutral point clamped inverter

Abstract

ABSTRACT This study outlines an effective power control strategy based on a finite control set model predictive control (FCS-MPC) of grid-tie four-level Nested Neutral Point Clamped Inverter. A mathematical model is employed to predict the behavior of grid current and power that is used to evaluate the cost function. In contrast to the traditional FCS-MPC, the suggested method only evaluates the optimization loop with the feasible candidate switching states, resulting in a reduced computational burden. The main contribution of our study is to incorporate the selection of distribution of inverter voltage vectors and self-balance of flying capacitor voltage without weighting factor. The computational load of the optimization processes is not only greatly decreased by selecting the appropriate switching states among redundant voltage vectors but also remaining the balance of flying capacitor voltages. Moreover, the difficulty of selecting the optimal weighting factor is avoided with our research. A simulation study of a 4 MW power system with various operational statuses is performed using Matlab software. The comparison results of the suggested method, traditional FCS-MPC, and previous FCS-MPC have verified the significance and validity of the offered technique with regard to steady-state, transient-state operational conditions, and computational burden.