Centralized Direct Model Predictive Control of Back-to-Back Converters

This paper investigates a centralized finite control set model predictive control scheme for back-to-back power converters. Based on known quasi-centralized schemes, the reference active power is computed by estimating the load power. Therefore only the DC-link voltage and currents that are flowing through the converter are measured. The active and reactive power of the system are not measured. Since the DC-link voltage is nonlinear, we linearize the system model around the current state. Based on those findings, a multistep formulation is furthermore established. In order to increase the performance of this formulation and due to the simple model a sphere decoding algorithm is used to solve corresponding multistep optimization problem. The results are then verified by numerical simulations.

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