Cost-Effective Model Predictive Control Techniques for Modular Multilevel Converters

Description

In this thesis, model predictive control (MPC) techniques are investigated with their applications to modular multilevel converters (MMCs). Since normally a large number of submodule (SM) capacitor voltages and gate signals need to be handled in an MMC, the MPC schemes studied in this thesis are employed for determining only the voltage levels of converter arms, while gate signals are subsequently generated by the conventional sorting method. Emphasis is given to inner-loop current control in terms of phase current and circulating current, aiming at performance enhancement and computation reduction. A variable rounding level control (VRLC) approach is developed in this thesis, which is based on a modification of the conventional nearest level control (NLC) scheme: instead of the conventional nearest integer function, a proper rounding function is selected for each arm of the MMC employing the MPC method. As a result, the simplicity of the NLC is maintained while the current regulating ability is improved. The VRLC technique can also be generalized from an MPC perspective. Different current controllers can be considered to generate the arm voltage references as input of the VRLC block, thus refining the control sets of the MPC. Based on the decoupled current models, the accumulated effect of SM capacitor voltage ripples is investigated, revealing that the VRLC strategy may not achieve a proper performance if the accumulated ripple is nontrivial compared to the voltage per level. Two indexes are also proposed for quantifying the current controllability of the VRLC. Benefiting from this analysis, A SM-grouping solution is put forward to apply such MPC techniques to an MMC with a large number of SMs, leading to an equivalent operation of an MMC with much reduced number of SMs, which significantly increases the current regulating capability with reduced complexity. As an example, the SM-grouping VRLC proposal is analyzed and its system design principles are described. This thesis also develops another MPC technique which directly optimizes the cost function using quadratic programming technique. Both a rigorous and a simplified procedure are provided to solve the optimization problem. Compared with the conventional finite control set (FCS)-MPC method which evaluates all voltage level combinations, the proposed scheme presents apparent advantage in terms of calculation cost while achieving similar performance.

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