Abstract
Model predictive control has become a tremendously popular control method for power converters, notably a modular multilevel converter, owing to the ability to control various objectives at once with a particular cost function and prominent dynamic performance. However, the high number of submodules in cascaded control means that the model predictive control for the modular multilevel converter suffers from a computational burden. Several approaches focused on reducing the computational burden based on limiting the number of possible switching states (possible choices) to be evaluated at each sampling instant. The dynamic performance of the modular multilevel converter is degraded in a transient state, despite the reduced computational burden. This paper presents an improved indirect model predictive control method to reduce the computational burden and enhance the dynamic performance. The proposed approach considers the steady-state and transient state individually and applies a different range of choices for each specific case. The range of choices during the steady-state is limited in order to reduce the computational burden without deteriorating the output quality, whereas the number of choices will be increased during the transient state to guarantee dynamic performance. The results that were obtained by implementing an experiment on a laboratory setup of a single-phase modular multilevel converter are presented in order to verify the proposed approach’s effectiveness. From the experimental setup, the computational time in the proposed approach was reduced by about 75% when compared with the conventional indirect model predictive control, whereas keeping fast dynamic performance.
Highlights
As a result of a notably modular structure, uncomplicated scalability, excellent harmonic performance, and the most potential for high-power applications due to cascaded topology, a modular multilevel converter (MMC) has emerged as one of the outstanding topologies for medium voltage, high power energy conversion applications [1,2,3]
The time that is required to change to the new reference during the transient state is measured to analyze how the proposed method’s dynamic performance corresponds to adjusting the number of choices compared to those of the simplified indirect model predictive control (MPC) and conventional indirect MPC
During the steady-state, certain conditions were predefined to narrow the range of inserted SMs, allowing the number of control actions and the computational burden to be of the number of inserted SMs, allowing the number of control actions and the computational reduced
Summary
As a result of a notably modular structure, uncomplicated scalability, excellent harmonic performance, and the most potential for high-power applications due to cascaded topology, a modular multilevel converter (MMC) has emerged as one of the outstanding topologies for medium voltage, high power energy conversion applications [1,2,3]. Based on certain conditions that are applied to each control objective, this approach can decrease the number of control actions in every sampling instant Another technique that is presented in [18] uses tolerance bands of capacitor voltage fluctuations and output voltage level to change the number of inserted SMs in one phase. The reduction of the number of switching control actions results in the rate of changes of switching states is limited This leads to slower dynamic performance compared to the conventional indirect MPC. The focus of this approach is based on the uses all possible switching states, can reduce the computational burden and improve the dynamic practical implementation ofto the anMPC experimental seven-level performance compared theMPC; simplified indirect in [21].
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