Hybrid closed-loop controller for modular multilevel converter with optima number of sensor approach

ABSTRACT

Model predictive control (MPC) is considered one of the best non-linear control methods for controlling the modular multilevel converter (MMC) due to various advantages, such as no need for direct modelling, high dynamic response, and the ability to manage multiple control targets simultaneously. In this paper, a current closed-loop controller (CCLC) based on the current predictive strategy (CPS) is used to control the circulating and output currents in an MMC. A bilinear mathematical model of the MMC is derived and discretized to predict the states of the MMC for one step ahead. In addition, to reduce the practical costs and reduce the converter sensors, a sensor reduction algorithm has been used to reduce the number of voltage sensors and increase the reliability of the system. The proposed method is implemented in a single-phase MMC with four sub-modules (SMs) in each arm. The accuracy and performance of the proposed method are evaluated with simulation and experimental results.

KEYWORDS:

• Modular multilevel converter
• current close-loop controller
• predictive control
• voltage balancing
• improve the dynamic response

Disclosure statement

No potential conflict of interest was reported by the author(s).