Capacitor Monitoring for Modular Multilevel Converters Based on Intelligent Algorithm

Abstract

As a kind of modularized design of high power converter, modular multilevel converter is widely used in various high-voltage and high-power applications, because of its good topology structure and expansibility, which is realized by sub-modules. As a result, a large number of sub-modules are integrated in the converter, within which the capacitors greatly affect the reliability of the converter. Thus, it is necessary to monitor the health of the capacitors in the sub-modules. In this paper, an intelligent algorithm-based method is proposed to monitor the sub-module capacitance in modular multilevel converter, by selecting bridge arm currents, dc voltage and sub-module switch signal integration as the characteristics of capacitor degradation. Neural network algorithm is selected as an example to monitor the sub-module capacitor value. Simulation results show the effectiveness and accuracy of the proposed method.