Capacitor voltage balancing strategy based on sub-module capacitor voltage estimation for modular multilevel converters

Abstract

The modular multilevel converter (MMC) is expected to be used extensively in high-voltage direct current (HVDC) transmission networks because of its superior characteristics over the line-commutated converter (LCC). A key issue of concern is balancing sub-module capacitor voltages in the MMCs, which is critical for the correct operation of these converters. The majority of voltage balancing techniques proposed thus far require that the measurement of the capacitor voltages use a reliable measuring system. This can increase the capital cost of the converters. This paper presents a voltage balancing strategy based on capacitor voltage estimation using the adaptive linear neuron (ADALINE) algorithm. The proposed estimation unit requires only three voltage sensors per phase for the arm reactors and the output phase voltages. Measurements of sub-module capacitor voltages and associated communication links with the central controller are not needed. The proposed strategy can be applied to MMC systems that contain a large number of sub-modules. The method uses PSCAD/EMTDC, with particular focus on dynamic performance under a variety of operating conditions.