Open AccessModel predictive control for a modular multilevel cascade converter with an improved zero‐sequence voltage injection method
Author(s) -
Guo Chujia,
Zhang Aimin,
Zhang Hang,
Zhang Lei
Publication year - 2019
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2018.5762
Subject(s) - control theory (sociology) , voltage , cascade , modular design , controller (irrigation) , model predictive control , engineering , algorithm , computer science , electronic engineering , control (management) , artificial intelligence , electrical engineering , agronomy , chemical engineering , biology , operating system
In this study, the authors propose a model predictive control method for modular multilevel cascade converter‐single star bridge cells (MMCC‐SSBC) with an improved zero‐sequence voltage injection algorithm under unbalanced conditions. First, a model predictive controller is designed to optimise the control process, and a novelty cost function is proposed to control the current, voltage and switching frequency. Second, an improved dc voltage balancing algorithm based on zero‐sequence voltage injection is proposed. New unknown variables are selected to avoid the inverse trigonometric calculation and convert the non‐linear problem to a linear problem. Third, the regulation capability is analysed to avoid the saturation and non‐linear characteristic caused by the zero‐sequence voltage injection. Simulation results indicate that the proposed algorithm shows a shorter calculation time and achieves better performance when single‐phase voltage sag occurs. The experimental results further demonstrate that MMCC‐SSBC combined with the proposed controller has excellent steady state and dynamic performance; at the same time, the switching frequency can be controlled by the new cost function.