A Simplified Branch and Bound Approach for Model Predictive Control of Multilevel Cascaded H-Bridge STATCOM

Applying model predictive control (MPC) to cascaded H-bridge multilevel converters, while improving the dynamic performance, suffers from high computation burden due to substantial voltage vectors and switching combinations. In this paper, a simplified branch and bound approach is proposed to reduce the computation of the MPC for a cascaded H-bridge Static Synchronous Compensator (STATCOM). The underlying optimization problem of the current predictive control is a two-variable integer quadratic programming problem. With the proposed approach, the global optimal voltage vector can be selected within linear time instead of polynomial time. This is achieved by selecting the possible values of one variable as the branch, and enumerating the optimal integer results of each branch. The execution time of the proposed approach and conventional methods are compared to demonstrate the effectiveness of the proposed approach. Simulation and experimental results for a seven-level cascaded H-bridge STATCOM system are presented to verify the usability and reliability of the proposed approach.