Battery Sources Power Balancing in a Cascaded Multilevel Inverter via an Optimal Moving Horizon Predictive Control

This paper presents an efficient and optimal model predictive control (MPC) scheme for cascaded multilevel inverters (CMI) interfaced with battery sources. One of the major control challenges with CMI is the equal power distribution amongst the cascaded cells. For the application in hand, the unbalance state-of-charge of battery cells due to unequal power drawn from them, will impact the battery lifetime and eventually the reliable operation of the overall system due to uneven stress on CMI cells. The existing classical control schemes for CMI with power balancing capability are suffering from slow dynamic response for power balancing. In addition, they require substantial tuning effort due to their multi-nested loop control structure. On the other hand, conventional MPC schemes demonstrates promising superiority for CMI control comparing to classical control schemes, but they suffer from uneven power distribution among cascaded cells. This paper proposes an optimal moving horizon predictive control scheme for CMI that addresses the challenges associated with classical control and conventional MPC schemes for battery sources interfaced grid interactive CMI. The proposed approach addresses the computational burden of MPC for CMI as number of level increases while ensure equal power drawn from battery cells with fast dynamic response which improves the lifetime of entire system by distributing the stresses on all cells of CMI. The functionality of the proposed approach is evaluated with several case studies. The complete experimental results will be included in the final paper.