| dc.description.abstract | Different new model predictive control (MPC) formulations have been recently proposed to reduce the real-time computation load, which makes the MPC algorithm promising for multilevel power converters. Unlike the conventional MPC formulation, which searches for the optimal switching state at each sampling time, the existing computationally efficient MPC formulations are to search for the optimal output voltage in the first stage. In the second stage, only the switching state redundancy under this optimal output voltage established in the first stage will be employed to achieve multiobjective. These computationally efficient MPC formulations based on searching an optimal voltage vector are usually validated on the power converter topologies with abundant switching redundancy or without floating capacitors. However, for the emerging topologies with less switching redundancy and floating capacitors, such as the five-level (5L) T-type nested neutral point clamped (T-NNPC) converters topology, the existing computationally efficient formulations based on optimal output voltage vector can lead to potential capacitor control failure due to the sacrificed multiobjective control performance. To address this issue, this article presents a novel MPC formulation based on suboptimal output voltage vectors considering both the system's multiobjective control performance and computation burden reduction. With the determined suboptimal voltage vectors, a small group of the switching state candidate can be established to improve the system's multiobjective control performance and efficiency. The proposed MPC formulation is finally validated on a 5L T-NNPC topology. | |
