Model Predictive Power Control With Dual Vectors for Three-Level Inverter

Abstract

Model predictive power control (MPPC) has been receiving plenty of concern due to its fast dynamic response. However, the varying switching frequency makes the harmonics of output voltage vary over a wide scope, which adds difficulty in designing alternating current (ac) filter. Here, on the basis of the active and reactive power derivatives of each vector and the effect of switching states on neutral point (NP) voltage, we present an MPPC with dual vectors (MPPCDV) to control the three-level (3L) inverter. In this algorithm, a new switching sequence is provided to balance the NP voltage of 3L inverter, and two cost functions are derived to reduce the number of cycle computation. According to the first cost functions, the sector containing optimal switching sequence (OSS) is obtained. The second cost function is assigned to achieve the multiobjective optimization. Simulations and experiments are built to test the effectiveness of MPPCDV. When the 3L inverter adopts the MPPCDV, the majority of the harmonic frequencies in the output voltage is concentrated near the sample frequency, the steady-state performances are improved remarkably, and the dynamic performance is as fast as the conventional MPPC.