An Improved Low-Computation Model Predictive Direct Power Control Strategy for Three-Level Four-Leg Active Power Filter

Abstract

Model predictive direct power control (MPDPC) strategy offers numerous benefits over the traditional control strategies in active power filters (APF). However, the real-time execution duration (RTED) reduction of model predictive control in multilevel inverters is a big challenge. In this paper, an improved low-computation model predictive direct power control strategy for three-level four-leg APF (TL-FL-APF) is presented. First, based on generalized instantaneous reactive power theory, a new predictive power model for TL-FL-APF is established. Then, in order to reduce the RTED, classical multiple power predictions are converted into single voltage prediction through the principle of deadbeat control, and the optimized vector range is reduced from 81 to 4–18 by the method of spatial stratification using the γ-component of reference voltage vector. Finally, simulation and experimental results demonstrate that proposed low-computation MPDPC has excellent performance.