Low-Complexity Model Predictive Power Control: Double-Vector-Based Approach

Abstract

Conventional model predictive power control (MPPC) achieves good steady-state performance and quick dynamic response by minimizing a cost function relating to the power errors. However, applying single voltage vector during the whole control period fails to reduce the power ripples to a minimal value; particularly in the two-level converter with limited switching states. Recently, the concept of duty cycle control has been introduced in MPPC to achieve further power ripple reduction. Although better steady-state performance is obtained, a lot of calculations are needed when deciding the best voltage vector and its corresponding duration. This paper proposes a low-complexity MPPC with quick voltage selection and fast duty cycle calculation. Different from prior MPPC, the negative conjugate of complex power in synchronous frame is selected as the control variable. As a result, only one prediction is required to select the best voltage vector, and its duration is determined base on the principle of error minimization of both active and reactive power. Further study reveals that the proposed low-complexity MPPC is equivalent to the recently reported MPPC with duty cycle control. Simulation and experimental results obtained from a two-level three-phase ac/dc converter are presented to confirm the theoretical study and the effectiveness of the proposed method.