Variable weight coefficient MPC control strategy for qZSI‐VSG wind power grid‐connected system

Abstract

Quasi‐Z source inverters (qZSI) can overcome the disadvantages of conventional wind power systems, because of achieving the balanced DC‐link voltage by using its boost ability. The majority of currently used control methods for conventional inverters are susceptible to parameter changes, and the qZSI are controlled by finite switching sequence model predictive control (FSS‐MPC). In this paper, a Variable weight coefficient Model Predictive Control (V‐MPC) strategy is proposed. First, based on the optimal scheduling algorithm, according to the priority of the controlled object. The proportioning weights of the global feasible solution and the local optimal solution in the algorithm are coordinated. Then, using the equality‐constraints quadratic programming method, according to the relationship between the system frequency and the reference value, increase the weight of the qZSI algorithm or increase the proportion of VSG control to improve the ability to suppress frequency fluctuations. It can give full play to the short‐term power support role of the virtual synchronous wind turbine. The modeling and testing findings validate the suggested control strategy. When compared to the conventional finite control set model predictive control (FCS‐MPC), the V‐MPC can minimize the big store inductance current ripple and have lower THD in the load currents waveform.