Adaptive Finite Control Set Model Predictive Control Scheme for Single-phase Inverters with LCL Filter

Grid-connected inverter, as one of the core components of power system, plays an important role in renewable energy generation. Many control methods for inverters are widely studied. Among them, finite control set model predictive control (FCS MPC) has many advantages, such as fast transient response, simple implementation and convenience to consider nonlinear and constraints. However, FCS MPC also has some shortcomings, one of which is that the performance of predictive algorithm is easily affected by the system model. The performance of the traditional FCS MPC algorithm is susceptible to model errors and parameter variations. To solve this problem, an adaptive FCS MPC algorithm is designed in this paper. The single-phase inverter with LCL filter is selected as the control plant. Since the use of sensors will increase the cost of system, how to reduce the number of sensors is also researched. The traditional FCS MPC and proposed adaptive FCS MPC algorithm with fewer sensors are simulated respectively. The effectiveness of proposed method is confirmed by the results.