Abstract
Aiming at improving the quality of output current when the inverter is connected to the grid, this paper proposes a control strategy of neutral point clamped (NPC) grid-connected inverter based on radial basis function neural network (RBFNN) multi-step predictive control. Firstly, the predictive control model for output current of NPC inverter is constructed by $\alpha \beta $ coordinate transformation. Then the future values of output current are predicted for each voltage vectors, using the RBFNN prediction model. After the predicted values are obtained, a cost function $f$ is calculated for each voltage vectors and the optimal voltage vector which minimizes cost function is selected. The switch state corresponding to the optimal voltage vector is applied to the inverter in the next sampling period. Thereby the control of grid-connected output current can be achieved. The simulation results show that the RBFNN multi-step predictive control method improves the capability of current tracking and reduces the harmonic rate of output current. The proposed method can balance output current under the condition of grid voltage imbalance.
Highlights
The inverter is a bridge connecting new energy generation with the grid or load, and it is a key device of the distributed generation system
This paper proposes a current control strategy for neutral point clamped (NPC) grid-connected inverter based on radial basis function neural network (RBFNN) multi-step predictive control
This paper proposes a control strategy for NPC inverter based on RBFNN multi-step predictive control
Summary
The inverter is a bridge connecting new energy generation (such as photovoltaic power generation, wind power generation, etc.) with the grid or load, and it is a key device of the distributed generation system. During actual operation of the system, voltage of the distribution network is affected by factors, The associate editor coordinating the review of this manuscript and approving it for publication was Kathiravan Srinivasan Such as load imbalance and short-circuit fault, which will cause a three-phase output current of inverter to be unbalanced. Compared with PI control, hysteresis control, and other control methods, MPC has advantages of fast dynamic response, strong robustness, explicit processing of nonlinear constraints, no current inner loop control and no related parameter tuning It has been widely used in the control of the inverter due to these outstanding capabilities. This paper proposes a current control strategy for NPC grid-connected inverter based on RBFNN multi-step predictive control. The feasibility and effectiveness of the RBFNN multi-step predictive control method are verified
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