Abstract Power quality is an important performance index of photovoltaic system, and the control of inverter plays a decisive role in it. The single-phase photovoltaic grid-connected inverter under traditional model predictive control omits pulse width modulation, which accelerates the response speed to a certain extent, but the premise is to operate at exact model parameter values. When the inductance value of the inverter circuit is changed by the influence of voltage and current, the model is not punctual, and the control effect will be reduced. To solve this problem, a model predictive control method with real-time inductance identification was proposed. The influence of the mismatch between inductance model and practical inductance on the error of predictive current was analyzed, and an inductance identification model based on the sampling value of actual current and voltage was established. Meanwhile, the time delay compensation and the reference value correction links were added, which guaranted the accuracy of the predicted current and the correctness of the output switching state. Simulation and experiment prove that the improved method can track the inductance in real-time and accurately, and effectively reduce the current distortion rate under the mismatch of model parameter.
Li Wei,Zhang Yongjun,Xiao Xiong. The Model Predictive Grid-Connected Inverter Control Method Based on Real-Time Inductance Identification[J]. Transactions of China Electrotechnical Society, 2018, 33(15): 3450-3460.
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2018, Vol. 33 
