Online Grid Impedance Identification Method for Three-Phase LCL Grid-Connected Inverters Based on Digital Twin

The high penetration of renewable energy and power electronic converters connected to the grid has led to a wide range of variations in grid impedance, which poses significant challenges to converter operation and control. Accurate grid impedance identification is essential for stable inverter control. Therefore, this paper proposes an online grid impedance identification method for three-phase LCL grid-connected inverters based on digital twin. First, a state-space model of the system's power circuit is established, and the variation of state variables is predicted using the Adams algorithm. Based on this, the modulation wave is calculated by integrating the system's control architecture. The digital twin model of the system is then constructed by combining the power circuit model and the control loop model. Next, the differential evolution (DE) algorithm is applied to compare the state variables of the actual system and the digital twin model, using the difference as a basis for iteratively optimizing the grid impedance of digital twin. The main advantage of this method is that high-accuracy grid impedance identification can be achieved while ensuring no intrusion into the system. Finally, simulation results demonstrate the correctness and effectiveness of the proposed method.