Parameters identification method of three-level T-type grid-connected inverters based on digital twin

In this paper, a parameters identification method for three-level T-type grid-connected inverters based on digital twin is proposed, which can monitor the health status of key components in the inverter economically and efficiently. First of all, the main circuit and control circuit of the inverter are discretized to establish its digital twin model. Then, the objective function is constructed based on the calculation data of the digital twin model and the sampling data of the physical circuit. The internal parameters of the digital twin model are updated and iterated by the particle swarm optimization (PSO) algorithm to optimize the objective function, thereby realizing the parameters identification of the power devices, DC side capacitors, and AC side inductors in the inverter. Finally, a simulation circuit is built in Matlab/Simulink to replace the physical circuit of the inverter for experimental verification. The experimental results prove the effectiveness of the method proposed in this paper.