Abstract: When the internal parameters and topology of grid-connected power converter is unknown in some

practical applications，the existing frequency scanning based impedance modeling method can only maintain the

dynamic equivalence at one operating point. To ensure the effectiveness of dynamic model in a wide operating

range，a deep learning based dynamic equivalent modeling method was proposed. Firstly，the equivalence between black-box modeling problem of power converter and deep recurrent neural network was studied. Secondly，a blackbox equivalent modeling method based on gate recurrent unit recurrent neural network was proposed to solve the wide range modeling issue. At last，under large perturbation and multi-operating points，simulations were implemented to validate the equivalence in a wide range of dynamic process of the proposed method.

      Key words: power converter；dynamicmodeling；deep learning；neural network；equivalentmodeling