Electromagnetic transient (EMT) modeling for the modularized solid-state transformer (MSST) faces critical difficulties because the dynamics of the complex-structured submodules, which contain dual active bridges (DAB) and multiple active bridges (MAB), are hard to be described in analytical formulas. Existing models have problems of a narrow dynamic frequency band, insufficient simulation accuracy, or are unable to operate under fast transients. This paper proposes a parallel simulation framework for MSST that preserves the original model's broadband characteristics and remarkably improves the simulation efficiency. The main novelty towards previous work is the detailed modeling of the multi-winding transformer, the decoupled modeling of the submodules, and the parallel design of simulation processes. Finally, the proposed framework is verified through the accuracy and efficiency analysis carried out in PSCAD/EMTDC. The simulation results verify that the proposed framework has excellent accuracy and time efficiency. Index Terms-Electromagnetic transient modeling, modularized solid-state transformer (MSST), multiple active bridge (MAB), decoupled modeling, parallel simulation framework I. INTRODUCTION OLID-state transformer (SST), also called as power electronic transformer (PET), can interconnect systems with different voltage levels and achieve multi-directional power flow control [1]-[4]. Due to the modular design, the modularized SST (MSST) can be used in high voltage and high power applications [5], [6]. MSST would be effective equipment to link the transmission system and distribution network [7]-[9]. The multiple active bridge (MAB)-based MSST has higher power density, less transformers and submodules, and higher flexibility than the dual active bridge (DAB)-based MSST. Intensive studies of the topology and control sheme of MABbased MSST have been made in recent years [10]. Fig. 1(a) illustrates a cascaded H-bridge MAB MSST (CHB-MAB-MSST) whose technology readiness has been validated by the This work is supported by Beijing Natural Science Foundation under grant 3222059.
