期刊论文详细信息
IEEE Access
Influence of Phase-Shifted Square Wave Modulation on Medium Frequency Transformer in a MMC Based SST
Sandro Martin1  Hui Li1  Rachit Agarwal1 
[1] Center for Advanced Power Systems, Florida State University, Tallahassee, FL, USA;
关键词: Modular multilevel converter (MMC);    DC solid state transformer (DC SST);    medium frequency transformer (MFT);    HVDC to MVDC conversion;    DC grid;    distributed energy resource (DER) integration;   
DOI  :  10.1109/ACCESS.2020.3042935
来源: DOAJ
【 摘 要 】

This article proposes an approach to identify intrinsic power losses of the medium frequency transformer that interfaces two modular multilevel converters (MMC) operated with phase-shifted square wave modulation (PS-SWM) to form a DC solid state transformer (DC SST) module. Cascaded MMC module based DC SST architecture is an excellent choice for HVDC to MVDC conversion for DC grid application as well as for renewable and distributed energy resource integration into the DC grid. Operation with PS-SWM allows reduced cell capacitor size and lower total semiconductor device ratings. However, this modulation generates a unique quasi-square waveform at the SST internal medium frequency (MF) AC interface, which differs from other known square-wave modulation types. This produces a similarly unique transformer flux density, resulting in a transformer core loss that cannot be predicted by existing methods which makes it challenging to identify. In the interest of presenting a useful and optimizable MF transformer design methodology, this article develops a tool to predict the loss of the MF transformer subjected to PS-SWM. The proposed loss estimation technique is validated through an experimental testbed operated in two different configurations and is demonstrated to provide a valid basis for the use of the proposed MF transformer design methodology. Furthermore, this article provides an analysis of the load-dependent MF transformer core loss, which demonstrates a secondary usefulness of the proposed loss prediction tool in identifying load-dependent converter losses.

【 授权许可】

Unknown   

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