Analysis of magnetic materials and the design of EI-core arm inductor for MV-AFE MMC application using Multi-objective optimization

Analysis of magnetic materials and the design of EI-core arm inductor for MV-AFE MMC application using Multi-objective optimization
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DOI：
10.1109/pedes49360.2020.9379849
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发表时间：
2020-12
期刊：
2020 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES)
影响因子：
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通讯作者：
Rounak Siddaiah;R. Cuzner
Rounak Siddaiah;R. Cuzner
中科院分区：
其他
文献类型：
--
作者：
Rounak Siddaiah;R. Cuzner

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模块化多电平转换器（MMC）是用于HVDC或MVDC微电网的流行拓扑，其需要用于每个系统的6个（每相2个）臂电感器，这在尺寸上是显著的。因此，表征用于MV电感器设计过程的不同磁性材料对于功率密度非常重要。在制造昂贵的MV电感器之前，必须分析许多变量。电感设计是一个多目标优化问题，本文采用进化算法来解决这一问题。损耗，质量和体积的优化使用遗传算法的2 mH，297 A（均方根）MMC臂电感器与E-I核心结构。
The Modular Multi-Level Converter (MMC) is a popular topology for HVDC or MVDC microgrids which require 6 (2 per phase) arm inductors for each system which are significant in size. Therefore characterizing different magnetic materials for a MV inductor design process is very important for power density. Many variables must be analyzed before expensive MV inductors are manufactured. Inductor design is a multi-objective optimization problem that is tackled by using an evolutionary algorithm to solve this is shown in this paper. Loss, Mass, and volume are optimized using a genetic algorithm for a 2mH, 297 A(rms) MMC arm inductor with an E-I core structure.