A Model Construction and Parameter Identification Method for MMC Half-bridge Sub-modules Based on Digital-twins

ZHAO Huanhuan; XIONG Wei; ZHANG Chao; XU Yutao; YUAN Xufeng; LUO Xiandong

doi:10.19725/j.cnki.1007-2322.2023.0408

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A Model Construction and Parameter Identification Method for MMC Half-bridge Sub-modules Based on Digital-twins

更新时间：2025-10-22

- A Model Construction and Parameter Identification Method for MMC Half-bridge Sub-modules Based on Digital-twins
- Vol. 42, Issue 5, Pages: 1092-1100(2025)
- 作者机构：
  
  1. 贵州大学电气工程学院,贵州省,贵阳市,550025
  2. 贵州电网有限责任公司电力科学研究院,贵州省,贵阳市,550002
  3. 贵州电网公司有限责任公司贵阳供电局,贵州省,贵阳市,550002
- 作者简介：
- 基金信息：
- DOI：10.19725/j.cnki.1007-2322.2023.0408
  CLC： 5
- Published：2025
- 稿件说明：
移动端阅览
ZHAO Huanhuan, XIONG Wei, ZHANG Chao, et al. A Model Construction and Parameter Identification Method for MMC Half-bridge Sub-modules Based on Digital-twins[J]. 2025, 42(5): 1092-1100.
DOI：

ZHAO Huanhuan, XIONG Wei, ZHANG Chao, et al. A Model Construction and Parameter Identification Method for MMC Half-bridge Sub-modules Based on Digital-twins[J]. 2025, 42(5): 1092-1100. DOI： 10.19725/j.cnki.1007-2322.2023.0408.

摘要

模块化多电平换流器(modular multilevel converter

MMC)广泛应用于大功率电机驱动、储能和柔性直流输配电等领域，因此其可靠运行十分重要。数字孪生技术将物理实体设备实时状态信息精准映射到数字孪生模型上，能实现设备状态可视化。该文提出一种基于数字孪生技术的MMC半桥子模块模型构建方法。在子模块运行原理和重要部件失效原理的基础上，构建MMC子模块数字孪生体，包括子模块等效简化模型和模拟MMC运行的全桥转换器电路。采用改进粒子群优化算法对孪生模型参数进行在线辨识，通过虚实交互反馈实时感知子模块运行状态。在此基础上，搭建MMC半桥子模块的非侵入式数字孪生体仿真平台，通过仿真验证该方法的有效性。仿真结果表明：物理和数字孪生模型之间的误差小于0.1%，参数辨识的误差小于1%。

Abstract

Modular multilevel converter (MMC) is widely applied in high power motor drive

energy storage and flexible DC power transmission distribution system

and parameter identification for MMC is essentially important for its reliable operation. The concept of digital twins (DT) enables mapping of real-time state information from physical entity onto a digital twin model

thus facilitating device state visualization. In this paper

we propose a DT based method for model construction and parameter identification of the MMC half-bridge sub-module (HBSM). The DT model of the HBSM is built

consisting of a simplified MMC sub-module (SM) equivalent model and an arm current simulator based full-bridge converter. A modified particle swarm optimization (MPSO) algorithm is proposed to achieve the online identification of internal parameters in the HBSM

thereby enabling the real-virtual interaction feedback for real-time sensing of the operation state of the HBSM. On this basis

a non-intrusive DT simulation platform is constructed for MMC HBSM. The result demonstrate that the average errors between the actual and model-calculated capacitor voltage values are within 0.1%

while the parameter identification results combined error is less than 1%.

关键词

Keywords

references

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