Scholarlink

A novel application of the Maximum Versoria Criterion (MVC) algorithm is proposed for the superconducting magnetic energy storage (SMES) device to improve the low voltage ride-through (LVRT) capability for the grid-integrated doubly fed induction generator (DFIG). The MVC is an adaptive filtering algorithm (AFA) and is proposed in this work due to its high convergence speed, low normalized misalignment error (NME) and low computational complexity. The proposed MVC is applied in the voltage source converter (VSC) and the dc-to-dc converter of the SMES device to regulate the proportional-integral (PI) controller with high convergence speed during grid disturbances. To validate the performance of the MVC-PI controller, it is compared with the least mean square (LMS) algorithm and it is applied in the IEEE 39 bus system. The proposed control topology is implemented using MATLAB/Simulink software.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An Adaptive Controlled Superconducting Magnetic Energy Storage for LVRT Improvement of DFIG

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Arindam Chakraborty,
  • Tanmoy Maity

摘要

A novel application of the Maximum Versoria Criterion (MVC) algorithm is proposed for the superconducting magnetic energy storage (SMES) device to improve the low voltage ride-through (LVRT) capability for the grid-integrated doubly fed induction generator (DFIG). The MVC is an adaptive filtering algorithm (AFA) and is proposed in this work due to its high convergence speed, low normalized misalignment error (NME) and low computational complexity. The proposed MVC is applied in the voltage source converter (VSC) and the dc-to-dc converter of the SMES device to regulate the proportional-integral (PI) controller with high convergence speed during grid disturbances. To validate the performance of the MVC-PI controller, it is compared with the least mean square (LMS) algorithm and it is applied in the IEEE 39 bus system. The proposed control topology is implemented using MATLAB/Simulink software.