Scholarlink

This research suggests a way to control current using finite control set model predictive control (FCS-MPC) for machine-side and grid-side converters (MSC/GSC) in direct-drive permanent magnet synchronous generators (DD-PMSG) that are connected to the grid and use both field-oriented and voltage-oriented controls. By focusing on direct and quadrature components, the FCS-MPC regulates stator and grid currents in the synchronous reference frame, eliminating the need for complex transformation calculations or voltage modulation. This FCS-MPC looks at the discrete states of the voltage-source inverter, guesses how the converter will act in the future, and chooses switching actions that minimize a cost function that has already been set. We simulate the control algorithm in MATLAB/Simulink and present results across different wind speeds to showcase the dynamic performance and efficiency of the proposed control strategy. We analyze and discuss multiple simulation outcomes to validate the accuracy of the developed models and the robustness of the controller design.

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

MPC Control Technique for Machine-Side and Grid-Side Converters in Grid-Connected PMSG Wind Turbines

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Adil El Kassoumi,
  • Mohamed Lamhamdi,
  • Imad Aboudrar,
  • Mohammed Fdaili,
  • Ahmed Mouhsen,
  • Azeddine Mouhsen

摘要

This research suggests a way to control current using finite control set model predictive control (FCS-MPC) for machine-side and grid-side converters (MSC/GSC) in direct-drive permanent magnet synchronous generators (DD-PMSG) that are connected to the grid and use both field-oriented and voltage-oriented controls. By focusing on direct and quadrature components, the FCS-MPC regulates stator and grid currents in the synchronous reference frame, eliminating the need for complex transformation calculations or voltage modulation. This FCS-MPC looks at the discrete states of the voltage-source inverter, guesses how the converter will act in the future, and chooses switching actions that minimize a cost function that has already been set. We simulate the control algorithm in MATLAB/Simulink and present results across different wind speeds to showcase the dynamic performance and efficiency of the proposed control strategy. We analyze and discuss multiple simulation outcomes to validate the accuracy of the developed models and the robustness of the controller design.