Scholarlink

<p>This paper proposes a robust control strategy to enhance the dynamic performance and power quality of standalone Doubly Fed Induction Generator (DFIG) systems under unbalanced loads. The approach employs metaheuristic optimization techniques the Cuckoo Search Algorithm (CSA) and Whale Optimization Algorithm (WOA) to optimally tune PI controllers in a direct-voltage control scheme for the rotor-side converter. Comprehensive simulation and experimental validation (using a dSPACE DS1104 platform) demonstrate the superiority of the optimized controllers over conventional PI tuning. Key experimental improvements include: overshoot reduced by up to 88% (from 36.8 to 4.2%), rise time accelerated by 99% (from 0.22 to 0.002 s), and stator voltage THD suppressed by 82% (from 31.8 to 5.9%) during load and voltage step variations. The results confirm that CSA and WOA optimization significantly boost transient response and power quality in off-grid DFIG wind energy systems.</p>

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

Experimental validation of metaheuristic-optimized control for standalone DFIG dynamic performance enhancement

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月25日

查看全文
  • Salah Soued,
  • Kada Boureguig,
  • Mohammed S. Chabani,
  • Khaled M. Himair Swhli

摘要

This paper proposes a robust control strategy to enhance the dynamic performance and power quality of standalone Doubly Fed Induction Generator (DFIG) systems under unbalanced loads. The approach employs metaheuristic optimization techniques the Cuckoo Search Algorithm (CSA) and Whale Optimization Algorithm (WOA) to optimally tune PI controllers in a direct-voltage control scheme for the rotor-side converter. Comprehensive simulation and experimental validation (using a dSPACE DS1104 platform) demonstrate the superiority of the optimized controllers over conventional PI tuning. Key experimental improvements include: overshoot reduced by up to 88% (from 36.8 to 4.2%), rise time accelerated by 99% (from 0.22 to 0.002 s), and stator voltage THD suppressed by 82% (from 31.8 to 5.9%) during load and voltage step variations. The results confirm that CSA and WOA optimization significantly boost transient response and power quality in off-grid DFIG wind energy systems.