聚合控制器和滑动模式极端寻找控制器的粒子群优化,用于风能发电系统
Abdelfatah Khatir1, Abdelhak Dida2, Badreddine Babes3
1Department of Electromechanical Engineering, Mohammed El Bachir El-Ibrahimi University of BBA, Bordj Bou Arreridj, Algeria.
Scientific reports
|November 12, 2025
概括
双感应发电机 (DFIG) 风力轮机的新控制策略集成了协同控制 (SC) 和滑动模式极端寻求控制 (SMESC). 这提高了性能和可靠性,提高了效率并减少了错误.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 可再生能源系统可再生能源系统
背景情况:
- 双电感应发电机 (DFIG) 对风能转换至关重要.
- 传统的控制方法,如带有PI监管器的野外导向控制 (FOC),在性能和稳定性方面存在局限性.
- 加强DFIG控制对于最大限度地提高风力发电和电网集成至关重要.
研究的目的:
- 为基于DFIG的风力轮机提出一种新的强有力的控制策略.
- 将协同控制 (SC) 与滑动模式极端寻找控制 (SMESC) 集成,以提高性能.
- 使用粒子优化 (PSO) 来优化控制器参数.
主要方法:
- 双循环控制架构结合了用于功率调节的SC和用于最大功率点跟踪 (MPPT) 的SMESC.
- 将传统的FOC-PI调节器替换为系统的SC-SMESC配方.
- 通过粒子优化 (PSO) 算法进行参数优化.
主要成果:
- 提高了2%的MPPT效率.
- 稳定状态误差减少了77.52%,结算时间减少了96.15%.
- 降低了稳压器电流的总波扭曲 (THD) 到0.63%.
结论:
- 拟议的SC-SMESC战略为DFIG风力轮机提供了卓越的性能和可靠性.
- 控制方案表现出对参数变化和外部干扰的强大稳定性.
- 这种方法对于高性能风能转换系统是有效的.
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