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SSO优化FOFPID调节器设计,以提高基于双引力发电机的风力轮机系统的性能

Rafik Dembri¹, Lazhar Rahmani¹, Badreddine Babes²

¹Automatic Laboratory of Sétif-LAS, Faculty of Technology, University of Ferhat Abbas, Setif-1, Sétif, Algeria.

Scientific reports

|November 16, 2024

概括

这项研究优化了使用社会蜘蛛优化用于风力轮机系统的分数顺序模糊PID控制器. 新的控制器在变化风条件下提高了功率质量和稳定性.

科学领域:

可再生能源系统可再生能源系统
控制理论控制理论
电气工程电气工程

背景情况:

风力轮机系统 (WTS) 是非线性的,对风速变化敏感,影响电力质量.
直向向量控制 (DVC) 是在动态条件下的基于DFIG的WTS中管理功率的关键策略.
优化控制参数对于稳定和高效的输出功率至关重要.

研究的目的:

为了提高WTS中的双输电感应发电机 (DFIG) 的电力质量和稳定性.
优化一个分数顺序模糊比例整合与导数 (FOFPID) 控制器的设计参数.
使用先进的控制策略,在动态和不确定的风条件下保持额定输出功率.

主要方法:

使用社会蜘蛛优化 (SSO) 技术调整FOFPID控制器参数.
在DFIG的旋翼侧转换器 (RSC) 的DVC策略中集成了FOFPID控制器.
用内部电流环中的优化FOFPID控制器取代传统的比例整合 (PI) 调节器.

主要成果:

与SSO优化的PID和Fuzzy调节器相比,SSO优化的FOFPID控制器表现出更高的性能.
在减少 overshoot, undershoot 和结算时间方面取得了显著的改进.
显示了对参数不确定性和环境变化的强化稳定性,具有较低的总波扭曲 (THD) 和加权总波扭曲 (WTHD).

结论:

拟议的FOFPID控制器通过SSO进行优化,为基于DFIG的WTS功率控制提供了强大而有效的解决方案.
这种先进的控制策略在波动的风速下显著提高了电源质量和系统稳定性.
对于下一代风能系统来说,FOFPID控制器是传统控制器的一个有希望的替代方案.

关键词:

直接向量控制控制的直接向量控制.双联储的感应发电机是双联储的分数顺序模糊的PID控制器控制器社交蜘蛛优化方法风力轮机发电机的发电机是一个风力轮机.

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