混合Fennec Fox-Sand Cat优化级联ANFIS MPPT,用于增强基于DFIG的WECS的控制,并支持电网支持
Prashanth Rajanala1, Malligunta Kiran Kumar1, K V Govardhan Rao2
1Department of Electrical and Electronics Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, A.P, India.
Scientific reports
|December 13, 2025
概括
本研究介绍了一种新的混合Fennec Fox-Sand Cat优化算法 (HFFSCOA),用于在基于双引力发电机 (DFIG) 的风能转换系统 (WECS) 中进行最大功率点跟踪 (MPPT). 先进的控制器确保了高效的电力提取和电网稳定性.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 人工智能在控制中
背景情况:
- 基于双源感应发电机 (DFIG) 的风能转换系统 (WECS) 对于高效的风能发电至关重要.
- 需要先进的控制策略来提高DFIG-WECS的性能和可靠性.
- 现有的最大功率点跟踪 (MPPT) 方法需要改进,以获得最佳的能量捕获和电网集成.
研究的目的:
- 引入一个混合Fennec狐-沙猫优化算法 (HFFSCOA) 集成与一个级联自适应神经模糊推理系统 (ANFIS) 用于MPPT控制.
- 以适应性调整ANFIS参数,以改善学习和准确的最大功率跟踪.
- 通过协调转换器控制,确保稳定的直流连接电压和平稳的电力输送到电网.
主要方法:
- 为ANFIS参数调整实施混合Fennec狐-沙优化算法 (HFFSCOA).
- 使用级联自适应神经模糊推理系统 (ANFIS) 进行MPPT控制.
- 使用d-q转换来抑制和协调控制转子侧转换器 (RSC) 和电网侧转换器 (GSC).
主要成果:
- 拟议的HFFSCOA-Cascaded ANFIS MPPT控制器证明了ANFIS的有效自适应调.
- 实现了精确的最大功率跟踪,最小的振荡和减少了主动 (Ps) 和反应 (Qs) 功率波动.
- 显示了非常低的0.09%的总波扭曲 (THD),确保了高功率质量.
结论:
- 基于HFFSCOA的联ANFIS MPPT为基于DFIG的WECS提供了一个智能和高效的解决方案.
- 拟议的方法提高了系统可靠性,电力质量和电网合规性.
- 这种方法提供了一个可扩展的解决方案,用于将可持续风能集成到智能电网中.
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