控制理论(社会学)
双馈电机
MATLAB语言
趋同(经济学)
感应发电机
涡轮机
理论(学习稳定性)
灵敏度(控制系统)
鉴定(生物学)
弹道
计算机科学
发电机(电路理论)
算法
工程类
交流电源
电压
功率(物理)
电子工程
控制(管理)
人工智能
经济增长
生物
操作系统
量子力学
机器学习
机械工程
植物
物理
天文
电气工程
经济
作者
Fanjie Yang,Yun Zeng,Jing Qian,Youtao Li,Shihao Xie
出处
期刊:Energies
[MDPI AG]
日期:2023-01-27
卷期号:16 (3): 1355-1355
被引量:1
摘要
Variations in generator parameters that occur during the operation of a doubly-fed induction wind turbine (DFIG) constitute a significant factor in the degradation of control performance. To address the problem of difficulty in identifying multiple parameters simultaneously in DFIG, a parameter identification method depending on the adaptive grey wolf algorithm with an information-sharing search strategy (ISIAGWO) is proposed to solve the problem of low accuracy and slow identification speed of multiple parameters in DFIG. The easily obtainable generator outlet current was selected as the observed quantity, and the trajectory sensitivity analysis was performed on the five electrical parameters of the DFIG to derive its discriminability. Finally, the parameter recognition of the DFIG was carried out using the ISIAGWO algorithm in the MATLAB/Simulink simulation software, applying the proposed calculation functions. The experimental results show that the ISIAGWO algorithm has better identification accuracy, stability, and convergence for DFIG’s generator parameter identification.
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