基于模糊RBF神经网络的双馈风机励磁控制方法研究  

Research on Excitation Control Method of Doubly-Fed Fan Based on Fuzzy RBF Neural Network

作　　者：温旭东 WEN Xudong(Huadian(Zhejiang)New Energy Co.,Ltd.,Hangzhou,Zhejiang 310000,China)

机构地区：[1]华电(浙江)新能源有限公司,浙江杭州310000

出　　处：《自动化应用》2024年第21期17-19,共3页Automation Application

摘　　要：为解决双馈风机运行中存在的有功功率调节波动较大的问题,引进模糊RBF神经网络,以浙江华电弁山风电场“面向多机型风电机组通用性自主可控关键技术研究与应用”项目为例,开展双馈风机励磁控制方法的设计研究。根据转子绕组励磁电压,建立双馈风机电磁关系模型;引进模糊RBF神经网络,设计双馈风机的有功功率调节;引进自抗扰控制技术,将未知扰动视为扩展状态,通过扩张状态观测器对其进行实时估计,以实现对双馈风机的自抗扰主动控制。结果证明,应用设计方法后,双馈风机有功功率波动范围最小,表明设计方法可有效保障在外界影响与干扰条件下双馈风机的运行。In order to solve the problem of large fluctuation of active power regulation in doubly-fed fan operation,fuzzy RBF neural network was introduced,and the project"Research and application of key technologies for universal and autonomous control of multi-type wind turbines"in Zhejiang Huadian Benshan Wind Farm was taken as an example to design and study the excitation control method of doubly-fed fan.According to the excitation voltage of rotor winding,the electromagnetic relation model of doubly-fed fan is established.Fuzzy RBF neural network is introduced to design the active power regulation of doubly-fed fan.The active control of doubly-fed fan is realized by introducing the active disturbance rejection control technology,which regards the unknown disturbance as the extended state and estimates it in real time through the extended state observer.The experimental results show that the fluctuation range of the active power of the doubly-fed fan is the smallest after the application of the designed method,that is,the method can effectively guarantee the operation of the doubly-fed fan under the conditions of external influence and interference.

关 键 词：模糊RBF神经网络 电磁关系模型 有功功率 励磁 双馈风机 

分 类 号：TM614[电气工程—电力系统及自动化]