双馈风力发电机转子绕组匝间短路故障诊断方法的研究

发布时间：2018-04-24 15:55

本文选题：双馈异步风力发电机 + 转子匝间短路　；参考：《华北电力大学》2017年硕士论文

【摘要】：双馈异步风力发电机是应用最早的变速恒频风发电机型,也是现代风力发电场的主流机型之一。转子绕组匝间短路故障是一种多发于双馈异步风力发电机的故障,一旦故障发生会引起绕组局部的温度升高,机械振动加剧,进而影响绝缘,使故障进一步恶化。因此,对双馈异步风力发电机转子绕组匝间短路故障诊断方法的研究,对保障风电机组的可靠运行以及提高整个风电系统的运行效率都具有指导意义。双馈异步风力发电机在实际运行过程中,转差率随风速的变化而时变。当转差率较小时,传统的定子电流频谱中的(1+2ks)f的转子匝间短路故障特征分量往往难以突出,易被基波分量淹没。针对这一问题,本文提出了四种故障诊断方法:基于Clarke矢量模变换频谱特性分析的转子匝间短路故障诊断方法;基于Hilbert模变换频谱特性分析的转子匝间短路故障诊断方法;基于定子平均瞬时功率频谱特性分析的转子匝间短路故障诊断方法以及基于Hilbert变换下瞬时功率频谱特性分析的转子匝间短路故障诊断方法。上述四种方法,均经过严格的数学推导,且仿真结果与理论分析一致,表明上述方法在双馈异步风力发电机转子匝间短路故障中具有应用前景。同时,本文根据多回路理论编写相应的M函数建立起了理想双馈异步发电机在三相坐标系下正常情况以及发生转子绕组匝间短路故障情况的数学模型。通过对模型仿真得到定转子电压电流波形,并采用所提出的四种方法对上述电气量进行变换并进行频谱分析。仿真结果结合理论分析表明,在低转差的情况下,与传统的定子电流频谱诊断方法相比,本文所提出的四种方法均能够避免因故障特征分量过于接近基波分量而被淹没的问题,有效提高检测的准确性,从而实现对双馈异步风力发电机转子绕组匝间短路故障的早期诊断。
[Abstract]:Doubly-fed asynchronous wind turbine is the earliest variable speed constant frequency wind generator and one of the mainstream models of modern wind farm. The inter-turn short circuit fault of rotor windings is a kind of fault that often occurs in doubly-fed asynchronous wind turbine. Once the fault occurs, it will cause the local temperature of windings to rise, the mechanical vibration will be intensified, and then affect the insulation, and make the fault worsen further. Therefore, the research on the diagnosis method of inter-turn short-circuit fault in the rotor winding of doubly-fed asynchronous wind generator is of guiding significance to ensure the reliable operation of wind turbine and to improve the operation efficiency of the whole wind power system. In the actual operation of doubly-fed asynchronous wind turbine, the slip rate is time-varying with the change of wind speed. When the slip rate is small, the characteristic component of rotor inter-turn short circuit in the traditional stator current spectrum is often difficult to protrude and is easily submerged by the fundamental wave component. In order to solve this problem, four kinds of fault diagnosis methods are proposed in this paper: the method of rotor inter-turn short circuit fault diagnosis based on Clarke vector mode transform spectrum characteristic analysis, the method of rotor inter-turn short circuit fault diagnosis method based on Hilbert mode transform spectrum characteristic analysis, and the method of rotor inter-turn short circuit fault diagnosis based on spectrum analysis of Clarke vector mode transform. The fault diagnosis method of rotor inter-turn short circuit based on the analysis of stator average instantaneous power spectrum characteristic and the method of rotor inter-turn short circuit fault diagnosis based on the analysis of instantaneous power spectrum characteristic under Hilbert transform are presented. The four methods mentioned above have been strictly deduced by mathematics and the simulation results are consistent with the theoretical analysis. The results show that these methods have the application prospect in the rotor inter-turn short circuit fault of doubly-fed asynchronous wind turbine. At the same time, according to the multi-loop theory, the corresponding M function is compiled to establish the mathematical model of the normal condition and the inter-turn short circuit fault of the ideal doubly-fed asynchronous generator in three-phase coordinate system. The voltage and current waveforms of stator and rotor are obtained by simulation of the model, and the proposed four methods are used to transform the electrical quantities and analyze the frequency spectrum. The simulation results combined with theoretical analysis show that the four methods proposed in this paper can avoid the problem that the fault characteristic component is too close to the fundamental component in comparison with the traditional stator current spectrum diagnosis method under the condition of low slip error. The accuracy of detection is improved effectively, and the early diagnosis of inter-turn short circuit fault in rotor winding of doubly-fed asynchronous wind generator is realized.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM315

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