高压输电线路故障定位技术的研究

发布时间：2018-05-25 22:08

  本文选题：故障定位 + 输电线路　； 参考：《西安理工大学》2017年硕士论文

【摘要】：随着智能电网工程的提出,特高压交流输电网大力发展。与此同时,电网中安装的无功补偿装置、柔性交流输电装置(FACTS)以及各种清洁能源的并网使整个电网动态化,造成故障定位变得更加复杂化,现有的故障定位方法也受到影响。输电线路作为电力系统的命脉,同时又是电力系统故障的多发部位,研究快速准确的输电线路故障定位算法,对电网的稳定高效运行意义重大。在此背景下,本文针对两种输电线路(高压输电线路和串补输电线路)进行研究,针对不同的线路提出了相应的故障定位算法,具体工作如下:首先,高压输电线路发生短路故障时会产生暂态行波,暂态行波中包含着丰富的故障信息。针对暂态行波的特点和行波波头的精准提取问题,采用TT变换提取双端输电线路行波波头。在此基础上,将TT变换应用到T型输电线路中,推导出一种故障分支判别方法,根据故障判别方法先进行故障分支判别之后进行故障定位。其次,串补输电线路因其能提高线路的输电距离、改善系统的稳定性等优点而广泛应用,但由于串补电容主保护MOV是非线性的,原有故障定位算法对串补线路不再适合。为此,将小波神经网络应用到串补输电线路故障定位中,该方法首先对故障零序电流进行离散小波变换,提取故障特征向量,然后将故障特征向量和对应的故障距离目标值送入BP神经网络的进行训练,训练结果即为故障距离。仿真结果验证:在双端及T型输电线路的故障定位中,采用TT变换能准确捕捉行波波头,实现故障定位;在串补输电线路故障定位中,采用小波神经网络不受串补主保护MOV的影响,样本测试证明该方法能准确实现故障定位。此外,这两种算法均不受线路长度、故障类型、过渡电阻的影响,具有很高的定位精度。
[Abstract]:With the development of smart grid project, UHV AC transmission network develops vigorously. At the same time, the installation of reactive power compensation device, flexible AC transmission device (facts) and the connection of various clean energy make the whole power network dynamic, which makes fault location more complicated, and the existing fault location methods are also affected. As the lifeblood of power system, transmission line is the fault location of power system at the same time. It is very important to study the fast and accurate fault location algorithm of transmission line for the stable and efficient operation of power network. In this context, this paper studies two transmission lines (high-voltage transmission line and series-compensated transmission line), and proposes the corresponding fault location algorithm for different transmission lines. The specific work is as follows: first of all, Transient traveling waves occur when short circuit faults occur in high voltage transmission lines, and the transient traveling waves contain abundant fault information. In view of the characteristics of transient traveling wave and accurate extraction of traveling wave head, TT transform is used to extract traveling wave head of dual terminal transmission line. On this basis, the TT transform is applied to T type transmission lines, and a fault branch discrimination method is derived, according to which fault branch identification is first performed and then fault location is carried out. Secondly series compensated transmission lines are widely used because of their advantages such as increasing transmission distance and improving the stability of the system. But because the main protection MOV of series compensation capacitor is nonlinear the original fault location algorithm is no longer suitable for series compensation lines. In this paper, wavelet neural network is applied to fault location of transmission line with series compensation. Firstly, the fault characteristic vector is extracted by discrete wavelet transform to zero sequence current of fault. Then the fault eigenvector and the corresponding target value of fault distance are sent to BP neural network for training. The training result is called fault distance. The simulation results show that the TT transform can accurately capture the traveling wave head and realize the fault location in the fault location of the double terminal and T transmission lines, and in the fault location of the series compensation transmission line, The wavelet neural network is not affected by the series compensation main protection MOV, and the sample test proves that this method can accurately realize the fault location. In addition, the two algorithms are independent of line length, fault type and transition resistance, so they have high positioning accuracy.
【学位授予单位】：西安理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM755

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