【作者】 张云岗；

【导师】 卫志农；

【作者基本信息】 河海大学 ， 电力系统及其自动化， 2001， 硕士

【摘要】 本文着重分析了配电网状态估计中的不良数据检测与辨识的问题。 本文的主要内容如下：首先，介绍了配电系统自动化（DSA）及其发展以及配电网状态估计的作用。并对配电网状态估计的研究现状和常用不良数据的检测与辨识方法进行了描述。 其次，对三相系统的量测设置，分解雅可比三相状态估计算法和伪量测权值的选取进行了阐述。 在此基础上，文章先对不良数据的检测与辨识问题进行了阐述，介绍了常用的一些算法。并提出了两种可行的三相状态估计中不良数据辨识的基本算法。首先采用模糊聚类分析中的迭代自组织数据分析技术（Iterative Self-Organizing Data Analysis Technique A），提出了改进ISODATA不良数据辨识法；其次，提出了递推不良数据辨识法。前者算法结构简单，便于编程实现，且计算速度快，主要适用于规模较小的系统；后者算法结构较前者复杂，程序实现困难，但由于采用了稀疏矩阵技术，并用递推法修正因子表，所以可以应用于规模较大的系统。 本文用MATLAB构成了仿真系统，用C语言编制基本状态估计计算程序。仿真结果表明这两种算法是高效、可靠的。 最后，得到了配电网络不良数据检测与辨识的若干结论。更多还原

【Abstract】 ABSTRACTThe problem about bad data detection and identification in distribution system state estimation is focused in this thesis.Firstly, the development of distribution system automation and the function of distribution system state estimation are discussed. Present status of the distribution system state estimation, and methods of bad data detection and identification are surveyed here.Secondly, measuring arrangement in three-phase distribution systems, decomposing Jacobian matrix algorithms and how to choose pseudo-measurement weight are discussed.After this, two kinds of algorithms are proposed in this thesis. Both of them are based on a decomposing Jacobian matrix algorithm.The first algorithm uses an iterative self-organizing data analysis technique and fuzzy clustering analysis theory. It is fast, simple and easy for programming, but more suitable for small system. The second one is a recursive algorithm. This one is complicated than the former. By using sparsity matrix technique and recursion, it can also be used in the larger system.The simulation system is constituted with MATLAB and the programs are formed with C language. The results of simulation denote that they are efficient and reliable.Lastly, several conclusions on bad data detection and identification for distribution system are given.更多还原