【作者】 陈海占；

【导师】 刘宗岐；

【作者基本信息】 华北电力大学（北京） ， 电力系统及其自动化， 2006， 硕士

【摘要】 电力系统的量测系统存在着错误和误差,为了提供准确的系统状态,需要对量测值进行状态估计。本文主要论述了电力系统状态估计中的状态估计和不良数据的检测与辨识两个方面。并采用了面向对象技术、稀疏矩阵技术、节点优化技术,编程实现了快速分解状态估计算法。文章介绍了不良数据检测与辨识方法中的量测量突变检测和估计辨识法。目前广域测量技术在电力系统中的应用具有很大的潜力,文章中论述了广域测量数据在状态估计中应用的三种方法:相量量测量作为未知量参与状态估计、相量量测量作为已知量参加状态估计、以PMU装置作为基准把大系统撕裂为小系统进行状态估计。更多还原

【Abstract】 There exists mistake or error in power system measuring system. To provideaccurate system status, it is necessary to carry out state estimation.Bad data detection and identification in state estimation are mainly discussed in thispaper. Object-oriented technology, sparse matrix technology and node optimizationtechnology are adopted to realize the fast decoupled state estimation method throughprogramming.With the large potential of wide area measurement system application in powersystem, three methods of using wide area measuring results in state estimation arediscussed, which are state estimation with phasor measuring points as unknownquantities, state estimation with phasor measuring points as known quantities, stateestimation through separating large system into small system based on the PMU. Thedetection and estimation identification method of measuring quantity abrupt change inbad data detection and identification is also introduced in this paper.更多还原