| RN检测与状态预估相结合的不良数据检测辨识法 |
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| 引用本文： | 刘浩,崔巍.RN检测与状态预估相结合的不良数据检测辨识法[J].电力系统及其自动化学报,2001,13(2):39-43. |
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| 作者姓名： | 刘浩 崔巍 |
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| 作者单位： | 山东建筑工程学院计算机系 |
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| 摘 要： | 本文将RN检测法与状态预估检测辨识法相结合，提出了一种新的不良数据的检测辨识方法，该法先用RN检测法来判断是否有不良数据的检测辨识方法，该法先用RN检测法来判断是否有不良数据测点存在，若有，再用状态预估辨识哪些测点存在不良数据，将不良数据测点的量测值换成其状态预估值再进行一次状态估计，该法既克服了RN检测法存在的残差污染，残差淹没现象，又解决了状态预估检测辨识法不能区分不良数据与突变量的问题，用FORTRAN77语言编写程序，对18节点系统进行了数字仿真实验，得到了在无不良数据，有不良数据，有突变量等情况下的检测辨识结果，验证了本文介绍的检测辨识方法的有效性。
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| 关 键 词： | 电力系统 状态估计 不良数据 检测辨识法 RN检测 |
| 修稿时间： | 2000年11月22 |
THE DETECTION AND IDENTIFICATION METHOD OF BAD DATA COMBINED Rn DETECTION AND STATE FORECAST |
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| Liu Hao,Cui Wei.THE DETECTION AND IDENTIFICATION METHOD OF BAD DATA COMBINED Rn DETECTION AND STATE FORECAST[J].Proceedings of the CSU-EPSA,2001,13(2):39-43. |
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| Authors: | Liu Hao Cui Wei |
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| Abstract: | Combining Rn detection with state-forecast detection and identification,a new bad data detection and identification method is presented. This method can overcome the phenomenon of residual pollution and residual submersion, and can differentiate between bad data and sudden change. To program with FORTRAN77 language reference to the program frame,digital simulation test is performed in an 18-node system. The detection and identification results of simulation for no bad data, having bad data and having sudden change is obtained. The results show that the detection and identification method produced in this paper is effective. |
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| Keywords: | state estimation bad data detection and identification |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
