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电网技术 ›› 2007, Vol. 31 ›› Issue (22): 21-25 .doi:

• 论文 • 上一篇    下一篇

基于经验模式分解的聚类树方法及其在同调机组分群中的应用

史坤鹏1,穆 钢1,李 婷1,吕 陆2   

  1. 1.东北电力大学 电气工程学院,吉林省 吉林市 132012;2.北京电力公司 怀柔供电公司,北京市 怀柔区 101400
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-11-20 发布日期:2007-11-20

Empirical Mode Decomposition Based Clustering-Tree Method and Its Application in Coherency Identification of Generating Sets

SHI Kun-peng1,MU Gang1,LI Ting1,LÜ Lu2   

  1. 1.Electrical Engineering Institute,Northeast Dianli University,Jilin 132012,Jilin Province,China;2.Huairou Power Supply Company,Beijing Electric Power Company,Huairou District,Beijing 101400,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-11-20 Published:2007-11-20

摘要:

提出了一种基于经验模式分解(empirical mode decomposition,EMD)的聚类树分群方法。在系统聚类分析的基础上,提出了基于权重距离的综合聚类指标,以各机功角轨迹之间距离最小为准则,实现了多机系统同调机组的合理分群。为解决电力系统受扰后动态行为非平稳、非线性的问题,文中采用EMD方法对原始数据进行预处理。EPRI-36节点系统计算结果表明,在不太严重的扰动下和允许的误差范围内,各种扰动下均可得到基本一致的聚类分群结果,从而佐证了该方法的有效性。

关键词: 聚类树, 功角轨迹, 加权距离, 同调分群, 经验模式分解(EMD)

Abstract:

An empirical mode decomposition (EMD) based clustering-tree method is presented. On the basis of system clustering analysis the synthetic clustering indices based on weighted distance is proposed; taking the least distances among angle trajectories of generating units as the criterion, the rational clustering of coherent units in a multi-machine system is realized. To solve the non-stationary and nonlinear problem of dynamic behavior of disturbed power system, the original data are preprocessed by empirical mode decomposition. Calculation results of EPRI 36-bus system show that within the range of allowable error the clustering results under various non-severe disturbance modes are basically accordant, thus the effectiveness of the presented method is proved.

Key words: clustering-tree, angle trajectory, weighted distance, coherency identification, empirical mode decomposition (EMD)

中图分类号: 

  • TM711
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