A Modified-distance-based Minimum Spanning Tree Method for Analyzing Hierarchical Structure of Power Generation System

被引：0

作者：

Fu, Dianzheng ^{[1
]}

Zhou, Tingting ^{[2
]}

Zheng, Zeyu ^{[1
]}

Fu, Yang ^{[1
]}

Tong, Yining ^{[1
]}

机构：

[1] Chinese Acad Sci, Shenyang Inst Automat, Shenyang, Peoples R China

[2] Guodian Technol & Environm Grp Co Ltd, Beijing, Peoples R China

来源：

PROCEEDINGS OF THE 2016 12TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2016年

关键词：

FINANCIAL-MARKETS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a modified-distance-based minimum spanning tree (MST) method is utilized in order to analyze the complexity and component interactions of the power generation system. The advanced method improved the traditional Mantegna-Sornette distance via considering the time lag effect and substituting the cross-correlation coefficient with its absolute value. The industrial big data investigated in this paper contain 19 groups of the two-month time series monitoring indices with the sampling time interval of one minute, which are originated from industrial sensors embedded within the power generation equipments in a power plant. The results shows the time lag effects are obvious between the generation load index and some other indices belonging to auxiliary equipments. Besides, from the generated MST using the modified distance, it can be seen that the apparent clustering feature exists in the spanning tree for the indices belonging to the same equipments. Moreover, such advanced MST can overcome the weakness associated with the conventional MST due to its capability of manifesting the connections between anticorrelated indices properly.

引用

页码：422 / 425

页数：4